Compare commits

...

12 Commits

Author SHA1 Message Date
leccelecce
05f87f0777
Merge 911834e223ac612bcedd4603b4071ecf0f4cf9e1 into de066d0062970153cabdf2dfe6998064ce3e94c6 2025-11-12 17:16:11 +11:00
GuoQing Liu
de066d0062
Fix i18n (#20857)
* fix: fix the missing i18n key

* fix: fix trackedObject i18n keys count variable

* fix: fix some pages audio label missing i18n

* fix: add 6214d52 missing variable

* fix: add more missing i18n

* fix: add menu missing key
2025-11-11 17:23:30 -06:00
Nicolas Mowen
f1a05d0f9b
Miscellaneous fixes (#20875)
* Improve stream fetching logic

* Reduce need to revalidate stream info

* fix frigate+ frame submission

* add UI setting to configure jsmpeg fallback timeout

* hide settings dropdown when fullscreen

* Fix arcface running on OpenVINO

---------

Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
2025-11-11 17:00:54 -06:00
Josh Hawkins
a623150811
Add Camera Wizard tweaks (#20889)
* digest auth backend

* frontend

* i18n

* update field description language to include note about onvif specific credentials

* mask util helper function

* language

* mask passwords in http-flv and others where a url param is password
2025-11-11 06:46:23 -07:00
Josh Hawkins
e4eac4ac81
Add Camera Wizard improvements (#20876)
* backend api endpoint

* don't add no-credentials version of streams to rtsp_candidates

* frontend types

* improve types

* add optional probe dialog to wizard step 1

* i18n

* form description and field change

* add onvif form description

* match onvif probe pane with other steps in the wizard

* refactor to add probe and snapshot as step 2

* consolidate probe dialog

* don't change dialog size

* radio button style

* refactor to select onvif urls via combobox in step 3

* i18n

* add scrollbar container

* i18n cleanup

* fix button activity indicator

* match test parsing in step 3 with step 2

* hide resolution if both width and height are zero

* use drawer for stream selection on mobile in step 3

* suppress double toasts

* api endpoint description
2025-11-10 15:49:52 -06:00
Josh Hawkins
c371fc0c87
Miscellaneous Fixes (#20866)
* Don't warn when event ids have expired for trigger sync

* Import faster_whisper conditinally to avoid illegal instruction

* Catch OpenVINO runtime error

* fix race condition in detail stream context

navigating between tracked objects in Explore would sometimes prevent the object track from appearing

* Handle case where classification images are deleted

* Adjust default rounded corners on larger screens

* Improve flow handling for classification state

* Remove images when wizard is cancelled

* Improve deletion handling for classes

* Set constraints on review buffers

* Update to support correct data format

* Set minimum duration for recording based review items

* Use friendly name in review genai prompt

---------

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2025-11-10 10:03:56 -07:00
Nicolas Mowen
99a363c047
Improve classification (#20863) 2025-11-09 16:21:13 -06:00
Nicolas Mowen
a374a60756
Miscellaneous Fixes (#20850)
* Fix wrongly added detection objects to alert

* Fix CudaGraph inverse condition

* Add debug logs

* Formatting
2025-11-09 08:38:38 -06:00
Nicolas Mowen
d41ee4ff88
Miscellaneous Fixes (#20848)
* Fix filtering for classification

* Adjust prompt to account for response tokens

* Correctly return response for reprocess

* Use API response to update data instead of trying to re-parse all of the values

* Implement rename class api

* Fix model deletion / rename dialog

* Remove camera spatial context

* Catch error
2025-11-08 13:13:40 -07:00
Josh Hawkins
c99ada8f6a
Tracked Object Details pane tweaks (#20849)
* use grid view on desktop

* refactor description box to remove buttons and add row of action icon buttons

* add tooltips

* fix trigger creation

when using the search effect to create a trigger, the prefilled object will not exist in the config yet

* i18n

* set max width on thumbnail
2025-11-08 12:26:30 -07:00
Josh Hawkins
01452e4c51
Miscellaneous Fixes (#20841)
* show id field when editing zone

* improve zone capitalization

* Update NPU models and docs

* fix mobilepage in tracked object details

* Use thread lock for openvino to avoid concurrent requests with JinaV2

* fix hashing function to avoid collisions

* remove extra flex div causing overflow

* ensure header stays on top of video controls

* don't smart capitalize friendly names

* Fix incorrect object classification crop

* don't display submit to plus if object doesn't have a snapshot

* check for snapshot and clip in actions menu

* frigate plus submission fix

still show frigate+ section if snapshot has already been submitted and run optimistic update, local state was being overridden

* Don't fail to show 0% when showing classification

* Don't fail on file system error

* Improve title and description for review genai

* fix overflowing truncated review item description in detail stream

* catch events with review items that start after the first timeline entry

review items may start later than events within them, so subtract a padding from the start time in the filter so the start of events are not incorrectly filtered out of the list in the detail stream

* also pad on review end_time

* fix

* change order of timeline zoom buttons on mobile

* use grid to ensure genai title does not cause overflow

* small tweaks

* Cleanup

---------

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2025-11-08 05:44:30 -07:00
leccelecce
911834e223 UI: disable animations on all charts 2025-04-11 10:05:49 +01:00
71 changed files with 4672 additions and 1922 deletions

View File

@ -68,36 +68,6 @@ The mere presence of an unidentified person in private areas during late night h
</details>
### Camera Spatial Context
In addition to defining activity patterns, you can provide spatial context for specific cameras to help the LLM generate more accurate and descriptive titles and scene descriptions. The `camera_context` field allows you to describe physical features and locations that are outside the camera's field of view but are relevant for understanding the scene.
**Important Guidelines:**
- This context is used **only for descriptive purposes** to help the LLM write better titles and scene descriptions
- It should describe **physical features and spatial relationships** (e.g., "front door is to the right", "driveway on the left")
- It should **NOT** include subjective assessments or threat evaluations (e.g., "high-crime area")
- Threat level determination remains based solely on observable actions defined in the activity patterns
Example configuration:
```yaml
cameras:
front_door:
review:
genai:
enabled: true
camera_context: |
- Front door entrance is to the right of the frame
- Driveway and street are to the left
- Steps in the center lead from the sidewalk to the front door
- Garage is located beyond the left edge of the frame
```
This helps the LLM generate more natural descriptions like "Person approaching front door" instead of "Person walking toward right side of frame".
The `camera_context` can be defined globally under `genai.review` and overridden per camera for specific spatial details.
### Image Source
By default, review summaries use preview images (cached preview frames) which have a lower resolution but use fewer tokens per image. For better image quality and more detailed analysis, you can configure Frigate to extract frames directly from recordings at a higher resolution:

View File

@ -5,7 +5,7 @@ title: Enrichments
# Enrichments
Some of Frigate's enrichments can use a discrete GPU / NPU for accelerated processing.
Some of Frigate's enrichments can use a discrete GPU or integrated GPU for accelerated processing.
## Requirements
@ -18,8 +18,10 @@ Object detection and enrichments (like Semantic Search, Face Recognition, and Li
- **Intel**
- OpenVINO will automatically be detected and used for enrichments in the default Frigate image.
- **Note:** Intel NPUs have limited model support for enrichments. GPU is recommended for enrichments when available.
- **Nvidia**
- Nvidia GPUs will automatically be detected and used for enrichments in the `-tensorrt` Frigate image.
- Jetson devices will automatically be detected and used for enrichments in the `-tensorrt-jp6` Frigate image.

View File

@ -261,6 +261,8 @@ OpenVINO is supported on 6th Gen Intel platforms (Skylake) and newer. It will al
:::tip
**NPU + GPU Systems:** If you have both NPU and GPU available (Intel Core Ultra processors), use NPU for object detection and GPU for enrichments (semantic search, face recognition, etc.) for best performance and compatibility.
When using many cameras one detector may not be enough to keep up. Multiple detectors can be defined assuming GPU resources are available. An example configuration would be:
```yaml
@ -283,7 +285,7 @@ detectors:
| [RF-DETR](#rf-detr) | ✅ | ✅ | Requires XE iGPU or Arc |
| [YOLO-NAS](#yolo-nas) | ✅ | ✅ | |
| [MobileNet v2](#ssdlite-mobilenet-v2) | ✅ | ✅ | Fast and lightweight model, less accurate than larger models |
| [YOLOX](#yolox) | ✅ | ? | |
| [YOLOX](#yolox) | ✅ | ? | |
| [D-FINE](#d-fine) | ❌ | ❌ | |
#### SSDLite MobileNet v2

View File

@ -78,7 +78,7 @@ Switching between V1 and V2 requires reindexing your embeddings. The embeddings
### GPU Acceleration
The CLIP models are downloaded in ONNX format, and the `large` model can be accelerated using GPU / NPU hardware, when available. This depends on the Docker build that is used. You can also target a specific device in a multi-GPU installation.
The CLIP models are downloaded in ONNX format, and the `large` model can be accelerated using GPU hardware, when available. This depends on the Docker build that is used. You can also target a specific device in a multi-GPU installation.
```yaml
semantic_search:
@ -90,7 +90,7 @@ semantic_search:
:::info
If the correct build is used for your GPU / NPU and the `large` model is configured, then the GPU / NPU will be detected and used automatically.
If the correct build is used for your GPU / NPU and the `large` model is configured, then the GPU will be detected and used automatically.
Specify the `device` option to target a specific GPU in a multi-GPU system (see [onnxruntime's provider options](https://onnxruntime.ai/docs/execution-providers/)).
If you do not specify a device, the first available GPU will be used.

View File

@ -3,11 +3,17 @@
import json
import logging
import re
from importlib.util import find_spec
from pathlib import Path
from urllib.parse import quote_plus
import httpx
import requests
from fastapi import APIRouter, Depends, Request, Response
from fastapi import APIRouter, Depends, Query, Request, Response
from fastapi.responses import JSONResponse
from onvif import ONVIFCamera, ONVIFError
from zeep.exceptions import Fault, TransportError
from zeep.transports import AsyncTransport
from frigate.api.auth import require_role
from frigate.api.defs.tags import Tags
@ -452,3 +458,537 @@ def _extract_fps(r_frame_rate: str) -> float | None:
return round(float(num) / float(den), 2)
except (ValueError, ZeroDivisionError):
return None
@router.get(
"/onvif/probe",
dependencies=[Depends(require_role(["admin"]))],
summary="Probe ONVIF device",
description=(
"Probe an ONVIF device to determine capabilities and optionally test available stream URIs. "
"Query params: host (required), port (default 80), username, password, test (boolean), "
"auth_type (basic or digest, default basic)."
),
)
async def onvif_probe(
request: Request,
host: str = Query(None),
port: int = Query(80),
username: str = Query(""),
password: str = Query(""),
test: bool = Query(False),
auth_type: str = Query("basic"), # Add auth_type parameter
):
"""
Probe a single ONVIF device to determine capabilities.
Connects to an ONVIF device and queries for:
- Device information (manufacturer, model)
- Media profiles count
- PTZ support
- Available presets
- Autotracking support
Query Parameters:
host: Device host/IP address (required)
port: Device port (default 80)
username: ONVIF username (optional)
password: ONVIF password (optional)
test: run ffprobe on the stream (optional)
auth_type: Authentication type - "basic" or "digest" (default "basic")
Returns:
JSON with device capabilities information
"""
if not host:
return JSONResponse(
content={"success": False, "message": "host parameter is required"},
status_code=400,
)
# Validate host format
if not _is_valid_host(host):
return JSONResponse(
content={"success": False, "message": "Invalid host format"},
status_code=400,
)
# Validate auth_type
if auth_type not in ["basic", "digest"]:
return JSONResponse(
content={
"success": False,
"message": "auth_type must be 'basic' or 'digest'",
},
status_code=400,
)
onvif_camera = None
try:
logger.debug(f"Probing ONVIF device at {host}:{port} with {auth_type} auth")
try:
wsdl_base = None
spec = find_spec("onvif")
if spec and getattr(spec, "origin", None):
wsdl_base = str(Path(spec.origin).parent / "wsdl")
except Exception:
wsdl_base = None
onvif_camera = ONVIFCamera(
host, port, username or "", password or "", wsdl_dir=wsdl_base
)
# Configure digest authentication if requested
if auth_type == "digest" and username and password:
# Create httpx client with digest auth
auth = httpx.DigestAuth(username, password)
client = httpx.AsyncClient(auth=auth, timeout=10.0)
# Replace the transport in the zeep client
transport = AsyncTransport(client=client)
# Update the xaddr before setting transport
await onvif_camera.update_xaddrs()
# Replace transport in all services
if hasattr(onvif_camera, "devicemgmt"):
onvif_camera.devicemgmt.zeep_client.transport = transport
if hasattr(onvif_camera, "media"):
onvif_camera.media.zeep_client.transport = transport
if hasattr(onvif_camera, "ptz"):
onvif_camera.ptz.zeep_client.transport = transport
logger.debug("Configured digest authentication")
else:
await onvif_camera.update_xaddrs()
# Get device information
device_info = {
"manufacturer": "Unknown",
"model": "Unknown",
"firmware_version": "Unknown",
}
try:
device_service = await onvif_camera.create_devicemgmt_service()
# Update transport for device service if digest auth
if auth_type == "digest" and username and password:
auth = httpx.DigestAuth(username, password)
client = httpx.AsyncClient(auth=auth, timeout=10.0)
transport = AsyncTransport(client=client)
device_service.zeep_client.transport = transport
device_info_resp = await device_service.GetDeviceInformation()
manufacturer = getattr(device_info_resp, "Manufacturer", None) or (
device_info_resp.get("Manufacturer")
if isinstance(device_info_resp, dict)
else None
)
model = getattr(device_info_resp, "Model", None) or (
device_info_resp.get("Model")
if isinstance(device_info_resp, dict)
else None
)
firmware = getattr(device_info_resp, "FirmwareVersion", None) or (
device_info_resp.get("FirmwareVersion")
if isinstance(device_info_resp, dict)
else None
)
device_info.update(
{
"manufacturer": manufacturer or "Unknown",
"model": model or "Unknown",
"firmware_version": firmware or "Unknown",
}
)
except Exception as e:
logger.debug(f"Failed to get device info: {e}")
# Get media profiles
profiles = []
profiles_count = 0
first_profile_token = None
ptz_config_token = None
try:
media_service = await onvif_camera.create_media_service()
# Update transport for media service if digest auth
if auth_type == "digest" and username and password:
auth = httpx.DigestAuth(username, password)
client = httpx.AsyncClient(auth=auth, timeout=10.0)
transport = AsyncTransport(client=client)
media_service.zeep_client.transport = transport
profiles = await media_service.GetProfiles()
profiles_count = len(profiles) if profiles else 0
if profiles and len(profiles) > 0:
p = profiles[0]
first_profile_token = getattr(p, "token", None) or (
p.get("token") if isinstance(p, dict) else None
)
# Get PTZ configuration token from the profile
ptz_configuration = getattr(p, "PTZConfiguration", None) or (
p.get("PTZConfiguration") if isinstance(p, dict) else None
)
if ptz_configuration:
ptz_config_token = getattr(ptz_configuration, "token", None) or (
ptz_configuration.get("token")
if isinstance(ptz_configuration, dict)
else None
)
except Exception as e:
logger.debug(f"Failed to get media profiles: {e}")
# Check PTZ support and capabilities
ptz_supported = False
presets_count = 0
autotrack_supported = False
try:
ptz_service = await onvif_camera.create_ptz_service()
# Update transport for PTZ service if digest auth
if auth_type == "digest" and username and password:
auth = httpx.DigestAuth(username, password)
client = httpx.AsyncClient(auth=auth, timeout=10.0)
transport = AsyncTransport(client=client)
ptz_service.zeep_client.transport = transport
# Check if PTZ service is available
try:
await ptz_service.GetServiceCapabilities()
ptz_supported = True
logger.debug("PTZ service is available")
except Exception as e:
logger.debug(f"PTZ service not available: {e}")
ptz_supported = False
# Try to get presets if PTZ is supported and we have a profile
if ptz_supported and first_profile_token:
try:
presets_resp = await ptz_service.GetPresets(
{"ProfileToken": first_profile_token}
)
presets_count = len(presets_resp) if presets_resp else 0
logger.debug(f"Found {presets_count} presets")
except Exception as e:
logger.debug(f"Failed to get presets: {e}")
presets_count = 0
# Check for autotracking support - requires both FOV relative movement and MoveStatus
if ptz_supported and first_profile_token and ptz_config_token:
# First check for FOV relative movement support
pt_r_fov_supported = False
try:
config_request = ptz_service.create_type("GetConfigurationOptions")
config_request.ConfigurationToken = ptz_config_token
ptz_config = await ptz_service.GetConfigurationOptions(
config_request
)
if ptz_config:
# Check for pt-r-fov support
spaces = getattr(ptz_config, "Spaces", None) or (
ptz_config.get("Spaces")
if isinstance(ptz_config, dict)
else None
)
if spaces:
rel_pan_tilt_space = getattr(
spaces, "RelativePanTiltTranslationSpace", None
) or (
spaces.get("RelativePanTiltTranslationSpace")
if isinstance(spaces, dict)
else None
)
if rel_pan_tilt_space:
# Look for FOV space
for i, space in enumerate(rel_pan_tilt_space):
uri = None
if isinstance(space, dict):
uri = space.get("URI")
else:
uri = getattr(space, "URI", None)
if uri and "TranslationSpaceFov" in uri:
pt_r_fov_supported = True
logger.debug(
"FOV relative movement (pt-r-fov) supported"
)
break
logger.debug(f"PTZ config spaces: {ptz_config}")
except Exception as e:
logger.debug(f"Failed to check FOV relative movement: {e}")
pt_r_fov_supported = False
# Now check for MoveStatus support via GetServiceCapabilities
if pt_r_fov_supported:
try:
service_capabilities_request = ptz_service.create_type(
"GetServiceCapabilities"
)
service_capabilities = await ptz_service.GetServiceCapabilities(
service_capabilities_request
)
# Look for MoveStatus in the capabilities
move_status_capable = False
if service_capabilities:
# Try to find MoveStatus key recursively
def find_move_status(obj, key="MoveStatus"):
if isinstance(obj, dict):
if key in obj:
return obj[key]
for v in obj.values():
result = find_move_status(v, key)
if result is not None:
return result
elif hasattr(obj, key):
return getattr(obj, key)
elif hasattr(obj, "__dict__"):
for v in vars(obj).values():
result = find_move_status(v, key)
if result is not None:
return result
return None
move_status_value = find_move_status(service_capabilities)
# MoveStatus should return "true" if supported
if isinstance(move_status_value, bool):
move_status_capable = move_status_value
elif isinstance(move_status_value, str):
move_status_capable = (
move_status_value.lower() == "true"
)
logger.debug(f"MoveStatus capability: {move_status_value}")
# Autotracking is supported if both conditions are met
autotrack_supported = pt_r_fov_supported and move_status_capable
if autotrack_supported:
logger.debug(
"Autotracking fully supported (pt-r-fov + MoveStatus)"
)
else:
logger.debug(
f"Autotracking not fully supported - pt-r-fov: {pt_r_fov_supported}, MoveStatus: {move_status_capable}"
)
except Exception as e:
logger.debug(f"Failed to check MoveStatus support: {e}")
autotrack_supported = False
except Exception as e:
logger.debug(f"Failed to probe PTZ service: {e}")
result = {
"success": True,
"host": host,
"port": port,
"manufacturer": device_info["manufacturer"],
"model": device_info["model"],
"firmware_version": device_info["firmware_version"],
"profiles_count": profiles_count,
"ptz_supported": ptz_supported,
"presets_count": presets_count,
"autotrack_supported": autotrack_supported,
}
# Gather RTSP candidates
rtsp_candidates: list[dict] = []
try:
media_service = await onvif_camera.create_media_service()
# Update transport for media service if digest auth
if auth_type == "digest" and username and password:
auth = httpx.DigestAuth(username, password)
client = httpx.AsyncClient(auth=auth, timeout=10.0)
transport = AsyncTransport(client=client)
media_service.zeep_client.transport = transport
if profiles_count and media_service:
for p in profiles or []:
token = getattr(p, "token", None) or (
p.get("token") if isinstance(p, dict) else None
)
if not token:
continue
try:
stream_setup = {
"Stream": "RTP-Unicast",
"Transport": {"Protocol": "RTSP"},
}
stream_req = {
"ProfileToken": token,
"StreamSetup": stream_setup,
}
stream_uri_resp = await media_service.GetStreamUri(stream_req)
uri = (
stream_uri_resp.get("Uri")
if isinstance(stream_uri_resp, dict)
else getattr(stream_uri_resp, "Uri", None)
)
if uri:
logger.debug(
f"GetStreamUri returned for token {token}: {uri}"
)
# If credentials were provided, do NOT add the unauthenticated URI.
try:
if isinstance(uri, str) and uri.startswith("rtsp://"):
if username and password and "@" not in uri:
# Inject URL-encoded credentials and add only the
# authenticated version.
cred = f"{quote_plus(username)}:{quote_plus(password)}@"
injected = uri.replace(
"rtsp://", f"rtsp://{cred}", 1
)
rtsp_candidates.append(
{
"source": "GetStreamUri",
"profile_token": token,
"uri": injected,
}
)
else:
# No credentials provided or URI already contains
# credentials — add the URI as returned.
rtsp_candidates.append(
{
"source": "GetStreamUri",
"profile_token": token,
"uri": uri,
}
)
else:
# Non-RTSP URIs (e.g., http-flv) — add as returned.
rtsp_candidates.append(
{
"source": "GetStreamUri",
"profile_token": token,
"uri": uri,
}
)
except Exception as e:
logger.debug(
f"Skipping stream URI for token {token} due to processing error: {e}"
)
continue
except Exception:
logger.debug(
f"GetStreamUri failed for token {token}", exc_info=True
)
continue
# Add common RTSP patterns as fallback
if not rtsp_candidates:
common_paths = [
"/h264",
"/live.sdp",
"/media.amp",
"/Streaming/Channels/101",
"/Streaming/Channels/1",
"/stream1",
"/cam/realmonitor?channel=1&subtype=0",
"/11",
]
# Use URL-encoded credentials for pattern fallback URIs when provided
auth_str = (
f"{quote_plus(username)}:{quote_plus(password)}@"
if username and password
else ""
)
rtsp_port = 554
for path in common_paths:
uri = f"rtsp://{auth_str}{host}:{rtsp_port}{path}"
rtsp_candidates.append({"source": "pattern", "uri": uri})
except Exception:
logger.debug("Failed to collect RTSP candidates")
# Optionally test RTSP candidates using ffprobe_stream
tested_candidates = []
if test and rtsp_candidates:
for c in rtsp_candidates:
uri = c["uri"]
to_test = [uri]
try:
if (
username
and password
and isinstance(uri, str)
and uri.startswith("rtsp://")
and "@" not in uri
):
cred = f"{quote_plus(username)}:{quote_plus(password)}@"
cred_uri = uri.replace("rtsp://", f"rtsp://{cred}", 1)
if cred_uri not in to_test:
to_test.append(cred_uri)
except Exception:
pass
for test_uri in to_test:
try:
probe = ffprobe_stream(
request.app.frigate_config.ffmpeg, test_uri, detailed=False
)
print(probe)
ok = probe is not None and getattr(probe, "returncode", 1) == 0
tested_candidates.append(
{
"uri": test_uri,
"source": c.get("source"),
"ok": ok,
"profile_token": c.get("profile_token"),
}
)
except Exception as e:
logger.debug(f"Unable to probe stream: {e}")
tested_candidates.append(
{
"uri": test_uri,
"source": c.get("source"),
"ok": False,
"profile_token": c.get("profile_token"),
}
)
result["rtsp_candidates"] = rtsp_candidates
if test:
result["rtsp_tested"] = tested_candidates
logger.debug(f"ONVIF probe successful: {result}")
return JSONResponse(content=result)
except ONVIFError as e:
logger.warning(f"ONVIF error probing {host}:{port}: {e}")
return JSONResponse(
content={"success": False, "message": "ONVIF error"},
status_code=400,
)
except (Fault, TransportError) as e:
logger.warning(f"Connection error probing {host}:{port}: {e}")
return JSONResponse(
content={"success": False, "message": "Connection error"},
status_code=503,
)
except Exception as e:
logger.warning(f"Error probing ONVIF device at {host}:{port}, {e}")
return JSONResponse(
content={"success": False, "message": "Probe failed"},
status_code=500,
)
finally:
# Best-effort cleanup of ONVIF camera client session
if onvif_camera is not None:
try:
# Check if the camera has a close method and call it
if hasattr(onvif_camera, "close"):
await onvif_camera.close()
except Exception as e:
logger.debug(f"Error closing ONVIF camera session: {e}")

View File

@ -37,6 +37,8 @@ from frigate.models import Event
from frigate.util.classification import (
collect_object_classification_examples,
collect_state_classification_examples,
get_dataset_image_count,
read_training_metadata,
)
from frigate.util.file import get_event_snapshot
@ -112,9 +114,18 @@ def reclassify_face(request: Request, body: dict = None):
context: EmbeddingsContext = request.app.embeddings
response = context.reprocess_face(training_file)
if not isinstance(response, dict):
return JSONResponse(
status_code=500,
content={
"success": False,
"message": "Could not process request.",
},
)
return JSONResponse(
status_code=200 if response.get("success", True) else 400,
content=response,
status_code=200,
)
@ -555,23 +566,59 @@ def get_classification_dataset(name: str):
dataset_dir = os.path.join(CLIPS_DIR, sanitize_filename(name), "dataset")
if not os.path.exists(dataset_dir):
return JSONResponse(status_code=200, content={})
return JSONResponse(
status_code=200, content={"categories": {}, "training_metadata": None}
)
for name in os.listdir(dataset_dir):
category_dir = os.path.join(dataset_dir, name)
for category_name in os.listdir(dataset_dir):
category_dir = os.path.join(dataset_dir, category_name)
if not os.path.isdir(category_dir):
continue
dataset_dict[name] = []
dataset_dict[category_name] = []
for file in filter(
lambda f: (f.lower().endswith((".webp", ".png", ".jpg", ".jpeg"))),
os.listdir(category_dir),
):
dataset_dict[name].append(file)
dataset_dict[category_name].append(file)
return JSONResponse(status_code=200, content=dataset_dict)
# Get training metadata
metadata = read_training_metadata(sanitize_filename(name))
current_image_count = get_dataset_image_count(sanitize_filename(name))
if metadata is None:
training_metadata = {
"has_trained": False,
"last_training_date": None,
"last_training_image_count": 0,
"current_image_count": current_image_count,
"new_images_count": current_image_count,
"dataset_changed": current_image_count > 0,
}
else:
last_training_count = metadata.get("last_training_image_count", 0)
# Dataset has changed if count is different (either added or deleted images)
dataset_changed = current_image_count != last_training_count
# Only show positive count for new images (ignore deletions in the count display)
new_images_count = max(0, current_image_count - last_training_count)
training_metadata = {
"has_trained": True,
"last_training_date": metadata.get("last_training_date"),
"last_training_image_count": last_training_count,
"current_image_count": current_image_count,
"new_images_count": new_images_count,
"dataset_changed": dataset_changed,
}
return JSONResponse(
status_code=200,
content={
"categories": dataset_dict,
"training_metadata": training_metadata,
},
)
@router.get(
@ -671,6 +718,97 @@ def delete_classification_dataset_images(
)
@router.put(
"/classification/{name}/dataset/{old_category}/rename",
response_model=GenericResponse,
dependencies=[Depends(require_role(["admin"]))],
summary="Rename a classification category",
description="""Renames a classification category for a given classification model.
The old category must exist and the new name must be valid. Returns a success message or an error if the name is invalid.""",
)
def rename_classification_category(
request: Request, name: str, old_category: str, body: dict = None
):
config: FrigateConfig = request.app.frigate_config
if name not in config.classification.custom:
return JSONResponse(
content=(
{
"success": False,
"message": f"{name} is not a known classification model.",
}
),
status_code=404,
)
json: dict[str, Any] = body or {}
new_category = sanitize_filename(json.get("new_category", ""))
if not new_category:
return JSONResponse(
content=(
{
"success": False,
"message": "New category name is required.",
}
),
status_code=400,
)
old_folder = os.path.join(
CLIPS_DIR, sanitize_filename(name), "dataset", sanitize_filename(old_category)
)
new_folder = os.path.join(
CLIPS_DIR, sanitize_filename(name), "dataset", new_category
)
if not os.path.exists(old_folder):
return JSONResponse(
content=(
{
"success": False,
"message": f"Category {old_category} does not exist.",
}
),
status_code=404,
)
if os.path.exists(new_folder):
return JSONResponse(
content=(
{
"success": False,
"message": f"Category {new_category} already exists.",
}
),
status_code=400,
)
try:
os.rename(old_folder, new_folder)
return JSONResponse(
content=(
{
"success": True,
"message": f"Successfully renamed category to {new_category}.",
}
),
status_code=200,
)
except Exception as e:
logger.error(f"Error renaming category: {e}")
return JSONResponse(
content=(
{
"success": False,
"message": "Failed to rename category",
}
),
status_code=500,
)
@router.post(
"/classification/{name}/dataset/categorize",
response_model=GenericResponse,
@ -815,31 +953,29 @@ async def generate_object_examples(request: Request, body: GenerateObjectExample
dependencies=[Depends(require_role(["admin"]))],
summary="Delete a classification model",
description="""Deletes a specific classification model and all its associated data.
The name must exist in the classification models. Returns a success message or an error if the name is invalid.""",
Works even if the model is not in the config (e.g., partially created during wizard).
Returns a success message.""",
)
def delete_classification_model(request: Request, name: str):
config: FrigateConfig = request.app.frigate_config
if name not in config.classification.custom:
return JSONResponse(
content=(
{
"success": False,
"message": f"{name} is not a known classification model.",
}
),
status_code=404,
)
sanitized_name = sanitize_filename(name)
# Delete the classification model's data directory in clips
data_dir = os.path.join(CLIPS_DIR, sanitize_filename(name))
data_dir = os.path.join(CLIPS_DIR, sanitized_name)
if os.path.exists(data_dir):
shutil.rmtree(data_dir)
try:
shutil.rmtree(data_dir)
logger.info(f"Deleted classification data directory for {name}")
except Exception as e:
logger.debug(f"Failed to delete data directory for {name}: {e}")
# Delete the classification model's files in model_cache
model_dir = os.path.join(MODEL_CACHE_DIR, sanitize_filename(name))
model_dir = os.path.join(MODEL_CACHE_DIR, sanitized_name)
if os.path.exists(model_dir):
shutil.rmtree(model_dir)
try:
shutil.rmtree(model_dir)
logger.info(f"Deleted classification model directory for {name}")
except Exception as e:
logger.debug(f"Failed to delete model directory for {name}: {e}")
return JSONResponse(
content=(

View File

@ -177,6 +177,12 @@ class CameraConfig(FrigateBaseModel):
def ffmpeg_cmds(self) -> list[dict[str, list[str]]]:
return self._ffmpeg_cmds
def get_formatted_name(self) -> str:
"""Return the friendly name if set, otherwise return a formatted version of the camera name."""
if self.friendly_name:
return self.friendly_name
return self.name.replace("_", " ").title() if self.name else ""
def create_ffmpeg_cmds(self):
if "_ffmpeg_cmds" in self:
return

View File

@ -140,10 +140,6 @@ Evaluate in this order:
The mere presence of an unidentified person in private areas during late night hours is inherently suspicious and warrants human review, regardless of what activity they appear to be doing or how brief the sequence is.""",
title="Custom activity context prompt defining normal and suspicious activity patterns for this property.",
)
camera_context: str = Field(
default="",
title="Spatial context about the camera's field of view to help with descriptive accuracy. Should describe physical features and locations outside the frame.",
)
class ReviewConfig(FrigateBaseModel):

View File

@ -56,6 +56,12 @@ class ZoneConfig(BaseModel):
def contour(self) -> np.ndarray:
return self._contour
def get_formatted_name(self, zone_name: str) -> str:
"""Return the friendly name if set, otherwise return a formatted version of the zone name."""
if self.friendly_name:
return self.friendly_name
return zone_name.replace("_", " ").title()
@field_validator("objects", mode="before")
@classmethod
def validate_objects(cls, v):

View File

@ -4,7 +4,6 @@ import logging
import os
import sherpa_onnx
from faster_whisper.utils import download_model
from frigate.comms.inter_process import InterProcessRequestor
from frigate.const import MODEL_CACHE_DIR
@ -25,6 +24,9 @@ class AudioTranscriptionModelRunner:
if model_size == "large":
# use the Whisper download function instead of our own
# Import dynamically to avoid crashes on systems without AVX support
from faster_whisper.utils import download_model
logger.debug("Downloading Whisper audio transcription model")
download_model(
size_or_id="small" if device == "cuda" else "tiny",

View File

@ -6,7 +6,6 @@ import threading
import time
from typing import Optional
from faster_whisper import WhisperModel
from peewee import DoesNotExist
from frigate.comms.inter_process import InterProcessRequestor
@ -51,6 +50,9 @@ class AudioTranscriptionPostProcessor(PostProcessorApi):
def __build_recognizer(self) -> None:
try:
# Import dynamically to avoid crashes on systems without AVX support
from faster_whisper import WhisperModel
self.recognizer = WhisperModel(
model_size_or_path="small",
device="cuda"

View File

@ -16,6 +16,7 @@ from peewee import DoesNotExist
from frigate.comms.embeddings_updater import EmbeddingsRequestEnum
from frigate.comms.inter_process import InterProcessRequestor
from frigate.config import FrigateConfig
from frigate.config.camera import CameraConfig
from frigate.config.camera.review import GenAIReviewConfig, ImageSourceEnum
from frigate.const import CACHE_DIR, CLIPS_DIR, UPDATE_REVIEW_DESCRIPTION
from frigate.data_processing.types import PostProcessDataEnum
@ -30,6 +31,7 @@ from ..types import DataProcessorMetrics
logger = logging.getLogger(__name__)
RECORDING_BUFFER_EXTENSION_PERCENT = 0.10
MIN_RECORDING_DURATION = 10
class ReviewDescriptionProcessor(PostProcessorApi):
@ -90,7 +92,8 @@ class ReviewDescriptionProcessor(PostProcessorApi):
pixels_per_image = width * height
tokens_per_image = pixels_per_image / 1250
prompt_tokens = 3500
available_tokens = context_size * 0.98 - prompt_tokens
response_tokens = 300
available_tokens = context_size - prompt_tokens - response_tokens
max_frames = int(available_tokens / tokens_per_image)
return min(max(max_frames, 3), 20)
@ -129,7 +132,17 @@ class ReviewDescriptionProcessor(PostProcessorApi):
if image_source == ImageSourceEnum.recordings:
duration = final_data["end_time"] - final_data["start_time"]
buffer_extension = duration * RECORDING_BUFFER_EXTENSION_PERCENT
buffer_extension = min(
10, max(2, duration * RECORDING_BUFFER_EXTENSION_PERCENT)
)
# Ensure minimum total duration for short review items
# This provides better context for brief events
total_duration = duration + (2 * buffer_extension)
if total_duration < MIN_RECORDING_DURATION:
# Expand buffer to reach minimum duration, still respecting max of 10s per side
additional_buffer_per_side = (MIN_RECORDING_DURATION - duration) / 2
buffer_extension = min(10, additional_buffer_per_side)
thumbs = self.get_recording_frames(
camera,
@ -181,7 +194,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
self.requestor,
self.genai_client,
self.review_desc_speed,
camera,
camera_config,
final_data,
thumbs,
camera_config.review.genai,
@ -410,7 +423,7 @@ def run_analysis(
requestor: InterProcessRequestor,
genai_client: GenAIClient,
review_inference_speed: InferenceSpeed,
camera: str,
camera_config: CameraConfig,
final_data: dict[str, str],
thumbs: list[bytes],
genai_config: GenAIReviewConfig,
@ -418,10 +431,19 @@ def run_analysis(
attribute_labels: list[str],
) -> None:
start = datetime.datetime.now().timestamp()
# Format zone names using zone config friendly names if available
formatted_zones = []
for zone_name in final_data["data"]["zones"]:
if zone_name in camera_config.zones:
formatted_zones.append(
camera_config.zones[zone_name].get_formatted_name(zone_name)
)
analytics_data = {
"id": final_data["id"],
"camera": camera,
"zones": final_data["data"]["zones"],
"camera": camera_config.get_formatted_name(),
"zones": formatted_zones,
"start": datetime.datetime.fromtimestamp(final_data["start_time"]).strftime(
"%A, %I:%M %p"
),
@ -458,7 +480,6 @@ def run_analysis(
genai_config.preferred_language,
genai_config.debug_save_thumbnails,
genai_config.activity_context_prompt,
genai_config.camera_context,
)
review_inference_speed.update(datetime.datetime.now().timestamp() - start)

View File

@ -227,6 +227,9 @@ class CustomStateClassificationProcessor(RealTimeProcessorApi):
self.tensor_output_details[0]["index"]
)[0]
probs = res / res.sum(axis=0)
logger.debug(
f"{self.model_config.name} Ran state classification with probabilities: {probs}"
)
best_id = np.argmax(probs)
score = round(probs[best_id], 2)
self.__update_metrics(datetime.datetime.now().timestamp() - now)
@ -418,8 +421,8 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
obj_data["box"][2],
obj_data["box"][3],
max(
obj_data["box"][1] - obj_data["box"][0],
obj_data["box"][3] - obj_data["box"][2],
obj_data["box"][2] - obj_data["box"][0],
obj_data["box"][3] - obj_data["box"][1],
),
1.0,
)
@ -455,6 +458,9 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
self.tensor_output_details[0]["index"]
)[0]
probs = res / res.sum(axis=0)
logger.debug(
f"{self.model_config.name} Ran object classification with probabilities: {probs}"
)
best_id = np.argmax(probs)
score = round(probs[best_id], 2)
self.__update_metrics(datetime.datetime.now().timestamp() - now)
@ -546,5 +552,8 @@ def write_classification_attempt(
)
# delete oldest face image if maximum is reached
if len(files) > max_files:
os.unlink(os.path.join(folder, files[-1]))
try:
if len(files) > max_files:
os.unlink(os.path.join(folder, files[-1]))
except FileNotFoundError:
pass

View File

@ -423,7 +423,10 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
res = self.recognizer.classify(img)
if not res:
return
return {
"message": "No face was recognized.",
"success": False,
}
sub_label, score = res
@ -442,6 +445,13 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
)
shutil.move(current_file, new_file)
return {
"message": f"Successfully reprocessed face. Result: {sub_label} (score: {score:.2f})",
"success": True,
"face_name": sub_label,
"score": score,
}
def expire_object(self, object_id: str, camera: str):
if object_id in self.person_face_history:
self.person_face_history.pop(object_id)

View File

@ -3,6 +3,7 @@
import logging
import os
import platform
import threading
from abc import ABC, abstractmethod
from typing import Any
@ -161,12 +162,12 @@ class CudaGraphRunner(BaseModelRunner):
"""
@staticmethod
def is_complex_model(model_type: str) -> bool:
def is_model_supported(model_type: str) -> bool:
# Import here to avoid circular imports
from frigate.detectors.detector_config import ModelTypeEnum
from frigate.embeddings.types import EnrichmentModelTypeEnum
return model_type in [
return model_type not in [
ModelTypeEnum.yolonas.value,
EnrichmentModelTypeEnum.paddleocr.value,
EnrichmentModelTypeEnum.jina_v1.value,
@ -239,9 +240,31 @@ class OpenVINOModelRunner(BaseModelRunner):
EnrichmentModelTypeEnum.jina_v2.value,
]
@staticmethod
def is_model_npu_supported(model_type: str) -> bool:
# Import here to avoid circular imports
from frigate.embeddings.types import EnrichmentModelTypeEnum
return model_type not in [
EnrichmentModelTypeEnum.paddleocr.value,
EnrichmentModelTypeEnum.jina_v1.value,
EnrichmentModelTypeEnum.jina_v2.value,
EnrichmentModelTypeEnum.arcface.value,
]
def __init__(self, model_path: str, device: str, model_type: str, **kwargs):
self.model_path = model_path
self.device = device
self.model_type = model_type
if device == "NPU" and not OpenVINOModelRunner.is_model_npu_supported(
model_type
):
logger.warning(
f"OpenVINO model {model_type} is not supported on NPU, using GPU instead"
)
device = "GPU"
self.complex_model = OpenVINOModelRunner.is_complex_model(model_type)
if not os.path.isfile(model_path):
@ -269,6 +292,10 @@ class OpenVINOModelRunner(BaseModelRunner):
self.infer_request = self.compiled_model.create_infer_request()
self.input_tensor: ov.Tensor | None = None
# Thread lock to prevent concurrent inference (needed for JinaV2 which shares
# one runner between text and vision embeddings called from different threads)
self._inference_lock = threading.Lock()
if not self.complex_model:
try:
input_shape = self.compiled_model.inputs[0].get_shape()
@ -312,67 +339,81 @@ class OpenVINOModelRunner(BaseModelRunner):
Returns:
List of output tensors
"""
# Handle single input case for backward compatibility
if (
len(inputs) == 1
and len(self.compiled_model.inputs) == 1
and self.input_tensor is not None
):
# Single input case - use the pre-allocated tensor for efficiency
input_data = list(inputs.values())[0]
np.copyto(self.input_tensor.data, input_data)
self.infer_request.infer(self.input_tensor)
else:
if self.complex_model:
# Lock prevents concurrent access to infer_request
# Needed for JinaV2: genai thread (text) + embeddings thread (vision)
with self._inference_lock:
from frigate.embeddings.types import EnrichmentModelTypeEnum
if self.model_type in [EnrichmentModelTypeEnum.arcface.value]:
# For face recognition models, create a fresh infer_request
# for each inference to avoid state pollution that causes incorrect results.
self.infer_request = self.compiled_model.create_infer_request()
# Handle single input case for backward compatibility
if (
len(inputs) == 1
and len(self.compiled_model.inputs) == 1
and self.input_tensor is not None
):
# Single input case - use the pre-allocated tensor for efficiency
input_data = list(inputs.values())[0]
np.copyto(self.input_tensor.data, input_data)
self.infer_request.infer(self.input_tensor)
else:
if self.complex_model:
try:
# This ensures the model starts with a clean state for each sequence
# Important for RNN models like PaddleOCR recognition
self.infer_request.reset_state()
except Exception:
# this will raise an exception for models with AUTO set as the device
pass
# Multiple inputs case - set each input by name
for input_name, input_data in inputs.items():
# Find the input by name and its index
input_port = None
input_index = None
for idx, port in enumerate(self.compiled_model.inputs):
if port.get_any_name() == input_name:
input_port = port
input_index = idx
break
if input_port is None:
raise ValueError(f"Input '{input_name}' not found in model")
# Create tensor with the correct element type
input_element_type = input_port.get_element_type()
# Ensure input data matches the expected dtype to prevent type mismatches
# that can occur with models like Jina-CLIP v2 running on OpenVINO
expected_dtype = input_element_type.to_dtype()
if input_data.dtype != expected_dtype:
logger.debug(
f"Converting input '{input_name}' from {input_data.dtype} to {expected_dtype}"
)
input_data = input_data.astype(expected_dtype)
input_tensor = ov.Tensor(input_element_type, input_data.shape)
np.copyto(input_tensor.data, input_data)
# Set the input tensor for the specific port index
self.infer_request.set_input_tensor(input_index, input_tensor)
# Run inference
try:
# This ensures the model starts with a clean state for each sequence
# Important for RNN models like PaddleOCR recognition
self.infer_request.reset_state()
except Exception:
# this will raise an exception for models with AUTO set as the device
pass
self.infer_request.infer()
except Exception as e:
logger.error(f"Error during OpenVINO inference: {e}")
return []
# Multiple inputs case - set each input by name
for input_name, input_data in inputs.items():
# Find the input by name and its index
input_port = None
input_index = None
for idx, port in enumerate(self.compiled_model.inputs):
if port.get_any_name() == input_name:
input_port = port
input_index = idx
break
# Get all output tensors
outputs = []
for i in range(len(self.compiled_model.outputs)):
outputs.append(self.infer_request.get_output_tensor(i).data)
if input_port is None:
raise ValueError(f"Input '{input_name}' not found in model")
# Create tensor with the correct element type
input_element_type = input_port.get_element_type()
# Ensure input data matches the expected dtype to prevent type mismatches
# that can occur with models like Jina-CLIP v2 running on OpenVINO
expected_dtype = input_element_type.to_dtype()
if input_data.dtype != expected_dtype:
logger.debug(
f"Converting input '{input_name}' from {input_data.dtype} to {expected_dtype}"
)
input_data = input_data.astype(expected_dtype)
input_tensor = ov.Tensor(input_element_type, input_data.shape)
np.copyto(input_tensor.data, input_data)
# Set the input tensor for the specific port index
self.infer_request.set_input_tensor(input_index, input_tensor)
# Run inference
self.infer_request.infer()
# Get all output tensors
outputs = []
for i in range(len(self.compiled_model.outputs)):
outputs.append(self.infer_request.get_output_tensor(i).data)
return outputs
return outputs
class RKNNModelRunner(BaseModelRunner):
@ -500,7 +541,7 @@ def get_optimized_runner(
return OpenVINOModelRunner(model_path, device, model_type, **kwargs)
if (
not CudaGraphRunner.is_complex_model(model_type)
CudaGraphRunner.is_model_supported(model_type)
and providers[0] == "CUDAExecutionProvider"
):
options[0] = {

View File

@ -472,7 +472,7 @@ class Embeddings:
)
thumbnail_missing = True
except DoesNotExist:
logger.warning(
logger.debug(
f"Event ID {trigger.data} for trigger {trigger_name} does not exist."
)
continue

View File

@ -45,15 +45,13 @@ class GenAIClient:
preferred_language: str | None,
debug_save: bool,
activity_context_prompt: str,
camera_context: str = "",
) -> ReviewMetadata | None:
"""Generate a description for the review item activity."""
def get_concern_prompt() -> str:
if concerns:
concern_list = "\n - ".join(concerns)
return f"""
- `other_concerns` (list of strings): Include a list of any of the following concerns that are occurring:
return f"""- `other_concerns` (list of strings): Include a list of any of the following concerns that are occurring:
- {concern_list}"""
else:
return ""
@ -70,25 +68,13 @@ class GenAIClient:
else:
return "\n- (No objects detected)"
def get_camera_context_section() -> str:
if camera_context:
return f"""## Camera Spatial Context
Use this spatial information when writing the title and scene description to provide more accurate context about where activity is occurring or where people/objects are moving to/from.
{camera_context}"""
return ""
camera_context_section = get_camera_context_section()
context_prompt = f"""
Your task is to analyze the sequence of images ({len(thumbnails)} total) taken in chronological order from the perspective of the {review_data["camera"].replace("_", " ")} security camera.
Your task is to analyze the sequence of images ({len(thumbnails)} total) taken in chronological order from the perspective of the {review_data["camera"]} security camera.
## Normal Activity Patterns for This Property
{activity_context_prompt}
{camera_context_section}
## Task Instructions
Your task is to provide a clear, accurate description of the scene that:
@ -113,8 +99,8 @@ When forming your description:
## Response Format
Your response MUST be a flat JSON object with:
- `title` (string): A concise, direct title that describes the purpose or overall action, not just what you literally see. {"Use spatial context when available to make titles more meaningful." if camera_context_section else ""} Use names from "Objects in Scene" based on what you visually observe. If you see both a name and an unidentified object of the same type but visually observe only one person/object, use ONLY the name. Examples: "Joe walking dog", "Person taking out trash", "Joe accessing vehicle", "Person leaving porch for driveway", "Joe and person on front porch".
- `scene` (string): A narrative description of what happens across the sequence from start to finish. **Only describe actions you can actually observe happening in the frames provided.** Do not infer or assume actions that aren't visible (e.g., if you see someone walking but never see them sit, don't say they sat down). Include setting, detected objects, and their observable actions. Avoid speculation or filling in assumed behaviors. Your description should align with and support the threat level you assign.
- `title` (string): A concise, direct title that describes the primary action or event in the sequence, not just what you literally see. Use spatial context when available to make titles more meaningful. When multiple objects/actions are present, prioritize whichever is most prominent or occurs first. Use names from "Objects in Scene" based on what you visually observe. If you see both a name and an unidentified object of the same type but visually observe only one person/object, use ONLY the name. Examples: "Joe walking dog", "Person taking out trash", "Vehicle arriving in driveway", "Joe accessing vehicle", "Person leaving porch for driveway".
- `scene` (string): A narrative description of what happens across the sequence from start to finish, in chronological order. Start by describing how the sequence begins, then describe the progression of events. **Describe all significant movements and actions in the order they occur.** For example, if a vehicle arrives and then a person exits, describe both actions sequentially. **Only describe actions you can actually observe happening in the frames provided.** Do not infer or assume actions that aren't visible (e.g., if you see someone walking but never see them sit, don't say they sat down). Include setting, detected objects, and their observable actions. Avoid speculation or filling in assumed behaviors. Your description should align with and support the threat level you assign.
- `confidence` (float): 0-1 confidence in your analysis. Higher confidence when objects/actions are clearly visible and context is unambiguous. Lower confidence when the sequence is unclear, objects are partially obscured, or context is ambiguous.
- `potential_threat_level` (integer): 0, 1, or 2 as defined in "Normal Activity Patterns for This Property" above. Your threat level must be consistent with your scene description and the guidance above.
{get_concern_prompt()}
@ -123,7 +109,7 @@ Your response MUST be a flat JSON object with:
- Frame 1 = earliest, Frame {len(thumbnails)} = latest
- Activity started at {review_data["start"]} and lasted {review_data["duration"]} seconds
- Zones involved: {", ".join(z.replace("_", " ").title() for z in review_data["zones"]) or "None"}
- Zones involved: {", ".join(review_data["zones"]) if review_data["zones"] else "None"}
## Objects in Scene

View File

@ -407,6 +407,19 @@ class ReviewSegmentMaintainer(threading.Thread):
segment.last_detection_time = frame_time
for object in activity.get_all_objects():
# Alert-level objects should always be added (they extend/upgrade the segment)
# Detection-level objects should only be added if:
# - The segment is a detection segment (matching severity), OR
# - The segment is an alert AND the object started before the alert ended
# (objects starting after will be in the new detection segment)
is_alert_object = object in activity.categorized_objects["alerts"]
if not is_alert_object and segment.severity == SeverityEnum.alert:
# This is a detection-level object
# Only add if it started during the alert's active period
if object["start_time"] > segment.last_alert_time:
continue
if not object["sub_label"]:
segment.detections[object["id"]] = object["label"]
elif object["sub_label"][0] in self.config.model.all_attributes:

View File

@ -23,6 +23,7 @@ class ModelStatusTypesEnum(str, Enum):
error = "error"
training = "training"
complete = "complete"
failed = "failed"
class TrackedObjectUpdateTypesEnum(str, Enum):

View File

@ -1,5 +1,7 @@
"""Util for classification models."""
import datetime
import json
import logging
import os
import random
@ -27,10 +29,96 @@ from frigate.util.process import FrigateProcess
BATCH_SIZE = 16
EPOCHS = 50
LEARNING_RATE = 0.001
TRAINING_METADATA_FILE = ".training_metadata.json"
logger = logging.getLogger(__name__)
def write_training_metadata(model_name: str, image_count: int) -> None:
"""
Write training metadata to a hidden file in the model's clips directory.
Args:
model_name: Name of the classification model
image_count: Number of images used in training
"""
clips_model_dir = os.path.join(CLIPS_DIR, model_name)
os.makedirs(clips_model_dir, exist_ok=True)
metadata_path = os.path.join(clips_model_dir, TRAINING_METADATA_FILE)
metadata = {
"last_training_date": datetime.datetime.now().isoformat(),
"last_training_image_count": image_count,
}
try:
with open(metadata_path, "w") as f:
json.dump(metadata, f, indent=2)
logger.info(f"Wrote training metadata for {model_name}: {image_count} images")
except Exception as e:
logger.error(f"Failed to write training metadata for {model_name}: {e}")
def read_training_metadata(model_name: str) -> dict[str, any] | None:
"""
Read training metadata from the hidden file in the model's clips directory.
Args:
model_name: Name of the classification model
Returns:
Dictionary with last_training_date and last_training_image_count, or None if not found
"""
clips_model_dir = os.path.join(CLIPS_DIR, model_name)
metadata_path = os.path.join(clips_model_dir, TRAINING_METADATA_FILE)
if not os.path.exists(metadata_path):
return None
try:
with open(metadata_path, "r") as f:
metadata = json.load(f)
return metadata
except Exception as e:
logger.error(f"Failed to read training metadata for {model_name}: {e}")
return None
def get_dataset_image_count(model_name: str) -> int:
"""
Count the total number of images in the model's dataset directory.
Args:
model_name: Name of the classification model
Returns:
Total count of images across all categories
"""
dataset_dir = os.path.join(CLIPS_DIR, model_name, "dataset")
if not os.path.exists(dataset_dir):
return 0
total_count = 0
try:
for category in os.listdir(dataset_dir):
category_dir = os.path.join(dataset_dir, category)
if not os.path.isdir(category_dir):
continue
image_files = [
f
for f in os.listdir(category_dir)
if f.lower().endswith((".webp", ".png", ".jpg", ".jpeg"))
]
total_count += len(image_files)
except Exception as e:
logger.error(f"Failed to count dataset images for {model_name}: {e}")
return 0
return total_count
class ClassificationTrainingProcess(FrigateProcess):
def __init__(self, model_name: str) -> None:
super().__init__(
@ -42,7 +130,8 @@ class ClassificationTrainingProcess(FrigateProcess):
def run(self) -> None:
self.pre_run_setup()
self.__train_classification_model()
success = self.__train_classification_model()
exit(0 if success else 1)
def __generate_representative_dataset_factory(self, dataset_dir: str):
def generate_representative_dataset():
@ -65,85 +154,117 @@ class ClassificationTrainingProcess(FrigateProcess):
@redirect_output_to_logger(logger, logging.DEBUG)
def __train_classification_model(self) -> bool:
"""Train a classification model."""
try:
# import in the function so that tensorflow is not initialized multiple times
import tensorflow as tf
from tensorflow.keras import layers, models, optimizers
from tensorflow.keras.applications import MobileNetV2
from tensorflow.keras.preprocessing.image import ImageDataGenerator
# import in the function so that tensorflow is not initialized multiple times
import tensorflow as tf
from tensorflow.keras import layers, models, optimizers
from tensorflow.keras.applications import MobileNetV2
from tensorflow.keras.preprocessing.image import ImageDataGenerator
dataset_dir = os.path.join(CLIPS_DIR, self.model_name, "dataset")
model_dir = os.path.join(MODEL_CACHE_DIR, self.model_name)
os.makedirs(model_dir, exist_ok=True)
logger.info(f"Kicking off classification training for {self.model_name}.")
dataset_dir = os.path.join(CLIPS_DIR, self.model_name, "dataset")
model_dir = os.path.join(MODEL_CACHE_DIR, self.model_name)
os.makedirs(model_dir, exist_ok=True)
num_classes = len(
[
d
for d in os.listdir(dataset_dir)
if os.path.isdir(os.path.join(dataset_dir, d))
]
)
num_classes = len(
[
d
for d in os.listdir(dataset_dir)
if os.path.isdir(os.path.join(dataset_dir, d))
]
)
# Start with imagenet base model with 35% of channels in each layer
base_model = MobileNetV2(
input_shape=(224, 224, 3),
include_top=False,
weights="imagenet",
alpha=0.35,
)
base_model.trainable = False # Freeze pre-trained layers
if num_classes < 2:
logger.error(
f"Training failed for {self.model_name}: Need at least 2 classes, found {num_classes}"
)
return False
model = models.Sequential(
[
base_model,
layers.GlobalAveragePooling2D(),
layers.Dense(128, activation="relu"),
layers.Dropout(0.3),
layers.Dense(num_classes, activation="softmax"),
]
)
# Start with imagenet base model with 35% of channels in each layer
base_model = MobileNetV2(
input_shape=(224, 224, 3),
include_top=False,
weights="imagenet",
alpha=0.35,
)
base_model.trainable = False # Freeze pre-trained layers
model.compile(
optimizer=optimizers.Adam(learning_rate=LEARNING_RATE),
loss="categorical_crossentropy",
metrics=["accuracy"],
)
model = models.Sequential(
[
base_model,
layers.GlobalAveragePooling2D(),
layers.Dense(128, activation="relu"),
layers.Dropout(0.3),
layers.Dense(num_classes, activation="softmax"),
]
)
# create training set
datagen = ImageDataGenerator(rescale=1.0 / 255, validation_split=0.2)
train_gen = datagen.flow_from_directory(
dataset_dir,
target_size=(224, 224),
batch_size=BATCH_SIZE,
class_mode="categorical",
subset="training",
)
model.compile(
optimizer=optimizers.Adam(learning_rate=LEARNING_RATE),
loss="categorical_crossentropy",
metrics=["accuracy"],
)
# write labelmap
class_indices = train_gen.class_indices
index_to_class = {v: k for k, v in class_indices.items()}
sorted_classes = [index_to_class[i] for i in range(len(index_to_class))]
with open(os.path.join(model_dir, "labelmap.txt"), "w") as f:
for class_name in sorted_classes:
f.write(f"{class_name}\n")
# create training set
datagen = ImageDataGenerator(rescale=1.0 / 255, validation_split=0.2)
train_gen = datagen.flow_from_directory(
dataset_dir,
target_size=(224, 224),
batch_size=BATCH_SIZE,
class_mode="categorical",
subset="training",
)
# train the model
model.fit(train_gen, epochs=EPOCHS, verbose=0)
total_images = train_gen.samples
logger.debug(
f"Training {self.model_name}: {total_images} images across {num_classes} classes"
)
# convert model to tflite
converter = tf.lite.TFLiteConverter.from_keras_model(model)
converter.optimizations = [tf.lite.Optimize.DEFAULT]
converter.representative_dataset = (
self.__generate_representative_dataset_factory(dataset_dir)
)
converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
converter.inference_input_type = tf.uint8
converter.inference_output_type = tf.uint8
tflite_model = converter.convert()
# write labelmap
class_indices = train_gen.class_indices
index_to_class = {v: k for k, v in class_indices.items()}
sorted_classes = [index_to_class[i] for i in range(len(index_to_class))]
with open(os.path.join(model_dir, "labelmap.txt"), "w") as f:
for class_name in sorted_classes:
f.write(f"{class_name}\n")
# write model
with open(os.path.join(model_dir, "model.tflite"), "wb") as f:
f.write(tflite_model)
# train the model
logger.debug(f"Training {self.model_name} for {EPOCHS} epochs...")
model.fit(train_gen, epochs=EPOCHS, verbose=0)
logger.debug(f"Converting {self.model_name} to TFLite...")
# convert model to tflite
converter = tf.lite.TFLiteConverter.from_keras_model(model)
converter.optimizations = [tf.lite.Optimize.DEFAULT]
converter.representative_dataset = (
self.__generate_representative_dataset_factory(dataset_dir)
)
converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
converter.inference_input_type = tf.uint8
converter.inference_output_type = tf.uint8
tflite_model = converter.convert()
# write model
model_path = os.path.join(model_dir, "model.tflite")
with open(model_path, "wb") as f:
f.write(tflite_model)
# verify model file was written successfully
if not os.path.exists(model_path) or os.path.getsize(model_path) == 0:
logger.error(
f"Training failed for {self.model_name}: Model file was not created or is empty"
)
return False
# write training metadata with image count
dataset_image_count = get_dataset_image_count(self.model_name)
write_training_metadata(self.model_name, dataset_image_count)
logger.info(f"Finished training {self.model_name}")
return True
except Exception as e:
logger.error(f"Training failed for {self.model_name}: {e}", exc_info=True)
return False
def kickoff_model_training(
@ -165,18 +286,36 @@ def kickoff_model_training(
training_process.start()
training_process.join()
# reload model and mark training as complete
embeddingRequestor.send_data(
EmbeddingsRequestEnum.reload_classification_model.value,
{"model_name": model_name},
)
requestor.send_data(
UPDATE_MODEL_STATE,
{
"model": model_name,
"state": ModelStatusTypesEnum.complete,
},
)
# check if training succeeded by examining the exit code
training_success = training_process.exitcode == 0
if training_success:
# reload model and mark training as complete
embeddingRequestor.send_data(
EmbeddingsRequestEnum.reload_classification_model.value,
{"model_name": model_name},
)
requestor.send_data(
UPDATE_MODEL_STATE,
{
"model": model_name,
"state": ModelStatusTypesEnum.complete,
},
)
else:
logger.error(
f"Training subprocess failed for {model_name} (exit code: {training_process.exitcode})"
)
# mark training as failed so UI shows error state
# don't reload the model since it failed
requestor.send_data(
UPDATE_MODEL_STATE,
{
"model": model_name,
"state": ModelStatusTypesEnum.failed,
},
)
requestor.stop()

View File

@ -72,7 +72,10 @@
"formattedTimestampFilename": {
"12hour": "MM-dd-yy-h-mm-ss-a",
"24hour": "MM-dd-yy-HH-mm-ss"
}
},
"inProgress": "In progress",
"invalidStartTime": "Invalid start time",
"invalidEndTime": "Invalid end time"
},
"unit": {
"speed": {
@ -96,7 +99,9 @@
"back": "Go back",
"hide": "Hide {{item}}",
"show": "Show {{item}}",
"ID": "ID"
"ID": "ID",
"none": "None",
"all": "All"
},
"list": {
"two": "{{0}} and {{1}}",
@ -142,7 +147,8 @@
"unselect": "Unselect",
"export": "Export",
"deleteNow": "Delete Now",
"next": "Next"
"next": "Next",
"continue": "Continue"
},
"menu": {
"system": "System",
@ -235,6 +241,7 @@
"export": "Export",
"uiPlayground": "UI Playground",
"faceLibrary": "Face Library",
"classification": "Classification",
"user": {
"title": "User",
"account": "Account",

View File

@ -67,9 +67,6 @@
},
"activity_context_prompt": {
"label": "Custom activity context prompt defining normal activity patterns for this property."
},
"camera_context": {
"label": "Spatial context about the camera's field of view to help with descriptive accuracy. Should describe physical features and locations outside the frame. This is for spatial reference only and should NOT include subjective assessments."
}
}
}

View File

@ -13,6 +13,12 @@
"deleteModels": "Delete Models",
"editModel": "Edit Model"
},
"tooltip": {
"trainingInProgress": "Model is currently training",
"noNewImages": "No new images to train. Classify more images in the dataset first.",
"noChanges": "No changes to the dataset since last training.",
"modelNotReady": "Model is not ready for training"
},
"toast": {
"success": {
"deletedCategory": "Deleted Class",
@ -22,20 +28,25 @@
"categorizedImage": "Successfully Classified Image",
"trainedModel": "Successfully trained model.",
"trainingModel": "Successfully started model training.",
"updatedModel": "Successfully updated model configuration"
"updatedModel": "Successfully updated model configuration",
"renamedCategory": "Successfully renamed class to {{name}}"
},
"error": {
"deleteImageFailed": "Failed to delete: {{errorMessage}}",
"deleteCategoryFailed": "Failed to delete class: {{errorMessage}}",
"deleteModelFailed": "Failed to delete model: {{errorMessage}}",
"categorizeFailed": "Failed to categorize image: {{errorMessage}}",
"trainingFailed": "Failed to start model training: {{errorMessage}}",
"updateModelFailed": "Failed to update model: {{errorMessage}}"
"trainingFailed": "Model training failed. Check Frigate logs for details.",
"trainingFailedToStart": "Failed to start model training: {{errorMessage}}",
"updateModelFailed": "Failed to update model: {{errorMessage}}",
"renameCategoryFailed": "Failed to rename class: {{errorMessage}}"
}
},
"deleteCategory": {
"title": "Delete Class",
"desc": "Are you sure you want to delete the class {{name}}? This will permanently delete all associated images and require re-training the model."
"desc": "Are you sure you want to delete the class {{name}}? This will permanently delete all associated images and require re-training the model.",
"minClassesTitle": "Cannot Delete Class",
"minClassesDesc": "A classification model must have at least 2 classes. Add another class before deleting this one."
},
"deleteModel": {
"title": "Delete Classification Model",
@ -141,6 +152,8 @@
"step3": {
"selectImagesPrompt": "Select all images with: {{className}}",
"selectImagesDescription": "Click on images to select them. Click Continue when you're done with this class.",
"allImagesRequired_one": "Please classify all images. {{count}} image remaining.",
"allImagesRequired_other": "Please classify all images. {{count}} images remaining.",
"generating": {
"title": "Generating Sample Images",
"description": "Frigate is pulling representative images from your recordings. This may take a moment..."

View File

@ -24,8 +24,8 @@
"label": "Detail",
"noDataFound": "No detail data to review",
"aria": "Toggle detail view",
"trackedObject_one": "object",
"trackedObject_other": "objects",
"trackedObject_one": "{{count}} object",
"trackedObject_other": "{{count}} objects",
"noObjectDetailData": "No object detail data available.",
"settings": "Detail View Settings",
"alwaysExpandActive": {

View File

@ -35,7 +35,7 @@
"snapshot": "snapshot",
"thumbnail": "thumbnail",
"video": "video",
"object_lifecycle": "object lifecycle"
"tracking_details": "tracking details"
},
"trackingDetails": {
"title": "Tracking Details",

View File

@ -75,7 +75,7 @@
"deletedName_other": "{{count}} faces have been successfully deleted.",
"renamedFace": "Successfully renamed face to {{name}}",
"trainedFace": "Successfully trained face.",
"updatedFaceScore": "Successfully updated face score."
"updatedFaceScore": "Successfully updated face score to {{name}} ({{score}})."
},
"error": {
"uploadingImageFailed": "Failed to upload image: {{errorMessage}}",

View File

@ -8,7 +8,7 @@
"masksAndZones": "Mask and Zone Editor - Frigate",
"motionTuner": "Motion Tuner - Frigate",
"object": "Debug - Frigate",
"general": "General Settings - Frigate",
"general": "UI Settings - Frigate",
"frigatePlus": "Frigate+ Settings - Frigate",
"notifications": "Notification Settings - Frigate"
},
@ -37,7 +37,7 @@
"noCamera": "No Camera"
},
"general": {
"title": "General Settings",
"title": "UI Settings",
"liveDashboard": {
"title": "Live Dashboard",
"automaticLiveView": {
@ -51,6 +51,10 @@
"displayCameraNames": {
"label": "Always Show Camera Names",
"desc": "Always show the camera names in a chip in the multi-camera live view dashboard."
},
"liveFallbackTimeout": {
"label": "Live Player Fallback Timeout",
"desc": "When a camera's high quality live stream is unavailable, fall back to low bandwidth mode after this many seconds. Default: 3."
}
},
"storedLayouts": {
@ -154,6 +158,7 @@
"description": "Follow the steps below to add a new camera to your Frigate installation.",
"steps": {
"nameAndConnection": "Name & Connection",
"probeOrSnapshot": "Probe or Snapshot",
"streamConfiguration": "Stream Configuration",
"validationAndTesting": "Validation & Testing"
},
@ -172,7 +177,7 @@
"testFailed": "Stream test failed: {{error}}"
},
"step1": {
"description": "Enter your camera details and test the connection.",
"description": "Enter your camera details and choose to probe the camera or manually select the brand.",
"cameraName": "Camera Name",
"cameraNamePlaceholder": "e.g., front_door or Back Yard Overview",
"host": "Host/IP Address",
@ -188,33 +193,65 @@
"brandInformation": "Brand information",
"brandUrlFormat": "For cameras with the RTSP URL format as: {{exampleUrl}}",
"customUrlPlaceholder": "rtsp://username:password@host:port/path",
"testConnection": "Test Connection",
"testSuccess": "Connection test successful!",
"testFailed": "Connection test failed. Please check your input and try again.",
"streamDetails": "Stream Details",
"testing": {
"probingMetadata": "Probing camera metadata...",
"fetchingSnapshot": "Fetching camera snapshot..."
},
"warnings": {
"noSnapshot": "Unable to fetch a snapshot from the configured stream."
},
"connectionSettings": "Connection Settings",
"detectionMethod": "Stream Detection Method",
"onvifPort": "ONVIF Port",
"probeMode": "Probe camera",
"manualMode": "Manual selection",
"detectionMethodDescription": "Probe the camera with ONVIF (if supported) to find camera stream URLs, or manually select the camera brand to use pre-defined URLs. To enter a custom RTSP URL, choose the manual method and select \"Other\".",
"onvifPortDescription": "For cameras that support ONVIF, this is usually 80 or 8080.",
"useDigestAuth": "Use digest authentication",
"useDigestAuthDescription": "Use HTTP digest authentication for ONVIF. Some cameras may require a dedicated ONVIF username/password instead of the standard admin user.",
"errors": {
"brandOrCustomUrlRequired": "Either select a camera brand with host/IP or choose 'Other' with a custom URL",
"nameRequired": "Camera name is required",
"nameLength": "Camera name must be 64 characters or less",
"invalidCharacters": "Camera name contains invalid characters",
"nameExists": "Camera name already exists",
"customUrlRtspRequired": "Custom URLs must begin with \"rtsp://\". Manual configuration is required for non-RTSP camera streams.",
"brands": {
"reolink-rtsp": "Reolink RTSP is not recommended. Enable HTTP in the camera's firmware settings and restart the wizard."
}
},
"docs": {
"reolink": "https://docs.frigate.video/configuration/camera_specific.html#reolink-cameras"
"customUrlRtspRequired": "Custom URLs must begin with \"rtsp://\". Manual configuration is required for non-RTSP camera streams."
}
},
"step2": {
"description": "Probe the camera for available streams or configure manual settings based on your selected detection method.",
"testSuccess": "Connection test successful!",
"testFailed": "Connection test failed. Please check your input and try again.",
"testFailedTitle": "Test Failed",
"streamDetails": "Stream Details",
"probing": "Probing camera...",
"retry": "Retry",
"testing": {
"probingMetadata": "Probing camera metadata...",
"fetchingSnapshot": "Fetching camera snapshot..."
},
"probeFailed": "Failed to probe camera: {{error}}",
"probingDevice": "Probing device...",
"probeSuccessful": "Probe successful",
"probeError": "Probe Error",
"probeNoSuccess": "Probe unsuccessful",
"deviceInfo": "Device Information",
"manufacturer": "Manufacturer",
"model": "Model",
"firmware": "Firmware",
"profiles": "Profiles",
"ptzSupport": "PTZ Support",
"autotrackingSupport": "Autotracking Support",
"presets": "Presets",
"rtspCandidates": "RTSP Candidates",
"rtspCandidatesDescription": "The following RTSP URLs were found from the camera probe. Test the connection to view stream metadata.",
"noRtspCandidates": "No RTSP URLs were found from the camera. Your credentials may be incorrect, or the camera may not support ONVIF or the method used to retrieve RTSP URLs. Go back and enter the RTSP URL manually.",
"candidateStreamTitle": "Candidate {{number}}",
"useCandidate": "Use",
"uriCopy": "Copy",
"uriCopied": "URI copied to clipboard",
"testConnection": "Test Connection",
"toggleUriView": "Click to toggle full URI view",
"connected": "Connected",
"notConnected": "Not Connected",
"errors": {
"hostRequired": "Host/IP address is required"
}
},
"step3": {
"description": "Configure stream roles and add additional streams for your camera.",
"streamsTitle": "Camera Streams",
"addStream": "Add Stream",
@ -222,6 +259,9 @@
"streamTitle": "Stream {{number}}",
"streamUrl": "Stream URL",
"streamUrlPlaceholder": "rtsp://username:password@host:port/path",
"selectStream": "Select a stream",
"searchCandidates": "Search candidates...",
"noStreamFound": "No stream found",
"url": "URL",
"resolution": "Resolution",
"selectResolution": "Select resolution",
@ -253,7 +293,7 @@
"description": "Use go2rtc restreaming to reduce connections to your camera."
}
},
"step3": {
"step4": {
"description": "Final validation and analysis before saving your new camera. Connect each stream before saving.",
"validationTitle": "Stream Validation",
"connectAllStreams": "Connect All Streams",
@ -289,6 +329,9 @@
"audioCodecRecordError": "The AAC audio codec is required to support audio in recordings.",
"audioCodecRequired": "An audio stream is required to support audio detection.",
"restreamingWarning": "Reducing connections to the camera for the record stream may increase CPU usage slightly.",
"brands": {
"reolink-rtsp": "Reolink RTSP is not recommended. Enable HTTP in the camera's firmware settings and restart the wizard."
},
"dahua": {
"substreamWarning": "Substream 1 is locked to a low resolution. Many Dahua / Amcrest / EmpireTech cameras support additional substreams that need to be enabled in the camera's settings. It is recommended to check and utilize those streams if available."
},

View File

@ -148,13 +148,13 @@ export const ClassificationCard = forwardRef<
<div
className={cn(
"flex flex-col items-start text-white",
data.score ? "text-xs" : "text-sm",
data.score != undefined ? "text-xs" : "text-sm",
)}
>
<div className="smart-capitalize">
{data.name == "unknown" ? t("details.unknown") : data.name}
</div>
{data.score && (
{data.score != undefined && (
<div
className={cn(
"",

View File

@ -28,6 +28,7 @@ import {
CustomClassificationModelConfig,
FrigateConfig,
} from "@/types/frigateConfig";
import { ClassificationDatasetResponse } from "@/types/classification";
import { getTranslatedLabel } from "@/utils/i18n";
import { zodResolver } from "@hookform/resolvers/zod";
import axios from "axios";
@ -140,16 +141,19 @@ export default function ClassificationModelEditDialog({
});
// Fetch dataset to get current classes for state models
const { data: dataset } = useSWR<{
[id: string]: string[];
}>(isStateModel ? `classification/${model.name}/dataset` : null, {
revalidateOnFocus: false,
});
const { data: dataset } = useSWR<ClassificationDatasetResponse>(
isStateModel ? `classification/${model.name}/dataset` : null,
{
revalidateOnFocus: false,
},
);
// Update form with classes from dataset when loaded
useEffect(() => {
if (isStateModel && dataset) {
const classes = Object.keys(dataset).filter((key) => key !== "none");
if (isStateModel && dataset?.categories) {
const classes = Object.keys(dataset.categories).filter(
(key) => key !== "none",
);
if (classes.length > 0) {
(form as ReturnType<typeof useForm<StateFormData>>).setValue(
"classes",

View File

@ -15,6 +15,7 @@ import Step3ChooseExamples, {
} from "./wizard/Step3ChooseExamples";
import { cn } from "@/lib/utils";
import { isDesktop } from "react-device-detect";
import axios from "axios";
const OBJECT_STEPS = [
"wizard.steps.nameAndDefine",
@ -120,7 +121,18 @@ export default function ClassificationModelWizardDialog({
dispatch({ type: "PREVIOUS_STEP" });
};
const handleCancel = () => {
const handleCancel = async () => {
// Clean up any generated training images if we're cancelling from Step 3
if (wizardState.step1Data && wizardState.step3Data?.examplesGenerated) {
try {
await axios.delete(
`/classification/${wizardState.step1Data.modelName}`,
);
} catch (error) {
// Silently fail - user is already cancelling
}
}
dispatch({ type: "RESET" });
onClose();
};

View File

@ -10,6 +10,12 @@ import useSWR from "swr";
import { baseUrl } from "@/api/baseUrl";
import { isMobile } from "react-device-detect";
import { cn } from "@/lib/utils";
import {
Tooltip,
TooltipContent,
TooltipTrigger,
} from "@/components/ui/tooltip";
import { TooltipPortal } from "@radix-ui/react-tooltip";
export type Step3FormData = {
examplesGenerated: boolean;
@ -159,18 +165,15 @@ export default function Step3ChooseExamples({
const isLastClass = currentClassIndex === allClasses.length - 1;
if (isLastClass) {
// Assign remaining unclassified images
unknownImages.slice(0, 24).forEach((imageName) => {
if (!newClassifications[imageName]) {
// For state models with 2 classes, assign to the last class
// For object models, assign to "none"
if (step1Data.modelType === "state" && allClasses.length === 2) {
newClassifications[imageName] = allClasses[allClasses.length - 1];
} else {
// For object models, assign remaining unclassified images to "none"
// For state models, this should never happen since we require all images to be classified
if (step1Data.modelType !== "state") {
unknownImages.slice(0, 24).forEach((imageName) => {
if (!newClassifications[imageName]) {
newClassifications[imageName] = "none";
}
}
});
});
}
// All done, trigger training immediately
setImageClassifications(newClassifications);
@ -310,13 +313,44 @@ export default function Step3ChooseExamples({
return images;
}
return images.filter((img) => !imageClassifications[img]);
}, [unknownImages, imageClassifications]);
// If we're viewing a previous class (going back), show images for that class
// Otherwise show only unclassified images
const currentClassInView = allClasses[currentClassIndex];
return images.filter((img) => {
const imgClass = imageClassifications[img];
// Show if: unclassified OR classified with current class we're viewing
return !imgClass || imgClass === currentClassInView;
});
}, [unknownImages, imageClassifications, allClasses, currentClassIndex]);
const allImagesClassified = useMemo(() => {
return unclassifiedImages.length === 0;
}, [unclassifiedImages]);
// For state models on the last class, require all images to be classified
const isLastClass = currentClassIndex === allClasses.length - 1;
const canProceed = useMemo(() => {
if (step1Data.modelType === "state" && isLastClass) {
// Check if all 24 images will be classified after current selections are applied
const totalImages = unknownImages.slice(0, 24).length;
// Count images that will be classified (either already classified or currently selected)
const allImages = unknownImages.slice(0, 24);
const willBeClassified = allImages.filter((img) => {
return imageClassifications[img] || selectedImages.has(img);
}).length;
return willBeClassified >= totalImages;
}
return true;
}, [
step1Data.modelType,
isLastClass,
unknownImages,
imageClassifications,
selectedImages,
]);
const handleBack = useCallback(() => {
if (currentClassIndex > 0) {
const previousClass = allClasses[currentClassIndex - 1];
@ -438,20 +472,35 @@ export default function Step3ChooseExamples({
<Button type="button" onClick={handleBack} className="sm:flex-1">
{t("button.back", { ns: "common" })}
</Button>
<Button
type="button"
onClick={
allImagesClassified
? handleContinue
: handleContinueClassification
}
variant="select"
className="flex items-center justify-center gap-2 sm:flex-1"
disabled={!hasGenerated || isGenerating || isProcessing}
>
{isProcessing && <ActivityIndicator className="size-4" />}
{t("button.continue", { ns: "common" })}
</Button>
<Tooltip>
<TooltipTrigger asChild>
<Button
type="button"
onClick={
allImagesClassified
? handleContinue
: handleContinueClassification
}
variant="select"
className="flex items-center justify-center gap-2 sm:flex-1"
disabled={
!hasGenerated || isGenerating || isProcessing || !canProceed
}
>
{isProcessing && <ActivityIndicator className="size-4" />}
{t("button.continue", { ns: "common" })}
</Button>
</TooltipTrigger>
{!canProceed && (
<TooltipPortal>
<TooltipContent>
{t("wizard.step3.allImagesRequired", {
count: unclassifiedImages.length,
})}
</TooltipContent>
</TooltipPortal>
)}
</Tooltip>
</div>
)}
</div>

View File

@ -454,6 +454,24 @@ export function GeneralFilterContent({
onClose,
}: GeneralFilterContentProps) {
const { t } = useTranslation(["components/filter", "views/events"]);
const { data: config } = useSWR<FrigateConfig>("config", {
revalidateOnFocus: false,
});
const allAudioListenLabels = useMemo<string[]>(() => {
if (!config) {
return [];
}
const labels = new Set<string>();
Object.values(config.cameras).forEach((camera) => {
if (camera?.audio?.enabled) {
camera.audio.listen.forEach((label) => {
labels.add(label);
});
}
});
return [...labels].sort();
}, [config]);
return (
<>
<div className="scrollbar-container h-auto max-h-[80dvh] overflow-y-auto overflow-x-hidden">
@ -504,7 +522,10 @@ export function GeneralFilterContent({
{allLabels.map((item) => (
<FilterSwitch
key={item}
label={getTranslatedLabel(item)}
label={getTranslatedLabel(
item,
allAudioListenLabels.includes(item) ? "audio" : "object",
)}
isChecked={filter.labels?.includes(item) ?? false}
onCheckedChange={(isChecked) => {
if (isChecked) {

View File

@ -80,6 +80,9 @@ export function CameraLineGraph({
zoom: {
enabled: false,
},
animations: {
enabled: false,
},
},
colors: GRAPH_COLORS,
grid: {
@ -223,6 +226,9 @@ export function EventsPerSecondsLineGraph({
zoom: {
enabled: false,
},
animations: {
enabled: false,
},
},
colors: GRAPH_COLORS,
grid: {

View File

@ -25,6 +25,9 @@ export function StorageGraph({ graphId, used, total }: StorageGraphProps) {
zoom: {
enabled: false,
},
animations: {
enabled: false,
},
},
grid: {
show: false,

View File

@ -90,6 +90,9 @@ export function ThresholdBarGraph({
zoom: {
enabled: false,
},
animations: {
enabled: false,
},
},
colors: [
({ value }: { value: number }) => {

View File

@ -81,6 +81,43 @@ export default function InputWithTags({
revalidateOnFocus: false,
});
const allAudioListenLabels = useMemo<Set<string>>(() => {
if (!config) {
return new Set<string>();
}
const labels = new Set<string>();
Object.values(config.cameras).forEach((camera) => {
if (camera?.audio?.enabled) {
camera.audio.listen.forEach((label) => {
labels.add(label);
});
}
});
return labels;
}, [config]);
const translatedAudioLabelMap = useMemo<Map<string, string>>(() => {
const map = new Map<string, string>();
if (!config) return map;
allAudioListenLabels.forEach((label) => {
// getTranslatedLabel likely depends on i18n internally; including `lang`
// in deps ensures this map is rebuilt when language changes
map.set(label, getTranslatedLabel(label, "audio"));
});
return map;
}, [allAudioListenLabels, config]);
function resolveLabel(value: string) {
const mapped = translatedAudioLabelMap.get(value);
if (mapped) return mapped;
return getTranslatedLabel(
value,
allAudioListenLabels.has(value) ? "audio" : "object",
);
}
const [inputValue, setInputValue] = useState(search || "");
const [currentFilterType, setCurrentFilterType] = useState<FilterType | null>(
null,
@ -421,7 +458,8 @@ export default function InputWithTags({
? t("button.yes", { ns: "common" })
: t("button.no", { ns: "common" });
} else if (filterType === "labels") {
return getTranslatedLabel(String(filterValues));
const value = String(filterValues);
return resolveLabel(value);
} else if (filterType === "search_type") {
return t("filter.searchType." + String(filterValues));
} else {
@ -828,7 +866,7 @@ export default function InputWithTags({
>
{t("filter.label." + filterType)}:{" "}
{filterType === "labels" ? (
getTranslatedLabel(value)
resolveLabel(value)
) : filterType === "cameras" ? (
<CameraNameLabel camera={value} />
) : filterType === "zones" ? (

View File

@ -159,7 +159,7 @@ export default function CreateTriggerDialog({
});
const onSubmit = async (values: z.infer<typeof formSchema>) => {
if (trigger) {
if (trigger && existingTriggerNames.includes(trigger.name)) {
onEdit({ ...values });
} else {
onCreate(

View File

@ -12,13 +12,13 @@ export function ImageShadowOverlay({
<>
<div
className={cn(
"pointer-events-none absolute inset-x-0 top-0 z-10 h-[30%] w-full rounded-lg bg-gradient-to-b from-black/20 to-transparent md:rounded-2xl",
"pointer-events-none absolute inset-x-0 top-0 z-10 h-[30%] w-full rounded-lg bg-gradient-to-b from-black/20 to-transparent",
upperClassName,
)}
/>
<div
className={cn(
"pointer-events-none absolute inset-x-0 bottom-0 z-10 h-[10%] w-full rounded-lg bg-gradient-to-t from-black/20 to-transparent md:rounded-2xl",
"pointer-events-none absolute inset-x-0 bottom-0 z-10 h-[10%] w-full rounded-lg bg-gradient-to-t from-black/20 to-transparent",
lowerClassName,
)}
/>

View File

@ -55,29 +55,32 @@ export default function DetailActionsMenu({
</DropdownMenuTrigger>
<DropdownMenuPortal>
<DropdownMenuContent align="end">
<DropdownMenuItem>
<a
className="w-full"
href={`${baseUrl}api/events/${search.id}/snapshot.jpg?bbox=1`}
download={`${search.camera}_${search.label}.jpg`}
>
<div className="flex cursor-pointer items-center gap-2">
<span>{t("itemMenu.downloadSnapshot.label")}</span>
</div>
</a>
</DropdownMenuItem>
<DropdownMenuItem>
<a
className="w-full"
href={`${baseUrl}api/${search.camera}/${clipTimeRange}/clip.mp4`}
download
>
<div className="flex cursor-pointer items-center gap-2">
<span>{t("itemMenu.downloadVideo.label")}</span>
</div>
</a>
</DropdownMenuItem>
{search.has_snapshot && (
<DropdownMenuItem>
<a
className="w-full"
href={`${baseUrl}api/events/${search.id}/snapshot.jpg?bbox=1`}
download={`${search.camera}_${search.label}.jpg`}
>
<div className="flex cursor-pointer items-center gap-2">
<span>{t("itemMenu.downloadSnapshot.label")}</span>
</div>
</a>
</DropdownMenuItem>
)}
{search.has_clip && (
<DropdownMenuItem>
<a
className="w-full"
href={`${baseUrl}api/${search.camera}/${clipTimeRange}/clip.mp4`}
download
>
<div className="flex cursor-pointer items-center gap-2">
<span>{t("itemMenu.downloadVideo.label")}</span>
</div>
</a>
</DropdownMenuItem>
)}
{config?.semantic_search.enabled &&
setSimilarity != undefined &&

View File

@ -34,9 +34,11 @@ import ActivityIndicator from "@/components/indicators/activity-indicator";
import {
FaArrowRight,
FaCheckCircle,
FaChevronDown,
FaChevronLeft,
FaChevronRight,
FaMicrophone,
FaCheck,
FaTimes,
} from "react-icons/fa";
import { TrackingDetails } from "./TrackingDetails";
import { AnnotationSettingsPane } from "./AnnotationSettingsPane";
@ -72,7 +74,12 @@ import {
PopoverContent,
PopoverTrigger,
} from "@/components/ui/popover";
import { Drawer, DrawerContent, DrawerTrigger } from "@/components/ui/drawer";
import {
Drawer,
DrawerContent,
DrawerTitle,
DrawerTrigger,
} from "@/components/ui/drawer";
import { LuInfo } from "react-icons/lu";
import { TooltipPortal } from "@radix-ui/react-tooltip";
import { FaPencilAlt } from "react-icons/fa";
@ -84,6 +91,7 @@ import { CameraNameLabel } from "@/components/camera/FriendlyNameLabel";
import { DialogPortal } from "@radix-ui/react-dialog";
import { useDetailStream } from "@/context/detail-stream-context";
import { PiSlidersHorizontalBold } from "react-icons/pi";
import { HiSparkles } from "react-icons/hi";
const SEARCH_TABS = ["snapshot", "tracking_details"] as const;
export type SearchTab = (typeof SEARCH_TABS)[number];
@ -126,7 +134,7 @@ function TabsWithActions({
return (
<div className="flex items-center justify-between gap-1">
<ScrollArea className="flex-1 whitespace-nowrap">
<div className="mb-2 flex flex-row md:mb-0">
<div className="mb-2 flex flex-row">
<ToggleGroup
className="*:rounded-md *:px-3 *:py-4"
type="single"
@ -224,6 +232,7 @@ function AnnotationSettings({
const Overlay = isDesktop ? Popover : Drawer;
const Trigger = isDesktop ? PopoverTrigger : DrawerTrigger;
const Content = isDesktop ? PopoverContent : DrawerContent;
const Title = isDesktop ? "div" : DrawerTitle;
const contentProps = isDesktop
? { align: "end" as const, container: container ?? undefined }
: {};
@ -248,7 +257,9 @@ function AnnotationSettings({
<PiSlidersHorizontalBold className="size-5" />
</Button>
</Trigger>
<Title className="sr-only">
{t("trackingDetails.adjustAnnotationSettings")}
</Title>
<Content
className={
isDesktop
@ -306,7 +317,7 @@ function DialogContentComponent({
if (page === "tracking_details") {
return (
<TrackingDetails
className={cn("size-full", !isDesktop && "flex flex-col gap-4")}
className={cn(isDesktop ? "size-full" : "flex flex-col gap-4")}
event={search as unknown as Event}
tabs={
isDesktop ? (
@ -340,7 +351,12 @@ function DialogContentComponent({
}
/>
) : (
<div className={cn(!isDesktop ? "mb-4 w-full" : "size-full")}>
<div
className={cn(
"max-w-lg",
!isDesktop ? "mb-4 w-full" : "mx-auto size-full",
)}
>
<img
className="w-full select-none rounded-lg object-contain transition-opacity"
style={
@ -359,16 +375,11 @@ function DialogContentComponent({
if (isDesktop) {
return (
<div className="flex h-full gap-4 overflow-hidden">
<div
className={cn(
"scrollbar-container flex-[3] overflow-y-hidden",
!search.has_snapshot && "flex-[2]",
)}
>
<div className="grid h-full w-full grid-cols-[60%_40%] gap-4">
<div className="scrollbar-container min-w-0 overflow-y-auto overflow-x-hidden">
{snapshotElement}
</div>
<div className="flex flex-col gap-4 overflow-hidden md:basis-2/5">
<div className="flex min-w-0 flex-col gap-4 pr-2">
<TabsWithActions
search={search}
searchTabs={searchTabs}
@ -381,7 +392,7 @@ function DialogContentComponent({
setIsPopoverOpen={setIsPopoverOpen}
dialogContainer={dialogContainer}
/>
<div className="scrollbar-container flex-1 overflow-y-auto">
<div className="scrollbar-container min-w-0 flex-1 overflow-y-auto overflow-x-hidden px-4">
<ObjectDetailsTab
search={search}
config={config}
@ -584,8 +595,13 @@ export default function SearchDetailDialog({
"scrollbar-container overflow-y-auto",
isDesktop &&
"max-h-[95dvh] sm:max-w-xl md:max-w-4xl lg:max-w-[70%]",
isMobile && "px-4",
isMobile && "flex h-full flex-col px-4",
)}
onEscapeKeyDown={(event) => {
if (isPopoverOpen) {
event.preventDefault();
}
}}
onInteractOutside={(e) => {
if (isPopoverOpen) {
e.preventDefault();
@ -596,7 +612,7 @@ export default function SearchDetailDialog({
}
}}
>
<Header>
<Header className={cn(!isDesktop && "top-0 z-[60] mb-0")}>
<Title>{t("trackedObjectDetails")}</Title>
<Description className="sr-only">
{t("trackedObjectDetails")}
@ -676,6 +692,8 @@ function ObjectDetailsTab({
const [desc, setDesc] = useState(search?.data.description);
const [isSubLabelDialogOpen, setIsSubLabelDialogOpen] = useState(false);
const [isLPRDialogOpen, setIsLPRDialogOpen] = useState(false);
const [isEditingDesc, setIsEditingDesc] = useState(false);
const originalDescRef = useRef<string | null>(null);
const handleDescriptionFocus = useCallback(() => {
setInputFocused(true);
@ -1078,15 +1096,51 @@ function ObjectDetailsTab({
});
setState("submitted");
setSearch({
...search,
plus_id: "new_upload",
});
mutate(
(key) =>
typeof key === "string" &&
(key.includes("events") ||
key.includes("events/search") ||
key.includes("events/explore")),
(currentData: SearchResult[][] | SearchResult[] | undefined) => {
if (!currentData) return currentData;
// optimistic update
return currentData
.flat()
.map((event) =>
event.id === search.id
? { ...event, plus_id: "new_upload" }
: event,
);
},
{
optimisticData: true,
rollbackOnError: true,
revalidate: false,
},
);
},
[search, setSearch],
[search, mutate],
);
const popoverContainerRef = useRef<HTMLDivElement | null>(null);
const canRegenerate = !!(
config?.cameras[search.camera].objects.genai.enabled && search.end_time
);
const showGenAIPlaceholder = !!(
config?.cameras[search.camera].objects.genai.enabled &&
!search.end_time &&
(config.cameras[search.camera].objects.genai.required_zones.length === 0 ||
search.zones.some((zone) =>
config.cameras[search.camera].objects.genai.required_zones.includes(
zone,
),
)) &&
(config.cameras[search.camera].objects.genai.objects.length === 0 ||
config.cameras[search.camera].objects.genai.objects.includes(
search.label,
))
);
return (
<div ref={popoverContainerRef} className="flex flex-col gap-5">
<div className="flex w-full flex-row">
@ -1101,7 +1155,7 @@ function ObjectDetailsTab({
</div>
<div className="flex flex-row items-center gap-2 text-sm smart-capitalize">
{getIconForLabel(search.label, "size-4 text-primary")}
{getTranslatedLabel(search.label)}
{getTranslatedLabel(search.label, search.data.type)}
{search.sub_label && ` (${search.sub_label})`}
{isAdmin && search.end_time && (
<Tooltip>
@ -1243,8 +1297,8 @@ function ObjectDetailsTab({
</div>
{search.data.type === "object" &&
!search.plus_id &&
config?.plus?.enabled && (
config?.plus?.enabled &&
search.has_snapshot && (
<div
className={cn(
"my-2 flex w-full flex-col justify-between gap-1.5",
@ -1340,82 +1394,77 @@ function ObjectDetailsTab({
{state == "submitted" && (
<div className="flex flex-row items-center justify-center gap-2">
<FaCheckCircle className="size-4 text-success" />
{t("explore.plus.review.state.submitted")}
{t("explore.plus.review.state.submitted", {
ns: "components/dialog",
})}
</div>
)}
</div>
</div>
)}
<div className="flex flex-col gap-1.5">
{config?.cameras[search.camera].objects.genai.enabled &&
!search.end_time &&
(config.cameras[search.camera].objects.genai.required_zones.length ===
0 ||
search.zones.some((zone) =>
config.cameras[search.camera].objects.genai.required_zones.includes(
zone,
),
)) &&
(config.cameras[search.camera].objects.genai.objects.length === 0 ||
config.cameras[search.camera].objects.genai.objects.includes(
search.label,
)) ? (
<>
<div className="text-sm text-primary/40">
{t("details.description.label")}
</div>
<div className="flex h-64 flex-col items-center justify-center gap-3 border p-4 text-sm text-primary/40">
<div className="flex">
<ActivityIndicator />
</div>
<div className="flex">{t("details.description.aiTips")}</div>
</div>
</>
) : (
<>
<div className="text-sm text-primary/40"></div>
<Textarea
className="text-md h-64"
placeholder={t("details.description.placeholder")}
value={desc}
onChange={(e) => setDesc(e.target.value)}
onFocus={handleDescriptionFocus}
onBlur={handleDescriptionBlur}
/>
</>
)}
<div className="flex w-full flex-row justify-end gap-2">
{config?.cameras[search?.camera].audio_transcription.enabled &&
search?.label == "speech" &&
search?.end_time && (
<Button onClick={onTranscribe}>
<div className="flex gap-1">
{t("itemMenu.audioTranscription.label")}
</div>
</Button>
)}
{config?.cameras[search.camera].objects.genai.enabled &&
search.end_time && (
<div className="flex items-start">
<Button
className="rounded-r-none border-r-0"
aria-label={t("details.button.regenerate.label")}
onClick={() => regenerateDescription("thumbnails")}
<div className="flex items-center justify-start gap-3">
<div className="text-sm text-primary/40">
{t("details.description.label")}
</div>
<div className="flex items-center gap-3">
<Tooltip>
<TooltipTrigger asChild>
<button
aria-label={t("button.edit", { ns: "common" })}
className="text-primary/40 hover:text-primary/80"
onClick={() => {
originalDescRef.current = desc ?? "";
setIsEditingDesc(true);
}}
>
{t("details.button.regenerate.title")}
</Button>
{search.has_snapshot && (
<DropdownMenu>
<DropdownMenuTrigger asChild>
<Button
className="rounded-l-none border-l-0 px-2"
aria-label={t("details.expandRegenerationMenu")}
>
<FaChevronDown className="size-3" />
</Button>
</DropdownMenuTrigger>
<DropdownMenuContent>
<FaPencilAlt className="size-4" />
</button>
</TooltipTrigger>
<TooltipContent>
{t("button.edit", { ns: "common" })}
</TooltipContent>
</Tooltip>
{config?.cameras[search?.camera].audio_transcription.enabled &&
search?.label == "speech" &&
search?.end_time && (
<Tooltip>
<TooltipTrigger asChild>
<button
aria-label={t("itemMenu.audioTranscription.label")}
className="text-primary/40 hover:text-primary/80"
onClick={onTranscribe}
>
<FaMicrophone className="size-4" />
</button>
</TooltipTrigger>
<TooltipContent>
{t("itemMenu.audioTranscription.label")}
</TooltipContent>
</Tooltip>
)}
{canRegenerate && (
<div className="relative">
<DropdownMenu>
<Tooltip>
<TooltipTrigger asChild>
<DropdownMenuTrigger asChild>
<button
aria-label={t("details.button.regenerate.label")}
className="text-primary/40 hover:text-primary/80"
>
<HiSparkles className="size-4" />
</button>
</DropdownMenuTrigger>
</TooltipTrigger>
<TooltipContent>
{t("details.button.regenerate.title")}
</TooltipContent>
</Tooltip>
<DropdownMenuContent>
{search.has_snapshot && (
<DropdownMenuItem
className="cursor-pointer"
aria-label={t("details.regenerateFromSnapshot")}
@ -1423,61 +1472,115 @@ function ObjectDetailsTab({
>
{t("details.regenerateFromSnapshot")}
</DropdownMenuItem>
<DropdownMenuItem
className="cursor-pointer"
aria-label={t("details.regenerateFromThumbnails")}
onClick={() => regenerateDescription("thumbnails")}
>
{t("details.regenerateFromThumbnails")}
</DropdownMenuItem>
</DropdownMenuContent>
</DropdownMenu>
)}
)}
<DropdownMenuItem
className="cursor-pointer"
aria-label={t("details.regenerateFromThumbnails")}
onClick={() => regenerateDescription("thumbnails")}
>
{t("details.regenerateFromThumbnails")}
</DropdownMenuItem>
</DropdownMenuContent>
</DropdownMenu>
</div>
)}
{((config?.cameras[search.camera].objects.genai.enabled &&
search.end_time) ||
!config?.cameras[search.camera].objects.genai.enabled) && (
<Button
variant="select"
aria-label={t("button.save", { ns: "common" })}
onClick={updateDescription}
>
{t("button.save", { ns: "common" })}
</Button>
)}
<TextEntryDialog
open={isSubLabelDialogOpen}
setOpen={setIsSubLabelDialogOpen}
title={t("details.editSubLabel.title")}
description={
search.label
? t("details.editSubLabel.desc", {
label: search.label,
})
: t("details.editSubLabel.descNoLabel")
}
onSave={handleSubLabelSave}
defaultValue={search?.sub_label || ""}
allowEmpty={true}
/>
<TextEntryDialog
open={isLPRDialogOpen}
setOpen={setIsLPRDialogOpen}
title={t("details.editLPR.title")}
description={
search.label
? t("details.editLPR.desc", {
label: search.label,
})
: t("details.editLPR.descNoLabel")
}
onSave={handleLPRSave}
defaultValue={search?.data.recognized_license_plate || ""}
allowEmpty={true}
/>
</div>
</div>
{!isEditingDesc ? (
showGenAIPlaceholder ? (
<div className="flex h-32 flex-col items-center justify-center gap-3 border p-4 text-sm text-primary/40">
<div className="flex">
<ActivityIndicator />
</div>
<div className="flex">{t("details.description.aiTips")}</div>
</div>
) : (
<div className="overflow-auto text-sm text-primary">
{desc || t("label.none", { ns: "common" })}
</div>
)
) : (
<div className="flex flex-col gap-2">
<Textarea
className="text-md h-32"
placeholder={t("details.description.placeholder")}
value={desc}
onChange={(e) => setDesc(e.target.value)}
onFocus={handleDescriptionFocus}
onBlur={handleDescriptionBlur}
autoFocus
/>
<div className="flex flex-row justify-end gap-4">
<Tooltip>
<TooltipTrigger asChild>
<button
aria-label={t("button.save", { ns: "common" })}
className="text-primary/40 hover:text-primary/80"
onClick={() => {
setIsEditingDesc(false);
updateDescription();
}}
>
<FaCheck className="size-4" />
</button>
</TooltipTrigger>
<TooltipContent>
{t("button.save", { ns: "common" })}
</TooltipContent>
</Tooltip>
<Tooltip>
<TooltipTrigger asChild>
<button
aria-label={t("button.cancel", { ns: "common" })}
className="text-primary/40 hover:text-primary"
onClick={() => {
setIsEditingDesc(false);
setDesc(originalDescRef.current ?? "");
}}
>
<FaTimes className="size-4" />
</button>
</TooltipTrigger>
<TooltipContent>
{t("button.cancel", { ns: "common" })}
</TooltipContent>
</Tooltip>
</div>
</div>
)}
<TextEntryDialog
open={isSubLabelDialogOpen}
setOpen={setIsSubLabelDialogOpen}
title={t("details.editSubLabel.title")}
description={
search.label
? t("details.editSubLabel.desc", {
label: search.label,
})
: t("details.editSubLabel.descNoLabel")
}
onSave={handleSubLabelSave}
defaultValue={search?.sub_label || ""}
allowEmpty={true}
/>
<TextEntryDialog
open={isLPRDialogOpen}
setOpen={setIsLPRDialogOpen}
title={t("details.editLPR.title")}
description={
search.label
? t("details.editLPR.desc", {
label: search.label,
})
: t("details.editLPR.descNoLabel")
}
onSave={handleLPRSave}
defaultValue={search?.data.recognized_license_plate || ""}
allowEmpty={true}
/>
</div>
</div>
);

View File

@ -343,6 +343,10 @@ export function TrackingDetails({
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [displayedRecordTime]);
const onUploadFrameToPlus = useCallback(() => {
return axios.post(`/${event.camera}/plus/${currentTime}`);
}, [event.camera, currentTime]);
if (!config) {
return <ActivityIndicator />;
}
@ -352,7 +356,8 @@ export function TrackingDetails({
className={cn(
isDesktop
? "flex size-full justify-evenly gap-4 overflow-hidden"
: "flex size-full flex-col gap-2",
: "flex flex-col gap-2",
!isDesktop && cameraAspect === "tall" && "size-full",
className,
)}
>
@ -387,6 +392,7 @@ export function TrackingDetails({
frigateControls={true}
onTimeUpdate={handleTimeUpdate}
onSeekToTime={handleSeekToTime}
onUploadFrame={onUploadFrameToPlus}
isDetailMode={true}
camera={event.camera}
currentTimeOverride={currentTime}
@ -453,7 +459,7 @@ export function TrackingDetails({
)}
>
{isDesktop && tabs && (
<div className="mb-4 flex items-center justify-between">
<div className="mb-2 flex items-center justify-between">
<div className="flex-1">{tabs}</div>
</div>
)}
@ -719,9 +725,13 @@ function LifecycleIconRow({
backgroundColor: `rgb(${color})`,
}}
/>
<span className="smart-capitalize">
{item.data?.zones_friendly_names?.[zidx] ??
zone.replaceAll("_", " ")}
<span
className={cn(
item.data?.zones_friendly_names?.[zidx] === zone &&
"smart-capitalize",
)}
>
{item.data?.zones_friendly_names?.[zidx]}
</span>
</Badge>
);

View File

@ -77,7 +77,10 @@ export default function BirdseyeLivePlayer({
)}
onClick={onClick}
>
<ImageShadowOverlay />
<ImageShadowOverlay
upperClassName="md:rounded-2xl"
lowerClassName="md:rounded-2xl"
/>
<div className="size-full" ref={playerRef}>
{player}
</div>

View File

@ -331,7 +331,10 @@ export default function LivePlayer({
>
{cameraEnabled &&
((showStillWithoutActivity && !liveReady) || liveReady) && (
<ImageShadowOverlay />
<ImageShadowOverlay
upperClassName="md:rounded-2xl"
lowerClassName="md:rounded-2xl"
/>
)}
{player}
{cameraEnabled &&

View File

@ -1,4 +1,5 @@
import { baseUrl } from "@/api/baseUrl";
import { usePersistence } from "@/hooks/use-persistence";
import {
LivePlayerError,
PlayerStatsType,
@ -71,6 +72,8 @@ function MSEPlayer({
const [errorCount, setErrorCount] = useState<number>(0);
const totalBytesLoaded = useRef(0);
const [fallbackTimeout] = usePersistence<number>("liveFallbackTimeout", 3);
const videoRef = useRef<HTMLVideoElement>(null);
const wsRef = useRef<WebSocket | null>(null);
const reconnectTIDRef = useRef<number | null>(null);
@ -475,7 +478,10 @@ function MSEPlayer({
setBufferTimeout(undefined);
}
const timeoutDuration = bufferTime == 0 ? 5000 : 3000;
const timeoutDuration =
bufferTime == 0
? (fallbackTimeout ?? 3) * 2 * 1000
: (fallbackTimeout ?? 3) * 1000;
setBufferTimeout(
setTimeout(() => {
if (
@ -500,6 +506,7 @@ function MSEPlayer({
onError,
onPlaying,
playbackEnabled,
fallbackTimeout,
]);
useEffect(() => {

View File

@ -12,15 +12,15 @@ import { toast } from "sonner";
import useSWR from "swr";
import axios from "axios";
import Step1NameCamera from "@/components/settings/wizard/Step1NameCamera";
import Step2StreamConfig from "@/components/settings/wizard/Step2StreamConfig";
import Step3Validation from "@/components/settings/wizard/Step3Validation";
import Step2ProbeOrSnapshot from "@/components/settings/wizard/Step2ProbeOrSnapshot";
import Step3StreamConfig from "@/components/settings/wizard/Step3StreamConfig";
import Step4Validation from "@/components/settings/wizard/Step4Validation";
import type {
WizardFormData,
CameraConfigData,
ConfigSetBody,
} from "@/types/cameraWizard";
import { processCameraName } from "@/utils/cameraUtil";
import { isDesktop } from "react-device-detect";
import { cn } from "@/lib/utils";
type WizardState = {
@ -57,6 +57,7 @@ const wizardReducer = (
const STEPS = [
"cameraWizard.steps.nameAndConnection",
"cameraWizard.steps.probeOrSnapshot",
"cameraWizard.steps.streamConfiguration",
"cameraWizard.steps.validationAndTesting",
];
@ -100,20 +101,20 @@ export default function CameraWizardDialog({
const canProceedToNext = useCallback((): boolean => {
switch (currentStep) {
case 0:
// Can proceed if camera name is set and at least one stream exists
return !!(
state.wizardData.cameraName &&
(state.wizardData.streams?.length ?? 0) > 0
);
// Step 1: Can proceed if camera name is set
return !!state.wizardData.cameraName;
case 1:
// Can proceed if at least one stream has 'detect' role
// Step 2: Can proceed if at least one stream exists (from probe or manual test)
return (state.wizardData.streams?.length ?? 0) > 0;
case 2:
// Step 3: Can proceed if at least one stream has 'detect' role
return !!(
state.wizardData.streams?.some((stream) =>
stream.roles.includes("detect"),
) ?? false
);
case 2:
// Always can proceed from final step (save will be handled there)
case 3:
// Step 4: Always can proceed from final step (save will be handled there)
return true;
default:
return false;
@ -340,13 +341,7 @@ export default function CameraWizardDialog({
<Dialog open={open} onOpenChange={handleClose}>
<DialogContent
className={cn(
"max-h-[90dvh] max-w-xl overflow-y-auto",
isDesktop &&
currentStep == 0 &&
state.wizardData?.streams?.[0]?.testResult?.snapshot &&
"max-w-4xl",
isDesktop && currentStep == 1 && "max-w-2xl",
isDesktop && currentStep > 1 && "max-w-4xl",
"scrollbar-container max-h-[90dvh] max-w-3xl overflow-y-auto",
)}
onInteractOutside={(e) => {
e.preventDefault();
@ -385,7 +380,16 @@ export default function CameraWizardDialog({
/>
)}
{currentStep === 1 && (
<Step2StreamConfig
<Step2ProbeOrSnapshot
wizardData={state.wizardData}
onUpdate={onUpdate}
onNext={handleNext}
onBack={handleBack}
probeMode={state.wizardData.probeMode ?? true}
/>
)}
{currentStep === 2 && (
<Step3StreamConfig
wizardData={state.wizardData}
onUpdate={onUpdate}
onBack={handleBack}
@ -393,8 +397,8 @@ export default function CameraWizardDialog({
canProceed={canProceedToNext()}
/>
)}
{currentStep === 2 && (
<Step3Validation
{currentStep === 3 && (
<Step4Validation
wizardData={state.wizardData}
onUpdate={onUpdate}
onSave={handleSave}

View File

@ -576,6 +576,7 @@ export default function ZoneEditPane({
control={form.control}
nameField="friendly_name"
idField="name"
idVisible={(polygon && polygon.name.length > 0) ?? false}
nameLabel={t("masksAndZones.zones.name.title")}
nameDescription={t("masksAndZones.zones.name.tips")}
placeholderName={t("masksAndZones.zones.name.inputPlaceHolder")}

View File

@ -0,0 +1,363 @@
import { useTranslation } from "react-i18next";
import { Card, CardContent } from "@/components/ui/card";
import { Button } from "@/components/ui/button";
import ActivityIndicator from "@/components/indicators/activity-indicator";
import { FaCopy, FaCheck } from "react-icons/fa";
import { LuX } from "react-icons/lu";
import { CiCircleAlert } from "react-icons/ci";
import { Alert, AlertDescription, AlertTitle } from "@/components/ui/alert";
import { useState } from "react";
import { toast } from "sonner";
import type {
OnvifProbeResponse,
OnvifRtspCandidate,
TestResult,
CandidateTestMap,
} from "@/types/cameraWizard";
import { FaCircleCheck } from "react-icons/fa6";
import { cn } from "@/lib/utils";
import { maskUri } from "@/utils/cameraUtil";
type OnvifProbeResultsProps = {
isLoading: boolean;
isError: boolean;
error?: string;
probeResult?: OnvifProbeResponse;
onRetry: () => void;
selectedUris?: string[];
testCandidate?: (uri: string) => void;
candidateTests?: CandidateTestMap;
testingCandidates?: Record<string, boolean>;
};
export default function OnvifProbeResults({
isLoading,
isError,
error,
probeResult,
onRetry,
selectedUris,
testCandidate,
candidateTests,
testingCandidates,
}: OnvifProbeResultsProps) {
const { t } = useTranslation(["views/settings"]);
const [copiedUri, setCopiedUri] = useState<string | null>(null);
const handleCopyUri = (uri: string) => {
navigator.clipboard.writeText(uri);
setCopiedUri(uri);
toast.success(t("cameraWizard.step2.uriCopied"));
setTimeout(() => setCopiedUri(null), 2000);
};
if (isLoading) {
return (
<div className="flex flex-col items-center justify-center gap-4 py-8">
<ActivityIndicator className="size-6" />
<p className="text-sm text-muted-foreground">
{t("cameraWizard.step2.probingDevice")}
</p>
</div>
);
}
if (isError) {
return (
<div className="space-y-4">
<Alert variant="destructive">
<CiCircleAlert className="size-5" />
<AlertTitle>{t("cameraWizard.step2.probeError")}</AlertTitle>
{error && <AlertDescription>{error}</AlertDescription>}
</Alert>
<Button onClick={onRetry} variant="outline" className="w-full">
{t("button.retry", { ns: "common" })}
</Button>
</div>
);
}
if (!probeResult?.success) {
return (
<div className="space-y-4">
<Alert variant="destructive">
<CiCircleAlert className="size-5" />
<AlertTitle>{t("cameraWizard.step2.probeNoSuccess")}</AlertTitle>
{probeResult?.message && (
<AlertDescription>{probeResult.message}</AlertDescription>
)}
</Alert>
<Button onClick={onRetry} variant="outline" className="w-full">
{t("button.retry", { ns: "common" })}
</Button>
</div>
);
}
const rtspCandidates = (probeResult.rtsp_candidates || []).filter(
(c) => c.source === "GetStreamUri",
);
if (probeResult?.success && rtspCandidates.length === 0) {
return (
<div className="space-y-4">
<Alert variant="destructive">
<CiCircleAlert className="size-5" />
<AlertTitle>{t("cameraWizard.step2.noRtspCandidates")}</AlertTitle>
</Alert>
</div>
);
}
return (
<>
<div className="space-y-2">
{probeResult?.success && (
<div className="mb-3 flex flex-row items-center gap-2 text-sm text-success">
<FaCircleCheck className="size-4" />
<span>{t("cameraWizard.step2.probeSuccessful")}</span>
</div>
)}
<div className="text-sm">{t("cameraWizard.step2.deviceInfo")}</div>
<Card>
<CardContent className="space-y-2 p-4 text-sm">
{probeResult.manufacturer && (
<div>
<span className="text-muted-foreground">
{t("cameraWizard.step2.manufacturer")}:
</span>{" "}
<span className="text-primary-variant">
{probeResult.manufacturer}
</span>
</div>
)}
{probeResult.model && (
<div>
<span className="text-muted-foreground">
{t("cameraWizard.step2.model")}:
</span>{" "}
<span className="text-primary-variant">
{probeResult.model}
</span>
</div>
)}
{probeResult.firmware_version && (
<div>
<span className="text-muted-foreground">
{t("cameraWizard.step2.firmware")}:
</span>{" "}
<span className="text-primary-variant">
{probeResult.firmware_version}
</span>
</div>
)}
{probeResult.profiles_count !== undefined && (
<div>
<span className="text-muted-foreground">
{t("cameraWizard.step2.profiles")}:
</span>{" "}
<span className="text-primary-variant">
{probeResult.profiles_count}
</span>
</div>
)}
{probeResult.ptz_supported !== undefined && (
<div>
<span className="text-muted-foreground">
{t("cameraWizard.step2.ptzSupport")}:
</span>{" "}
<span className="text-primary-variant">
{probeResult.ptz_supported
? t("yes", { ns: "common" })
: t("no", { ns: "common" })}
</span>
</div>
)}
{probeResult.ptz_supported && probeResult.autotrack_supported && (
<div>
<span className="text-muted-foreground">
{t("cameraWizard.step2.autotrackingSupport")}:
</span>{" "}
<span className="text-primary-variant">
{t("yes", { ns: "common" })}
</span>
</div>
)}
{probeResult.ptz_supported &&
probeResult.presets_count !== undefined && (
<div>
<span className="text-muted-foreground">
{t("cameraWizard.step2.presets")}:
</span>{" "}
<span className="text-primary-variant">
{probeResult.presets_count}
</span>
</div>
)}
</CardContent>
</Card>
</div>
<div className="space-y-2">
{rtspCandidates.length > 0 && (
<div className="mt-5 space-y-2">
<div className="text-sm">
{t("cameraWizard.step2.rtspCandidates")}
</div>
<div className="text-sm text-muted-foreground">
{t("cameraWizard.step2.rtspCandidatesDescription")}
</div>
<div className="space-y-2">
{rtspCandidates.map((candidate, idx) => {
const isSelected = !!selectedUris?.includes(candidate.uri);
const candidateTest = candidateTests?.[candidate.uri];
const isTesting = testingCandidates?.[candidate.uri];
return (
<CandidateItem
key={idx}
index={idx}
candidate={candidate}
copiedUri={copiedUri}
onCopy={() => handleCopyUri(candidate.uri)}
isSelected={isSelected}
testCandidate={testCandidate}
candidateTest={candidateTest}
isTesting={isTesting}
/>
);
})}
</div>
</div>
)}
</div>
</>
);
}
type CandidateItemProps = {
candidate: OnvifRtspCandidate;
index?: number;
copiedUri: string | null;
onCopy: () => void;
isSelected?: boolean;
testCandidate?: (uri: string) => void;
candidateTest?: TestResult | { success: false; error: string };
isTesting?: boolean;
};
function CandidateItem({
index,
candidate,
copiedUri,
onCopy,
isSelected,
testCandidate,
candidateTest,
isTesting,
}: CandidateItemProps) {
const { t } = useTranslation(["views/settings"]);
const [showFull, setShowFull] = useState(false);
return (
<Card
className={cn(
isSelected &&
"outline outline-[3px] -outline-offset-[2.8px] outline-selected duration-200",
)}
>
<CardContent className="p-4">
<div className="flex flex-col space-y-4">
<div className="flex items-center justify-between">
<div>
<h4 className="font-medium">
{t("cameraWizard.step2.candidateStreamTitle", {
number: (index ?? 0) + 1,
})}
</h4>
{candidateTest?.success && (
<div className="mt-1 text-sm text-muted-foreground">
{[
candidateTest.resolution,
candidateTest.fps
? `${candidateTest.fps} ${t(
"cameraWizard.testResultLabels.fps",
)}`
: null,
candidateTest.videoCodec,
candidateTest.audioCodec,
]
.filter(Boolean)
.join(" · ")}
</div>
)}
</div>
<div className="flex flex-shrink-0 items-center gap-2">
{candidateTest?.success && (
<div className="flex items-center gap-2 text-sm">
<FaCircleCheck className="size-4 text-success" />
<span className="text-success">
{t("cameraWizard.step2.connected")}
</span>
</div>
)}
{candidateTest && !candidateTest.success && (
<div className="flex items-center gap-2 text-sm">
<LuX className="size-4 text-danger" />
<span className="text-danger">
{t("cameraWizard.step2.notConnected")}
</span>
</div>
)}
</div>
</div>
<div className="mt-1 flex items-start gap-2">
<p
className="flex-1 cursor-pointer break-all text-sm text-primary-variant hover:underline"
onClick={() => setShowFull((s) => !s)}
title={t("cameraWizard.step2.toggleUriView")}
>
{showFull ? candidate.uri : maskUri(candidate.uri)}
</p>
<div className="flex items-center gap-2">
<Button
size="sm"
variant="ghost"
onClick={onCopy}
className="mr-4 size-8 p-0"
title={t("cameraWizard.step2.uriCopy")}
>
{copiedUri === candidate.uri ? (
<FaCheck className="size-3" />
) : (
<FaCopy className="size-3" />
)}
</Button>
<Button
size="sm"
variant="outline"
disabled={isTesting}
onClick={() => testCandidate?.(candidate.uri)}
className="h-8 px-3 text-sm"
>
{isTesting ? (
<>
<ActivityIndicator className="mr-2 size-4" />{" "}
{t("cameraWizard.step2.testConnection")}
</>
) : (
t("cameraWizard.step2.testConnection")
)}
</Button>
</div>
</div>
</div>
</CardContent>
</Card>
);
}

View File

@ -2,11 +2,13 @@ import { Button } from "@/components/ui/button";
import {
Form,
FormControl,
FormDescription,
FormField,
FormItem,
FormLabel,
FormMessage,
} from "@/components/ui/form";
import { Checkbox } from "@/components/ui/checkbox";
import { Input } from "@/components/ui/input";
import {
Select,
@ -15,15 +17,13 @@ import {
SelectTrigger,
SelectValue,
} from "@/components/ui/select";
import { RadioGroup, RadioGroupItem } from "@/components/ui/radio-group";
import { useForm } from "react-hook-form";
import { zodResolver } from "@hookform/resolvers/zod";
import { z } from "zod";
import { useTranslation } from "react-i18next";
import { useState, useCallback, useMemo } from "react";
import { LuEye, LuEyeOff } from "react-icons/lu";
import ActivityIndicator from "@/components/indicators/activity-indicator";
import axios from "axios";
import { toast } from "sonner";
import useSWR from "swr";
import { FrigateConfig } from "@/types/frigateConfig";
import {
@ -31,20 +31,13 @@ import {
CameraBrand,
CAMERA_BRANDS,
CAMERA_BRAND_VALUES,
TestResult,
FfprobeStream,
StreamRole,
StreamConfig,
} from "@/types/cameraWizard";
import { FaCircleCheck } from "react-icons/fa6";
import { Card, CardContent, CardTitle } from "../../ui/card";
import {
Popover,
PopoverContent,
PopoverTrigger,
} from "@/components/ui/popover";
import { LuInfo } from "react-icons/lu";
import { detectReolinkCamera } from "@/utils/cameraUtil";
type Step1NameCameraProps = {
wizardData: Partial<WizardFormData>;
@ -63,9 +56,9 @@ export default function Step1NameCamera({
const { t } = useTranslation(["views/settings"]);
const { data: config } = useSWR<FrigateConfig>("config");
const [showPassword, setShowPassword] = useState(false);
const [isTesting, setIsTesting] = useState(false);
const [testStatus, setTestStatus] = useState<string>("");
const [testResult, setTestResult] = useState<TestResult | null>(null);
const [probeMode, setProbeMode] = useState<boolean>(
wizardData.probeMode ?? true,
);
const existingCameraNames = useMemo(() => {
if (!config?.cameras) {
@ -88,6 +81,8 @@ export default function Step1NameCamera({
username: z.string().optional(),
password: z.string().optional(),
brandTemplate: z.enum(CAMERA_BRAND_VALUES).optional(),
onvifPort: z.coerce.number().int().min(1).max(65535).optional(),
useDigestAuth: z.boolean().optional(),
customUrl: z
.string()
.optional()
@ -124,6 +119,8 @@ export default function Step1NameCamera({
? (wizardData.brandTemplate as CameraBrand)
: "dahua",
customUrl: wizardData.customUrl || "",
onvifPort: wizardData.onvifPort ?? 80,
useDigestAuth: wizardData.useDigestAuth ?? false,
},
mode: "onChange",
});
@ -132,271 +129,238 @@ export default function Step1NameCamera({
const watchedHost = form.watch("host");
const watchedCustomUrl = form.watch("customUrl");
const isTestButtonEnabled =
watchedBrand === "other"
? !!(watchedCustomUrl && watchedCustomUrl.trim())
: !!(watchedHost && watchedHost.trim());
const hostPresent = !!(watchedHost && watchedHost.trim());
const customPresent = !!(watchedCustomUrl && watchedCustomUrl.trim());
const cameraNamePresent = !!(form.getValues().cameraName || "").trim();
const generateDynamicStreamUrl = useCallback(
async (data: z.infer<typeof step1FormData>): Promise<string | null> => {
const brand = CAMERA_BRANDS.find((b) => b.value === data.brandTemplate);
if (!brand || !data.host) return null;
let protocol = undefined;
if (data.brandTemplate === "reolink" && data.username && data.password) {
try {
protocol = await detectReolinkCamera(
data.host,
data.username,
data.password,
);
} catch (error) {
return null;
}
}
// Use detected protocol or fallback to rtsp
const protocolKey = protocol || "rtsp";
const templates: Record<string, string> = brand.dynamicTemplates || {};
if (Object.keys(templates).includes(protocolKey)) {
const template =
templates[protocolKey as keyof typeof brand.dynamicTemplates];
return template
.replace("{username}", data.username || "")
.replace("{password}", data.password || "")
.replace("{host}", data.host);
}
return null;
},
[],
);
const generateStreamUrl = useCallback(
async (data: z.infer<typeof step1FormData>): Promise<string> => {
if (data.brandTemplate === "other") {
return data.customUrl || "";
}
const brand = CAMERA_BRANDS.find((b) => b.value === data.brandTemplate);
if (!brand || !data.host) return "";
if (brand.template === "dynamic" && "dynamicTemplates" in brand) {
const dynamicUrl = await generateDynamicStreamUrl(data);
if (dynamicUrl) {
return dynamicUrl;
}
return "";
}
return brand.template
.replace("{username}", data.username || "")
.replace("{password}", data.password || "")
.replace("{host}", data.host);
},
[generateDynamicStreamUrl],
);
const testConnection = useCallback(async () => {
const data = form.getValues();
const streamUrl = await generateStreamUrl(data);
if (!streamUrl) {
toast.error(t("cameraWizard.commonErrors.noUrl"));
return;
}
setIsTesting(true);
setTestStatus("");
setTestResult(null);
try {
// First get probe data for metadata
setTestStatus(t("cameraWizard.step1.testing.probingMetadata"));
const probeResponse = await axios.get("ffprobe", {
params: { paths: streamUrl, detailed: true },
timeout: 10000,
});
let probeData = null;
if (
probeResponse.data &&
probeResponse.data.length > 0 &&
probeResponse.data[0].return_code === 0
) {
probeData = probeResponse.data[0];
}
// Then get snapshot for preview (only if probe succeeded)
let snapshotBlob = null;
if (probeData) {
setTestStatus(t("cameraWizard.step1.testing.fetchingSnapshot"));
try {
const snapshotResponse = await axios.get("ffprobe/snapshot", {
params: { url: streamUrl },
responseType: "blob",
timeout: 10000,
});
snapshotBlob = snapshotResponse.data;
} catch (snapshotError) {
// Snapshot is optional, don't fail if it doesn't work
toast.warning(t("cameraWizard.step1.warnings.noSnapshot"));
}
}
if (probeData) {
const ffprobeData = probeData.stdout;
const streams = ffprobeData.streams || [];
const videoStream = streams.find(
(s: FfprobeStream) =>
s.codec_type === "video" ||
s.codec_name?.includes("h264") ||
s.codec_name?.includes("hevc"),
);
const audioStream = streams.find(
(s: FfprobeStream) =>
s.codec_type === "audio" ||
s.codec_name?.includes("aac") ||
s.codec_name?.includes("mp3") ||
s.codec_name?.includes("pcm_mulaw") ||
s.codec_name?.includes("pcm_alaw"),
);
const resolution = videoStream
? `${videoStream.width}x${videoStream.height}`
: undefined;
// Extract FPS from rational (e.g., "15/1" -> 15)
const fps = videoStream?.avg_frame_rate
? parseFloat(videoStream.avg_frame_rate.split("/")[0]) /
parseFloat(videoStream.avg_frame_rate.split("/")[1])
: undefined;
// Convert snapshot blob to base64 if available
let snapshotBase64 = undefined;
if (snapshotBlob) {
snapshotBase64 = await new Promise<string>((resolve) => {
const reader = new FileReader();
reader.onload = () => resolve(reader.result as string);
reader.readAsDataURL(snapshotBlob);
});
}
const testResult: TestResult = {
success: true,
snapshot: snapshotBase64,
resolution,
videoCodec: videoStream?.codec_name,
audioCodec: audioStream?.codec_name,
fps: fps && !isNaN(fps) ? fps : undefined,
};
setTestResult(testResult);
onUpdate({ streams: [{ id: "", url: "", roles: [], testResult }] });
toast.success(t("cameraWizard.step1.testSuccess"));
} else {
const error =
Array.isArray(probeResponse.data?.[0]?.stderr) &&
probeResponse.data[0].stderr.length > 0
? probeResponse.data[0].stderr.join("\n")
: "Unable to probe stream";
setTestResult({
success: false,
error: error,
});
toast.error(t("cameraWizard.commonErrors.testFailed", { error }), {
duration: 6000,
});
}
} catch (error) {
const axiosError = error as {
response?: { data?: { message?: string; detail?: string } };
message?: string;
};
const errorMessage =
axiosError.response?.data?.message ||
axiosError.response?.data?.detail ||
axiosError.message ||
"Connection failed";
setTestResult({
success: false,
error: errorMessage,
});
toast.error(
t("cameraWizard.commonErrors.testFailed", { error: errorMessage }),
{
duration: 10000,
},
);
} finally {
setIsTesting(false);
setTestStatus("");
}
}, [form, generateStreamUrl, t, onUpdate]);
const isContinueButtonEnabled =
cameraNamePresent &&
(probeMode
? hostPresent
: watchedBrand === "other"
? customPresent
: hostPresent);
const onSubmit = (data: z.infer<typeof step1FormData>) => {
onUpdate(data);
onUpdate({ ...data, probeMode });
};
const handleContinue = useCallback(async () => {
const data = form.getValues();
const streamUrl = await generateStreamUrl(data);
const streamId = `stream_${Date.now()}`;
const streamConfig: StreamConfig = {
id: streamId,
url: streamUrl,
roles: ["detect" as StreamRole],
resolution: testResult?.resolution,
testResult: testResult || undefined,
userTested: false,
};
const updatedData = {
...data,
streams: [streamConfig],
};
onNext(updatedData);
}, [form, generateStreamUrl, testResult, onNext]);
const isValid = await form.trigger();
if (isValid) {
const data = form.getValues();
onNext({ ...data, probeMode });
}
}, [form, probeMode, onNext]);
return (
<div className="space-y-6">
{!testResult?.success && (
<>
<div className="text-sm text-muted-foreground">
{t("cameraWizard.step1.description")}
</div>
<div className="text-sm text-muted-foreground">
{t("cameraWizard.step1.description")}
</div>
<Form {...form}>
<form onSubmit={form.handleSubmit(onSubmit)} className="space-y-4">
<FormField
control={form.control}
name="cameraName"
render={({ field }) => (
<FormItem>
<FormLabel className="text-primary-variant">
{t("cameraWizard.step1.cameraName")}
</FormLabel>
<FormControl>
<Form {...form}>
<form onSubmit={form.handleSubmit(onSubmit)} className="space-y-4">
<FormField
control={form.control}
name="cameraName"
render={({ field }) => (
<FormItem>
<FormLabel className="text-primary-variant">
{t("cameraWizard.step1.cameraName")}
</FormLabel>
<FormControl>
<Input
className="text-md h-8"
placeholder={t("cameraWizard.step1.cameraNamePlaceholder")}
{...field}
/>
</FormControl>
<FormMessage />
</FormItem>
)}
/>
<div className="space-y-4">
<FormField
control={form.control}
name="host"
render={({ field }) => (
<FormItem>
<FormLabel className="text-primary-variant">
{t("cameraWizard.step1.host")}
</FormLabel>
<FormControl>
<Input
className="text-md h-8"
placeholder="192.168.1.100"
{...field}
/>
</FormControl>
<FormMessage />
</FormItem>
)}
/>
<FormField
control={form.control}
name="username"
render={({ field }) => (
<FormItem>
<FormLabel className="text-primary-variant">
{t("cameraWizard.step1.username")}
</FormLabel>
<FormControl>
<Input
className="text-md h-8"
placeholder={t("cameraWizard.step1.usernamePlaceholder")}
{...field}
/>
</FormControl>
<FormMessage />
</FormItem>
)}
/>
<FormField
control={form.control}
name="password"
render={({ field }) => (
<FormItem>
<FormLabel className="text-primary-variant">
{t("cameraWizard.step1.password")}
</FormLabel>
<FormControl>
<div className="relative">
<Input
className="text-md h-8"
className="text-md h-8 pr-10"
type={showPassword ? "text" : "password"}
placeholder={t(
"cameraWizard.step1.cameraNamePlaceholder",
"cameraWizard.step1.passwordPlaceholder",
)}
{...field}
/>
</FormControl>
<FormMessage />
</FormItem>
)}
/>
<Button
type="button"
variant="ghost"
size="sm"
className="absolute right-0 top-0 h-full px-3 py-2 hover:bg-transparent"
onClick={() => setShowPassword(!showPassword)}
>
{showPassword ? (
<LuEyeOff className="size-4" />
) : (
<LuEye className="size-4" />
)}
</Button>
</div>
</FormControl>
<FormMessage />
</FormItem>
)}
/>
</div>
<div className="space-y-3 pt-4">
<FormLabel className="text-primary-variant">
{t("cameraWizard.step1.detectionMethod")}
</FormLabel>
<RadioGroup
value={probeMode ? "probe" : "manual"}
onValueChange={(value) => {
setProbeMode(value === "probe");
}}
>
<div className="flex items-center space-x-2">
<RadioGroupItem
value="probe"
id="probe-mode"
className={
probeMode
? "bg-selected from-selected/50 to-selected/90 text-selected"
: "bg-secondary from-secondary/50 to-secondary/90 text-secondary"
}
/>
<label htmlFor="probe-mode" className="cursor-pointer text-sm">
{t("cameraWizard.step1.probeMode")}
</label>
</div>
<div className="flex items-center space-x-2">
<RadioGroupItem
value="manual"
id="manual-mode"
className={
!probeMode
? "bg-selected from-selected/50 to-selected/90 text-selected"
: "bg-secondary from-secondary/50 to-secondary/90 text-secondary"
}
/>
<label htmlFor="manual-mode" className="cursor-pointer text-sm">
{t("cameraWizard.step1.manualMode")}
</label>
</div>
</RadioGroup>
<FormDescription>
{t("cameraWizard.step1.detectionMethodDescription")}
</FormDescription>
</div>
{probeMode && (
<FormField
control={form.control}
name="onvifPort"
render={({ field, fieldState }) => (
<FormItem>
<FormLabel className="text-primary-variant">
{t("cameraWizard.step1.onvifPort")}
</FormLabel>
<FormControl>
<Input
className="text-md h-8"
type="text"
{...field}
placeholder="80"
/>
</FormControl>
<FormDescription>
{t("cameraWizard.step1.onvifPortDescription")}
</FormDescription>
<FormMessage>
{fieldState.error ? fieldState.error.message : null}
</FormMessage>
</FormItem>
)}
/>
)}
{probeMode && (
<FormField
control={form.control}
name="useDigestAuth"
render={({ field }) => (
<FormItem className="flex items-start space-x-2">
<FormControl>
<Checkbox
className="size-5 text-white accent-white data-[state=checked]:bg-selected data-[state=checked]:text-white"
checked={!!field.value}
onCheckedChange={(val) => field.onChange(!!val)}
/>
</FormControl>
<div className="flex flex-1 flex-col space-y-1">
<FormLabel className="mb-0 text-primary-variant">
{t("cameraWizard.step1.useDigestAuth")}
</FormLabel>
<FormDescription className="mt-0">
{t("cameraWizard.step1.useDigestAuthDescription")}
</FormDescription>
</div>
</FormItem>
)}
/>
)}
{!probeMode && (
<div className="space-y-4">
<FormField
control={form.control}
name="brandTemplate"
@ -463,90 +427,6 @@ export default function Step1NameCamera({
)}
/>
{watchedBrand !== "other" && (
<>
<FormField
control={form.control}
name="host"
render={({ field }) => (
<FormItem>
<FormLabel className="text-primary-variant">
{t("cameraWizard.step1.host")}
</FormLabel>
<FormControl>
<Input
className="text-md h-8"
placeholder="192.168.1.100"
{...field}
/>
</FormControl>
<FormMessage />
</FormItem>
)}
/>
<FormField
control={form.control}
name="username"
render={({ field }) => (
<FormItem>
<FormLabel className="text-primary-variant">
{t("cameraWizard.step1.username")}
</FormLabel>
<FormControl>
<Input
className="text-md h-8"
placeholder={t(
"cameraWizard.step1.usernamePlaceholder",
)}
{...field}
/>
</FormControl>
<FormMessage />
</FormItem>
)}
/>
<FormField
control={form.control}
name="password"
render={({ field }) => (
<FormItem>
<FormLabel className="text-primary-variant">
{t("cameraWizard.step1.password")}
</FormLabel>
<FormControl>
<div className="relative">
<Input
className="text-md h-8 pr-10"
type={showPassword ? "text" : "password"}
placeholder={t(
"cameraWizard.step1.passwordPlaceholder",
)}
{...field}
/>
<Button
type="button"
variant="ghost"
size="sm"
className="absolute right-0 top-0 h-full px-3 py-2 hover:bg-transparent"
onClick={() => setShowPassword(!showPassword)}
>
{showPassword ? (
<LuEyeOff className="size-4" />
) : (
<LuEye className="size-4" />
)}
</Button>
</div>
</FormControl>
<FormMessage />
</FormItem>
)}
/>
</>
)}
{watchedBrand == "other" && (
<FormField
control={form.control}
@ -568,124 +448,25 @@ export default function Step1NameCamera({
)}
/>
)}
</form>
</Form>
</>
)}
</div>
)}
</form>
</Form>
{testResult?.success && (
<div className="p-4">
<div className="mb-3 flex flex-row items-center gap-2 text-sm font-medium text-success">
<FaCircleCheck className="size-4" />
{t("cameraWizard.step1.testSuccess")}
</div>
<div className="space-y-3">
{testResult.snapshot ? (
<div className="relative flex justify-center">
<img
src={testResult.snapshot}
alt="Camera snapshot"
className="max-h-[50dvh] max-w-full rounded-lg object-contain"
/>
<div className="absolute bottom-2 right-2 rounded-md bg-black/70 p-3 text-sm backdrop-blur-sm">
<div className="space-y-1">
<StreamDetails testResult={testResult} />
</div>
</div>
</div>
) : (
<Card className="p-4">
<CardTitle className="mb-2 text-sm">
{t("cameraWizard.step1.streamDetails")}
</CardTitle>
<CardContent className="p-0 text-sm">
<StreamDetails testResult={testResult} />
</CardContent>
</Card>
)}
</div>
</div>
)}
{isTesting && (
<div className="flex items-center gap-2 text-sm text-muted-foreground">
<ActivityIndicator className="size-4" />
{testStatus}
</div>
)}
<div className="flex flex-col gap-3 pt-3 sm:flex-row sm:justify-end sm:gap-4">
<Button type="button" onClick={onCancel} className="sm:flex-1">
{t("button.cancel", { ns: "common" })}
</Button>
<Button
type="button"
onClick={testResult?.success ? () => setTestResult(null) : onCancel}
className="sm:flex-1"
onClick={handleContinue}
disabled={!isContinueButtonEnabled}
variant="select"
className="flex items-center justify-center gap-2 sm:flex-1"
>
{testResult?.success
? t("button.back", { ns: "common" })
: t("button.cancel", { ns: "common" })}
{t("button.continue", { ns: "common" })}
</Button>
{testResult?.success ? (
<Button
type="button"
onClick={handleContinue}
variant="select"
className="flex items-center justify-center gap-2 sm:flex-1"
>
{t("button.continue", { ns: "common" })}
</Button>
) : (
<Button
type="button"
onClick={testConnection}
disabled={isTesting || !isTestButtonEnabled}
variant="select"
className="flex items-center justify-center gap-2 sm:flex-1"
>
{t("cameraWizard.step1.testConnection")}
</Button>
)}
</div>
</div>
);
}
function StreamDetails({ testResult }: { testResult: TestResult }) {
const { t } = useTranslation(["views/settings"]);
return (
<>
{testResult.resolution && (
<div>
<span className="text-white/70">
{t("cameraWizard.testResultLabels.resolution")}:
</span>{" "}
<span className="text-white">{testResult.resolution}</span>
</div>
)}
{testResult.fps && (
<div>
<span className="text-white/70">
{t("cameraWizard.testResultLabels.fps")}:
</span>{" "}
<span className="text-white">{testResult.fps}</span>
</div>
)}
{testResult.videoCodec && (
<div>
<span className="text-white/70">
{t("cameraWizard.testResultLabels.video")}:
</span>{" "}
<span className="text-white">{testResult.videoCodec}</span>
</div>
)}
{testResult.audioCodec && (
<div>
<span className="text-white/70">
{t("cameraWizard.testResultLabels.audio")}:
</span>{" "}
<span className="text-white">{testResult.audioCodec}</span>
</div>
)}
</>
);
}

View File

@ -0,0 +1,725 @@
import { Button } from "@/components/ui/button";
import { useTranslation } from "react-i18next";
import { useState, useCallback, useEffect } from "react";
import ActivityIndicator from "@/components/indicators/activity-indicator";
import axios from "axios";
import { toast } from "sonner";
import type {
WizardFormData,
TestResult,
StreamConfig,
StreamRole,
OnvifProbeResponse,
CandidateTestMap,
FfprobeStream,
FfprobeData,
FfprobeResponse,
} from "@/types/cameraWizard";
import { FaCircleCheck } from "react-icons/fa6";
import { Card, CardContent, CardTitle } from "../../ui/card";
import OnvifProbeResults from "./OnvifProbeResults";
import { CAMERA_BRANDS } from "@/types/cameraWizard";
import { detectReolinkCamera } from "@/utils/cameraUtil";
type Step2ProbeOrSnapshotProps = {
wizardData: Partial<WizardFormData>;
onUpdate: (data: Partial<WizardFormData>) => void;
onNext: (data?: Partial<WizardFormData>) => void;
onBack: () => void;
probeMode: boolean;
};
export default function Step2ProbeOrSnapshot({
wizardData,
onUpdate,
onNext,
onBack,
probeMode,
}: Step2ProbeOrSnapshotProps) {
const { t } = useTranslation(["views/settings"]);
const [isTesting, setIsTesting] = useState(false);
const [testStatus, setTestStatus] = useState<string>("");
const [testResult, setTestResult] = useState<TestResult | null>(null);
const [isProbing, setIsProbing] = useState(false);
const [probeError, setProbeError] = useState<string | null>(null);
const [probeResult, setProbeResult] = useState<OnvifProbeResponse | null>(
null,
);
const [testingCandidates, setTestingCandidates] = useState<
Record<string, boolean>
>({} as Record<string, boolean>);
const [candidateTests, setCandidateTests] = useState<CandidateTestMap>(
{} as CandidateTestMap,
);
const probeUri = useCallback(
async (
uri: string,
fetchSnapshot = false,
setStatus?: (s: string) => void,
): Promise<TestResult> => {
try {
const probeResponse = await axios.get("ffprobe", {
params: { paths: uri, detailed: true },
timeout: 10000,
});
let probeData: FfprobeResponse | null = null;
if (
probeResponse.data &&
probeResponse.data.length > 0 &&
probeResponse.data[0].return_code === 0
) {
probeData = probeResponse.data[0];
}
if (!probeData) {
const error =
Array.isArray(probeResponse.data?.[0]?.stderr) &&
probeResponse.data[0].stderr.length > 0
? probeResponse.data[0].stderr.join("\n")
: "Unable to probe stream";
return { success: false, error };
}
let ffprobeData: FfprobeData;
if (typeof probeData.stdout === "string") {
try {
ffprobeData = JSON.parse(probeData.stdout as string) as FfprobeData;
} catch {
ffprobeData = { streams: [] };
}
} else {
ffprobeData = probeData.stdout as FfprobeData;
}
const streams = ffprobeData.streams || [];
const videoStream = streams.find(
(s: FfprobeStream) =>
s.codec_type === "video" ||
s.codec_name?.includes("h264") ||
s.codec_name?.includes("hevc"),
);
const audioStream = streams.find(
(s: FfprobeStream) =>
s.codec_type === "audio" ||
s.codec_name?.includes("aac") ||
s.codec_name?.includes("mp3") ||
s.codec_name?.includes("pcm_mulaw") ||
s.codec_name?.includes("pcm_alaw"),
);
let resolution: string | undefined = undefined;
if (videoStream) {
const width = Number(videoStream.width || 0);
const height = Number(videoStream.height || 0);
if (width > 0 && height > 0) {
resolution = `${width}x${height}`;
}
}
const fps = videoStream?.avg_frame_rate
? parseFloat(videoStream.avg_frame_rate.split("/")[0]) /
parseFloat(videoStream.avg_frame_rate.split("/")[1])
: undefined;
let snapshotBase64: string | undefined = undefined;
if (fetchSnapshot) {
if (setStatus) {
setStatus(t("cameraWizard.step2.testing.fetchingSnapshot"));
}
try {
const snapshotResponse = await axios.get("ffprobe/snapshot", {
params: { url: uri },
responseType: "blob",
timeout: 10000,
});
const snapshotBlob = snapshotResponse.data;
snapshotBase64 = await new Promise<string>((resolve) => {
const reader = new FileReader();
reader.onload = () => resolve(reader.result as string);
reader.readAsDataURL(snapshotBlob);
});
} catch (snapshotError) {
snapshotBase64 = undefined;
}
}
const streamTestResult: TestResult = {
success: true,
snapshot: snapshotBase64,
resolution,
videoCodec: videoStream?.codec_name,
audioCodec: audioStream?.codec_name,
fps: fps && !isNaN(fps) ? fps : undefined,
};
return streamTestResult;
} catch (err) {
const axiosError = err as {
response?: { data?: { message?: string; detail?: string } };
message?: string;
};
const errorMessage =
axiosError.response?.data?.message ||
axiosError.response?.data?.detail ||
axiosError.message ||
"Connection failed";
return { success: false, error: errorMessage };
}
},
[t],
);
const probeCamera = useCallback(async () => {
if (!wizardData.host) {
toast.error(t("cameraWizard.step2.errors.hostRequired"));
return;
}
setIsProbing(true);
setProbeError(null);
setProbeResult(null);
try {
const response = await axios.get("/onvif/probe", {
params: {
host: wizardData.host,
port: wizardData.onvifPort ?? 80,
username: wizardData.username || "",
password: wizardData.password || "",
test: false,
auth_type: wizardData.useDigestAuth ? "digest" : "basic",
},
timeout: 30000,
});
if (response.data && response.data.success) {
setProbeResult(response.data);
// Extract candidate URLs and pass to wizardData
const candidateUris = (response.data.rtsp_candidates || [])
.filter((c: { source: string }) => c.source === "GetStreamUri")
.map((c: { uri: string }) => c.uri);
onUpdate({
probeMode: true,
probeCandidates: candidateUris,
candidateTests: {},
});
} else {
setProbeError(response.data?.message || "Probe failed");
}
} catch (error) {
const axiosError = error as {
response?: { data?: { message?: string; detail?: string } };
message?: string;
};
const errorMessage =
axiosError.response?.data?.message ||
axiosError.response?.data?.detail ||
axiosError.message ||
"Failed to probe camera";
setProbeError(errorMessage);
toast.error(t("cameraWizard.step2.probeFailed", { error: errorMessage }));
} finally {
setIsProbing(false);
}
}, [wizardData, onUpdate, t]);
const testAllSelectedCandidates = useCallback(async () => {
const uris = (probeResult?.rtsp_candidates || [])
.filter((c) => c.source === "GetStreamUri")
.map((c) => c.uri);
if (!uris || uris.length === 0) {
toast.error(t("cameraWizard.commonErrors.noUrl"));
return;
}
// Prepare an initial stream so the wizard can proceed to step 3.
// Use the first candidate as the initial stream (no extra probing here).
const streamsToCreate: StreamConfig[] = [];
if (uris.length > 0) {
const first = uris[0];
streamsToCreate.push({
id: `stream_${Date.now()}`,
url: first,
roles: ["detect" as const],
testResult: candidateTests[first],
});
}
// Use existing candidateTests state (may contain entries from individual tests)
onNext({
probeMode: true,
probeCandidates: uris,
candidateTests: candidateTests,
streams: streamsToCreate,
});
}, [probeResult, candidateTests, onNext, t]);
const testCandidate = useCallback(
async (uri: string) => {
if (!uri) return;
setTestingCandidates((s) => ({ ...s, [uri]: true }));
try {
const result = await probeUri(uri, false);
setCandidateTests((s) => ({ ...s, [uri]: result }));
} finally {
setTestingCandidates((s) => ({ ...s, [uri]: false }));
}
},
[probeUri],
);
const generateDynamicStreamUrl = useCallback(
async (data: Partial<WizardFormData>): Promise<string | null> => {
const brand = CAMERA_BRANDS.find((b) => b.value === data.brandTemplate);
if (!brand || !data.host) return null;
let protocol = undefined;
if (data.brandTemplate === "reolink" && data.username && data.password) {
try {
protocol = await detectReolinkCamera(
data.host,
data.username,
data.password,
);
} catch (error) {
return null;
}
}
const protocolKey = protocol || "rtsp";
const templates: Record<string, string> = brand.dynamicTemplates || {};
if (Object.keys(templates).includes(protocolKey)) {
const template =
templates[protocolKey as keyof typeof brand.dynamicTemplates];
return template
.replace("{username}", data.username || "")
.replace("{password}", data.password || "")
.replace("{host}", data.host);
}
return null;
},
[],
);
const generateStreamUrl = useCallback(
async (data: Partial<WizardFormData>): Promise<string> => {
if (data.brandTemplate === "other") {
return data.customUrl || "";
}
const brand = CAMERA_BRANDS.find((b) => b.value === data.brandTemplate);
if (!brand || !data.host) return "";
if (brand.template === "dynamic" && "dynamicTemplates" in brand) {
const dynamicUrl = await generateDynamicStreamUrl(data);
if (dynamicUrl) {
return dynamicUrl;
}
return "";
}
return brand.template
.replace("{username}", data.username || "")
.replace("{password}", data.password || "")
.replace("{host}", data.host);
},
[generateDynamicStreamUrl],
);
const testConnection = useCallback(
async (showToast = true) => {
const streamUrl = await generateStreamUrl(wizardData);
if (!streamUrl) {
toast.error(t("cameraWizard.commonErrors.noUrl"));
return;
}
setIsTesting(true);
setTestStatus("");
setTestResult(null);
try {
setTestStatus(t("cameraWizard.step2.testing.probingMetadata"));
const result = await probeUri(streamUrl, true, setTestStatus);
if (result && result.success) {
setTestResult(result);
const streamId = `stream_${Date.now()}`;
onUpdate({
streams: [
{
id: streamId,
url: streamUrl,
roles: ["detect"] as StreamRole[],
testResult: result,
},
],
});
if (showToast) {
toast.success(t("cameraWizard.step2.testSuccess"));
}
} else {
const errMsg = result?.error || "Unable to probe stream";
setTestResult({
success: false,
error: errMsg,
});
if (showToast) {
toast.error(
t("cameraWizard.commonErrors.testFailed", { error: errMsg }),
{
duration: 6000,
},
);
}
}
} catch (error) {
const axiosError = error as {
response?: { data?: { message?: string; detail?: string } };
message?: string;
};
const errorMessage =
axiosError.response?.data?.message ||
axiosError.response?.data?.detail ||
axiosError.message ||
"Connection failed";
setTestResult({
success: false,
error: errorMessage,
});
if (showToast) {
toast.error(
t("cameraWizard.commonErrors.testFailed", { error: errorMessage }),
{
duration: 10000,
},
);
}
} finally {
setIsTesting(false);
setTestStatus("");
}
},
[wizardData, generateStreamUrl, t, onUpdate, probeUri],
);
const handleContinue = useCallback(() => {
onNext();
}, [onNext]);
// Auto-start probe or test when step loads
const [hasStarted, setHasStarted] = useState(false);
useEffect(() => {
if (!hasStarted) {
setHasStarted(true);
if (probeMode) {
probeCamera();
} else {
// Auto-run the connection test but suppress toasts to avoid duplicates
testConnection(false);
}
}
}, [hasStarted, probeMode, probeCamera, testConnection]);
return (
<div className="space-y-6">
{probeMode ? (
// Probe mode: show probe results directly
<>
{probeResult && (
<div className="space-y-4">
<OnvifProbeResults
isLoading={isProbing}
isError={!!probeError}
error={probeError || undefined}
probeResult={probeResult}
onRetry={probeCamera}
testCandidate={testCandidate}
candidateTests={candidateTests}
testingCandidates={testingCandidates}
/>
</div>
)}
<ProbeFooterButtons
isProbing={isProbing}
probeError={probeError}
onBack={onBack}
onTestAll={testAllSelectedCandidates}
onRetry={probeCamera}
// disable next if either the overall testConnection is running or any candidate test is running
isTesting={
isTesting || Object.values(testingCandidates).some((v) => v)
}
candidateCount={
(probeResult?.rtsp_candidates || []).filter(
(c) => c.source === "GetStreamUri",
).length
}
/>
</>
) : (
// Manual mode: show snapshot and stream details
<>
{testResult?.success && (
<div className="p-4">
<div className="mb-3 flex flex-row items-center gap-2 text-sm font-medium text-success">
<FaCircleCheck className="size-4" />
{t("cameraWizard.step2.testSuccess")}
</div>
<div className="space-y-3">
{testResult.snapshot ? (
<div className="relative flex justify-center">
<img
src={testResult.snapshot}
alt="Camera snapshot"
className="max-h-[50dvh] max-w-full rounded-lg object-contain"
/>
<div className="absolute bottom-2 right-2 rounded-md bg-black/70 p-3 text-sm backdrop-blur-sm">
<div className="space-y-1">
<StreamDetails testResult={testResult} />
</div>
</div>
</div>
) : (
<Card className="p-4">
<CardTitle className="mb-2 text-sm">
{t("cameraWizard.step2.streamDetails")}
</CardTitle>
<CardContent className="p-0 text-sm">
<StreamDetails testResult={testResult} />
</CardContent>
</Card>
)}
</div>
</div>
)}
{isTesting && (
<div className="flex items-center gap-2 text-sm text-muted-foreground">
<ActivityIndicator className="size-4" />
{testStatus}
</div>
)}
{testResult && !testResult.success && (
<div className="space-y-4">
<div className="text-sm text-destructive">{testResult.error}</div>
</div>
)}
<ProbeFooterButtons
mode="manual"
isProbing={false}
probeError={null}
onBack={onBack}
onTestAll={testAllSelectedCandidates}
onRetry={probeCamera}
isTesting={
isTesting || Object.values(testingCandidates).some((v) => v)
}
candidateCount={
(probeResult?.rtsp_candidates || []).filter(
(c) => c.source === "GetStreamUri",
).length
}
manualTestSuccess={!!testResult?.success}
onContinue={handleContinue}
onManualTest={testConnection}
/>
</>
)}
</div>
);
}
function StreamDetails({ testResult }: { testResult: TestResult }) {
const { t } = useTranslation(["views/settings"]);
return (
<>
{testResult.resolution && (
<div>
<span className="text-white/70">
{t("cameraWizard.testResultLabels.resolution")}:
</span>{" "}
<span className="text-white">{testResult.resolution}</span>
</div>
)}
{testResult.fps && (
<div>
<span className="text-white/70">
{t("cameraWizard.testResultLabels.fps")}:
</span>{" "}
<span className="text-white">{testResult.fps}</span>
</div>
)}
{testResult.videoCodec && (
<div>
<span className="text-white/70">
{t("cameraWizard.testResultLabels.video")}:
</span>{" "}
<span className="text-white">{testResult.videoCodec}</span>
</div>
)}
{testResult.audioCodec && (
<div>
<span className="text-white/70">
{t("cameraWizard.testResultLabels.audio")}:
</span>{" "}
<span className="text-white">{testResult.audioCodec}</span>
</div>
)}
</>
);
}
type ProbeFooterProps = {
isProbing: boolean;
probeError: string | null;
onBack: () => void;
onTestAll: () => void;
onRetry: () => void;
isTesting: boolean;
candidateCount?: number;
mode?: "probe" | "manual";
manualTestSuccess?: boolean;
onContinue?: () => void;
onManualTest?: () => void;
};
function ProbeFooterButtons({
isProbing,
probeError,
onBack,
onTestAll,
onRetry,
isTesting,
candidateCount = 0,
mode = "probe",
manualTestSuccess,
onContinue,
onManualTest,
}: ProbeFooterProps) {
const { t } = useTranslation(["views/settings"]);
// Loading footer
if (isProbing) {
return (
<div className="space-y-4">
<div className="flex items-center gap-2 text-sm text-muted-foreground">
<ActivityIndicator className="size-4" />
{t("cameraWizard.step2.probing")}
</div>
<div className="flex flex-col gap-3 pt-3 sm:flex-row sm:justify-end sm:gap-4">
<Button type="button" onClick={onBack} disabled className="sm:flex-1">
{t("button.back", { ns: "common" })}
</Button>
<Button
type="button"
disabled
variant="select"
className="flex items-center justify-center gap-2 sm:flex-1"
>
<ActivityIndicator className="size-4" />
{t("cameraWizard.step2.probing")}
</Button>
</div>
</div>
);
}
// Error footer
if (probeError) {
return (
<div className="space-y-4">
<div className="text-sm text-destructive">{probeError}</div>
<div className="flex flex-col gap-3 pt-3 sm:flex-row sm:justify-end sm:gap-4">
<Button type="button" onClick={onBack} className="sm:flex-1">
{t("button.back", { ns: "common" })}
</Button>
<Button
type="button"
onClick={onRetry}
variant="select"
className="flex items-center justify-center gap-2 sm:flex-1"
>
{t("cameraWizard.step2.retry")}
</Button>
</div>
</div>
);
}
// Default footer: show back + test (test disabled if none selected or testing)
// If manual mode, show Continue when test succeeded, otherwise show Test (calls onManualTest)
if (mode === "manual") {
return (
<div className="flex flex-col gap-3 pt-3 sm:flex-row sm:justify-end sm:gap-4">
<Button type="button" onClick={onBack} className="sm:flex-1">
{t("button.back", { ns: "common" })}
</Button>
{manualTestSuccess ? (
<Button
type="button"
onClick={onContinue}
variant="select"
className="flex items-center justify-center gap-2 sm:flex-1"
>
{t("button.continue", { ns: "common" })}
</Button>
) : (
<Button
type="button"
onClick={onManualTest}
disabled={isTesting}
variant="select"
className="flex items-center justify-center gap-2 sm:flex-1"
>
{isTesting ? (
<>
<ActivityIndicator className="size-4" />{" "}
{t("button.continue", { ns: "common" })}
</>
) : (
t("cameraWizard.step2.retry")
)}
</Button>
)}
</div>
);
}
// Default probe footer
return (
<div className="flex flex-col gap-3 pt-3 sm:flex-row sm:justify-end sm:gap-4">
<Button type="button" onClick={onBack} className="sm:flex-1">
{t("button.back", { ns: "common" })}
</Button>
<Button
type="button"
onClick={onTestAll}
disabled={isTesting || (candidateCount ?? 0) === 0}
variant="select"
className="flex items-center justify-center gap-2 sm:flex-1"
>
{t("button.next", { ns: "common" })}
</Button>
</div>
);
}

View File

@ -1,481 +0,0 @@
import { Button } from "@/components/ui/button";
import { Card, CardContent } from "@/components/ui/card";
import { Input } from "@/components/ui/input";
import { Switch } from "@/components/ui/switch";
import { useTranslation } from "react-i18next";
import { useState, useCallback, useMemo } from "react";
import { LuPlus, LuTrash2, LuX } from "react-icons/lu";
import ActivityIndicator from "@/components/indicators/activity-indicator";
import axios from "axios";
import { toast } from "sonner";
import {
WizardFormData,
StreamConfig,
StreamRole,
TestResult,
FfprobeStream,
} from "@/types/cameraWizard";
import { Label } from "../../ui/label";
import { FaCircleCheck } from "react-icons/fa6";
import {
Popover,
PopoverContent,
PopoverTrigger,
} from "@/components/ui/popover";
import { LuInfo, LuExternalLink } from "react-icons/lu";
import { Link } from "react-router-dom";
import { useDocDomain } from "@/hooks/use-doc-domain";
type Step2StreamConfigProps = {
wizardData: Partial<WizardFormData>;
onUpdate: (data: Partial<WizardFormData>) => void;
onBack?: () => void;
onNext?: () => void;
canProceed?: boolean;
};
export default function Step2StreamConfig({
wizardData,
onUpdate,
onBack,
onNext,
canProceed,
}: Step2StreamConfigProps) {
const { t } = useTranslation(["views/settings", "components/dialog"]);
const { getLocaleDocUrl } = useDocDomain();
const [testingStreams, setTestingStreams] = useState<Set<string>>(new Set());
const streams = useMemo(() => wizardData.streams || [], [wizardData.streams]);
const addStream = useCallback(() => {
const newStream: StreamConfig = {
id: `stream_${Date.now()}`,
url: "",
roles: [],
};
onUpdate({
streams: [...streams, newStream],
});
}, [streams, onUpdate]);
const removeStream = useCallback(
(streamId: string) => {
onUpdate({
streams: streams.filter((s) => s.id !== streamId),
});
},
[streams, onUpdate],
);
const updateStream = useCallback(
(streamId: string, updates: Partial<StreamConfig>) => {
onUpdate({
streams: streams.map((s) =>
s.id === streamId ? { ...s, ...updates } : s,
),
});
},
[streams, onUpdate],
);
const getUsedRolesExcludingStream = useCallback(
(excludeStreamId: string) => {
const roles = new Set<StreamRole>();
streams.forEach((stream) => {
if (stream.id !== excludeStreamId) {
stream.roles.forEach((role) => roles.add(role));
}
});
return roles;
},
[streams],
);
const toggleRole = useCallback(
(streamId: string, role: StreamRole) => {
const stream = streams.find((s) => s.id === streamId);
if (!stream) return;
const hasRole = stream.roles.includes(role);
if (hasRole) {
// Allow removing the role
const newRoles = stream.roles.filter((r) => r !== role);
updateStream(streamId, { roles: newRoles });
} else {
// Check if role is already used in another stream
const usedRoles = getUsedRolesExcludingStream(streamId);
if (!usedRoles.has(role)) {
// Allow adding the role
const newRoles = [...stream.roles, role];
updateStream(streamId, { roles: newRoles });
}
}
},
[streams, updateStream, getUsedRolesExcludingStream],
);
const testStream = useCallback(
(stream: StreamConfig) => {
if (!stream.url.trim()) {
toast.error(t("cameraWizard.commonErrors.noUrl"));
return;
}
setTestingStreams((prev) => new Set(prev).add(stream.id));
axios
.get("ffprobe", {
params: { paths: stream.url, detailed: true },
timeout: 10000,
})
.then((response) => {
if (response.data?.[0]?.return_code === 0) {
const probeData = response.data[0];
const streams = probeData.stdout.streams || [];
const videoStream = streams.find(
(s: FfprobeStream) =>
s.codec_type === "video" ||
s.codec_name?.includes("h264") ||
s.codec_name?.includes("h265"),
);
const audioStream = streams.find(
(s: FfprobeStream) =>
s.codec_type === "audio" ||
s.codec_name?.includes("aac") ||
s.codec_name?.includes("mp3"),
);
const resolution = videoStream
? `${videoStream.width}x${videoStream.height}`
: undefined;
const fps = videoStream?.avg_frame_rate
? parseFloat(videoStream.avg_frame_rate.split("/")[0]) /
parseFloat(videoStream.avg_frame_rate.split("/")[1])
: undefined;
const testResult: TestResult = {
success: true,
resolution,
videoCodec: videoStream?.codec_name,
audioCodec: audioStream?.codec_name,
fps: fps && !isNaN(fps) ? fps : undefined,
};
updateStream(stream.id, { testResult, userTested: true });
toast.success(t("cameraWizard.step2.testSuccess"));
} else {
const error = response.data?.[0]?.stderr || "Unknown error";
updateStream(stream.id, {
testResult: { success: false, error },
userTested: true,
});
toast.error(t("cameraWizard.commonErrors.testFailed", { error }));
}
})
.catch((error) => {
const errorMessage =
error.response?.data?.message ||
error.response?.data?.detail ||
"Connection failed";
updateStream(stream.id, {
testResult: { success: false, error: errorMessage },
userTested: true,
});
toast.error(
t("cameraWizard.commonErrors.testFailed", { error: errorMessage }),
);
})
.finally(() => {
setTestingStreams((prev) => {
const newSet = new Set(prev);
newSet.delete(stream.id);
return newSet;
});
});
},
[updateStream, t],
);
const setRestream = useCallback(
(streamId: string) => {
const stream = streams.find((s) => s.id === streamId);
if (!stream) return;
updateStream(streamId, { restream: !stream.restream });
},
[streams, updateStream],
);
const hasDetectRole = streams.some((s) => s.roles.includes("detect"));
return (
<div className="space-y-6">
<div className="text-sm text-secondary-foreground">
{t("cameraWizard.step2.description")}
</div>
<div className="space-y-4">
{streams.map((stream, index) => (
<Card key={stream.id} className="bg-secondary text-primary">
<CardContent className="space-y-4 p-4">
<div className="flex items-center justify-between">
<div>
<h4 className="font-medium">
{t("cameraWizard.step2.streamTitle", { number: index + 1 })}
</h4>
{stream.testResult && stream.testResult.success && (
<div className="mt-1 text-sm text-muted-foreground">
{[
stream.testResult.resolution,
stream.testResult.fps
? `${stream.testResult.fps} ${t("cameraWizard.testResultLabels.fps")}`
: null,
stream.testResult.videoCodec,
stream.testResult.audioCodec,
]
.filter(Boolean)
.join(" · ")}
</div>
)}
</div>
<div className="flex items-center gap-2">
{stream.testResult?.success && (
<div className="flex items-center gap-2 text-sm">
<FaCircleCheck className="size-4 text-success" />
<span className="text-success">
{t("cameraWizard.step2.connected")}
</span>
</div>
)}
{stream.testResult && !stream.testResult.success && (
<div className="flex items-center gap-2 text-sm">
<LuX className="size-4 text-danger" />
<span className="text-danger">
{t("cameraWizard.step2.notConnected")}
</span>
</div>
)}
{streams.length > 1 && (
<Button
variant="ghost"
size="sm"
onClick={() => removeStream(stream.id)}
className="text-secondary-foreground hover:text-secondary-foreground"
>
<LuTrash2 className="size-5" />
</Button>
)}
</div>
</div>
<div className="grid grid-cols-1 gap-4">
<div className="space-y-2">
<label className="text-sm font-medium text-primary-variant">
{t("cameraWizard.step2.url")}
</label>
<div className="flex flex-row items-center gap-2">
<Input
value={stream.url}
onChange={(e) =>
updateStream(stream.id, {
url: e.target.value,
testResult: undefined,
})
}
className="h-8 flex-1"
placeholder={t("cameraWizard.step2.streamUrlPlaceholder")}
/>
<Button
type="button"
onClick={() => testStream(stream)}
disabled={
testingStreams.has(stream.id) || !stream.url.trim()
}
variant="outline"
size="sm"
>
{testingStreams.has(stream.id) && (
<ActivityIndicator className="mr-2 size-4" />
)}
{t("cameraWizard.step2.testStream")}
</Button>
</div>
</div>
</div>
{stream.testResult &&
!stream.testResult.success &&
stream.userTested && (
<div className="rounded-md border border-danger/20 bg-danger/10 p-3 text-sm text-danger">
<div className="font-medium">
{t("cameraWizard.step2.testFailedTitle")}
</div>
<div className="mt-1 text-xs">
{stream.testResult.error}
</div>
</div>
)}
<div className="space-y-2">
<div className="flex items-center gap-1">
<Label className="text-sm font-medium text-primary-variant">
{t("cameraWizard.step2.roles")}
</Label>
<Popover>
<PopoverTrigger asChild>
<Button variant="ghost" size="sm" className="h-4 w-4 p-0">
<LuInfo className="size-3" />
</Button>
</PopoverTrigger>
<PopoverContent className="pointer-events-auto w-80 text-xs">
<div className="space-y-2">
<div className="font-medium">
{t("cameraWizard.step2.rolesPopover.title")}
</div>
<div className="space-y-1 text-muted-foreground">
<div>
<strong>detect</strong> -{" "}
{t("cameraWizard.step2.rolesPopover.detect")}
</div>
<div>
<strong>record</strong> -{" "}
{t("cameraWizard.step2.rolesPopover.record")}
</div>
<div>
<strong>audio</strong> -{" "}
{t("cameraWizard.step2.rolesPopover.audio")}
</div>
</div>
<div className="mt-3 flex items-center text-primary">
<Link
to={getLocaleDocUrl("configuration/cameras")}
target="_blank"
rel="noopener noreferrer"
className="inline"
>
{t("readTheDocumentation", { ns: "common" })}
<LuExternalLink className="ml-2 inline-flex size-3" />
</Link>
</div>
</div>
</PopoverContent>
</Popover>
</div>
<div className="rounded-lg bg-background p-3">
<div className="flex flex-wrap gap-2">
{(["detect", "record", "audio"] as const).map((role) => {
const isUsedElsewhere = getUsedRolesExcludingStream(
stream.id,
).has(role);
const isChecked = stream.roles.includes(role);
return (
<div
key={role}
className="flex w-full items-center justify-between"
>
<span className="text-sm capitalize">{role}</span>
<Switch
checked={isChecked}
onCheckedChange={() => toggleRole(stream.id, role)}
disabled={!isChecked && isUsedElsewhere}
/>
</div>
);
})}
</div>
</div>
</div>
<div className="space-y-2">
<div className="flex items-center gap-1">
<Label className="text-sm font-medium text-primary-variant">
{t("cameraWizard.step2.featuresTitle")}
</Label>
<Popover>
<PopoverTrigger asChild>
<Button variant="ghost" size="sm" className="h-4 w-4 p-0">
<LuInfo className="size-3" />
</Button>
</PopoverTrigger>
<PopoverContent className="pointer-events-auto w-80 text-xs">
<div className="space-y-2">
<div className="font-medium">
{t("cameraWizard.step2.featuresPopover.title")}
</div>
<div className="text-muted-foreground">
{t("cameraWizard.step2.featuresPopover.description")}
</div>
<div className="mt-3 flex items-center text-primary">
<Link
to={getLocaleDocUrl(
"configuration/restream#reduce-connections-to-camera",
)}
target="_blank"
rel="noopener noreferrer"
className="inline"
>
{t("readTheDocumentation", { ns: "common" })}
<LuExternalLink className="ml-2 inline-flex size-3" />
</Link>
</div>
</div>
</PopoverContent>
</Popover>
</div>
<div className="rounded-lg bg-background p-3">
<div className="flex items-center justify-between">
<span className="text-sm">
{t("cameraWizard.step2.go2rtc")}
</span>
<Switch
checked={stream.restream || false}
onCheckedChange={() => setRestream(stream.id)}
/>
</div>
</div>
</div>
</CardContent>
</Card>
))}
<Button
type="button"
onClick={addStream}
variant="outline"
className=""
>
<LuPlus className="mr-2 size-4" />
{t("cameraWizard.step2.addAnotherStream")}
</Button>
</div>
{!hasDetectRole && (
<div className="rounded-lg border border-danger/50 p-3 text-sm text-danger">
{t("cameraWizard.step2.detectRoleWarning")}
</div>
)}
<div className="flex flex-col gap-3 pt-6 sm:flex-row sm:justify-end sm:gap-4">
{onBack && (
<Button type="button" onClick={onBack} className="sm:flex-1">
{t("button.back", { ns: "common" })}
</Button>
)}
{onNext && (
<Button
type="button"
onClick={() => onNext?.()}
disabled={!canProceed}
variant="select"
className="sm:flex-1"
>
{t("button.next", { ns: "common" })}
</Button>
)}
</div>
</div>
);
}

View File

@ -0,0 +1,757 @@
import { Button } from "@/components/ui/button";
import { Card, CardContent } from "@/components/ui/card";
import { Input } from "@/components/ui/input";
import { Switch } from "@/components/ui/switch";
import { useTranslation } from "react-i18next";
import { useState, useCallback, useMemo } from "react";
import { LuPlus, LuTrash2, LuX } from "react-icons/lu";
import ActivityIndicator from "@/components/indicators/activity-indicator";
import axios from "axios";
import { toast } from "sonner";
import {
WizardFormData,
StreamConfig,
StreamRole,
TestResult,
FfprobeStream,
FfprobeData,
FfprobeResponse,
CandidateTestMap,
} from "@/types/cameraWizard";
import { Label } from "../../ui/label";
import { FaCircleCheck } from "react-icons/fa6";
import {
Popover,
PopoverContent,
PopoverTrigger,
} from "@/components/ui/popover";
import { Drawer, DrawerContent, DrawerTrigger } from "@/components/ui/drawer";
import { isMobile } from "react-device-detect";
import {
LuInfo,
LuExternalLink,
LuCheck,
LuChevronsUpDown,
} from "react-icons/lu";
import { Link } from "react-router-dom";
import { useDocDomain } from "@/hooks/use-doc-domain";
import { cn } from "@/lib/utils";
import {
Command,
CommandEmpty,
CommandGroup,
CommandInput,
CommandItem,
CommandList,
} from "@/components/ui/command";
type Step3StreamConfigProps = {
wizardData: Partial<WizardFormData>;
onUpdate: (data: Partial<WizardFormData>) => void;
onBack?: () => void;
onNext?: () => void;
canProceed?: boolean;
};
export default function Step3StreamConfig({
wizardData,
onUpdate,
onBack,
onNext,
canProceed,
}: Step3StreamConfigProps) {
const { t } = useTranslation(["views/settings", "components/dialog"]);
const { getLocaleDocUrl } = useDocDomain();
const [testingStreams, setTestingStreams] = useState<Set<string>>(new Set());
const [openCombobox, setOpenCombobox] = useState<string | null>(null);
const streams = useMemo(() => wizardData.streams || [], [wizardData.streams]);
// Probe mode candidate tracking
const probeCandidates = useMemo(
() => (wizardData.probeCandidates || []) as string[],
[wizardData.probeCandidates],
);
const candidateTests = useMemo(
() => (wizardData.candidateTests || {}) as CandidateTestMap,
[wizardData.candidateTests],
);
const isProbeMode = !!wizardData.probeMode;
const addStream = useCallback(() => {
const newStreamId = `stream_${Date.now()}`;
let initialUrl = "";
if (isProbeMode && probeCandidates.length > 0) {
// pick first candidate not already used
const used = new Set(streams.map((s) => s.url).filter(Boolean));
const firstAvailable = probeCandidates.find((c) => !used.has(c));
if (firstAvailable) {
initialUrl = firstAvailable;
}
}
const newStream: StreamConfig = {
id: newStreamId,
url: initialUrl,
roles: [],
testResult: initialUrl ? candidateTests[initialUrl] : undefined,
userTested: initialUrl ? !!candidateTests[initialUrl] : false,
};
onUpdate({
streams: [...streams, newStream],
});
}, [streams, onUpdate, isProbeMode, probeCandidates, candidateTests]);
const removeStream = useCallback(
(streamId: string) => {
onUpdate({
streams: streams.filter((s) => s.id !== streamId),
});
},
[streams, onUpdate],
);
const updateStream = useCallback(
(streamId: string, updates: Partial<StreamConfig>) => {
onUpdate({
streams: streams.map((s) =>
s.id === streamId ? { ...s, ...updates } : s,
),
});
},
[streams, onUpdate],
);
const getUsedRolesExcludingStream = useCallback(
(excludeStreamId: string) => {
const roles = new Set<StreamRole>();
streams.forEach((stream) => {
if (stream.id !== excludeStreamId) {
stream.roles.forEach((role) => roles.add(role));
}
});
return roles;
},
[streams],
);
const getUsedUrlsExcludingStream = useCallback(
(excludeStreamId: string) => {
const used = new Set<string>();
streams.forEach((s) => {
if (s.id !== excludeStreamId && s.url) {
used.add(s.url);
}
});
return used;
},
[streams],
);
const toggleRole = useCallback(
(streamId: string, role: StreamRole) => {
const stream = streams.find((s) => s.id === streamId);
if (!stream) return;
const hasRole = stream.roles.includes(role);
if (hasRole) {
// Allow removing the role
const newRoles = stream.roles.filter((r) => r !== role);
updateStream(streamId, { roles: newRoles });
} else {
// Check if role is already used in another stream
const usedRoles = getUsedRolesExcludingStream(streamId);
if (!usedRoles.has(role)) {
// Allow adding the role
const newRoles = [...stream.roles, role];
updateStream(streamId, { roles: newRoles });
}
}
},
[streams, updateStream, getUsedRolesExcludingStream],
);
const testStream = useCallback(
async (stream: StreamConfig) => {
if (!stream.url.trim()) {
toast.error(t("cameraWizard.commonErrors.noUrl"));
return;
}
setTestingStreams((prev) => new Set(prev).add(stream.id));
try {
const response = await axios.get("ffprobe", {
params: { paths: stream.url, detailed: true },
timeout: 10000,
});
let probeData: FfprobeResponse | null = null;
if (
response.data &&
response.data.length > 0 &&
response.data[0].return_code === 0
) {
probeData = response.data[0];
}
if (!probeData) {
const error =
Array.isArray(response.data?.[0]?.stderr) &&
response.data[0].stderr.length > 0
? response.data[0].stderr.join("\n")
: "Unable to probe stream";
const failResult: TestResult = { success: false, error };
updateStream(stream.id, { testResult: failResult, userTested: true });
onUpdate({
candidateTests: {
...(wizardData.candidateTests || {}),
[stream.url]: failResult,
} as CandidateTestMap,
});
toast.error(t("cameraWizard.commonErrors.testFailed", { error }));
return;
}
let ffprobeData: FfprobeData;
if (typeof probeData.stdout === "string") {
try {
ffprobeData = JSON.parse(probeData.stdout as string) as FfprobeData;
} catch {
ffprobeData = { streams: [] } as FfprobeData;
}
} else {
ffprobeData = probeData.stdout as FfprobeData;
}
const streamsArr = ffprobeData.streams || [];
const videoStream = streamsArr.find(
(s: FfprobeStream) =>
s.codec_type === "video" ||
s.codec_name?.includes("h264") ||
s.codec_name?.includes("hevc"),
);
const audioStream = streamsArr.find(
(s: FfprobeStream) =>
s.codec_type === "audio" ||
s.codec_name?.includes("aac") ||
s.codec_name?.includes("mp3") ||
s.codec_name?.includes("pcm_mulaw") ||
s.codec_name?.includes("pcm_alaw"),
);
let resolution: string | undefined = undefined;
if (videoStream) {
const width = Number(videoStream.width || 0);
const height = Number(videoStream.height || 0);
if (width > 0 && height > 0) {
resolution = `${width}x${height}`;
}
}
const fps = videoStream?.avg_frame_rate
? parseFloat(videoStream.avg_frame_rate.split("/")[0]) /
parseFloat(videoStream.avg_frame_rate.split("/")[1])
: undefined;
const testResult: TestResult = {
success: true,
resolution,
videoCodec: videoStream?.codec_name,
audioCodec: audioStream?.codec_name,
fps: fps && !isNaN(fps) ? fps : undefined,
};
updateStream(stream.id, { testResult, userTested: true });
onUpdate({
candidateTests: {
...(wizardData.candidateTests || {}),
[stream.url]: testResult,
} as CandidateTestMap,
});
toast.success(t("cameraWizard.step3.testSuccess"));
} catch (error) {
const axiosError = error as {
response?: { data?: { message?: string; detail?: string } };
message?: string;
};
const errorMessage =
axiosError.response?.data?.message ||
axiosError.response?.data?.detail ||
axiosError.message ||
"Connection failed";
const catchResult: TestResult = {
success: false,
error: errorMessage,
};
updateStream(stream.id, { testResult: catchResult, userTested: true });
onUpdate({
candidateTests: {
...(wizardData.candidateTests || {}),
[stream.url]: catchResult,
} as CandidateTestMap,
});
toast.error(
t("cameraWizard.commonErrors.testFailed", { error: errorMessage }),
);
} finally {
setTestingStreams((prev) => {
const newSet = new Set(prev);
newSet.delete(stream.id);
return newSet;
});
}
},
[updateStream, t, onUpdate, wizardData.candidateTests],
);
const setRestream = useCallback(
(streamId: string) => {
const stream = streams.find((s) => s.id === streamId);
if (!stream) return;
updateStream(streamId, { restream: !stream.restream });
},
[streams, updateStream],
);
const hasDetectRole = streams.some((s) => s.roles.includes("detect"));
return (
<div className="space-y-6">
<div className="text-sm text-secondary-foreground">
{t("cameraWizard.step3.description")}
</div>
<div className="space-y-4">
{streams.map((stream, index) => (
<Card key={stream.id} className="bg-secondary text-primary">
<CardContent className="space-y-4 p-4">
<div className="flex items-center justify-between">
<div>
<h4 className="font-medium">
{t("cameraWizard.step3.streamTitle", { number: index + 1 })}
</h4>
{stream.testResult && stream.testResult.success && (
<div className="mt-1 text-sm text-muted-foreground">
{[
stream.testResult.resolution,
stream.testResult.fps
? `${stream.testResult.fps} ${t("cameraWizard.testResultLabels.fps")}`
: null,
stream.testResult.videoCodec,
stream.testResult.audioCodec,
]
.filter(Boolean)
.join(" · ")}
</div>
)}
</div>
<div className="flex items-center gap-2">
{stream.testResult?.success && (
<div className="flex items-center gap-2 text-sm">
<FaCircleCheck className="size-4 text-success" />
<span className="text-success">
{t("cameraWizard.step3.connected")}
</span>
</div>
)}
{stream.testResult && !stream.testResult.success && (
<div className="flex items-center gap-2 text-sm">
<LuX className="size-4 text-danger" />
<span className="text-danger">
{t("cameraWizard.step3.notConnected")}
</span>
</div>
)}
{streams.length > 1 && (
<Button
variant="ghost"
size="sm"
onClick={() => removeStream(stream.id)}
className="text-secondary-foreground hover:text-secondary-foreground"
>
<LuTrash2 className="size-5" />
</Button>
)}
</div>
</div>
<div className="grid grid-cols-1 gap-4">
<div className="space-y-2">
<label className="text-sm font-medium text-primary-variant">
{t("cameraWizard.step3.url")}
</label>
<div className="flex flex-row items-center gap-2">
{isProbeMode && probeCandidates.length > 0 ? (
// Responsive: Popover on desktop, Drawer on mobile
!isMobile ? (
<Popover
open={openCombobox === stream.id}
onOpenChange={(isOpen) => {
setOpenCombobox(isOpen ? stream.id : null);
}}
>
<PopoverTrigger asChild>
<div className="min-w-0 flex-1">
<Button
variant="outline"
role="combobox"
aria-expanded={openCombobox === stream.id}
className="h-8 w-full justify-between overflow-hidden text-left"
>
<span className="truncate">
{stream.url
? stream.url
: t("cameraWizard.step3.selectStream")}
</span>
<LuChevronsUpDown className="ml-2 size-6 opacity-50" />
</Button>
</div>
</PopoverTrigger>
<PopoverContent
className="w-[--radix-popover-trigger-width] p-2"
disablePortal
>
<Command>
<CommandInput
placeholder={t(
"cameraWizard.step3.searchCandidates",
)}
className="h-9"
/>
<CommandList>
<CommandEmpty>
{t("cameraWizard.step3.noStreamFound")}
</CommandEmpty>
<CommandGroup>
{probeCandidates
.filter((c) => {
const used = getUsedUrlsExcludingStream(
stream.id,
);
return !used.has(c);
})
.map((candidate) => (
<CommandItem
key={candidate}
value={candidate}
onSelect={() => {
updateStream(stream.id, {
url: candidate,
testResult:
candidateTests[candidate] ||
undefined,
userTested:
!!candidateTests[candidate],
});
setOpenCombobox(null);
}}
>
<LuCheck
className={cn(
"mr-3 size-5",
stream.url === candidate
? "opacity-100"
: "opacity-0",
)}
/>
{candidate}
</CommandItem>
))}
</CommandGroup>
</CommandList>
</Command>
</PopoverContent>
</Popover>
) : (
<Drawer
open={openCombobox === stream.id}
onOpenChange={(isOpen) =>
setOpenCombobox(isOpen ? stream.id : null)
}
>
<DrawerTrigger asChild>
<div className="min-w-0 flex-1">
<Button
variant="outline"
role="combobox"
aria-expanded={openCombobox === stream.id}
className="h-8 w-full justify-between overflow-hidden text-left"
>
<span className="truncate">
{stream.url
? stream.url
: t("cameraWizard.step3.selectStream")}
</span>
<LuChevronsUpDown className="ml-2 size-6 opacity-50" />
</Button>
</div>
</DrawerTrigger>
<DrawerContent className="mx-1 max-h-[75dvh] overflow-hidden rounded-t-2xl px-2">
<div className="mt-2">
<Command>
<CommandInput
placeholder={t(
"cameraWizard.step3.searchCandidates",
)}
className="h-9"
/>
<CommandList>
<CommandEmpty>
{t("cameraWizard.step3.noStreamFound")}
</CommandEmpty>
<CommandGroup>
{probeCandidates
.filter((c) => {
const used = getUsedUrlsExcludingStream(
stream.id,
);
return !used.has(c);
})
.map((candidate) => (
<CommandItem
key={candidate}
value={candidate}
onSelect={() => {
updateStream(stream.id, {
url: candidate,
testResult:
candidateTests[candidate] ||
undefined,
userTested:
!!candidateTests[candidate],
});
setOpenCombobox(null);
}}
>
<LuCheck
className={cn(
"mr-3 size-5",
stream.url === candidate
? "opacity-100"
: "opacity-0",
)}
/>
{candidate}
</CommandItem>
))}
</CommandGroup>
</CommandList>
</Command>
</div>
</DrawerContent>
</Drawer>
)
) : (
<Input
value={stream.url}
onChange={(e) =>
updateStream(stream.id, {
url: e.target.value,
testResult: undefined,
})
}
className="h-8 flex-1"
placeholder={t(
"cameraWizard.step3.streamUrlPlaceholder",
)}
/>
)}
<Button
type="button"
onClick={() => testStream(stream)}
disabled={
testingStreams.has(stream.id) || !stream.url.trim()
}
variant="outline"
size="sm"
>
{testingStreams.has(stream.id) && (
<ActivityIndicator className="mr-2 size-4" />
)}
{t("cameraWizard.step3.testStream")}
</Button>
</div>
</div>
</div>
{stream.testResult &&
!stream.testResult.success &&
stream.userTested && (
<div className="rounded-md border border-danger/20 bg-danger/10 p-3 text-sm text-danger">
<div className="font-medium">
{t("cameraWizard.step3.testFailedTitle")}
</div>
<div className="mt-1 text-xs">
{stream.testResult.error}
</div>
</div>
)}
<div className="space-y-2">
<div className="flex items-center gap-1">
<Label className="text-sm font-medium text-primary-variant">
{t("cameraWizard.step3.roles")}
</Label>
<Popover>
<PopoverTrigger asChild>
<Button variant="ghost" size="sm" className="h-4 w-4 p-0">
<LuInfo className="size-3" />
</Button>
</PopoverTrigger>
<PopoverContent className="pointer-events-auto w-80 text-xs">
<div className="space-y-2">
<div className="font-medium">
{t("cameraWizard.step3.rolesPopover.title")}
</div>
<div className="space-y-1 text-muted-foreground">
<div>
<strong>detect</strong> -{" "}
{t("cameraWizard.step3.rolesPopover.detect")}
</div>
<div>
<strong>record</strong> -{" "}
{t("cameraWizard.step3.rolesPopover.record")}
</div>
<div>
<strong>audio</strong> -{" "}
{t("cameraWizard.step3.rolesPopover.audio")}
</div>
</div>
<div className="mt-3 flex items-center text-primary">
<Link
to={getLocaleDocUrl("configuration/cameras")}
target="_blank"
rel="noopener noreferrer"
className="inline"
>
{t("readTheDocumentation", { ns: "common" })}
<LuExternalLink className="ml-2 inline-flex size-3" />
</Link>
</div>
</div>
</PopoverContent>
</Popover>
</div>
<div className="rounded-lg bg-background p-3">
<div className="flex flex-wrap gap-2">
{(["detect", "record", "audio"] as const).map((role) => {
const isUsedElsewhere = getUsedRolesExcludingStream(
stream.id,
).has(role);
const isChecked = stream.roles.includes(role);
return (
<div
key={role}
className="flex w-full items-center justify-between"
>
<span className="text-sm capitalize">{role}</span>
<Switch
checked={isChecked}
onCheckedChange={() => toggleRole(stream.id, role)}
disabled={!isChecked && isUsedElsewhere}
/>
</div>
);
})}
</div>
</div>
</div>
<div className="space-y-2">
<div className="flex items-center gap-1">
<Label className="text-sm font-medium text-primary-variant">
{t("cameraWizard.step3.featuresTitle")}
</Label>
<Popover>
<PopoverTrigger asChild>
<Button variant="ghost" size="sm" className="h-4 w-4 p-0">
<LuInfo className="size-3" />
</Button>
</PopoverTrigger>
<PopoverContent className="pointer-events-auto w-80 text-xs">
<div className="space-y-2">
<div className="font-medium">
{t("cameraWizard.step3.featuresPopover.title")}
</div>
<div className="text-muted-foreground">
{t("cameraWizard.step3.featuresPopover.description")}
</div>
<div className="mt-3 flex items-center text-primary">
<Link
to={getLocaleDocUrl(
"configuration/restream#reduce-connections-to-camera",
)}
target="_blank"
rel="noopener noreferrer"
className="inline"
>
{t("readTheDocumentation", { ns: "common" })}
<LuExternalLink className="ml-2 inline-flex size-3" />
</Link>
</div>
</div>
</PopoverContent>
</Popover>
</div>
<div className="rounded-lg bg-background p-3">
<div className="flex items-center justify-between">
<span className="text-sm">
{t("cameraWizard.step3.go2rtc")}
</span>
<Switch
checked={stream.restream || false}
onCheckedChange={() => setRestream(stream.id)}
/>
</div>
</div>
</div>
</CardContent>
</Card>
))}
<Button
type="button"
onClick={addStream}
variant="outline"
className=""
>
<LuPlus className="mr-2 size-4" />
{t("cameraWizard.step3.addAnotherStream")}
</Button>
</div>
{!hasDetectRole && (
<div className="rounded-lg border border-danger/50 p-3 text-sm text-danger">
{t("cameraWizard.step3.detectRoleWarning")}
</div>
)}
<div className="flex flex-col gap-3 pt-6 sm:flex-row sm:justify-end sm:gap-4">
{onBack && (
<Button type="button" onClick={onBack} className="sm:flex-1">
{t("button.back", { ns: "common" })}
</Button>
)}
{onNext && (
<Button
type="button"
onClick={() => onNext?.()}
disabled={!canProceed || testingStreams.size > 0}
variant="select"
className="sm:flex-1"
>
{t("button.next", { ns: "common" })}
</Button>
)}
</div>
</div>
);
}

View File

@ -18,8 +18,9 @@ import { PlayerStatsType } from "@/types/live";
import { FaCircleCheck, FaTriangleExclamation } from "react-icons/fa6";
import { LuX } from "react-icons/lu";
import { Card, CardContent } from "../../ui/card";
import { maskUri } from "@/utils/cameraUtil";
type Step3ValidationProps = {
type Step4ValidationProps = {
wizardData: Partial<WizardFormData>;
onUpdate: (data: Partial<WizardFormData>) => void;
onSave: (config: WizardFormData) => void;
@ -27,13 +28,13 @@ type Step3ValidationProps = {
isLoading?: boolean;
};
export default function Step3Validation({
export default function Step4Validation({
wizardData,
onUpdate,
onSave,
onBack,
isLoading = false,
}: Step3ValidationProps) {
}: Step4ValidationProps) {
const { t } = useTranslation(["views/settings"]);
const [isValidating, setIsValidating] = useState(false);
const [testingStreams, setTestingStreams] = useState<Set<string>>(new Set());
@ -143,13 +144,13 @@ export default function Step3Validation({
if (testResult.success) {
toast.success(
t("cameraWizard.step3.streamValidated", {
t("cameraWizard.step4.streamValidated", {
number: streams.findIndex((s) => s.id === stream.id) + 1,
}),
);
} else {
toast.error(
t("cameraWizard.step3.streamValidationFailed", {
t("cameraWizard.step4.streamValidationFailed", {
number: streams.findIndex((s) => s.id === stream.id) + 1,
}),
);
@ -200,16 +201,16 @@ export default function Step3Validation({
(r) => r.success,
).length;
if (successfulTests === results.size) {
toast.success(t("cameraWizard.step3.reconnectionSuccess"));
toast.success(t("cameraWizard.step4.reconnectionSuccess"));
} else {
toast.warning(t("cameraWizard.step3.reconnectionPartial"));
toast.warning(t("cameraWizard.step4.reconnectionPartial"));
}
}
}, [streams, onUpdate, t, performStreamValidation]);
const handleSave = useCallback(() => {
if (!wizardData.cameraName || !wizardData.streams?.length) {
toast.error(t("cameraWizard.step3.saveError"));
toast.error(t("cameraWizard.step4.saveError"));
return;
}
@ -239,13 +240,13 @@ export default function Step3Validation({
return (
<div className="space-y-6">
<div className="text-sm text-muted-foreground">
{t("cameraWizard.step3.description")}
{t("cameraWizard.step4.description")}
</div>
<div className="space-y-4">
<div className="flex items-center justify-between">
<h3 className="text-lg font-medium">
{t("cameraWizard.step3.validationTitle")}
{t("cameraWizard.step4.validationTitle")}
</h3>
<Button
onClick={validateAllStreams}
@ -254,8 +255,8 @@ export default function Step3Validation({
>
{isValidating && <ActivityIndicator className="mr-2 size-4" />}
{isValidating
? t("cameraWizard.step3.connecting")
: t("cameraWizard.step3.connectAllStreams")}
? t("cameraWizard.step4.connecting")
: t("cameraWizard.step4.connectAllStreams")}
</Button>
</div>
@ -270,7 +271,7 @@ export default function Step3Validation({
<div className="flex flex-col space-y-1">
<div className="flex flex-row items-center">
<h4 className="mr-2 font-medium">
{t("cameraWizard.step3.streamTitle", {
{t("cameraWizard.step4.streamTitle", {
number: index + 1,
})}
</h4>
@ -331,7 +332,7 @@ export default function Step3Validation({
<div className="mb-3 flex items-center justify-between">
<div className="flex items-center gap-2">
<span className="text-sm">
{t("cameraWizard.step3.ffmpegModule")}
{t("cameraWizard.step4.ffmpegModule")}
</span>
<Popover>
<PopoverTrigger asChild>
@ -346,11 +347,11 @@ export default function Step3Validation({
<PopoverContent className="pointer-events-auto w-80 text-xs">
<div className="space-y-2">
<div className="font-medium">
{t("cameraWizard.step3.ffmpegModule")}
{t("cameraWizard.step4.ffmpegModule")}
</div>
<div className="text-muted-foreground">
{t(
"cameraWizard.step3.ffmpegModuleDescription",
"cameraWizard.step4.ffmpegModuleDescription",
)}
</div>
</div>
@ -374,7 +375,7 @@ export default function Step3Validation({
<div className="mb-2 flex flex-col justify-between gap-1 md:flex-row md:items-center">
<span className="break-all text-sm text-muted-foreground">
{stream.url}
{maskUri(stream.url)}
</span>
<Button
onClick={() => {
@ -402,17 +403,17 @@ export default function Step3Validation({
<ActivityIndicator className="mr-2 size-4" />
)}
{result?.success
? t("cameraWizard.step3.disconnectStream")
? t("cameraWizard.step4.disconnectStream")
: testingStreams.has(stream.id)
? t("cameraWizard.step3.connectingStream")
: t("cameraWizard.step3.connectStream")}
? t("cameraWizard.step4.connectingStream")
: t("cameraWizard.step4.connectStream")}
</Button>
</div>
{result && (
<div className="space-y-2">
<div className="text-xs">
{t("cameraWizard.step3.issues.title")}
{t("cameraWizard.step4.issues.title")}
</div>
<div className="rounded-lg bg-background p-3">
<StreamIssues
@ -455,7 +456,7 @@ export default function Step3Validation({
{isLoading && <ActivityIndicator className="mr-2 size-4" />}
{isLoading
? t("button.saving", { ns: "common" })
: t("cameraWizard.step3.saveAndApply")}
: t("cameraWizard.step4.saveAndApply")}
</Button>
</div>
</div>
@ -486,7 +487,7 @@ function StreamIssues({
if (streamUrl.startsWith("rtsp://")) {
result.push({
type: "warning",
message: t("cameraWizard.step1.errors.brands.reolink-rtsp"),
message: t("cameraWizard.step4.issues.brands.reolink-rtsp"),
});
}
}
@ -497,7 +498,7 @@ function StreamIssues({
if (["h264", "h265", "hevc"].includes(videoCodec)) {
result.push({
type: "good",
message: t("cameraWizard.step3.issues.videoCodecGood", {
message: t("cameraWizard.step4.issues.videoCodecGood", {
codec: stream.testResult.videoCodec,
}),
});
@ -511,20 +512,20 @@ function StreamIssues({
if (audioCodec === "aac") {
result.push({
type: "good",
message: t("cameraWizard.step3.issues.audioCodecGood", {
message: t("cameraWizard.step4.issues.audioCodecGood", {
codec: stream.testResult.audioCodec,
}),
});
} else {
result.push({
type: "error",
message: t("cameraWizard.step3.issues.audioCodecRecordError"),
message: t("cameraWizard.step4.issues.audioCodecRecordError"),
});
}
} else {
result.push({
type: "warning",
message: t("cameraWizard.step3.issues.noAudioWarning"),
message: t("cameraWizard.step4.issues.noAudioWarning"),
});
}
}
@ -534,7 +535,7 @@ function StreamIssues({
if (!stream.testResult?.audioCodec) {
result.push({
type: "error",
message: t("cameraWizard.step3.issues.audioCodecRequired"),
message: t("cameraWizard.step4.issues.audioCodecRequired"),
});
}
}
@ -544,7 +545,7 @@ function StreamIssues({
if (stream.restream) {
result.push({
type: "warning",
message: t("cameraWizard.step3.issues.restreamingWarning"),
message: t("cameraWizard.step4.issues.restreamingWarning"),
});
}
}
@ -557,14 +558,14 @@ function StreamIssues({
if (minDimension > 1080) {
result.push({
type: "warning",
message: t("cameraWizard.step3.issues.resolutionHigh", {
message: t("cameraWizard.step4.issues.resolutionHigh", {
resolution: stream.resolution,
}),
});
} else if (maxDimension < 640) {
result.push({
type: "error",
message: t("cameraWizard.step3.issues.resolutionLow", {
message: t("cameraWizard.step4.issues.resolutionLow", {
resolution: stream.resolution,
}),
});
@ -580,7 +581,7 @@ function StreamIssues({
) {
result.push({
type: "warning",
message: t("cameraWizard.step3.issues.dahua.substreamWarning"),
message: t("cameraWizard.step4.issues.dahua.substreamWarning"),
});
}
if (
@ -590,7 +591,7 @@ function StreamIssues({
) {
result.push({
type: "warning",
message: t("cameraWizard.step3.issues.hikvision.substreamWarning"),
message: t("cameraWizard.step4.issues.hikvision.substreamWarning"),
});
}
@ -662,7 +663,7 @@ function BandwidthDisplay({
return (
<div className="mb-2 text-sm">
<span className="font-medium text-muted-foreground">
{t("cameraWizard.step3.estimatedBandwidth")}:
{t("cameraWizard.step4.estimatedBandwidth")}:
</span>{" "}
<span className="text-secondary-foreground">
{streamBandwidth.toFixed(1)} {t("unit.data.kbps", { ns: "common" })}
@ -748,7 +749,7 @@ function StreamPreview({ stream, onBandwidthUpdate }: StreamPreviewProps) {
style={{ aspectRatio }}
>
<span className="text-sm text-danger">
{t("cameraWizard.step3.streamUnavailable")}
{t("cameraWizard.step4.streamUnavailable")}
</span>
<Button
variant="outline"
@ -757,7 +758,7 @@ function StreamPreview({ stream, onBandwidthUpdate }: StreamPreviewProps) {
className="flex items-center gap-2"
>
<LuRotateCcw className="size-4" />
{t("cameraWizard.step3.reload")}
{t("cameraWizard.step4.reload")}
</Button>
</div>
);
@ -771,7 +772,7 @@ function StreamPreview({ stream, onBandwidthUpdate }: StreamPreviewProps) {
>
<ActivityIndicator className="size-4" />
<span className="ml-2 text-sm">
{t("cameraWizard.step3.connecting")}
{t("cameraWizard.step4.connecting")}
</span>
</div>
);

View File

@ -15,7 +15,7 @@ import useSWR from "swr";
import ActivityIndicator from "../indicators/activity-indicator";
import { Event } from "@/types/event";
import { getIconForLabel } from "@/utils/iconUtil";
import { ReviewSegment } from "@/types/review";
import { REVIEW_PADDING, ReviewSegment } from "@/types/review";
import { LuChevronDown, LuCircle, LuChevronRight } from "react-icons/lu";
import { getTranslatedLabel } from "@/utils/i18n";
import EventMenu from "@/components/timeline/EventMenu";
@ -349,7 +349,7 @@ function ReviewGroup({
? fetchedEvents.length
: (review.data.objects ?? []).length;
return `${objectCount} ${t("detail.trackedObject", { count: objectCount })}`;
return `${t("detail.trackedObject", { count: objectCount })}`;
}, [review, t, fetchedEvents]);
const reviewDuration = useMemo(
@ -391,8 +391,8 @@ function ReviewGroup({
)}
/>
</div>
<div className="mr-3 flex w-full justify-between">
<div className="ml-1 flex flex-col items-start gap-1.5">
<div className="mr-3 grid w-full grid-cols-[1fr_auto] gap-2">
<div className="ml-1 flex min-w-0 flex-col gap-1.5">
<div className="flex flex-row gap-3">
<div className="text-sm font-medium">{displayTime}</div>
<div className="relative flex items-center gap-2 text-white">
@ -408,7 +408,7 @@ function ReviewGroup({
</div>
<div className="flex flex-col gap-0.5">
{review.data.metadata?.title && (
<div className="mb-1 flex items-center gap-1 text-sm text-primary-variant">
<div className="mb-1 flex min-w-0 items-center gap-1 text-sm text-primary-variant">
<MdAutoAwesome className="size-3 shrink-0" />
<span className="truncate">{review.data.metadata.title}</span>
</div>
@ -432,7 +432,7 @@ function ReviewGroup({
e.stopPropagation();
setOpen((v) => !v);
}}
className="ml-2 inline-flex items-center justify-center rounded p-1 hover:bg-secondary/10"
className="inline-flex items-center justify-center self-center rounded p-1 hover:bg-secondary/10"
>
{open ? (
<LuChevronDown className="size-4 text-primary-variant" />
@ -478,7 +478,7 @@ function ReviewGroup({
<div className="rounded-full bg-muted-foreground p-1">
{getIconForLabel(audioLabel, "size-3 text-white")}
</div>
<span>{getTranslatedLabel(audioLabel)}</span>
<span>{getTranslatedLabel(audioLabel, "audio")}</span>
</div>
</div>
))}
@ -513,7 +513,8 @@ function EventList({
const isSelected = selectedObjectIds.includes(event.id);
const label = event.sub_label || getTranslatedLabel(event.label);
const label =
event.sub_label || getTranslatedLabel(event.label, event.data.type);
const handleObjectSelect = (event: Event | undefined) => {
if (event) {
@ -803,8 +804,9 @@ function ObjectTimeline({
return fullTimeline
.filter(
(t) =>
t.timestamp >= review.start_time &&
(review.end_time == undefined || t.timestamp <= review.end_time),
t.timestamp >= review.start_time - REVIEW_PADDING &&
(review.end_time == undefined ||
t.timestamp <= review.end_time + REVIEW_PADDING),
)
.map((event) => ({
...event,

View File

@ -515,7 +515,7 @@ export function ReviewTimeline({
<div
className={`absolute z-30 flex gap-2 ${
isMobile
? "bottom-4 right-1 flex-col gap-3"
? "bottom-4 right-1 flex-col-reverse gap-3"
: "bottom-2 left-1/2 -translate-x-1/2"
}`}
>

View File

@ -1,4 +1,10 @@
import React, { createContext, useContext, useState, useEffect } from "react";
import React, {
createContext,
useContext,
useState,
useEffect,
useRef,
} from "react";
import { FrigateConfig } from "@/types/frigateConfig";
import useSWR from "swr";
@ -36,6 +42,23 @@ export function DetailStreamProvider({
() => initialSelectedObjectIds ?? [],
);
// When the parent provides a new initialSelectedObjectIds (for example
// when navigating between search results) update the selection so children
// like `ObjectTrackOverlay` receive the new ids immediately. We only
// perform this update when the incoming value actually changes.
useEffect(() => {
if (
initialSelectedObjectIds &&
(initialSelectedObjectIds.length !== selectedObjectIds.length ||
initialSelectedObjectIds.some((v, i) => selectedObjectIds[i] !== v))
) {
setSelectedObjectIds(initialSelectedObjectIds);
}
// Intentionally include selectedObjectIds to compare previous value and
// avoid overwriting user interactions unless the incoming prop changed.
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [initialSelectedObjectIds]);
const toggleObjectSelection = (id: string | undefined) => {
if (id === undefined) {
setSelectedObjectIds([]);
@ -63,10 +86,33 @@ export function DetailStreamProvider({
setAnnotationOffset(cfgOffset);
}, [config, camera]);
// Clear selected objects when exiting detail mode or changing cameras
// Clear selected objects when exiting detail mode or when the camera
// changes for providers that are not initialized with an explicit
// `initialSelectedObjectIds` (e.g., the RecordingView). For providers
// that receive `initialSelectedObjectIds` (like SearchDetailDialog) we
// avoid clearing on camera change to prevent a race with children that
// immediately set selection when mounting.
const prevCameraRef = useRef<string | undefined>(undefined);
useEffect(() => {
setSelectedObjectIds([]);
}, [isDetailMode, camera]);
// Always clear when leaving detail mode
if (!isDetailMode) {
setSelectedObjectIds([]);
prevCameraRef.current = camera;
return;
}
// If camera changed and the parent did not provide initialSelectedObjectIds,
// clear selection to preserve previous behavior.
if (
prevCameraRef.current !== undefined &&
prevCameraRef.current !== camera &&
initialSelectedObjectIds === undefined
) {
setSelectedObjectIds([]);
}
prevCameraRef.current = camera;
}, [isDetailMode, camera, initialSelectedObjectIds]);
const value: DetailStreamContextType = {
selectedObjectIds,

View File

@ -6,6 +6,7 @@ import { LivePlayerMode, LiveStreamMetadata } from "@/types/live";
export default function useCameraLiveMode(
cameras: CameraConfig[],
windowVisible: boolean,
activeStreams?: { [cameraName: string]: string },
) {
const { data: config } = useSWR<FrigateConfig>("config");
@ -20,16 +21,20 @@ export default function useCameraLiveMode(
);
if (isRestreamed) {
Object.values(camera.live.streams).forEach((streamName) => {
streamNames.add(streamName);
});
if (activeStreams && activeStreams[camera.name]) {
streamNames.add(activeStreams[camera.name]);
} else {
Object.values(camera.live.streams).forEach((streamName) => {
streamNames.add(streamName);
});
}
}
});
return streamNames.size > 0
? Array.from(streamNames).sort().join(",")
: null;
}, [cameras, config]);
}, [cameras, config, activeStreams]);
const streamsFetcher = useCallback(async (key: string) => {
const streamNames = key.split(",");
@ -68,7 +73,9 @@ export default function useCameraLiveMode(
[key: string]: LiveStreamMetadata;
}>(restreamedStreamsKey, streamsFetcher, {
revalidateOnFocus: false,
dedupingInterval: 10000,
revalidateOnReconnect: false,
revalidateIfStale: false,
dedupingInterval: 60000,
});
const [preferredLiveModes, setPreferredLiveModes] = useState<{

View File

@ -622,7 +622,15 @@ type TrainingGridProps = {
faceNames: string[];
selectedFaces: string[];
onClickFaces: (images: string[], ctrl: boolean) => void;
onRefresh: () => void;
onRefresh: (
data?:
| FaceLibraryData
| Promise<FaceLibraryData>
| ((
currentData: FaceLibraryData | undefined,
) => FaceLibraryData | undefined),
opts?: boolean | { revalidate?: boolean },
) => Promise<FaceLibraryData | undefined>;
};
function TrainingGrid({
config,
@ -726,7 +734,15 @@ type FaceAttemptGroupProps = {
faceNames: string[];
selectedFaces: string[];
onClickFaces: (image: string[], ctrl: boolean) => void;
onRefresh: () => void;
onRefresh: (
data?:
| FaceLibraryData
| Promise<FaceLibraryData>
| ((
currentData: FaceLibraryData | undefined,
) => FaceLibraryData | undefined),
opts?: boolean | { revalidate?: boolean },
) => Promise<FaceLibraryData | undefined>;
};
function FaceAttemptGroup({
config,
@ -814,11 +830,44 @@ function FaceAttemptGroup({
axios
.post(`/faces/reprocess`, { training_file: data.filename })
.then((resp) => {
if (resp.status == 200) {
toast.success(t("toast.success.updatedFaceScore"), {
position: "top-center",
});
onRefresh();
if (resp.status == 200 && resp.data?.success) {
const { face_name, score } = resp.data;
const oldFilename = data.filename;
const parts = oldFilename.split("-");
const newFilename = `${parts[0]}-${parts[1]}-${parts[2]}-${face_name}-${score}.webp`;
onRefresh(
(currentData: FaceLibraryData | undefined) => {
if (!currentData?.train) return currentData;
return {
...currentData,
train: currentData.train.map((filename: string) =>
filename === oldFilename ? newFilename : filename,
),
};
},
{ revalidate: true },
);
toast.success(
t("toast.success.updatedFaceScore", {
name: face_name,
score: score.toFixed(2),
}),
{
position: "top-center",
},
);
} else if (resp.data?.success === false) {
// Handle case where API returns success: false
const errorMessage = resp.data?.message || "Unknown error";
toast.error(
t("toast.error.updateFaceScoreFailed", { errorMessage }),
{
position: "top-center",
},
);
}
})
.catch((error) => {

View File

@ -99,6 +99,11 @@ export type TestResult = {
error?: string;
};
export type CandidateTestMap = Record<
string,
TestResult | { success: false; error: string }
>;
export type WizardFormData = {
cameraName?: string;
host?: string;
@ -107,12 +112,18 @@ export type WizardFormData = {
brandTemplate?: CameraBrand;
customUrl?: string;
streams?: StreamConfig[];
probeMode?: boolean; // true for probe, false for manual
onvifPort?: number;
useDigestAuth?: boolean;
probeResult?: OnvifProbeResponse;
probeCandidates?: string[]; // candidate URLs from probe
candidateTests?: CandidateTestMap; // test results for candidates
};
// API Response Types
export type FfprobeResponse = {
return_code: number;
stderr: string;
stderr: string | string[];
stdout: FfprobeData | string;
};
@ -167,3 +178,26 @@ export type ConfigSetBody = {
config_data: CameraConfigData;
update_topic?: string;
};
export type OnvifRtspCandidate = {
source: "GetStreamUri" | "pattern";
profile_token?: string;
uri: string;
};
export type OnvifProbeResponse = {
success: boolean;
host?: string;
port?: number;
manufacturer?: string;
model?: string;
firmware_version?: string;
profiles_count?: number;
ptz_supported?: boolean;
presets_count?: number;
autotrack_supported?: boolean;
move_status_supported?: boolean;
rtsp_candidates?: OnvifRtspCandidate[];
message?: string;
detail?: string;
};

View File

@ -20,3 +20,17 @@ export type ClassificationThreshold = {
recognition: number;
unknown: number;
};
export type ClassificationDatasetResponse = {
categories: {
[id: string]: string[];
};
training_metadata: {
has_trained: boolean;
last_training_date: string | null;
last_training_image_count: number;
current_image_count: number;
new_images_count: number;
dataset_changed: boolean;
} | null;
};

View File

@ -87,7 +87,8 @@ export type ModelState =
| "downloaded"
| "error"
| "training"
| "complete";
| "complete"
| "failed";
export type EmbeddingsReindexProgressType = {
thumbnails: number;

View File

@ -71,3 +71,26 @@ export async function detectReolinkCamera(
return null;
}
}
/**
* Mask credentials in RTSP URIs for display
*/
export function maskUri(uri: string): string {
try {
// Handle RTSP URLs with user:pass@host format
const rtspMatch = uri.match(/rtsp:\/\/([^:]+):([^@]+)@(.+)/);
if (rtspMatch) {
return `rtsp://${rtspMatch[1]}:${"*".repeat(4)}@${rtspMatch[3]}`;
}
// Handle HTTP/HTTPS URLs with password query parameter
const urlObj = new URL(uri);
if (urlObj.searchParams.has("password")) {
urlObj.searchParams.set("password", "*".repeat(4));
return urlObj.toString();
}
} catch (e) {
// ignore
}
return uri;
}

View File

@ -244,12 +244,12 @@ export const getDurationFromTimestamps = (
abbreviated: boolean = false,
): string => {
if (isNaN(start_time)) {
return "Invalid start time";
return i18n.t("time.invalidStartTime", { ns: "common" });
}
let duration = "In Progress";
let duration = i18n.t("time.inProgress", { ns: "common" });
if (end_time !== null) {
if (isNaN(end_time)) {
return "Invalid end time";
return i18n.t("time.invalidEndTime", { ns: "common" });
}
const start = fromUnixTime(start_time);
const end = fromUnixTime(end_time);

View File

@ -21,20 +21,30 @@ export const capitalizeAll = (text: string): string => {
* @returns A valid camera identifier (lowercase, alphanumeric, max 8 chars)
*/
export function generateFixedHash(name: string, prefix: string = "id"): string {
// Safely encode Unicode as UTF-8 bytes
// Use the full UTF-8 bytes of the name and compute an FNV-1a 32-bit hash.
// This is deterministic, fast, works with Unicode and avoids collisions from
// simple truncation of base64 output.
const utf8Bytes = new TextEncoder().encode(name);
// Convert to base64 manually
let binary = "";
for (const byte of utf8Bytes) {
binary += String.fromCharCode(byte);
// FNV-1a 32-bit hash algorithm
let hash = 0x811c9dc5; // FNV offset basis
for (let i = 0; i < utf8Bytes.length; i++) {
hash ^= utf8Bytes[i];
// Multiply by FNV prime (0x01000193) with 32-bit overflow
hash = (hash >>> 0) * 0x01000193;
// Ensure 32-bit unsigned integer
hash >>>= 0;
}
const base64 = btoa(binary);
// Strip out non-alphanumeric characters and truncate
const cleanHash = base64.replace(/[^a-zA-Z0-9]/g, "").substring(0, 8);
// Convert to an 8-character lowercase hex string
const hashHex = (hash >>> 0).toString(16).padStart(8, "0").toLowerCase();
return `${prefix}_${cleanHash.toLowerCase()}`;
// Ensure the first character is a letter to avoid an identifier that's purely
// numeric (isValidId forbids all-digit IDs). If it starts with a digit,
// replace with 'a'. This is extremely unlikely but a simple safeguard.
const safeHash = /^[0-9]/.test(hashHex[0]) ? `a${hashHex.slice(1)}` : hashHex;
return `${prefix}_${safeHash}`;
}
/**

View File

@ -11,6 +11,7 @@ import {
CustomClassificationModelConfig,
FrigateConfig,
} from "@/types/frigateConfig";
import { ClassificationDatasetResponse } from "@/types/classification";
import { useCallback, useEffect, useMemo, useState } from "react";
import { useTranslation } from "react-i18next";
import { FaFolderPlus } from "react-icons/fa";
@ -209,9 +210,10 @@ type ModelCardProps = {
function ModelCard({ config, onClick, onUpdate, onDelete }: ModelCardProps) {
const { t } = useTranslation(["views/classificationModel"]);
const { data: dataset } = useSWR<{
[id: string]: string[];
}>(`classification/${config.name}/dataset`, { revalidateOnFocus: false });
const { data: dataset } = useSWR<ClassificationDatasetResponse>(
`classification/${config.name}/dataset`,
{ revalidateOnFocus: false },
);
const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
const [editDialogOpen, setEditDialogOpen] = useState(false);
@ -260,20 +262,25 @@ function ModelCard({ config, onClick, onUpdate, onDelete }: ModelCardProps) {
}, []);
const coverImage = useMemo(() => {
if (!dataset) {
if (!dataset || !dataset.categories) {
return undefined;
}
const keys = Object.keys(dataset).filter((key) => key != "none");
const selectedKey = keys[0];
const keys = Object.keys(dataset.categories).filter((key) => key != "none");
if (keys.length === 0) {
return undefined;
}
if (!dataset[selectedKey]) {
const selectedKey = keys[0];
const images = dataset.categories[selectedKey];
if (!images || images.length === 0) {
return undefined;
}
return {
name: selectedKey,
img: dataset[selectedKey][0],
img: images[0],
};
}, [dataset]);
@ -317,11 +324,19 @@ function ModelCard({ config, onClick, onUpdate, onDelete }: ModelCardProps) {
)}
onClick={onClick}
>
<img
className="size-full"
src={`${baseUrl}clips/${config.name}/dataset/${coverImage?.name}/${coverImage?.img}`}
/>
<ImageShadowOverlay lowerClassName="h-[30%] z-0" />
{coverImage ? (
<>
<img
className="size-full"
src={`${baseUrl}clips/${config.name}/dataset/${coverImage.name}/${coverImage.img}`}
/>
<ImageShadowOverlay lowerClassName="h-[30%] z-0" />
</>
) : (
<div className="flex size-full items-center justify-center bg-background_alt">
<MdModelTraining className="size-16 text-muted-foreground" />
</div>
)}
<div className="absolute bottom-2 left-3 text-lg text-white smart-capitalize">
{config.name}
</div>

View File

@ -59,7 +59,11 @@ import { useNavigate } from "react-router-dom";
import { IoMdArrowRoundBack } from "react-icons/io";
import TrainFilterDialog from "@/components/overlay/dialog/TrainFilterDialog";
import useApiFilter from "@/hooks/use-api-filter";
import { ClassificationItemData, TrainFilter } from "@/types/classification";
import {
ClassificationDatasetResponse,
ClassificationItemData,
TrainFilter,
} from "@/types/classification";
import {
ClassificationCard,
GroupedClassificationCard,
@ -102,6 +106,12 @@ export default function ModelTrainingView({ model }: ModelTrainingViewProps) {
position: "top-center",
});
setWasTraining(false);
refreshDataset();
} else if (modelState == "failed") {
toast.error(t("toast.error.trainingFailed"), {
position: "top-center",
});
setWasTraining(false);
}
// only refresh when modelState changes
// eslint-disable-next-line react-hooks/exhaustive-deps
@ -112,9 +122,13 @@ export default function ModelTrainingView({ model }: ModelTrainingViewProps) {
const { data: trainImages, mutate: refreshTrain } = useSWR<string[]>(
`classification/${model.name}/train`,
);
const { data: dataset, mutate: refreshDataset } = useSWR<{
[id: string]: string[];
}>(`classification/${model.name}/dataset`);
const { data: datasetResponse, mutate: refreshDataset } =
useSWR<ClassificationDatasetResponse>(
`classification/${model.name}/dataset`,
);
const dataset = datasetResponse?.categories || {};
const trainingMetadata = datasetResponse?.training_metadata;
const [trainFilter, setTrainFilter] = useApiFilter<TrainFilter>();
@ -177,7 +191,7 @@ export default function ModelTrainingView({ model }: ModelTrainingViewProps) {
error.response?.data?.detail ||
"Unknown error";
toast.error(t("toast.error.trainingFailed", { errorMessage }), {
toast.error(t("toast.error.trainingFailedToStart", { errorMessage }), {
position: "top-center",
});
});
@ -187,6 +201,37 @@ export default function ModelTrainingView({ model }: ModelTrainingViewProps) {
null,
);
const onRename = useCallback(
(old_name: string, new_name: string) => {
axios
.put(`/classification/${model.name}/dataset/${old_name}/rename`, {
new_category: new_name,
})
.then((resp) => {
if (resp.status == 200) {
toast.success(
t("toast.success.renamedCategory", { name: new_name }),
{
position: "top-center",
},
);
setPageToggle(new_name);
refreshDataset();
}
})
.catch((error) => {
const errorMessage =
error.response?.data?.message ||
error.response?.data?.detail ||
"Unknown error";
toast.error(t("toast.error.renameCategoryFailed", { errorMessage }), {
position: "top-center",
});
});
},
[model, setPageToggle, refreshDataset, t],
);
const onDelete = useCallback(
(ids: string[], isName: boolean = false, category?: string) => {
const targetCategory = category || pageToggle;
@ -217,10 +262,11 @@ export default function ModelTrainingView({ model }: ModelTrainingViewProps) {
);
}
// Always refresh dataset to update the categories list
refreshDataset();
if (pageToggle == "train") {
refreshTrain();
} else {
refreshDataset();
}
}
})
@ -354,7 +400,7 @@ export default function ModelTrainingView({ model }: ModelTrainingViewProps) {
trainImages={trainImages || []}
setPageToggle={setPageToggle}
onDelete={onDelete}
onRename={() => {}}
onRename={onRename}
/>
</div>
)}
@ -390,19 +436,48 @@ export default function ModelTrainingView({ model }: ModelTrainingViewProps) {
filterValues={{ classes: Object.keys(dataset || {}) }}
onUpdateFilter={setTrainFilter}
/>
<Button
className="flex justify-center gap-2"
onClick={trainModel}
variant="select"
disabled={modelState != "complete"}
>
{modelState == "training" ? (
<ActivityIndicator size={20} />
) : (
<HiSparkles className="text-white" />
<Tooltip>
<TooltipTrigger asChild>
<Button
className="flex justify-center gap-2"
onClick={trainModel}
variant={modelState == "failed" ? "destructive" : "select"}
disabled={
(modelState != "complete" && modelState != "failed") ||
!trainingMetadata?.dataset_changed
}
>
{modelState == "training" ? (
<ActivityIndicator size={20} />
) : (
<HiSparkles className="text-white" />
)}
{isDesktop && (
<>
{t("button.trainModel")}
{trainingMetadata?.new_images_count !== undefined &&
trainingMetadata.new_images_count > 0 && (
<span className="text-sm text-selected-foreground">
({trainingMetadata.new_images_count})
</span>
)}
</>
)}
</Button>
</TooltipTrigger>
{(!trainingMetadata?.dataset_changed ||
(modelState != "complete" && modelState != "failed")) && (
<TooltipPortal>
<TooltipContent>
{modelState == "training"
? t("tooltip.trainingInProgress")
: !trainingMetadata?.dataset_changed
? t("tooltip.noChanges")
: t("tooltip.modelNotReady")}
</TooltipContent>
</TooltipPortal>
)}
{isDesktop && t("button.trainModel")}
</Button>
</Tooltip>
</div>
)}
</div>
@ -495,27 +570,44 @@ function LibrarySelector({
>
<DialogContent>
<DialogHeader>
<DialogTitle>{t("deleteCategory.title")}</DialogTitle>
<DialogTitle>
{Object.keys(dataset).length <= 2
? t("deleteCategory.minClassesTitle")
: t("deleteCategory.title")}
</DialogTitle>
<DialogDescription>
{t("deleteCategory.desc", { name: confirmDelete })}
{Object.keys(dataset).length <= 2
? t("deleteCategory.minClassesDesc")
: t("deleteCategory.desc", { name: confirmDelete })}
</DialogDescription>
</DialogHeader>
<div className="flex justify-end gap-2">
<Button variant="outline" onClick={() => setConfirmDelete(null)}>
{t("button.cancel", { ns: "common" })}
</Button>
<Button
variant="destructive"
className="text-white"
onClick={() => {
if (confirmDelete) {
handleDeleteCategory(confirmDelete);
setConfirmDelete(null);
}
}}
>
{t("button.delete", { ns: "common" })}
</Button>
{Object.keys(dataset).length <= 2 ? (
<Button variant="outline" onClick={() => setConfirmDelete(null)}>
{t("button.ok", { ns: "common" })}
</Button>
) : (
<>
<Button
variant="outline"
onClick={() => setConfirmDelete(null)}
>
{t("button.cancel", { ns: "common" })}
</Button>
<Button
variant="destructive"
className="text-white"
onClick={() => {
if (confirmDelete) {
handleDeleteCategory(confirmDelete);
setConfirmDelete(null);
}
}}
>
{t("button.delete", { ns: "common" })}
</Button>
</>
)}
</div>
</DialogContent>
</Dialog>
@ -534,7 +626,7 @@ function LibrarySelector({
regexErrorMessage={t("description.invalidName")}
/>
<DropdownMenu>
<DropdownMenu modal={false}>
<DropdownMenuTrigger asChild>
<Button className="flex justify-between smart-capitalize">
{pageTitle}
@ -585,48 +677,50 @@ function LibrarySelector({
({dataset?.[id].length})
</span>
</div>
<div className="flex gap-0.5">
<Tooltip>
<TooltipTrigger asChild>
<Button
variant="ghost"
size="icon"
className="size-7 lg:opacity-0 lg:transition-opacity lg:group-hover:opacity-100"
onClick={(e) => {
e.stopPropagation();
setRenameClass(id);
}}
>
<LuPencil className="size-4 text-primary" />
</Button>
</TooltipTrigger>
<TooltipPortal>
<TooltipContent>
{t("button.renameCategory")}
</TooltipContent>
</TooltipPortal>
</Tooltip>
<Tooltip>
<TooltipTrigger asChild>
<Button
variant="ghost"
size="icon"
className="size-7 lg:opacity-0 lg:transition-opacity lg:group-hover:opacity-100"
onClick={(e) => {
e.stopPropagation();
setConfirmDelete(id);
}}
>
<LuTrash2 className="size-4 text-destructive" />
</Button>
</TooltipTrigger>
<TooltipPortal>
<TooltipContent>
{t("button.deleteCategory")}
</TooltipContent>
</TooltipPortal>
</Tooltip>
</div>
{id != "none" && (
<div className="flex gap-0.5">
<Tooltip>
<TooltipTrigger asChild>
<Button
variant="ghost"
size="icon"
className="size-7 lg:opacity-0 lg:transition-opacity lg:group-hover:opacity-100"
onClick={(e) => {
e.stopPropagation();
setRenameClass(id);
}}
>
<LuPencil className="size-4 text-primary" />
</Button>
</TooltipTrigger>
<TooltipPortal>
<TooltipContent>
{t("button.renameCategory")}
</TooltipContent>
</TooltipPortal>
</Tooltip>
<Tooltip>
<TooltipTrigger asChild>
<Button
variant="ghost"
size="icon"
className="size-7 lg:opacity-0 lg:transition-opacity lg:group-hover:opacity-100"
onClick={(e) => {
e.stopPropagation();
setConfirmDelete(id);
}}
>
<LuTrash2 className="size-4 text-destructive" />
</Button>
</TooltipTrigger>
<TooltipPortal>
<TooltipContent>
{t("button.deleteCategory")}
</TooltipContent>
</TooltipPortal>
</Tooltip>
</div>
)}
</DropdownMenuItem>
))}
</DropdownMenuContent>
@ -745,17 +839,11 @@ function TrainGrid({
return false;
}
if (
trainFilter.min_score &&
trainFilter.min_score > data.score / 100.0
) {
if (trainFilter.min_score && trainFilter.min_score > data.score) {
return false;
}
if (
trainFilter.max_score &&
trainFilter.max_score < data.score / 100.0
) {
if (trainFilter.max_score && trainFilter.max_score < data.score) {
return false;
}

View File

@ -86,14 +86,6 @@ export default function DraggableGridLayout({
// preferred live modes per camera
const {
preferredLiveModes,
setPreferredLiveModes,
resetPreferredLiveMode,
isRestreamedStates,
supportsAudioOutputStates,
} = useCameraLiveMode(cameras, windowVisible);
const [globalAutoLive] = usePersistence("autoLiveView", true);
const [displayCameraNames] = usePersistence("displayCameraNames", false);
@ -106,6 +98,33 @@ export default function DraggableGridLayout({
}
}, [allGroupsStreamingSettings, cameraGroup]);
const activeStreams = useMemo(() => {
const streams: { [cameraName: string]: string } = {};
cameras.forEach((camera) => {
const availableStreams = camera.live.streams || {};
const streamNameFromSettings =
currentGroupStreamingSettings?.[camera.name]?.streamName || "";
const streamExists =
streamNameFromSettings &&
Object.values(availableStreams).includes(streamNameFromSettings);
const streamName = streamExists
? streamNameFromSettings
: Object.values(availableStreams)[0] || "";
streams[camera.name] = streamName;
});
return streams;
}, [cameras, currentGroupStreamingSettings]);
const {
preferredLiveModes,
setPreferredLiveModes,
resetPreferredLiveMode,
isRestreamedStates,
supportsAudioOutputStates,
} = useCameraLiveMode(cameras, windowVisible, activeStreams);
// grid layout
const ResponsiveGridLayout = useMemo(() => WidthProvider(Responsive), []);

View File

@ -162,6 +162,9 @@ export default function LiveCameraView({
isRestreamed ? `go2rtc/streams/${streamName}` : null,
{
revalidateOnFocus: false,
revalidateOnReconnect: false,
revalidateIfStale: false,
dedupingInterval: 60000,
},
);
@ -1027,294 +1030,298 @@ function FrigateCameraFeatures({
disabled={!cameraEnabled || debug || isSnapshotLoading}
loading={isSnapshotLoading}
/>
<DropdownMenu modal={false}>
<DropdownMenuTrigger>
<div
className={cn(
"flex flex-col items-center justify-center rounded-lg bg-secondary p-2 text-secondary-foreground md:p-0",
)}
>
<FaCog
className={`text-secondary-foreground" size-5 md:m-[6px]`}
/>
</div>
</DropdownMenuTrigger>
<DropdownMenuContent className="max-w-96">
<div className="flex flex-col gap-5 p-4">
{!isRestreamed && (
<div className="flex flex-col gap-2">
<Label>
{t("streaming.label", { ns: "components/dialog" })}
</Label>
<div className="flex flex-row items-center gap-1 text-sm text-muted-foreground">
<LuX className="size-4 text-danger" />
<div>
{t("streaming.restreaming.disabled", {
ns: "components/dialog",
})}
</div>
<Popover>
<PopoverTrigger asChild>
<div className="cursor-pointer p-0">
<LuInfo className="size-4" />
<span className="sr-only">
{t("button.info", { ns: "common" })}
</span>
</div>
</PopoverTrigger>
<PopoverContent className="w-80 text-xs">
{t("streaming.restreaming.desc.title", {
{!fullscreen && (
<DropdownMenu modal={false}>
<DropdownMenuTrigger>
<div
className={cn(
"flex flex-col items-center justify-center rounded-lg bg-secondary p-2 text-secondary-foreground md:p-0",
)}
>
<FaCog
className={`text-secondary-foreground" size-5 md:m-[6px]`}
/>
</div>
</DropdownMenuTrigger>
<DropdownMenuContent className="max-w-96">
<div className="flex flex-col gap-5 p-4">
{!isRestreamed && (
<div className="flex flex-col gap-2">
<Label>
{t("streaming.label", { ns: "components/dialog" })}
</Label>
<div className="flex flex-row items-center gap-1 text-sm text-muted-foreground">
<LuX className="size-4 text-danger" />
<div>
{t("streaming.restreaming.disabled", {
ns: "components/dialog",
})}
<div className="mt-2 flex items-center text-primary">
<Link
to={getLocaleDocUrl("configuration/live")}
target="_blank"
rel="noopener noreferrer"
className="inline"
>
{t("readTheDocumentation", { ns: "common" })}
<LuExternalLink className="ml-2 inline-flex size-3" />
</Link>
</div>
</PopoverContent>
</Popover>
</div>
</div>
)}
{isRestreamed &&
Object.values(camera.live.streams).length > 0 && (
<div className="flex flex-col gap-1">
<Label htmlFor="streaming-method">
{t("stream.title")}
</Label>
<Select
value={streamName}
disabled={debug}
onValueChange={(value) => {
setStreamName?.(value);
}}
>
<SelectTrigger className="w-full">
<SelectValue>
{Object.keys(camera.live.streams).find(
(key) => camera.live.streams[key] === streamName,
)}
</SelectValue>
</SelectTrigger>
<SelectContent>
<SelectGroup>
{Object.entries(camera.live.streams).map(
([stream, name]) => (
<SelectItem
key={stream}
className="cursor-pointer"
value={name}
>
{stream}
</SelectItem>
),
)}
</SelectGroup>
</SelectContent>
</Select>
{debug && (
<div className="flex flex-row items-center gap-1 text-sm text-muted-foreground">
<>
<LuX className="size-8 text-danger" />
<div>{t("stream.debug.picker")}</div>
</>
</div>
)}
{preferredLiveMode != "jsmpeg" &&
!debug &&
isRestreamed && (
<div className="flex flex-row items-center gap-1 text-sm text-muted-foreground">
{supportsAudioOutput ? (
<>
<LuCheck className="size-4 text-success" />
<div>{t("stream.audio.available")}</div>
</>
) : (
<>
<LuX className="size-4 text-danger" />
<div>{t("stream.audio.unavailable")}</div>
<Popover>
<PopoverTrigger asChild>
<div className="cursor-pointer p-0">
<LuInfo className="size-4" />
<span className="sr-only">
{t("button.info", { ns: "common" })}
</span>
</div>
</PopoverTrigger>
<PopoverContent className="w-80 text-xs">
{t("stream.audio.tips.title")}
<div className="mt-2 flex items-center text-primary">
<Link
to={getLocaleDocUrl("configuration/live")}
target="_blank"
rel="noopener noreferrer"
className="inline"
>
{t("readTheDocumentation", {
ns: "common",
})}
<LuExternalLink className="ml-2 inline-flex size-3" />
</Link>
</div>
</PopoverContent>
</Popover>
</>
)}
</div>
)}
{preferredLiveMode != "jsmpeg" &&
!debug &&
isRestreamed &&
supportsAudioOutput && (
<div className="flex flex-row items-center gap-1 text-sm text-muted-foreground">
{supports2WayTalk ? (
<>
<LuCheck className="size-4 text-success" />
<div>{t("stream.twoWayTalk.available")}</div>
</>
) : (
<>
<LuX className="size-4 text-danger" />
<div>{t("stream.twoWayTalk.unavailable")}</div>
<Popover>
<PopoverTrigger asChild>
<div className="cursor-pointer p-0">
<LuInfo className="size-4" />
<span className="sr-only">
{t("button.info", { ns: "common" })}
</span>
</div>
</PopoverTrigger>
<PopoverContent className="w-80 text-xs">
{t("stream.twoWayTalk.tips")}
<div className="mt-2 flex items-center text-primary">
<Link
to={getLocaleDocUrl(
"configuration/live/#webrtc-extra-configuration",
)}
target="_blank"
rel="noopener noreferrer"
className="inline"
>
{t("readTheDocumentation", {
ns: "common",
})}
<LuExternalLink className="ml-2 inline-flex size-3" />
</Link>
</div>
</PopoverContent>
</Popover>
</>
)}
</div>
)}
{preferredLiveMode == "jsmpeg" &&
!debug &&
isRestreamed && (
<div className="flex flex-col items-center gap-3">
<div className="flex flex-row items-center gap-2">
<IoIosWarning className="mr-1 size-8 text-danger" />
<p className="text-sm">
{t("stream.lowBandwidth.tips")}
</p>
<Popover>
<PopoverTrigger asChild>
<div className="cursor-pointer p-0">
<LuInfo className="size-4" />
<span className="sr-only">
{t("button.info", { ns: "common" })}
</span>
</div>
<Button
className={`flex items-center gap-2.5 rounded-lg`}
aria-label={t("stream.lowBandwidth.resetStream")}
variant="outline"
size="sm"
onClick={() => setLowBandwidth(false)}
>
<MdOutlineRestartAlt className="size-5 text-primary-variant" />
<div className="text-primary-variant">
{t("stream.lowBandwidth.resetStream")}
</div>
</Button>
</div>
)}
</PopoverTrigger>
<PopoverContent className="w-80 text-xs">
{t("streaming.restreaming.desc.title", {
ns: "components/dialog",
})}
<div className="mt-2 flex items-center text-primary">
<Link
to={getLocaleDocUrl("configuration/live")}
target="_blank"
rel="noopener noreferrer"
className="inline"
>
{t("readTheDocumentation", { ns: "common" })}
<LuExternalLink className="ml-2 inline-flex size-3" />
</Link>
</div>
</PopoverContent>
</Popover>
</div>
</div>
)}
{isRestreamed &&
Object.values(camera.live.streams).length > 0 && (
<div className="flex flex-col gap-1">
<Label htmlFor="streaming-method">
{t("stream.title")}
</Label>
<Select
value={streamName}
disabled={debug}
onValueChange={(value) => {
setStreamName?.(value);
}}
>
<SelectTrigger className="w-full">
<SelectValue>
{Object.keys(camera.live.streams).find(
(key) => camera.live.streams[key] === streamName,
)}
</SelectValue>
</SelectTrigger>
<SelectContent>
<SelectGroup>
{Object.entries(camera.live.streams).map(
([stream, name]) => (
<SelectItem
key={stream}
className="cursor-pointer"
value={name}
>
{stream}
</SelectItem>
),
)}
</SelectGroup>
</SelectContent>
</Select>
{debug && (
<div className="flex flex-row items-center gap-1 text-sm text-muted-foreground">
<>
<LuX className="size-8 text-danger" />
<div>{t("stream.debug.picker")}</div>
</>
</div>
)}
{preferredLiveMode != "jsmpeg" &&
!debug &&
isRestreamed && (
<div className="flex flex-row items-center gap-1 text-sm text-muted-foreground">
{supportsAudioOutput ? (
<>
<LuCheck className="size-4 text-success" />
<div>{t("stream.audio.available")}</div>
</>
) : (
<>
<LuX className="size-4 text-danger" />
<div>{t("stream.audio.unavailable")}</div>
<Popover>
<PopoverTrigger asChild>
<div className="cursor-pointer p-0">
<LuInfo className="size-4" />
<span className="sr-only">
{t("button.info", { ns: "common" })}
</span>
</div>
</PopoverTrigger>
<PopoverContent className="w-80 text-xs">
{t("stream.audio.tips.title")}
<div className="mt-2 flex items-center text-primary">
<Link
to={getLocaleDocUrl(
"configuration/live",
)}
target="_blank"
rel="noopener noreferrer"
className="inline"
>
{t("readTheDocumentation", {
ns: "common",
})}
<LuExternalLink className="ml-2 inline-flex size-3" />
</Link>
</div>
</PopoverContent>
</Popover>
</>
)}
</div>
)}
{preferredLiveMode != "jsmpeg" &&
!debug &&
isRestreamed &&
supportsAudioOutput && (
<div className="flex flex-row items-center gap-1 text-sm text-muted-foreground">
{supports2WayTalk ? (
<>
<LuCheck className="size-4 text-success" />
<div>{t("stream.twoWayTalk.available")}</div>
</>
) : (
<>
<LuX className="size-4 text-danger" />
<div>{t("stream.twoWayTalk.unavailable")}</div>
<Popover>
<PopoverTrigger asChild>
<div className="cursor-pointer p-0">
<LuInfo className="size-4" />
<span className="sr-only">
{t("button.info", { ns: "common" })}
</span>
</div>
</PopoverTrigger>
<PopoverContent className="w-80 text-xs">
{t("stream.twoWayTalk.tips")}
<div className="mt-2 flex items-center text-primary">
<Link
to={getLocaleDocUrl(
"configuration/live/#webrtc-extra-configuration",
)}
target="_blank"
rel="noopener noreferrer"
className="inline"
>
{t("readTheDocumentation", {
ns: "common",
})}
<LuExternalLink className="ml-2 inline-flex size-3" />
</Link>
</div>
</PopoverContent>
</Popover>
</>
)}
</div>
)}
{preferredLiveMode == "jsmpeg" &&
!debug &&
isRestreamed && (
<div className="flex flex-col items-center gap-3">
<div className="flex flex-row items-center gap-2">
<IoIosWarning className="mr-1 size-8 text-danger" />
<p className="text-sm">
{t("stream.lowBandwidth.tips")}
</p>
</div>
<Button
className={`flex items-center gap-2.5 rounded-lg`}
aria-label={t("stream.lowBandwidth.resetStream")}
variant="outline"
size="sm"
onClick={() => setLowBandwidth(false)}
>
<MdOutlineRestartAlt className="size-5 text-primary-variant" />
<div className="text-primary-variant">
{t("stream.lowBandwidth.resetStream")}
</div>
</Button>
</div>
)}
</div>
)}
{isRestreamed && (
<div className="flex flex-col gap-1">
<div className="flex items-center justify-between">
<Label
className="mx-0 cursor-pointer text-primary"
htmlFor="backgroundplay"
>
{t("stream.playInBackground.label")}
</Label>
<Switch
className="ml-1"
id="backgroundplay"
disabled={debug}
checked={playInBackground}
onCheckedChange={(checked) =>
setPlayInBackground(checked)
}
/>
</div>
<p className="text-sm text-muted-foreground">
{t("stream.playInBackground.tips")}
</p>
</div>
)}
{isRestreamed && (
<div className="flex flex-col gap-1">
<div className="flex items-center justify-between">
<Label
className="mx-0 cursor-pointer text-primary"
htmlFor="backgroundplay"
htmlFor="showstats"
>
{t("stream.playInBackground.label")}
{t("streaming.showStats.label", {
ns: "components/dialog",
})}
</Label>
<Switch
className="ml-1"
id="backgroundplay"
id="showstats"
disabled={debug}
checked={playInBackground}
onCheckedChange={(checked) =>
setPlayInBackground(checked)
}
checked={showStats}
onCheckedChange={(checked) => setShowStats(checked)}
/>
</div>
<p className="text-sm text-muted-foreground">
{t("stream.playInBackground.tips")}
{t("streaming.showStats.desc", {
ns: "components/dialog",
})}
</p>
</div>
)}
<div className="flex flex-col gap-1">
<div className="flex items-center justify-between">
<Label
className="mx-0 cursor-pointer text-primary"
htmlFor="showstats"
>
{t("streaming.showStats.label", {
ns: "components/dialog",
})}
</Label>
<Switch
className="ml-1"
id="showstats"
disabled={debug}
checked={showStats}
onCheckedChange={(checked) => setShowStats(checked)}
/>
</div>
<p className="text-sm text-muted-foreground">
{t("streaming.showStats.desc", {
ns: "components/dialog",
})}
</p>
</div>
<div className="flex flex-col gap-1">
<div className="flex items-center justify-between">
<Label
className="mx-0 cursor-pointer text-primary"
htmlFor="debug"
>
{t("streaming.debugView", {
ns: "components/dialog",
})}
</Label>
<Switch
className="ml-1"
id="debug"
checked={debug}
onCheckedChange={(checked) => setDebug(checked)}
/>
<div className="flex flex-col gap-1">
<div className="flex items-center justify-between">
<Label
className="mx-0 cursor-pointer text-primary"
htmlFor="debug"
>
{t("streaming.debugView", {
ns: "components/dialog",
})}
</Label>
<Switch
className="ml-1"
id="debug"
checked={debug}
onCheckedChange={(checked) => setDebug(checked)}
/>
</div>
</div>
</div>
</div>
</DropdownMenuContent>
</DropdownMenu>
</DropdownMenuContent>
</DropdownMenu>
)}
</>
);
}

View File

@ -202,14 +202,6 @@ export default function LiveDashboardView({
};
}, []);
const {
preferredLiveModes,
setPreferredLiveModes,
resetPreferredLiveMode,
isRestreamedStates,
supportsAudioOutputStates,
} = useCameraLiveMode(cameras, windowVisible);
const [globalAutoLive] = usePersistence("autoLiveView", true);
const [displayCameraNames] = usePersistence("displayCameraNames", false);
@ -239,6 +231,33 @@ export default function LiveDashboardView({
[visibleCameraObserver.current],
);
const activeStreams = useMemo(() => {
const streams: { [cameraName: string]: string } = {};
cameras.forEach((camera) => {
const availableStreams = camera.live.streams || {};
const streamNameFromSettings =
currentGroupStreamingSettings?.[camera.name]?.streamName || "";
const streamExists =
streamNameFromSettings &&
Object.values(availableStreams).includes(streamNameFromSettings);
const streamName = streamExists
? streamNameFromSettings
: Object.values(availableStreams)[0] || "";
streams[camera.name] = streamName;
});
return streams;
}, [cameras, currentGroupStreamingSettings]);
const {
preferredLiveModes,
setPreferredLiveModes,
resetPreferredLiveMode,
isRestreamedStates,
supportsAudioOutputStates,
} = useCameraLiveMode(cameras, windowVisible, activeStreams);
const birdseyeConfig = useMemo(() => config?.birdseye, [config]);
const handleError = useCallback(

View File

@ -649,7 +649,7 @@ export function RecordingView({
value="detail"
aria-label="Detail Stream"
>
<div className="">Detail</div>
<div className="">{t("detail.label")}</div>
</ToggleGroupItem>
</ToggleGroup>
) : (

View File

@ -98,12 +98,12 @@ export default function CameraSettingsView({
return Object.entries(cameraConfig.zones).map(([name, zoneData]) => ({
camera: cameraConfig.name,
name,
friendly_name: getZoneName(name, cameraConfig.name),
friendly_name: cameraConfig.zones[name].friendly_name,
objects: zoneData.objects,
color: zoneData.color,
}));
}
}, [cameraConfig, getZoneName]);
}, [cameraConfig]);
const alertsLabels = useMemo(() => {
return cameraConfig?.review.alerts.labels
@ -533,8 +533,14 @@ export default function CameraSettingsView({
}}
/>
</FormControl>
<FormLabel className="font-normal smart-capitalize">
{zone.friendly_name}
<FormLabel
className={cn(
"font-normal",
!zone.friendly_name &&
"smart-capitalize",
)}
>
{zone.friendly_name || zone.name}
</FormLabel>
</FormItem>
)}
@ -632,8 +638,14 @@ export default function CameraSettingsView({
}}
/>
</FormControl>
<FormLabel className="font-normal smart-capitalize">
{zone.friendly_name}
<FormLabel
className={cn(
"font-normal",
!zone.friendly_name &&
"smart-capitalize",
)}
>
{zone.friendly_name || zone.name}
</FormLabel>
</FormItem>
)}

View File

@ -99,6 +99,10 @@ export default function UiSettingsView() {
const [playbackRate, setPlaybackRate] = usePersistence("playbackRate", 1);
const [weekStartsOn, setWeekStartsOn] = usePersistence("weekStartsOn", 0);
const [alertVideos, setAlertVideos] = usePersistence("alertVideos", true);
const [fallbackTimeout, setFallbackTimeout] = usePersistence(
"liveFallbackTimeout",
3,
);
return (
<>
@ -161,6 +165,48 @@ export default function UiSettingsView() {
<p>{t("general.liveDashboard.displayCameraNames.desc")}</p>
</div>
</div>
<div className="space-y-3">
<div className="flex flex-row items-center justify-start gap-2">
<Label
className="cursor-pointer"
htmlFor="live-fallback-timeout"
>
{t("general.liveDashboard.liveFallbackTimeout.label")}
</Label>
</div>
<div className="my-2 max-w-5xl text-sm text-muted-foreground">
<p>{t("general.liveDashboard.liveFallbackTimeout.desc")}</p>
</div>
<Select
value={fallbackTimeout?.toString()}
onValueChange={(value) => setFallbackTimeout(parseInt(value))}
>
<SelectTrigger className="w-36">
{t("time.second", {
ns: "common",
time: fallbackTimeout,
count: fallbackTimeout,
})}
</SelectTrigger>
<SelectContent>
<SelectGroup>
{[1, 2, 3, 4, 5, 6, 7, 8, 9, 10].map((timeout) => (
<SelectItem
key={timeout}
className="cursor-pointer"
value={timeout.toString()}
>
{t("time.second", {
ns: "common",
time: timeout,
count: timeout,
})}
</SelectItem>
))}
</SelectGroup>
</SelectContent>
</Select>
</div>
</div>
<div className="my-3 flex w-full flex-col space-y-6">