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Merge remote-tracking branch 'upstream/dev' into dev

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This commit is contained in:
Rui Alves 2024-12-18 09:07:40 +00:00
commit 3193651977
39 changed files with 459 additions and 242 deletions
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16
.github/workflows/ci.yml vendored
View File

@ -7,7 +7,7 @@ on:
- dev
- master
paths-ignore:
- 'docs/**'
- "docs/**"
# only run the latest commit to avoid cache overwrites
concurrency:
@ -24,6 +24,8 @@ jobs:
steps:
- name: Check out code
uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up QEMU and Buildx
id: setup
uses: ./.github/actions/setup
@ -45,6 +47,8 @@ jobs:
steps:
- name: Check out code
uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up QEMU and Buildx
id: setup
uses: ./.github/actions/setup
@ -86,6 +90,8 @@ jobs:
steps:
- name: Check out code
uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up QEMU and Buildx
id: setup
uses: ./.github/actions/setup
@ -112,6 +118,8 @@ jobs:
steps:
- name: Check out code
uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up QEMU and Buildx
id: setup
uses: ./.github/actions/setup
@ -140,6 +148,8 @@ jobs:
steps:
- name: Check out code
uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up QEMU and Buildx
id: setup
uses: ./.github/actions/setup
@ -165,6 +175,8 @@ jobs:
steps:
- name: Check out code
uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up QEMU and Buildx
id: setup
uses: ./.github/actions/setup
@ -188,6 +200,8 @@ jobs:
steps:
- name: Check out code
uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up QEMU and Buildx
id: setup
uses: ./.github/actions/setup

24
.github/workflows/dependabot-auto-merge.yaml vendored
View File

@ -1,24 +0,0 @@
name: dependabot-auto-merge
on: pull_request
permissions:
contents: write
jobs:
dependabot-auto-merge:
runs-on: ubuntu-latest
if: github.actor == 'dependabot[bot]'
steps:
- name: Get Dependabot metadata
id: metadata
uses: dependabot/fetch-metadata@v2
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
- name: Enable auto-merge for Dependabot PRs
if: steps.metadata.outputs.dependency-type == 'direct:development' && (steps.metadata.outputs.update-type == 'version-update:semver-minor' || steps.metadata.outputs.update-type == 'version-update:semver-patch')
run: |
gh pr review --approve "$PR_URL"
gh pr merge --auto --squash "$PR_URL"
env:
PR_URL: ${{ github.event.pull_request.html_url }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

12
.github/workflows/pull_request.yml vendored
View File

@ -3,7 +3,7 @@ name: On pull request
on:
pull_request:
paths-ignore:
- 'docs/**'
- "docs/**"
env:
DEFAULT_PYTHON: 3.9
@ -19,6 +19,8 @@ jobs:
DOCKER_BUILDKIT: "1"
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- uses: actions/setup-node@master
with:
node-version: 16.x
@ -38,6 +40,8 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- uses: actions/setup-node@master
with:
node-version: 16.x
@ -52,6 +56,8 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- uses: actions/setup-node@master
with:
node-version: 20.x
@ -67,6 +73,8 @@ jobs:
steps:
- name: Check out the repository
uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python ${{ env.DEFAULT_PYTHON }}
uses: actions/setup-python@v5.1.0
with:
@ -88,6 +96,8 @@ jobs:
steps:
- name: Check out code
uses: actions/checkout@v4
with:
persist-credentials: false
- uses: actions/setup-node@master
with:
node-version: 16.x

9
.github/workflows/release.yml vendored
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@ -11,6 +11,8 @@ jobs:
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- id: lowercaseRepo
uses: ASzc/change-string-case-action@v6
with:
@ -22,10 +24,13 @@ jobs:
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Create tag variables
env:
TAG: ${{ github.ref_name }}
LOWERCASE_REPO: ${{ steps.lowercaseRepo.outputs.lowercase }}
run: |
BUILD_TYPE=$([[ "${{ github.ref_name }}" =~ ^v[0-9]+\.[0-9]+\.[0-9]+$ ]] && echo "stable" || echo "beta")
BUILD_TYPE=$([[ "${TAG}" =~ ^v[0-9]+\.[0-9]+\.[0-9]+$ ]] && echo "stable" || echo "beta")
echo "BUILD_TYPE=${BUILD_TYPE}" >> $GITHUB_ENV
echo "BASE=ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}" >> $GITHUB_ENV
echo "BASE=ghcr.io/${LOWERCASE_REPO}" >> $GITHUB_ENV
echo "BUILD_TAG=${GITHUB_SHA::7}" >> $GITHUB_ENV
echo "CLEAN_VERSION=$(echo ${GITHUB_REF##*/} | tr '[:upper:]' '[:lower:]' | sed 's/^[v]//')" >> $GITHUB_ENV
- name: Tag and push the main image

5
.github/workflows/stale.yml vendored
View File

@ -23,7 +23,9 @@ jobs:
exempt-pr-labels: "pinned,security,dependencies"
operations-per-run: 120
- name: Print outputs
run: echo ${{ join(steps.stale.outputs.*, ',') }}
env:
STALE_OUTPUT: ${{ join(steps.stale.outputs.*, ',') }}
run: echo "$STALE_OUTPUT"
# clean_ghcr:
# name: Delete outdated dev container images
@ -38,4 +40,3 @@ jobs:
# account-type: personal
# token: ${{ secrets.GITHUB_TOKEN }}
# token-type: github-token

2
docs/docs/configuration/advanced.md
View File

@ -174,7 +174,7 @@ NOTE: The folder that is set for the config needs to be the folder that contains
### Custom go2rtc version
Frigate currently includes go2rtc v1.9.4, there may be certain cases where you want to run a different version of go2rtc.
Frigate currently includes go2rtc v1.9.2, there may be certain cases where you want to run a different version of go2rtc.
To do this:

2
docs/docs/configuration/genai.md
View File

@ -5,6 +5,8 @@ title: Generative AI
Generative AI can be used to automatically generate descriptive text based on the thumbnails of your tracked objects. This helps with [Semantic Search](/configuration/semantic_search) in Frigate to provide more context about your tracked objects. Descriptions are accessed via the _Explore_ view in the Frigate UI by clicking on a tracked object's thumbnail.
Requests for a description are sent off automatically to your AI provider at the end of the tracked object's lifecycle. Descriptions can also be regenerated manually via the Frigate UI.
:::info
Semantic Search must be enabled to use Generative AI.

2
docs/docs/configuration/live.md
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@ -23,7 +23,7 @@ If you are using go2rtc, you should adjust the following settings in your camera
- Video codec: **H.264** - provides the most compatible video codec with all Live view technologies and browsers. Avoid any kind of "smart codec" or "+" codec like _H.264+_ or _H.265+_. as these non-standard codecs remove keyframes (see below).
- Audio codec: **AAC** - provides the most compatible audio codec with all Live view technologies and browsers that support audio.
- I-frame interval (sometimes called the keyframe interval, the interframe space, or the GOP length): match your camera's frame rate, or choose "1x" (for interframe space on Reolink cameras). For example, if your stream outputs 20fps, your i-frame interval should be 20 (or 1x on Reolink). Values higher than the frame rate will cause the stream to take longer to begin playback. See [this page](https://gardinal.net/understanding-the-keyframe-interval/) for more on keyframes.
- I-frame interval (sometimes called the keyframe interval, the interframe space, or the GOP length): match your camera's frame rate, or choose "1x" (for interframe space on Reolink cameras). For example, if your stream outputs 20fps, your i-frame interval should be 20 (or 1x on Reolink). Values higher than the frame rate will cause the stream to take longer to begin playback. See [this page](https://gardinal.net/understanding-the-keyframe-interval/) for more on keyframes. For many users this may not be an issue, but it should be noted that that a 1x i-frame interval will cause more storage utilization if you are using the stream for the `record` role as well.
The default video and audio codec on your camera may not always be compatible with your browser, which is why setting them to H.264 and AAC is recommended. See the [go2rtc docs](https://github.com/AlexxIT/go2rtc?tab=readme-ov-file#codecs-madness) for codec support information.

16
docs/docs/configuration/semantic_search.md
View File

@ -5,7 +5,7 @@ title: Using Semantic Search
Semantic Search in Frigate allows you to find tracked objects within your review items using either the image itself, a user-defined text description, or an automatically generated one. This feature works by creating _embeddings_ — numerical vector representations — for both the images and text descriptions of your tracked objects. By comparing these embeddings, Frigate assesses their similarities to deliver relevant search results.
Frigate has support for [Jina AI's CLIP model](https://huggingface.co/jinaai/jina-clip-v1) to create embeddings, which runs locally. Embeddings are then saved to Frigate's database.
Frigate uses [Jina AI's CLIP model](https://huggingface.co/jinaai/jina-clip-v1) to create and save embeddings to Frigate's database. All of this runs locally.
Semantic Search is accessed via the _Explore_ view in the Frigate UI.
@ -19,7 +19,7 @@ For best performance, 16GB or more of RAM and a dedicated GPU are recommended.
## Configuration
Semantic Search is disabled by default, and must be enabled in your config file before it can be used. Semantic Search is a global configuration setting.
Semantic Search is disabled by default, and must be enabled in your config file or in the UI's Settings page before it can be used. Semantic Search is a global configuration setting.
```yaml
semantic_search:
@ -29,9 +29,9 @@ semantic_search:
:::tip
The embeddings database can be re-indexed from the existing tracked objects in your database by adding `reindex: True` to your `semantic_search` configuration. Depending on the number of tracked objects you have, it can take a long while to complete and may max out your CPU while indexing. Make sure to set the config back to `False` before restarting Frigate again.
The embeddings database can be re-indexed from the existing tracked objects in your database by adding `reindex: True` to your `semantic_search` configuration or by toggling the switch on the Search Settings page in the UI and restarting Frigate. Depending on the number of tracked objects you have, it can take a long while to complete and may max out your CPU while indexing. Make sure to turn the UI's switch off or set the config back to `False` before restarting Frigate again.
If you are enabling the Search feature for the first time, be advised that Frigate does not automatically index older tracked objects. You will need to enable the `reindex` feature in order to do that.
If you are enabling Semantic Search for the first time, be advised that Frigate does not automatically index older tracked objects. You will need to enable the `reindex` feature in order to do that.
:::
@ -39,9 +39,9 @@ If you are enabling the Search feature for the first time, be advised that Friga
The vision model is able to embed both images and text into the same vector space, which allows `image -> image` and `text -> image` similarity searches. Frigate uses this model on tracked objects to encode the thumbnail image and store it in the database. When searching for tracked objects via text in the search box, Frigate will perform a `text -> image` similarity search against this embedding. When clicking "Find Similar" in the tracked object detail pane, Frigate will perform an `image -> image` similarity search to retrieve the closest matching thumbnails.
The text model is used to embed tracked object descriptions and perform searches against them. Descriptions can be created, viewed, and modified on the Search page when clicking on the gray tracked object chip at the top left of each review item. See [the Generative AI docs](/configuration/genai.md) for more information on how to automatically generate tracked object descriptions.
The text model is used to embed tracked object descriptions and perform searches against them. Descriptions can be created, viewed, and modified on the Explore page when clicking on thumbnail of a tracked object. See [the Generative AI docs](/configuration/genai.md) for more information on how to automatically generate tracked object descriptions.
Differently weighted CLIP models are available and can be selected by setting the `model_size` config option as `small` or `large`:
Differently weighted versions of the Jina model are available and can be selected by setting the `model_size` config option as `small` or `large`:
```yaml
semantic_search:
@ -50,7 +50,7 @@ semantic_search:
```
- Configuring the `large` model employs the full Jina model and will automatically run on the GPU if applicable.
- Configuring the `small` model employs a quantized version of the model that uses less RAM and runs on CPU with a very negligible difference in embedding quality.
- Configuring the `small` model employs a quantized version of the Jina model that uses less RAM and runs on CPU with a very negligible difference in embedding quality.
### GPU Acceleration
@ -84,7 +84,7 @@ If the correct build is used for your GPU and the `large` model is configured, t
## Usage and Best Practices
1. Semantic Search is used in conjunction with the other filters available on the Search page. Use a combination of traditional filtering and Semantic Search for the best results.
1. Semantic Search is used in conjunction with the other filters available on the Explore page. Use a combination of traditional filtering and Semantic Search for the best results.
2. Use the thumbnail search type when searching for particular objects in the scene. Use the description search type when attempting to discern the intent of your object.
3. Because of how the AI models Frigate uses have been trained, the comparison between text and image embedding distances generally means that with multi-modal (`thumbnail` and `description`) searches, results matching `description` will appear first, even if a `thumbnail` embedding may be a better match. Play with the "Search Type" setting to help find what you are looking for. Note that if you are generating descriptions for specific objects or zones only, this may cause search results to prioritize the objects with descriptions even if the the ones without them are more relevant.
4. Make your search language and tone closely match exactly what you're looking for. If you are using thumbnail search, **phrase your query as an image caption**. Searching for "red car" may not work as well as "red sedan driving down a residential street on a sunny day".

2
docs/docs/frigate/camera_setup.md
View File

@ -28,7 +28,7 @@ For the Dahua/Loryta 5442 camera, I use the following settings:
- Encode Mode: H.264
- Resolution: 2688\*1520
- Frame Rate(FPS): 15
- I Frame Interval: 30
- I Frame Interval: 30 (15 can also be used to prioritize streaming performance - see the [camera settings recommendations](../configuration/live) for more info)
**Sub Stream (Detection)**

8
docs/docs/troubleshooting/faqs.md
View File

@ -98,3 +98,11 @@ docker run -d \
-p 8555:8555/udp \
ghcr.io/blakeblackshear/frigate:stable
```
### My RTSP stream works fine in VLC, but it does not work when I put the same URL in my Frigate config. Is this a bug?
No. Frigate uses the TCP protocol to connect to your camera's RTSP URL. VLC automatically switches between UDP and TCP depending on network conditions and stream availability. So a stream that works in VLC but not in Frigate is likely due to VLC selecting UDP as the transfer protocol.
TCP ensures that all data packets arrive in the correct order. This is crucial for video recording, decoding, and stream processing, which is why Frigate enforces a TCP connection. UDP is faster but less reliable, as it does not guarantee packet delivery or order, and VLC does not have the same requirements as Frigate.
You can still configure Frigate to use UDP by using ffmpeg input args or the preset `preset-rtsp-udp`. See the [ffmpeg presets](/configuration/ffmpeg_presets) documentation.

42
frigate/api/app.py
View File

@ -21,13 +21,13 @@ from frigate.api.defs.query.app_query_parameters import AppTimelineHourlyQueryPa
from frigate.api.defs.request.app_body import AppConfigSetBody
from frigate.api.defs.tags import Tags
from frigate.config import FrigateConfig
from frigate.const import CONFIG_DIR
from frigate.models import Event, Timeline
from frigate.util.builtin import (
clean_camera_user_pass,
get_tz_modifiers,
update_yaml_from_url,
)
from frigate.util.config import find_config_file
from frigate.util.services import (
ffprobe_stream,
get_nvidia_driver_info,
@ -134,9 +134,25 @@ def config(request: Request):
for zone_name, zone in config_obj.cameras[camera_name].zones.items():
camera_dict["zones"][zone_name]["color"] = zone.color
# remove go2rtc stream passwords
go2rtc: dict[str, any] = config_obj.go2rtc.model_dump(
mode="json", warnings="none", exclude_none=True
)
for stream_name, stream in go2rtc.get("streams", {}).items():
if isinstance(stream, str):
cleaned = clean_camera_user_pass(stream)
else:
cleaned = []
for item in stream:
cleaned.append(clean_camera_user_pass(item))
config["go2rtc"]["streams"][stream_name] = cleaned
config["plus"] = {"enabled": request.app.frigate_config.plus_api.is_active()}
config["model"]["colormap"] = config_obj.model.colormap
# use merged labelamp
for detector_config in config["detectors"].values():
detector_config["model"]["labelmap"] = (
request.app.frigate_config.model.merged_labelmap
@ -147,13 +163,7 @@ def config(request: Request):
@router.get("/config/raw")
def config_raw():
config_file = os.environ.get("CONFIG_FILE", "/config/config.yml")
# Check if we can use .yaml instead of .yml
config_file_yaml = config_file.replace(".yml", ".yaml")
if os.path.isfile(config_file_yaml):
config_file = config_file_yaml
config_file = find_config_file()
if not os.path.isfile(config_file):
return JSONResponse(
@ -198,13 +208,7 @@ def config_save(save_option: str, body: Any = Body(media_type="text/plain")):
# Save the config to file
try:
config_file = os.environ.get("CONFIG_FILE", "/config/config.yml")
# Check if we can use .yaml instead of .yml
config_file_yaml = config_file.replace(".yml", ".yaml")
if os.path.isfile(config_file_yaml):
config_file = config_file_yaml
config_file = find_config_file()
with open(config_file, "w") as f:
f.write(new_config)
@ -253,13 +257,7 @@ def config_save(save_option: str, body: Any = Body(media_type="text/plain")):
@router.put("/config/set")
def config_set(request: Request, body: AppConfigSetBody):
config_file = os.environ.get("CONFIG_FILE", f"{CONFIG_DIR}/config.yml")
# Check if we can use .yaml instead of .yml
config_file_yaml = config_file.replace(".yml", ".yaml")
if os.path.isfile(config_file_yaml):
config_file = config_file_yaml
config_file = find_config_file()
with open(config_file, "r") as f:
old_raw_config = f.read()

4
frigate/api/auth.py
View File

@ -329,7 +329,7 @@ def login(request: Request, body: AppPostLoginBody):
try:
db_user: User = User.get_by_id(user)
except DoesNotExist:
return JSONResponse(content={"message": "Login failed"}, status_code=400)
return JSONResponse(content={"message": "Login failed"}, status_code=401)
password_hash = db_user.password_hash
if verify_password(password, password_hash):
@ -340,7 +340,7 @@ def login(request: Request, body: AppPostLoginBody):
response, JWT_COOKIE_NAME, encoded_jwt, expiration, JWT_COOKIE_SECURE
)
return response
return JSONResponse(content={"message": "Login failed"}, status_code=400)
return JSONResponse(content={"message": "Login failed"}, status_code=401)
@router.get("/users")

2
frigate/api/defs/query/review_query_parameters.py
View File

@ -3,7 +3,7 @@ from typing import Union
from pydantic import BaseModel
from pydantic.json_schema import SkipJsonSchema
from frigate.review.maintainer import SeverityEnum
from frigate.review.types import SeverityEnum
class ReviewQueryParams(BaseModel):

2
frigate/api/defs/response/review_response.py
View File

@ -3,7 +3,7 @@ from typing import Dict
from pydantic import BaseModel, Json
from frigate.review.maintainer import SeverityEnum
from frigate.review.types import SeverityEnum
class ReviewSegmentResponse(BaseModel):

6
frigate/api/fastapi_app.py
View File

@ -87,7 +87,11 @@ def create_fastapi_app(
logger.info("FastAPI started")
# Rate limiter (used for login endpoint)
auth.rateLimiter.set_limit(frigate_config.auth.failed_login_rate_limit or "")
if frigate_config.auth.failed_login_rate_limit is None:
limiter.enabled = False
else:
auth.rateLimiter.set_limit(frigate_config.auth.failed_login_rate_limit)
app.state.limiter = limiter
app.add_exception_handler(RateLimitExceeded, _rate_limit_exceeded_handler)
app.add_middleware(SlowAPIMiddleware)

2
frigate/api/review.py
View File

@ -26,7 +26,7 @@ from frigate.api.defs.response.review_response import (
)
from frigate.api.defs.tags import Tags
from frigate.models import Recordings, ReviewSegment
from frigate.review.maintainer import SeverityEnum
from frigate.review.types import SeverityEnum
from frigate.util.builtin import get_tz_modifiers
logger = logging.getLogger(__name__)

9
frigate/config/config.py
View File

@ -29,6 +29,7 @@ from frigate.util.builtin import (
)
from frigate.util.config import (
StreamInfoRetriever,
find_config_file,
get_relative_coordinates,
migrate_frigate_config,
)
@ -67,7 +68,6 @@ logger = logging.getLogger(__name__)
yaml = YAML()
DEFAULT_CONFIG_FILE = "/config/config.yml"
DEFAULT_CONFIG = """
mqtt:
enabled: False
@ -638,16 +638,13 @@ class FrigateConfig(FrigateBaseModel):
@classmethod
def load(cls, **kwargs):
config_path = os.environ.get("CONFIG_FILE", DEFAULT_CONFIG_FILE)
if not os.path.isfile(config_path):
config_path = config_path.replace("yml", "yaml")
config_path = find_config_file()
# No configuration file found, create one.
new_config = False
if not os.path.isfile(config_path):
logger.info("No config file found, saving default config")
config_path = DEFAULT_CONFIG_FILE
config_path = config_path
new_config = True
else:
# Check if the config file needs to be migrated.

3
frigate/detectors/plugins/deepstack.py
View File

@ -32,6 +32,7 @@ class DeepStack(DetectionApi):
self.api_timeout = detector_config.api_timeout
self.api_key = detector_config.api_key
self.labels = detector_config.model.merged_labelmap
self.session = requests.Session()
def get_label_index(self, label_value):
if label_value.lower() == "truck":
@ -51,7 +52,7 @@ class DeepStack(DetectionApi):
data = {"api_key": self.api_key}
try:
response = requests.post(
response = self.session.post(
self.api_url,
data=data,
files={"image": image_bytes},

6
frigate/detectors/plugins/rknn.py
View File

@ -136,17 +136,17 @@ class Rknn(DetectionApi):
def check_config(self, config):
if (config.model.width != 320) or (config.model.height != 320):
raise Exception(
"Make sure to set the model width and height to 320 in your config.yml."
"Make sure to set the model width and height to 320 in your config."
)
if config.model.input_pixel_format != "bgr":
raise Exception(
'Make sure to set the model input_pixel_format to "bgr" in your config.yml.'
'Make sure to set the model input_pixel_format to "bgr" in your config.'
)
if config.model.input_tensor != "nhwc":
raise Exception(
'Make sure to set the model input_tensor to "nhwc" in your config.yml.'
'Make sure to set the model input_tensor to "nhwc" in your config.'
)
def detect_raw(self, tensor_input):

24
frigate/embeddings/maintainer.py
View File

@ -221,7 +221,10 @@ class EmbeddingMaintainer(threading.Thread):
[snapshot_image]
if event.has_snapshot and camera_config.genai.use_snapshot
else (
[thumbnail for data in self.tracked_events[event_id]]
[
data["thumbnail"]
for data in self.tracked_events[event_id]
]
if len(self.tracked_events.get(event_id, [])) > 0
else [thumbnail]
)
@ -325,18 +328,25 @@ class EmbeddingMaintainer(threading.Thread):
)
if event.has_snapshot and source == "snapshot":
with open(
os.path.join(CLIPS_DIR, f"{event.camera}-{event.id}.jpg"),
"rb",
) as image_file:
snapshot_file = os.path.join(CLIPS_DIR, f"{event.camera}-{event.id}.jpg")
if not os.path.isfile(snapshot_file):
logger.error(
f"Cannot regenerate description for {event.id}, snapshot file not found: {snapshot_file}"
)
return
with open(snapshot_file, "rb") as image_file:
snapshot_image = image_file.read()
img = cv2.imdecode(
np.frombuffer(snapshot_image, dtype=np.int8), cv2.IMREAD_COLOR
)
# crop snapshot based on region before sending off to genai
# provide full image if region doesn't exist (manual events)
region = event.data.get("region", [0, 0, 1, 1])
height, width = img.shape[:2]
x1_rel, y1_rel, width_rel, height_rel = event.data["region"]
x1_rel, y1_rel, width_rel, height_rel = region
x1, y1 = int(x1_rel * width), int(y1_rel * height)
cropped_image = img[
@ -350,7 +360,7 @@ class EmbeddingMaintainer(threading.Thread):
[snapshot_image]
if event.has_snapshot and source == "snapshot"
else (
[thumbnail for data in self.tracked_events[event_id]]
[data["thumbnail"] for data in self.tracked_events[event_id]]
if len(self.tracked_events.get(event_id, [])) > 0
else [thumbnail]
)

197
frigate/events/cleanup.py
View File

@ -4,7 +4,6 @@ import datetime
import logging
import os
import threading
from enum import Enum
from multiprocessing.synchronize import Event as MpEvent
from pathlib import Path
@ -16,11 +15,6 @@ from frigate.models import Event, Timeline
logger = logging.getLogger(__name__)
class EventCleanupType(str, Enum):
clips = "clips"
snapshots = "snapshots"
CHUNK_SIZE = 50
@ -67,19 +61,11 @@ class EventCleanup(threading.Thread):
return self.camera_labels[camera]["labels"]
def expire(self, media_type: EventCleanupType) -> list[str]:
def expire_snapshots(self) -> list[str]:
## Expire events from unlisted cameras based on the global config
if media_type == EventCleanupType.clips:
expire_days = max(
self.config.record.alerts.retain.days,
self.config.record.detections.retain.days,
)
file_extension = None # mp4 clips are no longer stored in /clips
update_params = {"has_clip": False}
else:
retain_config = self.config.snapshots.retain
file_extension = "jpg"
update_params = {"has_snapshot": False}
retain_config = self.config.snapshots.retain
file_extension = "jpg"
update_params = {"has_snapshot": False}
distinct_labels = self.get_removed_camera_labels()
@ -87,10 +73,7 @@ class EventCleanup(threading.Thread):
# loop over object types in db
for event in distinct_labels:
# get expiration time for this label
if media_type == EventCleanupType.snapshots:
expire_days = retain_config.objects.get(
event.label, retain_config.default
)
expire_days = retain_config.objects.get(event.label, retain_config.default)
expire_after = (
datetime.datetime.now() - datetime.timedelta(days=expire_days)
@ -162,13 +145,7 @@ class EventCleanup(threading.Thread):
## Expire events from cameras based on the camera config
for name, camera in self.config.cameras.items():
if media_type == EventCleanupType.clips:
expire_days = max(
camera.record.alerts.retain.days,
camera.record.detections.retain.days,
)
else:
retain_config = camera.snapshots.retain
retain_config = camera.snapshots.retain
# get distinct objects in database for this camera
distinct_labels = self.get_camera_labels(name)
@ -176,10 +153,9 @@ class EventCleanup(threading.Thread):
# loop over object types in db
for event in distinct_labels:
# get expiration time for this label
if media_type == EventCleanupType.snapshots:
expire_days = retain_config.objects.get(
event.label, retain_config.default
)
expire_days = retain_config.objects.get(
event.label, retain_config.default
)
expire_after = (
datetime.datetime.now() - datetime.timedelta(days=expire_days)
@ -206,19 +182,144 @@ class EventCleanup(threading.Thread):
for event in expired_events:
events_to_update.append(event.id)
if media_type == EventCleanupType.snapshots:
try:
media_name = f"{event.camera}-{event.id}"
media_path = Path(
f"{os.path.join(CLIPS_DIR, media_name)}.{file_extension}"
)
media_path.unlink(missing_ok=True)
media_path = Path(
f"{os.path.join(CLIPS_DIR, media_name)}-clean.png"
)
media_path.unlink(missing_ok=True)
except OSError as e:
logger.warning(f"Unable to delete event images: {e}")
try:
media_name = f"{event.camera}-{event.id}"
media_path = Path(
f"{os.path.join(CLIPS_DIR, media_name)}.{file_extension}"
)
media_path.unlink(missing_ok=True)
media_path = Path(
f"{os.path.join(CLIPS_DIR, media_name)}-clean.png"
)
media_path.unlink(missing_ok=True)
except OSError as e:
logger.warning(f"Unable to delete event images: {e}")
# update the clips attribute for the db entry
for i in range(0, len(events_to_update), CHUNK_SIZE):
batch = events_to_update[i : i + CHUNK_SIZE]
logger.debug(f"Updating {update_params} for {len(batch)} events")
Event.update(update_params).where(Event.id << batch).execute()
return events_to_update
def expire_clips(self) -> list[str]:
## Expire events from unlisted cameras based on the global config
expire_days = max(
self.config.record.alerts.retain.days,
self.config.record.detections.retain.days,
)
file_extension = None # mp4 clips are no longer stored in /clips
update_params = {"has_clip": False}
# get expiration time for this label
expire_after = (
datetime.datetime.now() - datetime.timedelta(days=expire_days)
).timestamp()
# grab all events after specific time
expired_events: list[Event] = (
Event.select(
Event.id,
Event.camera,
)
.where(
Event.camera.not_in(self.camera_keys),
Event.start_time < expire_after,
Event.retain_indefinitely == False,
)
.namedtuples()
.iterator()
)
logger.debug(f"{len(list(expired_events))} events can be expired")
# delete the media from disk
for expired in expired_events:
media_name = f"{expired.camera}-{expired.id}"
media_path = Path(f"{os.path.join(CLIPS_DIR, media_name)}.{file_extension}")
try:
media_path.unlink(missing_ok=True)
if file_extension == "jpg":
media_path = Path(
f"{os.path.join(CLIPS_DIR, media_name)}-clean.png"
)
media_path.unlink(missing_ok=True)
except OSError as e:
logger.warning(f"Unable to delete event images: {e}")
# update the clips attribute for the db entry
query = Event.select(Event.id).where(
Event.camera.not_in(self.camera_keys),
Event.start_time < expire_after,
Event.retain_indefinitely == False,
)
events_to_update = []
for event in query.iterator():
events_to_update.append(event)
if len(events_to_update) >= CHUNK_SIZE:
logger.debug(
f"Updating {update_params} for {len(events_to_update)} events"
)
Event.update(update_params).where(
Event.id << events_to_update
).execute()
events_to_update = []
# Update any remaining events
if events_to_update:
logger.debug(
f"Updating clips/snapshots attribute for {len(events_to_update)} events"
)
Event.update(update_params).where(Event.id << events_to_update).execute()
events_to_update = []
now = datetime.datetime.now()
## Expire events from cameras based on the camera config
for name, camera in self.config.cameras.items():
expire_days = max(
camera.record.alerts.retain.days,
camera.record.detections.retain.days,
)
alert_expire_date = (
now - datetime.timedelta(days=camera.record.alerts.retain.days)
).timestamp()
detection_expire_date = (
now - datetime.timedelta(days=camera.record.detections.retain.days)
).timestamp()
# grab all events after specific time
expired_events = (
Event.select(
Event.id,
Event.camera,
)
.where(
Event.camera == name,
Event.retain_indefinitely == False,
(
(
(Event.data["max_severity"] != "detection")
| (Event.data["max_severity"].is_null())
)
& (Event.end_time < alert_expire_date)
)
| (
(Event.data["max_severity"] == "detection")
& (Event.end_time < detection_expire_date)
),
)
.namedtuples()
.iterator()
)
# delete the grabbed clips from disk
# only snapshots are stored in /clips
# so no need to delete mp4 files
for event in expired_events:
events_to_update.append(event.id)
# update the clips attribute for the db entry
for i in range(0, len(events_to_update), CHUNK_SIZE):
@ -231,7 +332,7 @@ class EventCleanup(threading.Thread):
def run(self) -> None:
# only expire events every 5 minutes
while not self.stop_event.wait(300):
events_with_expired_clips = self.expire(EventCleanupType.clips)
events_with_expired_clips = self.expire_clips()
# delete timeline entries for events that have expired recordings
# delete up to 100,000 at a time
@ -242,7 +343,7 @@ class EventCleanup(threading.Thread):
Timeline.source_id << deleted_events_list[i : i + max_deletes]
).execute()
self.expire(EventCleanupType.snapshots)
self.expire_snapshots()
# drop events from db where has_clip and has_snapshot are false
events = (

16
frigate/events/maintainer.py
View File

@ -82,18 +82,23 @@ class EventProcessor(threading.Thread):
)
if source_type == EventTypeEnum.tracked_object:
id = event_data["id"]
self.timeline_queue.put(
(
camera,
source_type,
event_type,
self.events_in_process.get(event_data["id"]),
self.events_in_process.get(id),
event_data,
)
)
if event_type == EventStateEnum.start:
self.events_in_process[event_data["id"]] = event_data
# if this is the first message, just store it and continue, its not time to insert it in the db
if (
event_type == EventStateEnum.start
or id not in self.events_in_process
):
self.events_in_process[id] = event_data
continue
self.handle_object_detection(event_type, camera, event_data)
@ -123,10 +128,6 @@ class EventProcessor(threading.Thread):
"""handle tracked object event updates."""
updated_db = False
# if this is the first message, just store it and continue, its not time to insert it in the db
if event_type == EventStateEnum.start:
self.events_in_process[event_data["id"]] = event_data
if should_update_db(self.events_in_process[event_data["id"]], event_data):
updated_db = True
camera_config = self.config.cameras[camera]
@ -210,6 +211,7 @@ class EventProcessor(threading.Thread):
"top_score": event_data["top_score"],
"attributes": attributes,
"type": "object",
"max_severity": event_data.get("max_severity"),
},
}

5
frigate/genai/ollama.py
View File

@ -38,6 +38,11 @@ class OllamaClient(GenAIClient):
def _send(self, prompt: str, images: list[bytes]) -> Optional[str]:
"""Submit a request to Ollama"""
if self.provider is None:
logger.warning(
"Ollama provider has not been initialized, a description will not be generated. Check your Ollama configuration."
)
return None
try:
result = self.provider.generate(
self.genai_config.model,

25
frigate/object_processing.py
View File

@ -702,30 +702,7 @@ class TrackedObjectProcessor(threading.Thread):
return False
# If the object is not considered an alert or detection
review_config = self.config.cameras[camera].review
if not (
(
obj.obj_data["label"] in review_config.alerts.labels
and (
not review_config.alerts.required_zones
or set(obj.entered_zones) & set(review_config.alerts.required_zones)
)
)
or (
(
not review_config.detections.labels
or obj.obj_data["label"] in review_config.detections.labels
)
and (
not review_config.detections.required_zones
or set(obj.entered_zones)
& set(review_config.detections.required_zones)
)
)
):
logger.debug(
f"Not creating clip for {obj.obj_data['id']} because it did not qualify as an alert or detection"
)
if obj.max_severity is None:
return False
return True

11
frigate/ptz/autotrack.py
View File

@ -2,7 +2,6 @@
import copy
import logging
import os
import queue
import threading
import time
@ -29,11 +28,11 @@ from frigate.const import (
AUTOTRACKING_ZOOM_EDGE_THRESHOLD,
AUTOTRACKING_ZOOM_IN_HYSTERESIS,
AUTOTRACKING_ZOOM_OUT_HYSTERESIS,
CONFIG_DIR,
)
from frigate.ptz.onvif import OnvifController
from frigate.track.tracked_object import TrackedObject
from frigate.util.builtin import update_yaml_file
from frigate.util.config import find_config_file
from frigate.util.image import SharedMemoryFrameManager, intersection_over_union
logger = logging.getLogger(__name__)
@ -328,13 +327,7 @@ class PtzAutoTracker:
self.autotracker_init[camera] = True
def _write_config(self, camera):
config_file = os.environ.get("CONFIG_FILE", f"{CONFIG_DIR}/config.yml")
# Check if we can use .yaml instead of .yml
config_file_yaml = config_file.replace(".yml", ".yaml")
if os.path.isfile(config_file_yaml):
config_file = config_file_yaml
config_file = find_config_file()
logger.debug(
f"{camera}: Writing new config with autotracker motion coefficients: {self.config.cameras[camera].onvif.autotracking.movement_weights}"

7
frigate/review/maintainer.py
View File

@ -7,7 +7,6 @@ import random
import string
import sys
import threading
from enum import Enum
from multiprocessing.synchronize import Event as MpEvent
from pathlib import Path
from typing import Optional
@ -27,6 +26,7 @@ from frigate.const import (
from frigate.events.external import ManualEventState
from frigate.models import ReviewSegment
from frigate.object_processing import TrackedObject
from frigate.review.types import SeverityEnum
from frigate.util.image import SharedMemoryFrameManager, calculate_16_9_crop
logger = logging.getLogger(__name__)
@ -39,11 +39,6 @@ THRESHOLD_ALERT_ACTIVITY = 120
THRESHOLD_DETECTION_ACTIVITY = 30
class SeverityEnum(str, Enum):
alert = "alert"
detection = "detection"
class PendingReviewSegment:
def __init__(
self,

6
frigate/review/types.py Normal file
View File

@ -0,0 +1,6 @@
from enum import Enum
class SeverityEnum(str, Enum):
alert = "alert"
detection = "detection"

8
frigate/storage.py
View File

@ -17,6 +17,8 @@ bandwidth_equation = Recordings.segment_size / (
Recordings.end_time - Recordings.start_time
)
MAX_CALCULATED_BANDWIDTH = 10000 # 10Gb/hr
class StorageMaintainer(threading.Thread):
"""Maintain frigates recording storage."""
@ -52,6 +54,12 @@ class StorageMaintainer(threading.Thread):
* 3600,
2,
)
if bandwidth > MAX_CALCULATED_BANDWIDTH:
logger.warning(
f"{camera} has a bandwidth of {bandwidth} MB/hr which exceeds the expected maximum. This typically indicates an issue with the cameras recordings."
)
bandwidth = MAX_CALCULATED_BANDWIDTH
except TypeError:
bandwidth = 0

2
frigate/test/http_api/base_http_test.py
View File

@ -10,7 +10,7 @@ from playhouse.sqliteq import SqliteQueueDatabase
from frigate.api.fastapi_app import create_fastapi_app
from frigate.config import FrigateConfig
from frigate.models import Event, Recordings, ReviewSegment
from frigate.review.maintainer import SeverityEnum
from frigate.review.types import SeverityEnum
from frigate.test.const import TEST_DB, TEST_DB_CLEANUPS

2
frigate/test/http_api/test_http_review.py
View File

@ -3,7 +3,7 @@ from datetime import datetime, timedelta
from fastapi.testclient import TestClient
from frigate.models import Event, Recordings, ReviewSegment
from frigate.review.maintainer import SeverityEnum
from frigate.review.types import SeverityEnum
from frigate.test.http_api.base_http_test import BaseTestHttp

23
frigate/track/tracked_object.py
View File

@ -13,6 +13,7 @@ from frigate.config import (
CameraConfig,
ModelConfig,
)
from frigate.review.types import SeverityEnum
from frigate.util.image import (
area,
calculate_region,
@ -59,6 +60,27 @@ class TrackedObject:
self.pending_loitering = False
self.previous = self.to_dict()
@property
def max_severity(self) -> Optional[str]:
review_config = self.camera_config.review
if self.obj_data["label"] in review_config.alerts.labels and (
not review_config.alerts.required_zones
or set(self.entered_zones) & set(review_config.alerts.required_zones)
):
return SeverityEnum.alert
if (
not review_config.detections.labels
or self.obj_data["label"] in review_config.detections.labels
) and (
not review_config.detections.required_zones
or set(self.entered_zones) & set(review_config.detections.required_zones)
):
return SeverityEnum.detection
return None
def _is_false_positive(self):
# once a true positive, always a true positive
if not self.false_positive:
@ -232,6 +254,7 @@ class TrackedObject:
"attributes": self.attributes,
"current_attributes": self.obj_data["attributes"],
"pending_loitering": self.pending_loitering,
"max_severity": self.max_severity,
}
if include_thumbnail:

10
frigate/util/config.py
View File

@ -14,6 +14,16 @@ from frigate.util.services import get_video_properties
logger = logging.getLogger(__name__)
CURRENT_CONFIG_VERSION = "0.15-0"
DEFAULT_CONFIG_FILE = "/config/config.yml"
def find_config_file() -> str:
config_path = os.environ.get("CONFIG_FILE", DEFAULT_CONFIG_FILE)
if not os.path.isfile(config_path):
config_path = config_path.replace("yml", "yaml")
return config_path
def migrate_frigate_config(config_file: str):

7
web/src/api/index.tsx
View File

@ -29,8 +29,11 @@ export function ApiProvider({ children, options }: ApiProviderType) {
error.response &&
[401, 302, 307].includes(error.response.status)
) {
window.location.href =
error.response.headers.get("location") ?? "login";
// redirect to the login page if not already there
const loginPage = error.response.headers.get("location") ?? "login";
if (window.location.href !== loginPage) {
window.location.href = loginPage;
}
}
},
...options,

2
web/src/components/auth/AuthForm.tsx
View File

@ -63,7 +63,7 @@ export function UserAuthForm({ className, ...props }: UserAuthFormProps) {
toast.error("Exceeded rate limit. Try again later.", {
position: "top-center",
});
} else if (err.response?.status === 400) {
} else if (err.response?.status === 401) {
toast.error("Login failed", {
position: "top-center",
});

38
web/src/components/overlay/detail/ReviewDetailDialog.tsx
View File

@ -74,6 +74,23 @@ export default function ReviewDetailDialog({
return events.length != review?.data.detections.length;
}, [review, events]);
const missingObjects = useMemo(() => {
if (!review || !events) {
return [];
}
const detectedIds = review.data.detections;
const missing = Array.from(
new Set(
events
.filter((event) => !detectedIds.includes(event.id))
.map((event) => event.label),
),
);
return missing;
}, [review, events]);
const formattedDate = useFormattedTimestamp(
review?.start_time ?? 0,
config?.ui.time_format == "24hour"
@ -263,8 +280,25 @@ export default function ReviewDetailDialog({
</div>
{hasMismatch && (
<div className="p-4 text-center text-sm">
Some objects that were detected are not included in this list
because the object does not have a snapshot
{(() => {
const detectedCount = Math.abs(
(events?.length ?? 0) -
(review?.data.detections.length ?? 0),
);
const objectLabel =
detectedCount === 1 ? "object was" : "objects were";
return `${detectedCount} unavailable ${objectLabel} detected and included in this review item.`;
})()}{" "}
Those objects either did not qualify as an alert or detection
or have already been cleaned up/deleted.
{missingObjects.length > 0 && (
<div className="mt-2">
Adjust your configuration if you want Frigate to save
tracked objects for the following labels:{" "}
{missingObjects.join(", ")}
</div>
)}
</div>
)}
<div className="relative flex size-full flex-col gap-2">

134
web/src/components/overlay/detail/SearchDetailDialog.tsx
View File

@ -469,60 +469,90 @@ function ObjectDetailsTab({
</div>
</div>
<div className="flex flex-col gap-1.5">
<div className="text-sm text-primary/40">Description</div>
<Textarea
className="h-64"
placeholder="Description of the tracked object"
value={desc}
onChange={(e) => setDesc(e.target.value)}
/>
<div className="flex w-full flex-row justify-end gap-2">
{config?.cameras[search.camera].genai.enabled && (
<div className="flex items-center">
<Button
className="rounded-r-none border-r-0"
aria-label="Regenerate tracked object description"
onClick={() => regenerateDescription("thumbnails")}
>
Regenerate
</Button>
{search.has_snapshot && (
<DropdownMenu>
<DropdownMenuTrigger asChild>
<Button
className="rounded-l-none border-l-0 px-2"
aria-label="Expand regeneration menu"
>
<FaChevronDown className="size-3" />
</Button>
</DropdownMenuTrigger>
<DropdownMenuContent>
<DropdownMenuItem
className="cursor-pointer"
aria-label="Regenerate from snapshot"
onClick={() => regenerateDescription("snapshot")}
>
Regenerate from Snapshot
</DropdownMenuItem>
<DropdownMenuItem
className="cursor-pointer"
aria-label="Regenerate from thumbnails"
onClick={() => regenerateDescription("thumbnails")}
>
Regenerate from Thumbnails
</DropdownMenuItem>
</DropdownMenuContent>
</DropdownMenu>
)}
{config?.cameras[search.camera].genai.enabled &&
!search.end_time &&
(config.cameras[search.camera].genai.required_zones.length === 0 ||
search.zones.some((zone) =>
config.cameras[search.camera].genai.required_zones.includes(zone),
)) &&
(config.cameras[search.camera].genai.objects.length === 0 ||
config.cameras[search.camera].genai.objects.includes(
search.label,
)) ? (
<>
<div className="text-sm text-primary/40">Description</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">
Frigate will not request a description from your Generative AI
provider until the tracked object's lifecycle has ended.
</div>
</div>
</>
) : (
<>
<div className="text-sm text-primary/40">Description</div>
<Textarea
className="h-64"
placeholder="Description of the tracked object"
value={desc}
onChange={(e) => setDesc(e.target.value)}
/>
</>
)}
<div className="flex w-full flex-row justify-end gap-2">
{config?.cameras[search.camera].genai.enabled && search.end_time && (
<>
<div className="flex items-start">
<Button
className="rounded-r-none border-r-0"
aria-label="Regenerate tracked object description"
onClick={() => regenerateDescription("thumbnails")}
>
Regenerate
</Button>
{search.has_snapshot && (
<DropdownMenu>
<DropdownMenuTrigger asChild>
<Button
className="rounded-l-none border-l-0 px-2"
aria-label="Expand regeneration menu"
>
<FaChevronDown className="size-3" />
</Button>
</DropdownMenuTrigger>
<DropdownMenuContent>
<DropdownMenuItem
className="cursor-pointer"
aria-label="Regenerate from snapshot"
onClick={() => regenerateDescription("snapshot")}
>
Regenerate from Snapshot
</DropdownMenuItem>
<DropdownMenuItem
className="cursor-pointer"
aria-label="Regenerate from thumbnails"
onClick={() => regenerateDescription("thumbnails")}
>
Regenerate from Thumbnails
</DropdownMenuItem>
</DropdownMenuContent>
</DropdownMenu>
)}
</div>
<Button
variant="select"
aria-label="Save"
onClick={updateDescription}
>
Save
</Button>
</>
)}
<Button
variant="select"
aria-label="Save"
onClick={updateDescription}
>
Save
</Button>
</div>
</div>
</div>

3
web/src/hooks/use-overlay-state.tsx
View File

@ -5,6 +5,7 @@ import { usePersistence } from "./use-persistence";
export function useOverlayState<S>(
key: string,
defaultValue: S | undefined = undefined,
preserveSearch: boolean = true,
): [S | undefined, (value: S, replace?: boolean) => void] {
const location = useLocation();
const navigate = useNavigate();
@ -15,7 +16,7 @@ export function useOverlayState<S>(
(value: S, replace: boolean = false) => {
const newLocationState = { ...currentLocationState };
newLocationState[key] = value;
navigate(location.pathname + location.search, {
navigate(location.pathname + (preserveSearch ? location.search : ""), {
state: newLocationState,
replace,
});

7
web/src/pages/Events.tsx
View File

@ -39,8 +39,11 @@ export default function Events() {
const [showReviewed, setShowReviewed] = usePersistence("showReviewed", false);
const [recording, setRecording] =
useOverlayState<RecordingStartingPoint>("recording");
const [recording, setRecording] = useOverlayState<RecordingStartingPoint>(
"recording",
undefined,
false,
);
useSearchEffect("id", (reviewId: string) => {
axios