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18 Commits
v0.16.0-be
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v0.15.1
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dc79af2d98 |
@@ -20,7 +20,7 @@ FIRST_MODEL=true
|
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MODEL_DOWNLOAD=""
|
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MODEL_CONVERT=""
|
||||
|
||||
if [ -z "$YOLO_MODELS"]; then
|
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if [ -z "$YOLO_MODELS" ]; then
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echo "tensorrt model preparation disabled"
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exit 0
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fi
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|
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@@ -231,3 +231,38 @@ ffmpeg:
|
||||
### TP-Link VIGI Cameras
|
||||
|
||||
TP-Link VIGI cameras need some adjustments to the main stream settings on the camera itself to avoid issues. The stream needs to be configured as `H264` with `Smart Coding` set to `off`. Without these settings you may have problems when trying to watch recorded footage. For example Firefox will stop playback after a few seconds and show the following error message: `The media playback was aborted due to a corruption problem or because the media used features your browser did not support.`.
|
||||
|
||||
## USB Cameras (aka Webcams)
|
||||
|
||||
To use a USB camera (webcam) with Frigate, the recommendation is to use go2rtc's [FFmpeg Device](https://github.com/AlexxIT/go2rtc?tab=readme-ov-file#source-ffmpeg-device) support:
|
||||
|
||||
- Preparation outside of Frigate:
|
||||
- Get USB camera path. Run `v4l2-ctl --list-devices` to get a listing of locally-connected cameras available. (You may need to install `v4l-utils` in a way appropriate for your Linux distribution). In the sample configuration below, we use `video=0` to correlate with a detected device path of `/dev/video0`
|
||||
- Get USB camera formats & resolutions. Run `ffmpeg -f v4l2 -list_formats all -i /dev/video0` to get an idea of what formats and resolutions the USB Camera supports. In the sample configuration below, we use a width of 1024 and height of 576 in the stream and detection settings based on what was reported back.
|
||||
- If using Frigate in a container (e.g. Docker on TrueNAS), ensure you have USB Passthrough support enabled, along with a specific Host Device (`/dev/video0`) + Container Device (`/dev/video0`) listed.
|
||||
|
||||
- In your Frigate Configuration File, add the go2rtc stream and roles as appropriate:
|
||||
|
||||
```
|
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go2rtc:
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streams:
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usb_camera:
|
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- "ffmpeg:device?video=0&video_size=1024x576#video=h264"
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||||
|
||||
cameras:
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usb_camera:
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enabled: true
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||||
ffmpeg:
|
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inputs:
|
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- path: rtsp://127.0.0.1:8554/usb_camera
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input_args: preset-rtsp-restream
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roles:
|
||||
- detect
|
||||
- record
|
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detect:
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enabled: false # <---- disable detection until you have a working camera feed
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width: 1024
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height: 576
|
||||
```
|
||||
|
||||
|
||||
|
||||
@@ -100,6 +100,8 @@ This list of working and non-working PTZ cameras is based on user feedback.
|
||||
| Ctronics PTZ | ✅ | ❌ | |
|
||||
| Dahua | ✅ | ✅ | |
|
||||
| Dahua DH-SD2A500HB | ✅ | ❌ | |
|
||||
| Dahua DH-SD49825GB-HNR | ✅ | ✅ | |
|
||||
| Dahua DH-P5AE-PV | ❌ | ❌ | |
|
||||
| Foscam R5 | ✅ | ❌ | |
|
||||
| Hanwha XNP-6550RH | ✅ | ❌ | |
|
||||
| Hikvision | ✅ | ❌ | Incomplete ONVIF support (MoveStatus won't update even on latest firmware) - reported with HWP-N4215IH-DE and DS-2DE3304W-DE, but likely others |
|
||||
|
||||
@@ -27,12 +27,23 @@ genai:
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model: gemini-1.5-flash
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||||
|
||||
cameras:
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front_camera: ...
|
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front_camera:
|
||||
genai:
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||||
enabled: True # <- enable GenAI for your front camera
|
||||
use_snapshot: True
|
||||
objects:
|
||||
- person
|
||||
required_zones:
|
||||
- steps
|
||||
indoor_camera:
|
||||
genai: # <- disable GenAI for your indoor camera
|
||||
enabled: False
|
||||
genai:
|
||||
enabled: False # <- disable GenAI for your indoor camera
|
||||
```
|
||||
|
||||
By default, descriptions will be generated for all tracked objects and all zones. But you can also optionally specify `objects` and `required_zones` to only generate descriptions for certain tracked objects or zones.
|
||||
|
||||
Optionally, you can generate the description using a snapshot (if enabled) by setting `use_snapshot` to `True`. By default, this is set to `False`, which sends the uncompressed images from the `detect` stream collected over the object's lifetime to the model. Once the object lifecycle ends, only a single compressed and cropped thumbnail is saved with the tracked object. Using a snapshot might be useful when you want to _regenerate_ a tracked object's description as it will provide the AI with a higher-quality image (typically downscaled by the AI itself) than the cropped/compressed thumbnail. Using a snapshot otherwise has a trade-off in that only a single image is sent to your provider, which will limit the model's ability to determine object movement or direction.
|
||||
|
||||
## Ollama
|
||||
|
||||
:::warning
|
||||
@@ -182,9 +193,7 @@ genai:
|
||||
car: "Observe the primary vehicle in these images. Focus on its movement, direction, or purpose (e.g., parking, approaching, circling). If it's a delivery vehicle, mention the company."
|
||||
```
|
||||
|
||||
Prompts can also be overriden at the camera level to provide a more detailed prompt to the model about your specific camera, if you desire. By default, descriptions will be generated for all tracked objects and all zones. But you can also optionally specify `objects` and `required_zones` to only generate descriptions for certain tracked objects or zones.
|
||||
|
||||
Optionally, you can generate the description using a snapshot (if enabled) by setting `use_snapshot` to `True`. By default, this is set to `False`, which sends the uncompressed images from the `detect` stream collected over the object's lifetime to the model. Once the object lifecycle ends, only a single compressed and cropped thumbnail is saved with the tracked object. Using a snapshot might be useful when you want to _regenerate_ a tracked object's description as it will provide the AI with a higher-quality image (typically downscaled by the AI itself) than the cropped/compressed thumbnail. Using a snapshot otherwise has a trade-off in that only a single image is sent to your provider, which will limit the model's ability to determine object movement or direction.
|
||||
Prompts can also be overriden at the camera level to provide a more detailed prompt to the model about your specific camera, if you desire.
|
||||
|
||||
```yaml
|
||||
cameras:
|
||||
|
||||
@@ -145,6 +145,6 @@ For devices that support two way talk, Frigate can be configured to use the feat
|
||||
|
||||
- Set up go2rtc with [WebRTC](#webrtc-extra-configuration).
|
||||
- Ensure you access Frigate via https (may require [opening port 8971](/frigate/installation/#ports)).
|
||||
- For the Home Assistant Frigate card, [follow the docs](https://github.com/dermotduffy/frigate-hass-card?tab=readme-ov-file#using-2-way-audio) for the correct source.
|
||||
- For the Home Assistant Frigate card, [follow the docs](http://card.camera/#/usage/2-way-audio) for the correct source.
|
||||
|
||||
To use the Reolink Doorbell with two way talk, you should use the [recommended Reolink configuration](/configuration/camera_specific#reolink-doorbell)
|
||||
|
||||
@@ -327,6 +327,7 @@ detectors:
|
||||
|
||||
model:
|
||||
path: /config/model_cache/tensorrt/yolov7-320.trt
|
||||
labelmap_path: /labelmap/coco-80.txt
|
||||
input_tensor: nchw
|
||||
input_pixel_format: rgb
|
||||
width: 320
|
||||
|
||||
@@ -21,6 +21,21 @@ In 0.14 and later, all of that is bundled into a single review item which starts
|
||||
|
||||
Not every segment of video captured by Frigate may be of the same level of interest to you. Video of people who enter your property may be a different priority than those walking by on the sidewalk. For this reason, Frigate 0.14 categorizes review items as _alerts_ and _detections_. By default, all person and car objects are considered alerts. You can refine categorization of your review items by configuring required zones for them.
|
||||
|
||||
:::note
|
||||
|
||||
Alerts and detections categorize the tracked objects in review items, but Frigate must first detect those objects with your configured object detector (Coral, OpenVINO, etc). By default, the object tracker only detects `person`. Setting `labels` for `alerts` and `detections` does not automatically enable detection of new objects. To detect more than `person`, you should add the following to your config:
|
||||
|
||||
```yaml
|
||||
objects:
|
||||
track:
|
||||
- person
|
||||
- car
|
||||
- ...
|
||||
```
|
||||
|
||||
See the [objects documentation](objects.md) for the list of objects that Frigate's default model tracks.
|
||||
:::
|
||||
|
||||
## Restricting alerts to specific labels
|
||||
|
||||
By default a review item will only be marked as an alert if a person or car is detected. This can be configured to include any object or audio label using the following config:
|
||||
|
||||
@@ -16,16 +16,27 @@ Here are some of the camera's I recommend:
|
||||
- <a href="https://amzn.to/4fwoNWA" target="_blank" rel="nofollow noopener sponsored">Loryta(Dahua) IPC-T549M-ALED-S3</a> (affiliate link)
|
||||
- <a href="https://amzn.to/3YXpcMw" target="_blank" rel="nofollow noopener sponsored">Loryta(Dahua) IPC-T54IR-AS</a> (affiliate link)
|
||||
- <a href="https://amzn.to/3AvBHoY" target="_blank" rel="nofollow noopener sponsored">Amcrest IP5M-T1179EW-AI-V3</a> (affiliate link)
|
||||
- <a href="https://amzn.to/4ltOpaC" target="_blank" rel="nofollow noopener sponsored">HIKVISION DS-2CD2387G2P-LSU/SL ColorVu 8MP Panoramic Turret IP Camera</a> (affiliate link)
|
||||
|
||||
I may earn a small commission for my endorsement, recommendation, testimonial, or link to any products or services from this website.
|
||||
|
||||
## Server
|
||||
|
||||
My current favorite is the Beelink EQ13 because of the efficient N100 CPU and dual NICs that allow you to setup a dedicated private network for your cameras where they can be blocked from accessing the internet. There are many used workstation options on eBay that work very well. Anything with an Intel CPU and capable of running Debian should work fine. As a bonus, you may want to look for devices with a M.2 or PCIe express slot that is compatible with the Google Coral. I may earn a small commission for my endorsement, recommendation, testimonial, or link to any products or services from this website.
|
||||
My current favorite is the Beelink EQ13 because of the efficient N100 CPU and dual NICs that allow you to setup a dedicated private network for your cameras where they can be blocked from accessing the internet. There are many used workstation options on eBay that work very well. Anything with an Intel CPU and capable of running Debian should work fine. As a bonus, you may want to look for devices with a M.2 or PCIe express slot that is compatible with the Google Coral, Hailo, or other AI accelerators.
|
||||
|
||||
Note that many of these mini PCs come with Windows pre-installed, and you will need to install Linux according to the [getting started guide](../guides/getting_started.md).
|
||||
|
||||
I may earn a small commission for my endorsement, recommendation, testimonial, or link to any products or services from this website.
|
||||
|
||||
:::warning
|
||||
|
||||
If the EQ13 is out of stock, the link below may take you to a suggested alternative on Amazon. The Beelink EQ14 has some known compatibility issues, so you should avoid that model for now.
|
||||
|
||||
:::
|
||||
|
||||
| Name | Coral Inference Speed | Coral Compatibility | Notes |
|
||||
| ------------------------------------------------------------------------------------------------------------- | --------------------- | ------------------- | ----------------------------------------------------------------------------------------- |
|
||||
| Beelink EQ13 (<a href="https://amzn.to/4iQaBKu" target="_blank" rel="nofollow noopener sponsored">Amazon</a>) | 5-10ms | USB | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras. |
|
||||
| Beelink EQ13 (<a href="https://amzn.to/4jn2qVr" target="_blank" rel="nofollow noopener sponsored">Amazon</a>) | 5-10ms | USB | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras. |
|
||||
|
||||
## Detectors
|
||||
|
||||
@@ -53,23 +64,24 @@ More information is available [in the detector docs](/configuration/object_detec
|
||||
|
||||
Inference speeds vary greatly depending on the CPU or GPU used, some known examples of GPU inference times are below:
|
||||
|
||||
| Name | MobileNetV2 Inference Time | YOLO-NAS Inference Time | Notes |
|
||||
| -------------------- | -------------------------- | ------------------------- | -------------------------------------- |
|
||||
| Intel Celeron J4105 | ~ 25 ms | | Can only run one detector instance |
|
||||
| Intel Celeron N3060 | 130 - 150 ms | | Can only run one detector instance |
|
||||
| Intel Celeron N3205U | ~ 120 ms | | Can only run one detector instance |
|
||||
| Intel Celeron N4020 | 50 - 200 ms | | Inference speed depends on other loads |
|
||||
| Intel i3 6100T | 15 - 35 ms | | Can only run one detector instance |
|
||||
| Intel i3 8100 | ~ 15 ms | | |
|
||||
| Intel i5 4590 | ~ 20 ms | | |
|
||||
| Intel i5 6500 | ~ 15 ms | | |
|
||||
| Intel i5 7200u | 15 - 25 ms | | |
|
||||
| Intel i5 7500 | ~ 15 ms | | |
|
||||
| Intel i5 1135G7 | 10 - 15 ms | | |
|
||||
| Intel i3 12000 | | 320: ~ 19 ms 640: ~ 54 ms | |
|
||||
| Intel i5 12600K | ~ 15 ms | 320: ~ 20 ms 640: ~ 46 ms | |
|
||||
| Intel Arc A380 | ~ 6 ms | 320: ~ 10 ms | |
|
||||
| Intel Arc A750 | ~ 4 ms | 320: ~ 8 ms | |
|
||||
| Name | MobileNetV2 Inference Time | YOLO-NAS Inference Time | Notes |
|
||||
| --------------------- | --------------------------- | --------------------------- | --------------------------------------- |
|
||||
| Intel Arc A750 | ~ 4 ms | 320: ~ 8 ms | |
|
||||
| Intel Arc A380 | ~ 6 ms | 320: ~ 10 ms | |
|
||||
| Intel Ultra 5 125H | | 320: ~ 10 ms 640: ~ 22 ms | |
|
||||
| Intel i5 12600K | ~ 15 ms | 320: ~ 20 ms 640: ~ 46 ms | |
|
||||
| Intel i3 12000 | | 320: ~ 19 ms 640: ~ 54 ms | |
|
||||
| Intel i5 1135G7 | 10 - 15 ms | | |
|
||||
| Intel i5 7500 | ~ 15 ms | | |
|
||||
| Intel i5 7200u | 15 - 25 ms | | |
|
||||
| Intel i5 6500 | ~ 15 ms | | |
|
||||
| Intel i5 4590 | ~ 20 ms | | |
|
||||
| Intel i3 8100 | ~ 15 ms | | |
|
||||
| Intel i3 6100T | 15 - 35 ms | | Can only run one detector instance |
|
||||
| Intel Celeron N4020 | 50 - 200 ms | | Inference speed depends on other loads |
|
||||
| Intel Celeron N3205U | ~ 120 ms | | Can only run one detector instance |
|
||||
| Intel Celeron N3060 | 130 - 150 ms | | Can only run one detector instance |
|
||||
| Intel Celeron J4105 | ~ 25 ms | | Can only run one |
|
||||
|
||||
### TensorRT - Nvidia GPU
|
||||
|
||||
@@ -78,15 +90,15 @@ The TensortRT detector is able to run on x86 hosts that have an Nvidia GPU which
|
||||
Inference speeds will vary greatly depending on the GPU and the model used.
|
||||
`tiny` variants are faster than the equivalent non-tiny model, some known examples are below:
|
||||
|
||||
| Name | YoloV7 Inference Time | YOLO-NAS Inference Time |
|
||||
| --------------- | --------------------- | ------------------------- |
|
||||
| GTX 1060 6GB | ~ 7 ms | |
|
||||
| GTX 1070 | ~ 6 ms | |
|
||||
| GTX 1660 SUPER | ~ 4 ms | |
|
||||
| RTX 3050 | 5 - 7 ms | 320: ~ 10 ms 640: ~ 16 ms |
|
||||
| RTX 3070 Mobile | ~ 5 ms | |
|
||||
| Quadro P400 2GB | 20 - 25 ms | |
|
||||
| Quadro P2000 | ~ 12 ms | |
|
||||
| Name | YoloV7 Inference Time | YOLO-NAS Inference Time |
|
||||
| --------------- | ---------------------- | --------------------------- |
|
||||
| Quadro P2000 | ~ 12 ms | |
|
||||
| Quadro P400 2GB | 20 - 25 ms | |
|
||||
| RTX 3070 Mobile | ~ 5 ms | |
|
||||
| RTX 3050 | 5 - 7 ms | 320: ~ 10 ms 640: ~ 16 ms |
|
||||
| GTX 1660 SUPER | ~ 4 ms | |
|
||||
| GTX 1070 | ~ 6 ms | |
|
||||
| GTX 1060 6GB | ~ 7 ms | |
|
||||
|
||||
### AMD GPUs
|
||||
|
||||
|
||||
119
docs/docs/frigate/updating.md
Normal file
119
docs/docs/frigate/updating.md
Normal file
@@ -0,0 +1,119 @@
|
||||
---
|
||||
id: updating
|
||||
title: Updating
|
||||
---
|
||||
|
||||
# Updating Frigate
|
||||
|
||||
The current stable version of Frigate is **0.15.0**. The release notes and any breaking changes for this version can be found on the [Frigate GitHub releases page](https://github.com/blakeblackshear/frigate/releases/tag/v0.15.0).
|
||||
|
||||
Keeping Frigate up to date ensures you benefit from the latest features, performance improvements, and bug fixes. The update process varies slightly depending on your installation method (Docker, Home Assistant Addon, etc.). Below are instructions for the most common setups.
|
||||
|
||||
## Before You Begin
|
||||
|
||||
- **Stop Frigate**: For most methods, you’ll need to stop the running Frigate instance before backing up and updating.
|
||||
- **Backup Your Configuration**: Always back up your `/config` directory (e.g., `config.yml` and `frigate.db`, the SQLite database) before updating. This ensures you can roll back if something goes wrong.
|
||||
- **Check Release Notes**: Carefully review the [Frigate GitHub releases page](https://github.com/blakeblackshear/frigate/releases) for breaking changes or configuration updates that might affect your setup.
|
||||
|
||||
## Updating with Docker
|
||||
|
||||
If you’re running Frigate via Docker (recommended method), follow these steps:
|
||||
|
||||
1. **Stop the Container**:
|
||||
|
||||
- If using Docker Compose:
|
||||
```bash
|
||||
docker compose down frigate
|
||||
```
|
||||
- If using `docker run`:
|
||||
```bash
|
||||
docker stop frigate
|
||||
```
|
||||
|
||||
2. **Update and Pull the Latest Image**:
|
||||
|
||||
- If using Docker Compose:
|
||||
- Edit your `docker-compose.yml` file to specify the desired version tag (e.g., `0.15.0` instead of `0.14.1`). For example:
|
||||
```yaml
|
||||
services:
|
||||
frigate:
|
||||
image: ghcr.io/blakeblackshear/frigate:0.15.0
|
||||
```
|
||||
- Then pull the image:
|
||||
```bash
|
||||
docker pull ghcr.io/blakeblackshear/frigate:0.15.0
|
||||
```
|
||||
- **Note for `stable` Tag Users**: If your `docker-compose.yml` uses the `stable` tag (e.g., `ghcr.io/blakeblackshear/frigate:stable`), you don’t need to update the tag manually. The `stable` tag always points to the latest stable release after pulling.
|
||||
- If using `docker run`:
|
||||
- Pull the image with the appropriate tag (e.g., `0.15.0`, `0.15.0-tensorrt`, or `stable`):
|
||||
```bash
|
||||
docker pull ghcr.io/blakeblackshear/frigate:0.15.0
|
||||
```
|
||||
|
||||
3. **Start the Container**:
|
||||
|
||||
- If using Docker Compose:
|
||||
```bash
|
||||
docker compose up -d
|
||||
```
|
||||
- If using `docker run`, re-run your original command (e.g., from the [Installation](#docker) section) with the updated image tag.
|
||||
|
||||
4. **Verify the Update**:
|
||||
- Check the container logs to ensure Frigate starts successfully:
|
||||
```bash
|
||||
docker logs frigate
|
||||
```
|
||||
- Visit the Frigate Web UI (default: `http://<your-ip>:5000`) to confirm the new version is running. The version number is displayed at the top of the System Metrics page.
|
||||
|
||||
### Notes
|
||||
|
||||
- If you’ve customized other settings (e.g., `shm-size`), ensure they’re still appropriate after the update.
|
||||
- Docker will automatically use the updated image when you restart the container, as long as you pulled the correct version.
|
||||
|
||||
## Updating the Home Assistant Addon
|
||||
|
||||
For users running Frigate as a Home Assistant Addon:
|
||||
|
||||
1. **Check for Updates**:
|
||||
|
||||
- Navigate to **Settings > Add-ons** in Home Assistant.
|
||||
- Find your installed Frigate addon (e.g., "Frigate NVR" or "Frigate NVR (Full Access)").
|
||||
- If an update is available, you’ll see an "Update" button.
|
||||
|
||||
2. **Update the Addon**:
|
||||
|
||||
- Click the "Update" button next to the Frigate addon.
|
||||
- Wait for the process to complete. Home Assistant will handle downloading and installing the new version.
|
||||
|
||||
3. **Restart the Addon**:
|
||||
|
||||
- After updating, go to the addon’s page and click "Restart" to apply the changes.
|
||||
|
||||
4. **Verify the Update**:
|
||||
- Check the addon logs (under the "Log" tab) to ensure Frigate starts without errors.
|
||||
- Access the Frigate Web UI to confirm the new version is running.
|
||||
|
||||
### Notes
|
||||
|
||||
- Ensure your `/config/frigate.yml` is compatible with the new version by reviewing the [Release notes](https://github.com/blakeblackshear/frigate/releases).
|
||||
- If using custom hardware (e.g., Coral or GPU), verify that configurations still work, as addon updates don’t modify your hardware settings.
|
||||
|
||||
## Rolling Back
|
||||
|
||||
If an update causes issues:
|
||||
|
||||
1. Stop Frigate.
|
||||
2. Restore your backed-up config file and database.
|
||||
3. Revert to the previous image version:
|
||||
- For Docker: Specify an older tag (e.g., `ghcr.io/blakeblackshear/frigate:0.14.1`) in your `docker run` command.
|
||||
- For Docker Compose: Edit your `docker-compose.yml`, specify the older version tag (e.g., `ghcr.io/blakeblackshear/frigate:0.14.1`), and re-run `docker compose up -d`.
|
||||
- For Home Assistant: Reinstall the previous addon version manually via the repository if needed and restart the addon.
|
||||
4. Verify the old version is running again.
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
- **Container Fails to Start**: Check logs (`docker logs frigate`) for errors.
|
||||
- **UI Not Loading**: Ensure ports (e.g., 5000, 8971) are still mapped correctly and the service is running.
|
||||
- **Hardware Issues**: Revisit hardware-specific setup (e.g., Coral, GPU) if detection or decoding fails post-update.
|
||||
|
||||
Common questions are often answered in the [FAQ](https://github.com/blakeblackshear/frigate/discussions), pinned at the top of the support discussions.
|
||||
@@ -113,6 +113,14 @@ If you run Frigate on a separate device within your local network, Home Assistan
|
||||
|
||||
Use `http://<frigate_device_ip>:8971` as the URL for the integration so that authentication is required.
|
||||
|
||||
:::tip
|
||||
|
||||
The above URL assumes you have [disabled TLS](../configuration/tls).
|
||||
By default, TLS is enabled and Frigate will be using a self-signed certificate. HomeAssistant will fail to connect HTTPS to port 8971 since it fails to verify the self-signed certificate.
|
||||
Either disable TLS and use HTTP from HomeAssistant, or configure Frigate to be acessible with a valid certificate.
|
||||
|
||||
:::
|
||||
|
||||
```yaml
|
||||
services:
|
||||
frigate:
|
||||
|
||||
@@ -28,7 +28,14 @@ Message published for each changed tracked object. The first message is publishe
|
||||
"id": "1607123955.475377-mxklsc",
|
||||
"camera": "front_door",
|
||||
"frame_time": 1607123961.837752,
|
||||
"snapshot_time": 1607123961.837752,
|
||||
"snapshot": {
|
||||
"frame_time": 1607123965.975463,
|
||||
"box": [415, 489, 528, 700],
|
||||
"area": 12728,
|
||||
"region": [260, 446, 660, 846],
|
||||
"score": 0.77546,
|
||||
"attributes": [],
|
||||
},
|
||||
"label": "person",
|
||||
"sub_label": null,
|
||||
"top_score": 0.958984375,
|
||||
@@ -58,7 +65,14 @@ Message published for each changed tracked object. The first message is publishe
|
||||
"id": "1607123955.475377-mxklsc",
|
||||
"camera": "front_door",
|
||||
"frame_time": 1607123962.082975,
|
||||
"snapshot_time": 1607123961.837752,
|
||||
"snapshot": {
|
||||
"frame_time": 1607123965.975463,
|
||||
"box": [415, 489, 528, 700],
|
||||
"area": 12728,
|
||||
"region": [260, 446, 660, 846],
|
||||
"score": 0.77546,
|
||||
"attributes": [],
|
||||
},
|
||||
"label": "person",
|
||||
"sub_label": ["John Smith", 0.79],
|
||||
"top_score": 0.958984375,
|
||||
|
||||
@@ -13,6 +13,10 @@ Please use your own knowledge to assess and vet them before you install anything
|
||||
|
||||
:::
|
||||
|
||||
## [Advanced Camera Card (formerly known as Frigate Card](https://card.camera/#/README)
|
||||
|
||||
The [Advanced Camera Card](https://card.camera/#/README) is a Home Assistant dashboard card with deep Frigate integration.
|
||||
|
||||
## [Double Take](https://github.com/skrashevich/double-take)
|
||||
|
||||
[Double Take](https://github.com/skrashevich/double-take) provides an unified UI and API for processing and training images for facial recognition.
|
||||
|
||||
@@ -1,56 +1,89 @@
|
||||
import type * as Preset from '@docusaurus/preset-classic';
|
||||
import * as path from 'node:path';
|
||||
import type { Config, PluginConfig } from '@docusaurus/types';
|
||||
import type * as OpenApiPlugin from 'docusaurus-plugin-openapi-docs';
|
||||
import type * as Preset from "@docusaurus/preset-classic";
|
||||
import * as path from "node:path";
|
||||
import type { Config, PluginConfig } from "@docusaurus/types";
|
||||
import type * as OpenApiPlugin from "docusaurus-plugin-openapi-docs";
|
||||
|
||||
const config: Config = {
|
||||
title: 'Frigate',
|
||||
tagline: 'NVR With Realtime Object Detection for IP Cameras',
|
||||
url: 'https://docs.frigate.video',
|
||||
baseUrl: '/',
|
||||
onBrokenLinks: 'throw',
|
||||
onBrokenMarkdownLinks: 'warn',
|
||||
favicon: 'img/favicon.ico',
|
||||
organizationName: 'blakeblackshear',
|
||||
projectName: 'frigate',
|
||||
themes: ['@docusaurus/theme-mermaid', 'docusaurus-theme-openapi-docs'],
|
||||
title: "Frigate",
|
||||
tagline: "NVR With Realtime Object Detection for IP Cameras",
|
||||
url: "https://docs.frigate.video",
|
||||
baseUrl: "/",
|
||||
onBrokenLinks: "throw",
|
||||
onBrokenMarkdownLinks: "warn",
|
||||
favicon: "img/favicon.ico",
|
||||
organizationName: "blakeblackshear",
|
||||
projectName: "frigate",
|
||||
themes: [
|
||||
"@docusaurus/theme-mermaid",
|
||||
"docusaurus-theme-openapi-docs",
|
||||
"@inkeep/docusaurus/chatButton",
|
||||
"@inkeep/docusaurus/searchBar",
|
||||
],
|
||||
markdown: {
|
||||
mermaid: true,
|
||||
},
|
||||
themeConfig: {
|
||||
algolia: {
|
||||
appId: 'WIURGBNBPY',
|
||||
apiKey: 'd02cc0a6a61178b25da550212925226b',
|
||||
indexName: 'frigate',
|
||||
appId: "WIURGBNBPY",
|
||||
apiKey: "d02cc0a6a61178b25da550212925226b",
|
||||
indexName: "frigate",
|
||||
},
|
||||
docs: {
|
||||
sidebar: {
|
||||
hideable: true,
|
||||
},
|
||||
},
|
||||
inkeepConfig: {
|
||||
baseSettings: {
|
||||
apiKey: "b1a4c4d73c9b48aa5b3cdae6e4c81f0bb3d1134eeb5a7100",
|
||||
integrationId: "cm6xmhn9h000gs601495fkkdx",
|
||||
organizationId: "org_map2JQEOco8U1ZYY",
|
||||
primaryBrandColor: "#010101",
|
||||
},
|
||||
aiChatSettings: {
|
||||
chatSubjectName: "Frigate",
|
||||
botAvatarSrcUrl: "https://frigate.video/images/favicon.png",
|
||||
getHelpCallToActions: [
|
||||
{
|
||||
name: "GitHub",
|
||||
url: "https://github.com/blakeblackshear/frigate",
|
||||
icon: {
|
||||
builtIn: "FaGithub",
|
||||
},
|
||||
},
|
||||
],
|
||||
quickQuestions: [
|
||||
"How to configure and setup camera settings?",
|
||||
"How to setup notifications?",
|
||||
"Supported builtin detectors?",
|
||||
"How to restream video feed?",
|
||||
"How can I get sound or audio in my recordings?",
|
||||
],
|
||||
},
|
||||
},
|
||||
prism: {
|
||||
additionalLanguages: ['bash', 'json'],
|
||||
additionalLanguages: ["bash", "json"],
|
||||
},
|
||||
languageTabs: [
|
||||
{
|
||||
highlight: 'python',
|
||||
language: 'python',
|
||||
logoClass: 'python',
|
||||
highlight: "python",
|
||||
language: "python",
|
||||
logoClass: "python",
|
||||
},
|
||||
{
|
||||
highlight: 'javascript',
|
||||
language: 'nodejs',
|
||||
logoClass: 'nodejs',
|
||||
highlight: "javascript",
|
||||
language: "nodejs",
|
||||
logoClass: "nodejs",
|
||||
},
|
||||
{
|
||||
highlight: 'javascript',
|
||||
language: 'javascript',
|
||||
logoClass: 'javascript',
|
||||
highlight: "javascript",
|
||||
language: "javascript",
|
||||
logoClass: "javascript",
|
||||
},
|
||||
{
|
||||
highlight: 'bash',
|
||||
language: 'curl',
|
||||
logoClass: 'curl',
|
||||
highlight: "bash",
|
||||
language: "curl",
|
||||
logoClass: "curl",
|
||||
},
|
||||
{
|
||||
highlight: "rust",
|
||||
@@ -59,49 +92,49 @@ const config: Config = {
|
||||
},
|
||||
],
|
||||
navbar: {
|
||||
title: 'Frigate',
|
||||
title: "Frigate",
|
||||
logo: {
|
||||
alt: 'Frigate',
|
||||
src: 'img/logo.svg',
|
||||
srcDark: 'img/logo-dark.svg',
|
||||
alt: "Frigate",
|
||||
src: "img/logo.svg",
|
||||
srcDark: "img/logo-dark.svg",
|
||||
},
|
||||
items: [
|
||||
{
|
||||
to: '/',
|
||||
activeBasePath: 'docs',
|
||||
label: 'Docs',
|
||||
position: 'left',
|
||||
to: "/",
|
||||
activeBasePath: "docs",
|
||||
label: "Docs",
|
||||
position: "left",
|
||||
},
|
||||
{
|
||||
href: 'https://frigate.video',
|
||||
label: 'Website',
|
||||
position: 'right',
|
||||
href: "https://frigate.video",
|
||||
label: "Website",
|
||||
position: "right",
|
||||
},
|
||||
{
|
||||
href: 'http://demo.frigate.video',
|
||||
label: 'Demo',
|
||||
position: 'right',
|
||||
href: "http://demo.frigate.video",
|
||||
label: "Demo",
|
||||
position: "right",
|
||||
},
|
||||
{
|
||||
href: 'https://github.com/blakeblackshear/frigate',
|
||||
label: 'GitHub',
|
||||
position: 'right',
|
||||
href: "https://github.com/blakeblackshear/frigate",
|
||||
label: "GitHub",
|
||||
position: "right",
|
||||
},
|
||||
],
|
||||
},
|
||||
footer: {
|
||||
style: 'dark',
|
||||
style: "dark",
|
||||
links: [
|
||||
{
|
||||
title: 'Community',
|
||||
title: "Community",
|
||||
items: [
|
||||
{
|
||||
label: 'GitHub',
|
||||
href: 'https://github.com/blakeblackshear/frigate',
|
||||
label: "GitHub",
|
||||
href: "https://github.com/blakeblackshear/frigate",
|
||||
},
|
||||
{
|
||||
label: 'Discussions',
|
||||
href: 'https://github.com/blakeblackshear/frigate/discussions',
|
||||
label: "Discussions",
|
||||
href: "https://github.com/blakeblackshear/frigate/discussions",
|
||||
},
|
||||
],
|
||||
},
|
||||
@@ -110,19 +143,19 @@ const config: Config = {
|
||||
},
|
||||
},
|
||||
plugins: [
|
||||
path.resolve(__dirname, 'plugins', 'raw-loader'),
|
||||
path.resolve(__dirname, "plugins", "raw-loader"),
|
||||
[
|
||||
'docusaurus-plugin-openapi-docs',
|
||||
"docusaurus-plugin-openapi-docs",
|
||||
{
|
||||
id: 'openapi',
|
||||
docsPluginId: 'classic', // configured for preset-classic
|
||||
id: "openapi",
|
||||
docsPluginId: "classic", // configured for preset-classic
|
||||
config: {
|
||||
frigateApi: {
|
||||
specPath: 'static/frigate-api.yaml',
|
||||
outputDir: 'docs/integrations/api',
|
||||
specPath: "static/frigate-api.yaml",
|
||||
outputDir: "docs/integrations/api",
|
||||
sidebarOptions: {
|
||||
groupPathsBy: 'tag',
|
||||
categoryLinkSource: 'tag',
|
||||
groupPathsBy: "tag",
|
||||
categoryLinkSource: "tag",
|
||||
sidebarCollapsible: true,
|
||||
sidebarCollapsed: true,
|
||||
},
|
||||
@@ -130,23 +163,24 @@ const config: Config = {
|
||||
} satisfies OpenApiPlugin.Options,
|
||||
},
|
||||
},
|
||||
]
|
||||
],
|
||||
] as PluginConfig[],
|
||||
presets: [
|
||||
[
|
||||
'classic',
|
||||
"classic",
|
||||
{
|
||||
docs: {
|
||||
routeBasePath: '/',
|
||||
sidebarPath: './sidebars.ts',
|
||||
routeBasePath: "/",
|
||||
sidebarPath: "./sidebars.ts",
|
||||
// Please change this to your repo.
|
||||
editUrl: 'https://github.com/blakeblackshear/frigate/edit/master/docs/',
|
||||
editUrl:
|
||||
"https://github.com/blakeblackshear/frigate/edit/master/docs/",
|
||||
sidebarCollapsible: false,
|
||||
docItemComponent: '@theme/ApiItem', // Derived from docusaurus-theme-openapi
|
||||
docItemComponent: "@theme/ApiItem", // Derived from docusaurus-theme-openapi
|
||||
},
|
||||
|
||||
theme: {
|
||||
customCss: './src/css/custom.css',
|
||||
customCss: "./src/css/custom.css",
|
||||
},
|
||||
} satisfies Preset.Options,
|
||||
],
|
||||
|
||||
7
docs/package-lock.json
generated
7
docs/package-lock.json
generated
@@ -12,6 +12,7 @@
|
||||
"@docusaurus/plugin-content-docs": "^3.6.3",
|
||||
"@docusaurus/preset-classic": "^3.6.3",
|
||||
"@docusaurus/theme-mermaid": "^3.6.3",
|
||||
"@inkeep/docusaurus": "^2.0.16",
|
||||
"@mdx-js/react": "^3.1.0",
|
||||
"clsx": "^2.1.1",
|
||||
"docusaurus-plugin-openapi-docs": "^4.3.1",
|
||||
@@ -4056,6 +4057,12 @@
|
||||
"react-hook-form": "^7.0.0"
|
||||
}
|
||||
},
|
||||
"node_modules/@inkeep/docusaurus": {
|
||||
"version": "2.0.16",
|
||||
"resolved": "https://registry.npmjs.org/@inkeep/docusaurus/-/docusaurus-2.0.16.tgz",
|
||||
"integrity": "sha512-dQhjlvFnl3CVr0gWeJ/V/qLnDy1XYrCfkdVSa2D3gJTxI9/vOf9639Y1aPxTxO88DiXuW9CertLrZLB6SoJ2yg==",
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/@isaacs/cliui": {
|
||||
"version": "8.0.2",
|
||||
"resolved": "https://registry.npmjs.org/@isaacs/cliui/-/cliui-8.0.2.tgz",
|
||||
|
||||
@@ -18,9 +18,10 @@
|
||||
},
|
||||
"dependencies": {
|
||||
"@docusaurus/core": "^3.6.3",
|
||||
"@docusaurus/plugin-content-docs": "^3.6.3",
|
||||
"@docusaurus/preset-classic": "^3.6.3",
|
||||
"@docusaurus/theme-mermaid": "^3.6.3",
|
||||
"@docusaurus/plugin-content-docs": "^3.6.3",
|
||||
"@inkeep/docusaurus": "^2.0.16",
|
||||
"@mdx-js/react": "^3.1.0",
|
||||
"clsx": "^2.1.1",
|
||||
"docusaurus-plugin-openapi-docs": "^4.3.1",
|
||||
|
||||
@@ -8,6 +8,7 @@ const sidebars: SidebarsConfig = {
|
||||
'frigate/index',
|
||||
'frigate/hardware',
|
||||
'frigate/installation',
|
||||
'frigate/updating',
|
||||
'frigate/camera_setup',
|
||||
'frigate/video_pipeline',
|
||||
'frigate/glossary',
|
||||
|
||||
@@ -473,7 +473,7 @@ class CameraState:
|
||||
|
||||
if current_frame is not None:
|
||||
self.current_frame_time = frame_time
|
||||
self._current_frame = current_frame
|
||||
self._current_frame = np.copy(current_frame)
|
||||
|
||||
if self.previous_frame_id is not None:
|
||||
self.frame_manager.close(self.previous_frame_id)
|
||||
|
||||
Reference in New Issue
Block a user