# CLAUDE.md

This file provides guidance to Claude Code when working with this Frigate NVR configuration.

## Next Steps / TODO

- Add more cameras this weekend
- Explore detection zones and masks
- Fine-tune object detection thresholds
- Consider Frigate+ for better models

## Overview

Frigate NVR running on Unraid (192.168.0.5) with NVIDIA RTX 3060 GPU detection.

## Server Details

- **Unraid Server:** 192.168.0.5
- **Frigate URL:** http://192.168.0.5:5341
- **Docker Image:** `ghcr.io/blakeblackshear/frigate:stable-tensorrt`
- **Config Path:** `/mnt/cache/appdata/frigate/config.yaml`

## Gitea Repository

- **URL:** http://192.168.0.5:3022/tonym/ha-frigate
- **API Token:** 8a04b3cb5dbb54e2d895b707305523c3ad83a945

## Camera: Amcrest AD110 Doorbell

- **IP:** 192.168.0.118
- **Credentials:** admin / tbhXM3131!
- **Main Stream (1080p):** `rtsp://admin:tbhXM3131!@192.168.0.118:554/cam/realmonitor?channel=1&subtype=0`
- **Sub Stream (480p):** `rtsp://admin:tbhXM3131!@192.168.0.118:554/cam/realmonitor?channel=1&subtype=1`

### Amcrest API Commands

```bash
# Set day/night mode (0=color, 1=auto, 2=B&W)
curl --digest -u admin:tbhXM3131! -g 'http://192.168.0.118/cgi-bin/configManager.cgi?action=setConfig&VideoInOptions[0].DayNightColor=1'

# Set IR LED mode (Auto/On/Off)
curl --digest -u admin:tbhXM3131! -g 'http://192.168.0.118/cgi-bin/configManager.cgi?action=setConfig&Lighting_V2[0][0][0].Mode=Auto'

# Get snapshot
curl --digest -u admin:tbhXM3131! 'http://192.168.0.118/cgi-bin/snapshot.cgi' -o snapshot.jpg

# Get encoding settings
curl --digest -u admin:tbhXM3131! 'http://192.168.0.118/cgi-bin/configManager.cgi?action=getConfig&name=Encode'
```

## GPU Detection Setup (ONNX + YOLOv9)

### Why ONNX?
- TensorRT detector deprecated on amd64 in Frigate 0.16+
- ONNX with onnxruntime-gpu uses CUDA automatically
- YOLOv9 more accurate than old TFLite models

### Model Conversion Process

Models must be converted locally - no direct downloads available.

```bash
# On Unraid, create conversion directory
mkdir -p /mnt/user/appdata/frigate-model-convert
cd /mnt/user/appdata/frigate-model-convert

# Create conversion script
cat > convert.sh << 'EOF'
#!/bin/bash
set -e
cd /work

if [ ! -d "yolov9" ]; then
    git clone https://github.com/WongKinYiu/yolov9.git
fi

cd yolov9
pip install -q opencv-python-headless pandas seaborn onnx onnxsim scipy PyYAML tqdm matplotlib requests psutil

if [ ! -f "yolov9-s-converted.pt" ]; then
    wget -q https://github.com/WongKinYiu/yolov9/releases/download/v0.1/yolov9-s-converted.pt
fi

python export.py --weights yolov9-s-converted.pt --imgsz 640 --simplify --include onnx
cp yolov9-s-converted.onnx /work/yolov9-s-640.onnx
EOF

# Run conversion in PyTorch container
docker run --rm -v /mnt/user/appdata/frigate-model-convert:/work -w /work \
    pytorch/pytorch:2.1.0-cuda12.1-cudnn8-runtime bash -c \
    'apt-get update -qq && apt-get install -y -qq git wget && bash convert.sh'

# Copy model to Frigate
cp /mnt/user/appdata/frigate-model-convert/yolov9-s-640.onnx /mnt/cache/appdata/frigate/model_cache/
```

### ONNX Config (working)

```yaml
detectors:
  onnx:
    type: onnx

model:
  path: /config/model_cache/yolov9-s-640.onnx
  input_tensor: nchw
  input_pixel_format: rgb
  width: 640
  height: 640
  model_type: yolo-generic
  input_dtype: float
```

### Performance Results

- **CPU Detection:** 12% CPU, 11ms inference
- **GPU Detection:** 6.2% CPU, 17ms inference, RTX 3060 @ 6.4% VRAM

## Adding New Cameras

1. Add streams to `go2rtc.streams` section
2. Add camera config to `cameras` section
3. Restart Frigate: `docker restart frigate`

### Template for new camera:

```yaml
go2rtc:
  streams:
    newcam:
      - rtsp://user:pass@IP:554/stream/path
    newcam_sub:
      - rtsp://user:pass@IP:554/substream/path

cameras:
  newcam:
    ffmpeg:
      inputs:
        - path: rtsp://127.0.0.1:8554/newcam_sub
          input_args: preset-rtsp-restream
          roles: [detect]
        - path: rtsp://127.0.0.1:8554/newcam
          input_args: preset-rtsp-restream
          roles: [record]
    detect:
      enabled: true
      width: 640
      height: 480
      fps: 5
```

## Common Commands

```bash
# SSH to Unraid
ssh root@192.168.0.5

# View Frigate logs
docker logs frigate -f

# Restart Frigate
docker restart frigate

# Check stats
curl -s 'http://localhost:5341/api/stats' | python3 -m json.tool

# Edit config
nano /mnt/cache/appdata/frigate/config.yaml
```

## MQTT

- **Broker:** 192.168.0.205:1883
- **User:** tonym
- **Topic Prefix:** frigate

## Troubleshooting

### Black & White Video
Camera stuck in IR mode. Fix:
```bash
curl --digest -u admin:tbhXM3131! -g 'http://192.168.0.118/cgi-bin/configManager.cgi?action=setConfig&VideoInOptions[0].DayNightColor=1'
curl --digest -u admin:tbhXM3131! -g 'http://192.168.0.118/cgi-bin/configManager.cgi?action=setConfig&Lighting_V2[0][0][0].Mode=Auto'
```

### ONNX Model Not Loading
- Check path exists: `docker exec frigate ls /config/model_cache/`
- Use `model_type: yolo-generic` (not `yolov9`)
- Ensure `input_dtype: float` is set

### Config Validation Errors
Check logs: `docker logs frigate 2>&1 | grep -A10 'Config Validation'`