Firearm detection with Frigate NVR on R2000

Introduction

Frigate NVR is an open-source network video recorder designed for AI-first, real-time video analytics at the edge. Deployed on a reComputer AI box with Hailo, the system locally ingests multiple camera streams, runs a quantitative object detection model, and emits MQTT events within milliseconds, eliminating cloud latency and bandwidth costs.

For this deployment, we expanded Frigate's existing model library and added a custom yolov11s model specifically fine-tuned for pistol and rifle recognition. When a firearm is detected, Frigate's rules engine immediately triggers an alert, giving security teams precious seconds to lock down the area and coordinate a response before the threat escalates.

Prerequisites

Hardware Requirements

reComputer AI Industrial R2000	reComputer AI R2000

Get One Now 🖱️	Get One Now 🖱️

Configuring Frigate

Modifying PCIe Settings

Opening config.txt:

sudo nano /boot/firmware/config.txt

Add the following to config.txt:

dtparam=pciex1_gen=3
dtoverlay=pciex1-compat-pi5,no-mip

Then save the file using Ctrl+x and restart the AI box.

Install Docker and hailo-all

sudo apt update
sudo apt install hailo-all
curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh
sudo usermod -aG docker $USER
sudo apt install docker-compose-plugin

Creating a yml file

Create the frigate.yml file so that Docker Compose can run Frigate.

cd ~
sudo nano frigate.yml

Here is an example of frigate.yml:

services:
  frigate-hailo:
    container_name: frigate-hailo
    privileged: true
    restart: unless-stopped
    image: ghcr.io/blakeblackshear/frigate:0.16.0-beta3-standard-arm64
    shm_size: "512mb" # calculate on your own
    stop_grace_period: 30s # allow enough time to shut down the various services
    devices:
      - /dev/hailo0:/dev/hailo0
      - /dev/video19:/dev/video19  # USB camera (physical device)
      - /dev/video20:/dev/video20  # USB camera backup device
    volumes:
      - /etc/localtime:/etc/localtime:ro
      - ./config/:/config
      - ./data/db/:/data/db
      - ./data/storage:/media/frigate
      - ./media:/media/frigate  # Mapping local media files to the container
      - type: tmpfs
        target: /tmp/cache
        tmpfs:
          size: 1g
    ports:
      - 5000:5000
    environment:
      - FRIGATE_RTSP_PASSWORD=password
      - LIBVA_DRIVER_NAME=i965
    group_add:
      - "44"  # video group

Download the case video:

mkdir media && cd media
wget -c \
"https://files.seeedstudio.com/wiki/reComputer/Application/Firearm_Detection_With_Frigate_NVR_on_R2130/model_cache/yolov11s.hef"

Download the YOLO model and create config.yml:

cd .. && mkdir config && cd config && mkdir model_cache
cd model_cache && wget https://hailo-model-zoo.s3.eu-west-2.amazonaws.com/ModelZoo/Compiled/v2.14.0/hailo8/yolov8n.hef
cd .. && nano config.yml

The following is an example config.yml:

database:
  path: /data/db/frigate.db

go2rtc:
  streams:
    # USB camera streaming
    usb_camera:
      - "ffmpeg:/dev/video0#input=-f v4l2 -input_format mjpeg -video_size 640x480 -framerate 15"
    
    # RTSP stream configuration

    hikvision_main:
      - "rtsp://admin:[email protected]:554/h264/ch1/main/av_stream"
    
    # Video file streaming - close.mp4
    video_files_close:
      - "ffmpeg:/media/frigate/close.mp4"
    
    # Video file streaming - close2.mp4
    video_files_close2:
      - "ffmpeg:/media/frigate/close2.mp4"
    
    # Video file streaming - y4.mp4
    video_files_y4:
      - "ffmpeg:/media/frigate/y4.mp4"
    
    # Video file streaming - y5.mp4
    video_files_y5:
      - "ffmpeg:/media/frigate/y5.mp4"

cameras:
  # USB camera
  usb_camera:
    ffmpeg:
      inputs:
        - path: /dev/video0
          input_args: -f v4l2 -input_format mjpeg -video_size 640x480 -framerate 15
          roles:
            - record
            - detect
    detect:
      width: 640
      height: 480
      fps: 3
    record:
      enabled: true
      retain:
        days: 7
        mode: motion
    objects:
      track:
        - gun
      filters:
        gun:
          min_area: 10
          max_area: 100000
          threshold: 0.25

  # Video file camera - close.mp4
  video_files_close:
    ffmpeg:
      inputs:
        - path: /media/frigate/close.mp4
          input_args: -stream_loop -1 -re
          roles:
            - detect
            - record
    detect:
      width: 1280
      height: 720
      fps: 2
    record:
      enabled: false
      retain:
        days: 3
        mode: all
    objects:
      track:
        - gun
      filters:
        gun:
          min_area: 20
          max_area: 500000
          threshold: 0.25

  # Video file camera - close2.mp4
  video_files_close2:
    ffmpeg:
      inputs:
        - path: /media/frigate/close2.mp4
          input_args: -stream_loop -1 -re
          roles:
            - detect
            - record
    detect:
      width: 1280
      height: 720
      fps: 2
    record:
      enabled: false
      retain:
        days: 3
        mode: all
    objects:
      track:
        - gun
      filters:
        gun:
          min_area: 20
          max_area: 500000
          threshold: 0.25

  # Video file camera - y4.mp4
  video_files_y4:
    ffmpeg:
      inputs:
        - path: /media/frigate/y4.mp4
          input_args: -stream_loop -1 -re
          roles:
            - detect
            - record
    detect:
      width: 1280
      height: 720
      fps: 3
    record:
      enabled: true
      retain:
        days: 3
        mode: all
    objects:
      track:
        - gun
      filters:
        gun:
          min_area: 10
          max_area: 500000
          threshold: 0.3

  # Video file camera - y5.mp4
  video_files_y5:
    ffmpeg:
      inputs:
        - path: /media/frigate/y5.mp4
          input_args: -stream_loop -1 -re
          roles:
            - detect
            - record
    detect:
      width: 1280
      height: 720
      fps: 3
    record:
      enabled: true
      retain:
        days: 3
        mode: all
    objects:
      track:
        - gun
      filters:
        gun:
          min_area: 10
          max_area: 500000
          threshold: 0.25

  # RTSP IP camera - hikvision
  hikvision_main:
    ffmpeg:
      inputs:
        - path: rtsp://admin:[email protected]:554/h264/ch1/main/av_stream
          input_args: -rtsp_transport tcp -avoid_negative_ts make_zero
          roles:
            - detect
            - record
    detect:
      width: 1920
      height: 1080
      fps: 3
    record:
      enabled: true
      retain:
        days: 7
        mode: motion
    objects:
      track:
        - gun
      filters:
        gun:
          min_area: 20
          max_area: 500000
          threshold: 0.25

mqtt:
  enabled: false

objects:
  track:
    - gun
  filters:
    gun:
      min_area: 10
      max_area: 500000
      threshold: 0.25

detectors:
  hailo8l:
    type: hailo8l
    device: PCIe

model:
  width: 640
  height: 640
  input_tensor: nhwc
  input_pixel_format: rgb
  input_dtype: int
  model_type: yolo-generic
  path: /config/model_cache/yolov11s.hef
  labelmap:
    0: person
    1: gun

detect:
  enabled: true

snapshots:
  enabled: true
  clean_copy: true
  timestamp: true
  bounding_box: true
  crop: false
  retain:
    default: 14
  quality: 95

record:
  enabled: true
  retain:
    days: 30
    mode: all

ui:
  timezone: Asia/Shanghai

auth:
  enabled: false

live:
  height: 720
  quality: 8

birdseye:
  enabled: true
  width: 1280
  height: 720
  quality: 8
  mode: objects
version: 0.16-0
semantic_search:
  enabled: false
  reindex: false
  model_size: small
face_recognition:
  enabled: false
lpr:
  enabled: false

Run the project

Pull and run the project:

cd ~
sudo docker pull mjqx2023/frigate_seeed
docker compose -f frigate.yml up -d

Then open localhost:5000 in the web browser of the AI box:

Select one of the videos to start debugging, select the display box, and the results will be automatically displayed:

Switch tabs to view past test results:

Result

When it sees someone holding a gun, the model will identify it and select it. Switch to debug mode, select the display box, and the results will be automatically displayed; switch tabs to view past detection results.

pir

Other configurations

Configuration of other video sources	Frame rate configuration
Frigate supports RTSP, video streaming, and USB cameras. Once the configuration file is configured, it will take effect after reboot.	The configuration file can configure the detection frame rate of each camera, which will take effect after restart.
You can access configuration options in Settings, such as changing the RTSP path to connect to an RTSP camera. Once you've made changes, click Save & Restart in the upper-right corner for the changes to take effect.

Tech Support & Product Discussion

Thank you for choosing our products! We are here to provide you with different support to ensure that your experience with our products is as smooth as possible. We offer several communication channels to cater to different preferences and needs.

Introduction​

Prerequisites​

Hardware Requirements​

Configuring Frigate​

Modifying PCIe Settings​

Install Docker and hailo-all​

Creating a yml file​

Run the project​

Result​

Other configurations​

Tech Support & Product Discussion​