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tsutof / tiny_yolov2_onnx_cam

Tiny YOLO v2 Inference Application with NVIDIA TensorRT
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tiny_yolov2_onnx_cam

Tiny YOLO v2 Inference Application with NVIDIA TensorRT

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Table of Contents

What Does This Application Do?

This application downloads the tiny YOLO v2 model from Open Neural Network eXchange (ONNX) Model Zoo and converts it to NVIDIA TensorRT plan, then starts the object detection for camera captured image.

Prerequisites

Installation

  1. Install dependent libraries.

    sudo apt update
    sudo apt install python3-pip protobuf-compiler libprotoc-dev libjpeg-dev cmake libcanberra-gtk-module libcanberra-gtk3-module

  2. Some Python modules have restrictions on the installation order.

    pip3 install --user --upgrade setuptools wheel Cython
    pip3 install --user numpy protobuf==3.16.0
    pip3 install --user --no-deps "onnx>=1.6.0,<=1.11.0"

  3. Install this application and the dependent modules.

    git clone https://github.com/tsutof/tiny_yolov2_onnx_cam
    cd tiny_yolov2_onnx_cam
    export PATH=$PATH:/usr/local/cuda/bin
    python3 -m pip install --user -r requirements.txt

Usage

First, clock up your Jetson. Only the nvpmodel is not enough, the jetson_clocks command is also needed. Without the jetson_clocks, "select timeout" error happens at the frame capture.

sudo nvpmodel -m 0
sudo jetson_clocks

The following command starts this application. Press ESC key to exit from this application.

python3 tiny_yolov2_onnx_cam.py [-h] [--camera CAMERA_NUM] [--csi]
                               [--width WIDTH] [--height HEIGHT]
                               [--objth OBJ_THRESH] [--nmsth NMS_THRESH]

optional arguments:
  -h, --help            show this help message and exit
  --camera CAMERA_NUM, -c CAMERA_NUM
                        Camera number
  --csi                 Use CSI camera
  --width WIDTH         Capture width
  --height HEIGHT       Capture height
  --objth OBJ_THRESH    Threshold of object confidence score (between 0 and 1)
  --nmsth NMS_THRESH    Threshold of NMS algorithm (between 0 and 1)

For Raspberry Pi camera v2, set --csi option.

python3 tiny_yolov2_onnx_cam.py --csi --camera 0

For USB Web camera, if you camera is detected as /dev/video1, use 1 as the camera number.

python3 tiny_yolov2_onnx_cam.py --camera 1

If your USB Web camera does not support this application's default capture resolution, please change it with the --widht and --height command-line options.

To know the supported resolutions by your camera, the gst-device-monitor-1.0 command is very useful.

Docker Support

Please refer to this page

MQTT Support

Please refer to this page

Microservices Demo

Please refer to this page

Third Party License

This program is using open source software which is licensed with the following conditions:

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