yolov9

YOLOv9

Input

(Image from https://pixabay.com/ja/photos/%E3%83%AD%E3%83%B3%E3%83%89%E3%83%B3%E5%B8%82-%E9%8A%80%E8%A1%8C-%E3%83%AD%E3%83%B3%E3%83%89%E3%83%B3-4481399/)

Ailia input shape : (1, 3, h, w) Range : [0.0, 1.0] Color : RGB

Output

Usage

Automatically downloads the onnx and prototxt files on the first run. It is necessary to be connected to the Internet while downloading.

For the sample image,

$ python3 yolov9.py

If you want to specify the input image, put the image path after the --input option. You can use --savepath option to change the name of the output file to save.

$ python3 yolov9.py --input IMAGE_PATH --savepath SAVE_IMAGE_PATH

By adding the --video option, you can input the video. If you pass 0 as an argument to VIDEO_PATH, you can use the webcam input instead of the video file.

$ python3 yolov9.py --video VIDEO_PATH

By adding the --model_type option, you can specify model type which is selected from "v9c", "v8e" (default is "v8e").

$ python3 yolov9.py --model_type v9c

You can use --detection_size option to change the detection resolution.

$ python3 yolov9.py --detection_size 1280

Reference

• YOLOv9

Framework

Pytorch

Model Format

ONNX opset=12

Netron

• yolov9c.onnx.prototxt
• yolov9e.onnx.prototxt