mlsd

M-LSD: Towards Light-weight and Real-time Line Segment Detection

Input

(Image from https://pixabay.com/ja/photos/%e6%97%85%e8%a1%8c%e3%81%99%e3%82%8b-%e3%83%9b%e3%83%86%e3%83%ab%e3%81%ae%e9%83%a8%e5%b1%8b-%e3%83%9b%e3%83%86%e3%83%ab-1677347/)

Input shape: (1, 512, 512, 4)

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 mlsd.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 mlsd.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 mlsd.py --video VIDEO_PATH

Reference

M-LSD: Towards Light-weight and Real-time Line Segment Detection

Framework

Tensorflow

Model Format

ONNX opset = 11

Netron

M-LSD_512_large.opt.onnx.prototxt