dfm

DFM: A Performance Baseline for Deep Feature Matching

Input

• img_A

• img_B

(Image from https://github.com/ufukefe/DFM/tree/main/python/data)

Output

• Matches result

• Plot keypoints for img_A

• Plot keypoints for img_B

Caution

The software can only be used for personal, research, academic and non-commercial purposes.

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 dfm.py

If you want to specify the input image, put the image path (as img_B) after the --input option, and the second image path (as img_A) after the --input2 option.
You can use --savepath option to change the name of the output file to save.

$ python3 dfm.py --input IMAGE_B --input2 IMAGE_A --savepath SAVE_IMAGE_PATH

Use the --draw-keypoints option to save plot results of keypoints.

$ python3 dfm.py --draw-keypoints

Reference

• DFM

Framework

Pytorch

Model Format

ONNX opset=11

Netron

VGG19.onnx.prototxt