README.md

InsightFace

Input

(Image from https://github.com/deepinsight/insightface/blob/master/sample-images/t1.jpg)

Output

Note

The code of InsightFace is released under the MIT License. There is no limitation for both acadmic and commercial usage.

The training data containing the annotation (and the models trained with these data) are available for non-commercial research purposes only.

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 insightface.py

The sample code reads the face images under the identities directory and uses the file name as the label.

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 insightface.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 insightface.py --video VIDEO_PATH

Reference

• RetinaFace in PyTorch
• InsightFace: 2D and 3D Face Analysis Project

Framework

Pytorch

Model Format

ONNX opset=11

Netron

retinaface_resnet.onnx.prototxt arcface_r100_v1.onnx.prototxt