retinaface

RetinaFace

Input

(Image from https://github.com/dlunion/DBFace/blob/master/datas/selfie.jpg)

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, the more powerful resnet50 is used as backbone by default, you can also choose mobilenet as backbone for a real-time inference.

python3 retinaface.py --arch resnet50
python3 retinaface.py --arch mobile0.25

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.
You can alse use --rescale option to scale down the input image size to prevent memory overflow. By default the original image size is used as input.

$ python3 retinaface.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 retinaface.py --video VIDEO_PATH

Reference

RetinaFace: Single-stage Dense Face Localisation in the Wild.

Framework

PyTorch

Model Format

ONNX opset = 11

Netron

retinaface_resnet50.onnx.prototxt
retinaface_mobile0.25.onnx.prototxt