SCRFD is an efficient high accuracy face detection approach

Inference code of SCRFD using ONNX Runtime

Installation

conda create -n ONNX python=3.8
conda activate ONNX
conda install pytorch torchvision torchaudio pytorch-cuda=11.6 -c pytorch -c nvidia
pip install onnxruntime-gpu==1.14.0
pip install opencv-python==4.5.5.64

Inference

$ python main.py

Model Performances

Name	Easy	Medium	Hard	FLOPs	Params(M)	Infer(ms)
SCRFD_500M	90.57	88.12	68.51	500M	0.57	3.6
SCRFD_1G	92.38	90.57	74.80	1G	0.64	4.1
SCRFD_2.5G	93.78	92.16	77.87	2.5G	0.67	4.2
SCRFD_10G	95.16	93.87	83.05	10G	3.86	4.9
SCRFD_34G	96.06	94.92	85.29	34G	9.80	11.7
SCRFD_500M_KPS	90.97	88.44	69.49	500M	0.57	3.6
SCRFD_2.5G_KPS	93.80	92.02	77.13	2.5G	0.82	4.3
SCRFD_10G_KPS	95.40	94.01	82.80	10G	4.23	5.0

Note

• This repo supports only inference, see reference for more details

Reference

• https://github.com/deepinsight/insightface/tree/master/detection/scrfd