A fast and simplified implementation of biubug6/Pytorch_Retinaface inference module
Project description
Tiny RetinaFace
Tiny RetinaFace is a fast and simplified implementation of biubug6/Pytorch_Retinaface inference module
Installation
pip install tiny-retinaface
Usage
from retinaface import read_image, detect_faces
# Read image as RGB ndarray
image = read_image("images/test.jpg")
# Detect faces as list of Face objects
faces = detect_faces(image)
Face object
Face(
score=0.9997380375862122,
x=142,
y=322,
width=60,
height=72,
landmarks=[
Point(x=160, y=348),
Point(x=187, y=345),
Point(x=177, y=362),
Point(x=165, y=376),
Point(x=188, y=374)
]
)
Tiny RetinaFace Results on World Largest Selfie
from retinaface import read_image_url, detect_faces, draw_faces
url = "https://github.com/yakhyo/retinaface-pytorch/blob/main/assets/large_selfi.jpg?raw=true"
image = read_image_url(url)
faces = detect_faces(image, score_threshold=0.1, nms_threshold=0.1)
draw_faces(image, faces, filename="images/results.jpg")
Acknowledgements
- Original RetinaFace implementation: deepinsight/insightface
- Pytorch RetinaFace implementation: biubug6/Pytorch_Retinaface
- RetinaFace pretrained onnx weights: yakhyo/retinaface-pytorch
References
@inproceedings{Deng2020CVPR,
title = {RetinaFace: Single-Shot Multi-Level Face Localisation in the Wild},
author = {Deng, Jiankang and Guo, Jia and Ververas, Evangelos and Kotsia, Irene and Zafeiriou, Stefanos},
booktitle = {CVPR},
year = {2020}
}
License
This project is licensed under the MIT License. See the LICENSE file for details.
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