Yolov5 Face Detection

Description

The project is a wrap over yolov5-face repo. Made simple portable interface for model import and inference. Model detects faces on images and returns bounding boxes and coordinates of 5 facial keypoints, which can be used for face alignment.

Installation

pip install yolov5facedetector

Usage example

from yolov5facedetector.face_detector import YoloDetector
import numpy as np
from PIL import Image

model = YoloDetector(target_size=720,gpu=0,min_face=90)
rgb_array_img = np.array(Image.open('test_image.jpg')) # Will make RGB Numpy Array Image
bboxes, confs, points = model.predict(rgb_array_img)

You can also pass several images packed in a list to get multi-image predictions.

bboxes, confs, points = model.predict([image1,image2])

Other pretrained models

Currently Support YOLOv5 type n,m & l type of model from yolov5-face repo. Default model type is 'yolov5n' but you can change to m & l (larger model version) which is auto download when first time used

Example below:

model = YoloFace(yolo_type='yolov5l',target_size=720) # Will download weight file automatically
bboxes, confs, points = model.predict(rgb_array_img)

Result example

Citiation

Thanks to deepcam-cn for pretrained models and Rebrikov Artem for providing wrapper function of YOLOv5Face.