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import seetaface

import cv2

root = 'example1.jpg'

fd = seetaface.FaceDetector('/mnt/new/s1/Alec/SeetaFaceDetector2.0.ats')

pd = seetaface.PointDetector('/mnt/new/s1/Alec/SeetaPointDetector2.0.pts5.ats')

im = cv2.imread(root)

image = seetaface.SeetaImage(im)

# or you can pass image path to SeetaImage

# image = seetaface.SeetaImage(root)

rects = fd.detect(image)

for rect in rects:

cv2.rectangle(im, (rect.x, rect.y), (rect.x + rect.width, rect.y + rect.height), (0,0,255), 2)

points = pd.detect(image, rect)

for p in points:

cv2.circle(im, (int(p.x), int(p.y)), 2, (0,0,255), -1)

cv2.imwrite('example1_result.jpg', im)

cv2.imshow('win', im)

cv2.waitKey(0)