Beispiel #1
0
def main(aligner_fname, cascade_fname, image_fnames):
    aligner = Aligner(aligner_fname)
    cascade = load_cascade(cascade_fname)
    images = (pvImage(fname) for fname in image_fnames)
    return [
        aligner.align_face(detect_faces(img, cascade)[0], img)
        for img in images
    ]
Beispiel #2
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def main(img_dir,pts_dir,haar_file,num_trains):
	t = Trainer()
	cascade = load_cascade(haar_file)
	sglob = lambda dir: sorted(glob(dir+"/*"))
	paths = izip(sglob(img_dir),sglob(pts_dir))
	# split into training and testing
	for im,pf in islice(paths,num_trains):
		img = pvImage(im)
		pts = read_pointsfile(pf)
		faces = detect_faces(img,cascade)
		if faces:
			t.add_training_image(img,pts,faces[0])
		else:
			print "No face found for %s"%im
	t.train()
	t.export_aligner('aligner.yaml')
Beispiel #3
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def main(aligner_fname, cascade_fname, image_fnames):
    aligner = Aligner(aligner_fname)
    cascade = load_cascade(cascade_fname)
    images = (pvImage(fname) for fname in image_fnames)
    return [aligner.align_face(detect_faces(img, cascade)[0], img) for img in images]