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https://github.com/deepinsight/insightface.git
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tiny
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@@ -101,7 +101,8 @@ def main(args):
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pnet, rnet, onet = detect_face.create_mtcnn(sess, None)
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minsize = 100 # minimum size of face
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threshold = [ 0.6, 0.7, 0.7 ] # three steps's threshold
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#threshold = [ 0.6, 0.7, 0.7 ] # three steps's threshold
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threshold = [ 0.6, 0.6, 0.3 ] # three steps's threshold
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factor = 0.709 # scale factor
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print(minsize)
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@@ -126,8 +127,9 @@ def main(args):
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v = datamap.get(person, None)
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if v is None:
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continue
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if not img_id in v[1]:
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continue
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#TODO
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#if not img_id in v[1]:
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# continue
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labelid = v[0]
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img_str = base64.b64decode(vec[-1])
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nparr = np.fromstring(img_str, np.uint8)
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@@ -148,7 +150,8 @@ def main(args):
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if fimage.bbox is not None:
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_bb = fimage.bbox
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_minsize = min( [_bb[2]-_bb[0], _bb[3]-_bb[1], img.shape[0]//2, img.shape[1]//2] )
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else:
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_minsize = min(img.shape[0]//5, img.shape[1]//5)
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bounding_boxes, points = detect_face.detect_face(img, _minsize, pnet, rnet, onet, threshold, factor)
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bindex = -1
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nrof_faces = bounding_boxes.shape[0]
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