73 lines
2.5 KiB
Python
Executable File
73 lines
2.5 KiB
Python
Executable File
#!/usr/bin/env python2
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#
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# Copyright 2015-2016 Carnegie Mellon University
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Example usage: ./util/annotate-image.py /data/path_to_your_image.jpg outerEyesAndNose
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import os
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import sys
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fileDir = os.path.dirname(os.path.realpath(__file__))
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sys.path.append(os.path.join(fileDir, ".."))
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import argparse
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import cv2
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from openface.align_dlib import AlignDlib
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modelDir = os.path.join(fileDir, '..', 'models')
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dlibModelDir = os.path.join(modelDir, 'dlib')
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openfaceModelDir = os.path.join(modelDir, 'openface')
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def main(args):
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align = AlignDlib(args.dlibFacePredictor)
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bgrImg = cv2.imread(args.img)
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if bgrImg is None:
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raise Exception("Unable to load image: {}".format(args.img))
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rgbImg = cv2.cvtColor(bgrImg, cv2.COLOR_BGR2RGB)
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bb = align.getLargestFaceBoundingBox(rgbImg)
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if bb is None:
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raise Exception("Unable to find a face: {}".format(args.img))
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landmarks = align.findLandmarks(rgbImg, bb)
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if landmarks is None:
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raise Exception("Unable to find landmarks within image: {}".format(args.img))
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bl = (bb.left(), bb.bottom())
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tr = (bb.right(), bb.top())
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cv2.rectangle(bgrImg, bl, tr, color=(153, 255, 204), thickness=3)
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for landmark in landmarks:
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cv2.circle(bgrImg, center=landmark, radius=3, color=(102, 204, 255), thickness=-1)
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print("Saving image to 'annotated.png'")
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cv2.imwrite("annotated.png", bgrImg)
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument('img', type=str, help="Input image.")
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parser.add_argument('--dlibFacePredictor', type=str, help="Path to dlib's face predictor.",
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default=os.path.join(dlibModelDir, "shape_predictor_68_face_landmarks.dat"))
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parser.add_argument('landmarks', type=str,
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choices=['outerEyesAndNose', 'innerEyesAndBottomLip'],
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help='The landmarks to align to.')
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parser.add_argument('--size', type=int, help="Default image size.",
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default=96)
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args = parser.parse_args()
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main(args)
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