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97 lines
4.0 KiB
97 lines
4.0 KiB
# Copyright 2014 The Android Open Source Project |
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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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import os.path |
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import cv2 |
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import its.caps |
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import its.device |
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import its.image |
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import its.objects |
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NAME = os.path.basename(__file__).split('.')[0] |
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NUM_TEST_FRAMES = 20 |
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NUM_FACES = 3 |
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FD_MODE_OFF = 0 |
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FD_MODE_SIMPLE = 1 |
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FD_MODE_FULL = 2 |
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W, H = 640, 480 |
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def main(): |
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"""Test face detection.""" |
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with its.device.ItsSession() as cam: |
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props = cam.get_camera_properties() |
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fd_modes = props['android.statistics.info.availableFaceDetectModes'] |
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a = props['android.sensor.info.activeArraySize'] |
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aw, ah = a['right'] - a['left'], a['bottom'] - a['top'] |
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if its.caps.read_3a(props): |
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_, _, _, _, _ = cam.do_3a(get_results=True) |
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for fd_mode in fd_modes: |
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assert FD_MODE_OFF <= fd_mode <= FD_MODE_FULL |
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req = its.objects.auto_capture_request() |
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req['android.statistics.faceDetectMode'] = fd_mode |
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fmt = {'format': 'yuv', 'width': W, 'height': H} |
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caps = cam.do_capture([req]*NUM_TEST_FRAMES, fmt) |
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for i, cap in enumerate(caps): |
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md = cap['metadata'] |
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assert md['android.statistics.faceDetectMode'] == fd_mode |
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faces = md['android.statistics.faces'] |
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# 0 faces should be returned for OFF mode |
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if fd_mode == FD_MODE_OFF: |
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assert not faces |
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continue |
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# Face detection could take several frames to warm up, |
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# but should detect the correct number of faces in last frame |
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if i == NUM_TEST_FRAMES - 1: |
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img = its.image.convert_capture_to_rgb_image(cap, |
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props=props) |
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fnd_faces = len(faces) |
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print 'Found %d face(s), expected %d.' % (fnd_faces, |
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NUM_FACES) |
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# draw boxes around faces |
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for rect in [face['bounds'] for face in faces]: |
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top_left = (int(round(rect['left']*W/aw)), |
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int(round(rect['top']*H/ah))) |
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bot_rght = (int(round(rect['right']*W/aw)), |
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int(round(rect['bottom']*H/ah))) |
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cv2.rectangle(img, top_left, bot_rght, (0, 1, 0), 2) |
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img_name = '%s_fd_mode_%s.jpg' % (NAME, fd_mode) |
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its.image.write_image(img, img_name) |
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assert fnd_faces == NUM_FACES |
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if not faces: |
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continue |
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print 'Frame %d face metadata:' % i |
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print ' Faces:', faces |
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print '' |
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# Reasonable scores for faces |
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face_scores = [face['score'] for face in faces] |
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for score in face_scores: |
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assert score >= 1 and score <= 100 |
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# Face bounds should be within active array |
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face_rectangles = [face['bounds'] for face in faces] |
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for rect in face_rectangles: |
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assert rect['top'] < rect['bottom'] |
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assert rect['left'] < rect['right'] |
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assert 0 <= rect['top'] <= ah |
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assert 0 <= rect['bottom'] <= ah |
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assert 0 <= rect['left'] <= aw |
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assert 0 <= rect['right'] <= aw |
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if __name__ == '__main__': |
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main()
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