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116 lines
4.9 KiB
116 lines
4.9 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 its.image |
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import its.caps |
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import its.device |
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import its.objects |
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import os.path |
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def main(): |
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"""Test face detection. |
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""" |
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NAME = os.path.basename(__file__).split(".")[0] |
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NUM_TEST_FRAMES = 20 |
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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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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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gain, exp, _, _, focus = cam.do_3a(get_results=True) |
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print 'iso = %d' % gain |
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print 'exp = %.2fms' % (exp*1.0E-6) |
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if focus == 0.0: |
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print 'fd = infinity' |
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else: |
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print 'fd = %.2fcm' % (1.0E2/focus) |
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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(len(faces) == 0) |
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continue |
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# Face detection could take several frames to warm up, |
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# but it should detect at least one face 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, props=props) |
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img = its.image.flip_mirror_img_per_argv(img) |
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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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if len(faces) == 0: |
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print "Error: no face detected in mode", fd_mode |
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assert(0) |
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if len(faces) == 0: |
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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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face_scores = [face['score'] for face in faces] |
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face_rectangles = [face['bounds'] 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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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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# Face landmarks are reported if and only if fd_mode is FULL |
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# Face ID should be -1 for SIMPLE and unique for FULL |
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if fd_mode == FD_MODE_SIMPLE: |
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for face in faces: |
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assert('leftEye' not in face) |
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assert('rightEye' not in face) |
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assert('mouth' not in face) |
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assert(face['id'] == -1) |
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elif fd_mode == FD_MODE_FULL: |
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face_ids = [face['id'] for face in faces] |
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assert(len(face_ids) == len(set(face_ids))) |
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# Face landmarks should be within face bounds |
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for face in faces: |
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left_eye = face['leftEye'] |
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right_eye = face['rightEye'] |
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mouth = face['mouth'] |
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l, r = face['bounds']['left'], face['bounds']['right'] |
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t, b = face['bounds']['top'], face['bounds']['bottom'] |
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assert(l <= left_eye['x'] <= r) |
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assert(t <= left_eye['y'] <= b) |
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assert(l <= right_eye['x'] <= r) |
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assert(t <= right_eye['y'] <= b) |
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assert(l <= mouth['x'] <= r) |
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assert(t <= mouth['y'] <= b) |
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if __name__ == '__main__': |
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main() |
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