# Copyright 2014 The Android Open Source Project # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import its.image import its.caps import its.device import its.objects import os.path def main(): """Test face detection. """ NAME = os.path.basename(__file__).split(".")[0] NUM_TEST_FRAMES = 20 FD_MODE_OFF = 0 FD_MODE_SIMPLE = 1 FD_MODE_FULL = 2 W, H = 640, 480 with its.device.ItsSession() as cam: props = cam.get_camera_properties() its.caps.skip_unless(its.caps.face_detect(props)) mono_camera = its.caps.mono_camera(props) fd_modes = props['android.statistics.info.availableFaceDetectModes'] a = props['android.sensor.info.activeArraySize'] aw, ah = a['right'] - a['left'], a['bottom'] - a['top'] if its.caps.read_3a(props): gain, exp, _, _, focus = cam.do_3a(get_results=True, mono_camera=mono_camera) print 'iso = %d' % gain print 'exp = %.2fms' % (exp*1.0E-6) if focus == 0.0: print 'fd = infinity' else: print 'fd = %.2fcm' % (1.0E2/focus) for fd_mode in fd_modes: assert(FD_MODE_OFF <= fd_mode <= FD_MODE_FULL) req = its.objects.auto_capture_request() req['android.statistics.faceDetectMode'] = fd_mode fmt = {"format":"yuv", "width":W, "height":H} caps = cam.do_capture([req]*NUM_TEST_FRAMES, fmt) for i,cap in enumerate(caps): md = cap['metadata'] assert(md['android.statistics.faceDetectMode'] == fd_mode) faces = md['android.statistics.faces'] # 0 faces should be returned for OFF mode if fd_mode == FD_MODE_OFF: assert(len(faces) == 0) continue # Face detection could take several frames to warm up, # but it should detect at least one face in last frame if i == NUM_TEST_FRAMES - 1: img = its.image.convert_capture_to_rgb_image(cap, props=props) img = its.image.rotate_img_per_argv(img) img_name = "%s_fd_mode_%s.jpg" % (NAME, fd_mode) its.image.write_image(img, img_name) if len(faces) == 0: print "Error: no face detected in mode", fd_mode assert(0) if len(faces) == 0: continue print "Frame %d face metadata:" % i print " Faces:", faces print "" face_scores = [face['score'] for face in faces] face_rectangles = [face['bounds'] for face in faces] for score in face_scores: assert(score >= 1 and score <= 100) # Face bounds should be within active array for rect in face_rectangles: assert(rect['top'] < rect['bottom']) assert(rect['left'] < rect['right']) assert(0 <= rect['top'] <= ah) assert(0 <= rect['bottom'] <= ah) assert(0 <= rect['left'] <= aw) assert(0 <= rect['right'] <= aw) # Face landmarks are reported if and only if fd_mode is FULL # Face ID should be -1 for SIMPLE and unique for FULL if fd_mode == FD_MODE_SIMPLE: for face in faces: assert('leftEye' not in face) assert('rightEye' not in face) assert('mouth' not in face) assert(face['id'] == -1) elif fd_mode == FD_MODE_FULL: face_ids = [face['id'] for face in faces] assert(len(face_ids) == len(set(face_ids))) # Face landmarks should be within face bounds for face in faces: left_eye = face['leftEye'] right_eye = face['rightEye'] mouth = face['mouth'] l, r = face['bounds']['left'], face['bounds']['right'] t, b = face['bounds']['top'], face['bounds']['bottom'] assert(l <= left_eye['x'] <= r) assert(t <= left_eye['y'] <= b) assert(l <= right_eye['x'] <= r) assert(t <= right_eye['y'] <= b) assert(l <= mouth['x'] <= r) assert(t <= mouth['y'] <= b) if __name__ == '__main__': main()