1 # Copyright 2014 The Android Open Source Project 2 # 3 # Licensed under the Apache License, Version 2.0 (the "License"); 4 # you may not use this file except in compliance with the License. 5 # You may obtain a copy of the License at 6 # 7 # http://www.apache.org/licenses/LICENSE-2.0 8 # 9 # Unless required by applicable law or agreed to in writing, software 10 # distributed under the License is distributed on an "AS IS" BASIS, 11 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 # See the License for the specific language governing permissions and 13 # limitations under the License. 14 15 import os.path 16 import cv2 17 import its.caps 18 import its.device 19 import its.image 20 import its.objects 21 22 NAME = os.path.basename(__file__).split('.')[0] 23 NUM_TEST_FRAMES = 20 24 NUM_FACES = 3 25 FD_MODE_OFF = 0 26 FD_MODE_SIMPLE = 1 27 FD_MODE_FULL = 2 28 W, H = 640, 480 29 30 31 def main(): 32 """Test face detection.""" 33 with its.device.ItsSession() as cam: 34 props = cam.get_camera_properties() 35 its.caps.skip_unless(its.caps.face_detect(props)) 36 mono_camera = its.caps.mono_camera(props) 37 fd_modes = props['android.statistics.info.availableFaceDetectModes'] 38 a = props['android.sensor.info.activeArraySize'] 39 aw, ah = a['right'] - a['left'], a['bottom'] - a['top'] 40 41 if its.caps.read_3a(props): 42 _, _, _, _, _ = cam.do_3a(get_results=True, 43 mono_camera=mono_camera) 44 45 for fd_mode in fd_modes: 46 assert FD_MODE_OFF <= fd_mode <= FD_MODE_FULL 47 req = its.objects.auto_capture_request() 48 req['android.statistics.faceDetectMode'] = fd_mode 49 fmt = {'format': 'yuv', 'width': W, 'height': H} 50 caps = cam.do_capture([req]*NUM_TEST_FRAMES, fmt) 51 for i, cap in enumerate(caps): 52 md = cap['metadata'] 53 assert md['android.statistics.faceDetectMode'] == fd_mode 54 faces = md['android.statistics.faces'] 55 56 # 0 faces should be returned for OFF mode 57 if fd_mode == FD_MODE_OFF: 58 assert not faces 59 continue 60 # Face detection could take several frames to warm up, 61 # but should detect the correct number of faces in last frame 62 if i == NUM_TEST_FRAMES - 1: 63 img = its.image.convert_capture_to_rgb_image(cap, 64 props=props) 65 fnd_faces = len(faces) 66 print 'Found %d face(s), expected %d.' % (fnd_faces, 67 NUM_FACES) 68 # draw boxes around faces 69 for rect in [face['bounds'] for face in faces]: 70 top_left = (int(round(rect['left']*W/aw)), 71 int(round(rect['top']*H/ah))) 72 bot_rght = (int(round(rect['right']*W/aw)), 73 int(round(rect['bottom']*H/ah))) 74 cv2.rectangle(img, top_left, bot_rght, (0, 1, 0), 2) 75 img_name = '%s_fd_mode_%s.jpg' % (NAME, fd_mode) 76 its.image.write_image(img, img_name) 77 assert fnd_faces == NUM_FACES 78 if not faces: 79 continue 80 81 print 'Frame %d face metadata:' % i 82 print ' Faces:', faces 83 print '' 84 85 # Reasonable scores for faces 86 face_scores = [face['score'] for face in faces] 87 for score in face_scores: 88 assert score >= 1 and score <= 100 89 # Face bounds should be within active array 90 face_rectangles = [face['bounds'] for face in faces] 91 for rect in face_rectangles: 92 assert rect['top'] < rect['bottom'] 93 assert rect['left'] < rect['right'] 94 assert 0 <= rect['top'] <= ah 95 assert 0 <= rect['bottom'] <= ah 96 assert 0 <= rect['left'] <= aw 97 assert 0 <= rect['right'] <= aw 98 99 if __name__ == '__main__': 100 main() 101
