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 props = cam.override_with_hidden_physical_camera_props(props) 36 its.caps.skip_unless(its.caps.face_detect(props)) 37 mono_camera = its.caps.mono_camera(props) 38 fd_modes = props['android.statistics.info.availableFaceDetectModes'] 39 a = props['android.sensor.info.activeArraySize'] 40 aw, ah = a['right'] - a['left'], a['bottom'] - a['top'] 41 42 if its.caps.read_3a(props): 43 _, _, _, _, _ = cam.do_3a(get_results=True, 44 mono_camera=mono_camera) 45 46 for fd_mode in fd_modes: 47 assert FD_MODE_OFF <= fd_mode <= FD_MODE_FULL 48 req = its.objects.auto_capture_request() 49 req['android.statistics.faceDetectMode'] = fd_mode 50 fmt = {'format': 'yuv', 'width': W, 'height': H} 51 caps = cam.do_capture([req]*NUM_TEST_FRAMES, fmt) 52 for i, cap in enumerate(caps): 53 md = cap['metadata'] 54 assert md['android.statistics.faceDetectMode'] == fd_mode 55 faces = md['android.statistics.faces'] 56 57 # 0 faces should be returned for OFF mode 58 if fd_mode == FD_MODE_OFF: 59 assert not faces 60 continue 61 # Face detection could take several frames to warm up, 62 # but should detect the correct number of faces in last frame 63 if i == NUM_TEST_FRAMES - 1: 64 img = its.image.convert_capture_to_rgb_image(cap, 65 props=props) 66 fnd_faces = len(faces) 67 print 'Found %d face(s), expected %d.' % (fnd_faces, 68 NUM_FACES) 69 # draw boxes around faces 70 for rect in [face['bounds'] for face in faces]: 71 top_left = (int(round(rect['left']*W/aw)), 72 int(round(rect['top']*H/ah))) 73 bot_rght = (int(round(rect['right']*W/aw)), 74 int(round(rect['bottom']*H/ah))) 75 cv2.rectangle(img, top_left, bot_rght, (0, 1, 0), 2) 76 img_name = '%s_fd_mode_%s.jpg' % (NAME, fd_mode) 77 its.image.write_image(img, img_name) 78 assert fnd_faces == NUM_FACES 79 if not faces: 80 continue 81 82 print 'Frame %d face metadata:' % i 83 print ' Faces:', faces 84 print '' 85 86 # Reasonable scores for faces 87 face_scores = [face['score'] for face in faces] 88 for score in face_scores: 89 assert score >= 1 and score <= 100 90 # Face bounds should be within active array 91 face_rectangles = [face['bounds'] for face in faces] 92 for rect in face_rectangles: 93 assert rect['top'] < rect['bottom'] 94 assert rect['left'] < rect['right'] 95 assert 0 <= rect['top'] <= ah 96 assert 0 <= rect['bottom'] <= ah 97 assert 0 <= rect['left'] <= aw 98 assert 0 <= rect['right'] <= aw 99 100 if __name__ == '__main__': 101 main() 102
