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 15import os.path 16import cv2 17import its.caps 18import its.device 19import its.image 20import its.objects 21 22NAME = os.path.basename(__file__).split('.')[0] 23NUM_TEST_FRAMES = 20 24NUM_FACES = 3 25FD_MODE_OFF = 0 26FD_MODE_SIMPLE = 1 27FD_MODE_FULL = 2 28W, H = 640, 480 29 30 31def main(): 32 """Test face detection.""" 33 with its.device.ItsSession() as cam: 34 props = cam.get_camera_properties() 35 fd_modes = props['android.statistics.info.availableFaceDetectModes'] 36 a = props['android.sensor.info.activeArraySize'] 37 aw, ah = a['right'] - a['left'], a['bottom'] - a['top'] 38 39 if its.caps.read_3a(props): 40 _, _, _, _, _ = cam.do_3a(get_results=True) 41 42 for fd_mode in fd_modes: 43 assert FD_MODE_OFF <= fd_mode <= FD_MODE_FULL 44 req = its.objects.auto_capture_request() 45 req['android.statistics.faceDetectMode'] = fd_mode 46 fmt = {'format': 'yuv', 'width': W, 'height': H} 47 caps = cam.do_capture([req]*NUM_TEST_FRAMES, fmt) 48 for i, cap in enumerate(caps): 49 md = cap['metadata'] 50 assert md['android.statistics.faceDetectMode'] == fd_mode 51 faces = md['android.statistics.faces'] 52 53 # 0 faces should be returned for OFF mode 54 if fd_mode == FD_MODE_OFF: 55 assert not faces 56 continue 57 # Face detection could take several frames to warm up, 58 # but should detect the correct number of faces in last frame 59 if i == NUM_TEST_FRAMES - 1: 60 img = its.image.convert_capture_to_rgb_image(cap, 61 props=props) 62 fnd_faces = len(faces) 63 print 'Found %d face(s), expected %d.' % (fnd_faces, 64 NUM_FACES) 65 # draw boxes around faces 66 for rect in [face['bounds'] for face in faces]: 67 top_left = (int(round(rect['left']*W/aw)), 68 int(round(rect['top']*H/ah))) 69 bot_rght = (int(round(rect['right']*W/aw)), 70 int(round(rect['bottom']*H/ah))) 71 cv2.rectangle(img, top_left, bot_rght, (0, 1, 0), 2) 72 img_name = '%s_fd_mode_%s.jpg' % (NAME, fd_mode) 73 its.image.write_image(img, img_name) 74 assert fnd_faces == NUM_FACES 75 if not faces: 76 continue 77 78 print 'Frame %d face metadata:' % i 79 print ' Faces:', faces 80 print '' 81 82 # Reasonable scores for faces 83 face_scores = [face['score'] for face in faces] 84 for score in face_scores: 85 assert score >= 1 and score <= 100 86 # Face bounds should be within active array 87 face_rectangles = [face['bounds'] for face in faces] 88 for rect in face_rectangles: 89 assert rect['top'] < rect['bottom'] 90 assert rect['left'] < rect['right'] 91 assert 0 <= rect['top'] <= ah 92 assert 0 <= rect['bottom'] <= ah 93 assert 0 <= rect['left'] <= aw 94 assert 0 <= rect['right'] <= aw 95 96if __name__ == '__main__': 97 main() 98