# 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. """Verifies faces are detected and landmarks in bounding boxes.""" import logging import os.path from mobly import test_runner import its_base_test import camera_properties_utils import capture_request_utils import image_processing_utils import its_session_utils NAME = os.path.splitext(os.path.basename(__file__))[0] NUM_TEST_FRAMES = 20 FD_MODE_OFF = 0 FD_MODE_SIMPLE = 1 FD_MODE_FULL = 2 W, H = 640, 480 def check_face_bounding_box(rect, aa_w, aa_h): """Check that face bounding box is within the active array area.""" rect_t = rect['top'] rect_b = rect['bottom'] rect_l = rect['left'] rect_r = rect['right'] if rect_t > rect_b: raise AssertionError(f'Face top > bottom! t: {rect_t}, b: {rect_b}') if rect_l > rect_r: raise AssertionError(f'Face left > right! l: {rect_l}, r: {rect_r}') if not 0 <= rect_l <= aa_w: raise AssertionError(f'Face l: {rect_l} outside of active W: 0,{aa_w}') if not 0 <= rect_r <= aa_w: raise AssertionError(f'Face r: {rect_r} outside of active W: 0,{aa_w}') if not 0 <= rect_t <= aa_h: raise AssertionError(f'Face t: {rect_t} outside active H: 0,{aa_h}') if not 0 <= rect_b <= aa_h: raise AssertionError(f'Face b: {rect_b} outside active H: 0,{aa_h}') def check_face_landmarks(face): """Check that face landmarks fall within face bounding box.""" l, r = face['bounds']['left'], face['bounds']['right'] t, b = face['bounds']['top'], face['bounds']['bottom'] l_eye_x, l_eye_y = face['leftEye']['x'], face['leftEye']['y'] r_eye_x, r_eye_y = face['rightEye']['x'], face['rightEye']['y'] mouth_x, mouth_y = face['mouth']['x'], face['mouth']['y'] if not l <= l_eye_x <= r: raise AssertionError(f'Face l: {l}, r: {r}, left eye x: {l_eye_x}') if not t <= l_eye_y <= b: raise AssertionError(f'Face t: {t}, b: {b}, left eye y: {l_eye_y}') if not l <= r_eye_x <= r: raise AssertionError(f'Face l: {l}, r: {r}, right eye x: {r_eye_x}') if not t <= r_eye_y <= b: raise AssertionError(f'Face t: {t}, b: {b}, right eye y: {r_eye_y}') if not l <= mouth_x <= r: raise AssertionError(f'Face l: {l}, r: {r}, mouth x: {mouth_x}') if not t <= mouth_y <= b: raise AssertionError(f'Face t: {t}, b: {b}, mouth y: {mouth_y}') class FacesTest(its_base_test.ItsBaseTest): """Tests face detection algorithms. Allows NUM_TEST_FRAMES for face detection algorithm to find all faces. Tests OFF, SIMPLE, and FULL modes if available. OFF --> no faces should be found. SIMPLE --> face(s) should be found, but no landmarks. FULL --> face(s) should be found and face landmarks reported. """ def test_faces(self): logging.debug('Starting %s', NAME) with its_session_utils.ItsSession( device_id=self.dut.serial, camera_id=self.camera_id, hidden_physical_id=self.hidden_physical_id) as cam: props = cam.get_camera_properties() props = cam.override_with_hidden_physical_camera_props(props) # Load chart for scene. its_session_utils.load_scene( cam, props, self.scene, self.tablet, self.chart_distance) camera_properties_utils.skip_unless( camera_properties_utils.face_detect(props)) mono_camera = camera_properties_utils.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 camera_properties_utils.read_3a(props): gain, exp, _, _, focus = cam.do_3a( get_results=True, mono_camera=mono_camera) logging.debug('iso = %d', gain) logging.debug('exp = %.2fms', (exp * 1.0E-6)) if focus == 0.0: logging.debug('fd = infinity') else: logging.debug('fd = %.2fcm', (1.0E2 / focus)) for fd_mode in fd_modes: if not FD_MODE_OFF <= fd_mode <= FD_MODE_FULL: raise AssertionError(f'fd_mode undefined: {fd_mode}') req = capture_request_utils.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): fd_mode_md = cap['metadata']['android.statistics.faceDetectMode'] if fd_mode_md != fd_mode: raise AssertionError('Metadata does not match request! ' f'Request: {fd_mode} metadata: {fd_mode_md}.') faces = cap['metadata']['android.statistics.faces'] # 0 faces should be returned for OFF mode if fd_mode == FD_MODE_OFF: if faces: raise AssertionError('Faces found in OFF mode.') continue # Save last frame. if i == NUM_TEST_FRAMES - 1: img = image_processing_utils.convert_capture_to_rgb_image( cap, props=props) img = image_processing_utils.rotate_img_per_argv(img) img_name = '%s_fd_mode_%s.jpg' % (os.path.join(self.log_path, NAME), fd_mode) image_processing_utils.write_image(img, img_name) if not faces: raise AssertionError(f'No face detected in mode {fd_mode}.') if not faces: continue logging.debug('Frame %d face metadata:', i) logging.debug('Faces: %s', faces) face_scores = [face['score'] for face in faces] face_rectangles = [face['bounds'] for face in faces] for score in face_scores: if not 1 <= score <= 100: raise AssertionError(f'Face score not valid! score: {score}.') # Face bounds should be within active array. for j, rect in enumerate(face_rectangles): logging.debug('Checking face rectangle %d', j) check_face_bounding_box(rect, aw, ah) # Face ID should be -1 for SIMPLE and unique for FULL if fd_mode == FD_MODE_SIMPLE: for face in faces: if 'leftEye' in face or 'rightEye' in face: raise AssertionError('Eyes not supported in FD_MODE_SIMPLE.') if 'mouth' in face: raise AssertionError('Mouth not supported in FD_MODE_SIMPLE.') if face['id'] != -1: raise AssertionError('face_id should be -1 in FD_MODE_SIMPLE.') elif fd_mode == FD_MODE_FULL: face_ids = [face['id'] for face in faces] if len(face_ids) != len(set(face_ids)): raise AssertionError('Same face detected more than 1x.') # Face landmarks should be within face bounds for k, face in enumerate(faces): logging.debug('Checking landmarks in face %d: %s', k, str(face)) check_face_landmarks(face) if __name__ == '__main__': test_runner.main()