| # 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 3 faces with different skin tones are detected.""" |
| |
| |
| import logging |
| import os.path |
| |
| import cv2 |
| 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 |
| |
| FD_MODE_OFF = 0 |
| FD_MODE_SIMPLE = 1 |
| FD_MODE_FULL = 2 |
| NAME = os.path.splitext(os.path.basename(__file__))[0] |
| NUM_TEST_FRAMES = 20 |
| NUM_FACES = 3 |
| W, H = 640, 480 |
| |
| |
| def check_face_bounding_box(rect, aw, ah, index): |
| """Checks face bounding box is within the active array area. |
| |
| Args: |
| rect: dict; with face bounding box information |
| aw: int; active array width |
| ah: int; active array height |
| index: int to designate face number |
| """ |
| logging.debug('Checking bounding box in face %d: %s', index, str(rect)) |
| if (rect['top'] >= rect['bottom'] or |
| rect['left'] >= rect['right']): |
| raise AssertionError('Face coordinates incorrect! ' |
| f" t: {rect['top']}, b: {rect['bottom']}, " |
| f" l: {rect['left']}, r: {rect['right']}") |
| if (not 0 <= rect['top'] <= ah or |
| not 0 <= rect['bottom'] <= ah): |
| raise AssertionError('Face top/bottom outside of image height! ' |
| f"t: {rect['top']}, b: {rect['bottom']}, " |
| f"h: {ah}") |
| if (not 0 <= rect['left'] <= aw or |
| not 0 <= rect['right'] <= aw): |
| raise AssertionError('Face left/right outside of image width! ' |
| f"l: {rect['left']}, r: {rect['right']}, " |
| f" w: {aw}") |
| |
| |
| def check_face_landmarks(face, fd_mode, index): |
| """Checks face landmarks fall within face bounding box. |
| |
| Face ID should be -1 for SIMPLE and unique for FULL |
| Args: |
| face: dict from face detection algorithm |
| fd_mode: int of face detection mode |
| index: int to designate face number |
| """ |
| logging.debug('Checking landmarks in face %d: %s', index, str(face)) |
| if fd_mode == FD_MODE_SIMPLE: |
| 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: |
| 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}') |
| else: |
| raise AssertionError(f'Unknown face detection mode: {fd_mode}.') |
| |
| |
| def draw_face_rectangles(img, faces, crop): |
| """Draw rectangles on top of image. |
| |
| Args: |
| img: image array |
| faces: list of dicts with face information |
| crop: dict; crop region size with 'top, right, left, bottom' as keys |
| Returns: |
| img with face rectangles drawn on it |
| """ |
| cw, ch = crop['right'] - crop['left'], crop['bottom'] - crop['top'] |
| logging.debug('crop region: %s', str(crop)) |
| for rect in [face['bounds'] for face in faces]: |
| logging.debug('rect: %s', str(rect)) |
| top_left = (int(round((rect['left'] - crop['left']) * img.shape[1] / cw)), |
| int(round((rect['top'] - crop['top']) * img.shape[0] / ch))) |
| bot_rght = (int(round((rect['right'] - crop['left']) * img.shape[1] / cw)), |
| int(round((rect['bottom'] - crop['top']) * img.shape[0] / ch))) |
| cv2.rectangle(img, top_left, bot_rght, (0, 1, 0), 2) |
| return img |
| |
| |
| class NumFacesTest(its_base_test.ItsBaseTest): |
| """Test face detection with different skin tones. |
| """ |
| |
| def test_num_faces(self): |
| """Test face detection.""" |
| 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) |
| |
| # Check skip conditions |
| 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'] |
| logging.debug('active array size: %s', str(a)) |
| file_name_stem = os.path.join(self.log_path, NAME) |
| |
| cam.do_3a(mono_camera=mono_camera) |
| |
| for fd_mode in fd_modes: |
| logging.debug('face detection mode: %d', fd_mode) |
| if not FD_MODE_OFF <= fd_mode <= FD_MODE_FULL: |
| raise AssertionError(f'FD mode {fd_mode} not in MODES! ' |
| f'OFF: {FD_MODE_OFF}, FULL: {FD_MODE_FULL}') |
| 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_cap = cap['metadata']['android.statistics.faceDetectMode'] |
| if fd_mode_cap != fd_mode: |
| raise AssertionError(f'metadata {fd_mode_cap} != req {fd_mode}') |
| |
| faces = cap['metadata']['android.statistics.faces'] |
| # 0 faces should be returned for OFF mode |
| if fd_mode == FD_MODE_OFF: |
| if faces: |
| raise AssertionError(f'Error: faces detected in OFF: {faces}') |
| continue |
| # Face detection could take several frames to warm up, |
| # but should detect the correct number of faces in last frame |
| if i == NUM_TEST_FRAMES - 1: |
| img = image_processing_utils.convert_capture_to_rgb_image( |
| cap, props=props) |
| fnd_faces = len(faces) |
| logging.debug('Found %d face(s), expected %d.', |
| fnd_faces, NUM_FACES) |
| # draw boxes around faces |
| crop_region = cap['metadata']['android.scaler.cropRegion'] |
| img = draw_face_rectangles(img, faces, crop_region) |
| # save image with rectangles |
| img_name = f'{file_name_stem}_fd_mode_{fd_mode}.jpg' |
| image_processing_utils.write_image(img, img_name) |
| if fnd_faces != NUM_FACES: |
| raise AssertionError('Wrong num of faces found! ' |
| f'Found: {fnd_faces}, expected: {NUM_FACES}') |
| if not faces: |
| continue |
| |
| logging.debug('Frame %d face metadata:', i) |
| logging.debug(' Faces: %s', str(faces)) |
| |
| # Reasonable scores for faces |
| face_scores = [face['score'] for face in faces] |
| for score in face_scores: |
| if not 1 <= score <= 100: |
| raise AssertionError(f'score not between [1:100]! {score}') |
| |
| # Face bounds should be within active array |
| face_rectangles = [face['bounds'] for face in faces] |
| for j, rect in enumerate(face_rectangles): |
| check_face_bounding_box(rect, aw, ah, j) |
| |
| # Face landmarks (if provided) are within face bounding box |
| for k, face in enumerate(faces): |
| check_face_landmarks(face, fd_mode, k) |
| |
| |
| if __name__ == '__main__': |
| test_runner.main() |
