def test_create_models_from_image_list(self): base_path = os.path.join('..', 'test_files', 'face_models') face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data')) params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1, c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data} fm = FaceModels(params) fm.delete_models() model_id = 0 im_list = [os.path.join(base_path, '0000000_aligned.png'), os.path.join(base_path, '0000005_aligned.png')] model_path_0 = fm.create_model_from_image_list(im_list, model_id) model_id = 1 im_list = [os.path.join(base_path, '0000001_aligned.png')] model_path_1 = fm.create_model_from_image_list(im_list, model_id) model_id = 2 im_list = [os.path.join(base_path, '0000002_aligned.png')] model_path_2 = fm.create_model_from_image_list(im_list, model_id) model_id = 3 im_list = [os.path.join(base_path, '0000003_aligned.png'), os.path.join(base_path, '0000004_aligned.png')] model_path_3 = fm.create_model_from_image_list(im_list, model_id) self.assertTrue(os.path.exists(model_path_0)) self.assertTrue(os.path.exists(model_path_1)) self.assertTrue(os.path.exists(model_path_2)) self.assertTrue(os.path.exists(model_path_3))
def test_remove_face(self): base_path = os.path.join('..', 'test_files', 'face_models') face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data')) params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1, c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data} fm = FaceModels(params) fm.delete_models() self.test_add_face() training_set_path = os.path.join( fm._data_dir_path, c.TRAINING_SET_DIR) aligned_faces_path = os.path.join( training_set_path, c.ALIGNED_FACES_DIR) label = 3812 subject_path = os.path.join(aligned_faces_path, str(label)) im_name = '' for im in os.listdir(subject_path): im_name = im ok = fm.remove_face(label, im_name) self.assertTrue(ok)
def test_recognize_model_external_models(self): base_path = os.path.join('..', 'test_files', 'face_models') face_rec_data = os.path.abspath( os.path.join(base_path, 'face_rec_data')) params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1, c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data} model_path_0 = os.path.join(face_rec_data, c.FACE_MODELS_DIR, '0') model_path_1 = os.path.join(face_rec_data, c.FACE_MODELS_DIR, '1') model_path_2 = os.path.join(face_rec_data, c.FACE_MODELS_DIR, '2') model_path_3 = os.path.join(face_rec_data, c.FACE_MODELS_DIR, '3') model_0 = {c.MODEL_ID_KEY: 0, c.MODEL_FILE_KEY: model_path_0, c.TAG_KEY: 'Mameli_Giacomo'} model_1 = {c.MODEL_ID_KEY: 1, c.MODEL_FILE_KEY: model_path_1, c.TAG_KEY: 'Fadda_Paolo'} model_2 = {c.MODEL_ID_KEY: 2, c.MODEL_FILE_KEY: model_path_2, c.TAG_KEY: 'Giannotta_Michele'} model_3 = {c.MODEL_ID_KEY: 3, c.MODEL_FILE_KEY: model_path_3, c.TAG_KEY: 'Leoni_Mario'} fm = FaceModels(params, [model_0, model_1, model_2, model_3]) fm.delete_models() self.test_create_models_from_image_list() fm.load_models() model_id = 0 im_list = [os.path.join(base_path, '0000000_aligned.png'), os.path.join(base_path, '0000005_aligned.png')] model_path_0 = fm.create_model_from_image_list(im_list, model_id) query_model = cv2.createLBPHFaceRecognizer() query_model.load(model_path_0) rec_results = fm.recognize_model(query_model) rec_result = rec_results[0] self.assertEqual(rec_result[c.ASSIGNED_TAG_KEY], 0)
def test_create_models_from_whole_images_and_labels(self): orig_images_dir_path = os.path.join( '..', 'test_files', 'face_models', 'Whole images') base_path = os.path.join('..', 'test_files', 'face_models') face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data')) params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1, c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data} fm = FaceModels(params) fm.delete_models() labels = [1000, 1001, 1002, 1003] fm.create_models_from_whole_images(orig_images_dir_path, labels) # Check that all files exist db_file_name = os.path.join(fm._data_dir_path, c.FACE_MODELS_FILE) self.assertTrue(os.path.exists(db_file_name)) tag_label_associations_file = os.path.join( fm._data_dir_path, c.TAG_LABEL_ASSOCIATIONS_FILE) self.assertTrue(os.path.exists(tag_label_associations_file)) faces_file = os.path.join(fm._data_dir_path, c.FACES_FILE) self.assertTrue(os.path.exists(faces_file)) aligned_faces_path = os.path.join( fm._data_dir_path, c.TRAINING_SET_DIR, c.ALIGNED_FACES_DIR) # Check that directory with aligned faces exists # and has the right number of sub directories # and that each sub directory has the right name sub_dir_counter = 0 if os.path.exists(aligned_faces_path): for sub_dir in os.listdir(aligned_faces_path): self.assertEqual(sub_dir, str(labels[sub_dir_counter])) sub_dir_counter += 1 self.assertEqual(sub_dir_counter, 4)
def test_remove_label_not_removed(self): base_path = os.path.join('..', 'test_files', 'face_models') face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data')) params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1, c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data} fm = FaceModels(params) fm.delete_models() self.test_add_face() label = -1 ok = fm.remove_label(label) self.assertFalse(ok)
def test_get_tags(self): base_path = os.path.join('..', 'test_files', 'face_models') face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data')) params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1, c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data} fm = FaceModels(params) fm.delete_models() self.test_add_face() fm.load_models() tags = fm.get_tags() self.assertEquals(len(tags), 4)
c.MAX_EYE_ANGLE_KEY: 0.125, c.MIN_EYE_DISTANCE_KEY: 0.25, c.USE_EYES_POSITION_KEY: True, c.USE_NOSE_POS_IN_DETECTION_KEY: False, c.ALIGNED_FACES_PATH_KEY: align_path, c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: 'face_rec_data', c.LBP_GRID_X_KEY: 4, c.LBP_GRID_Y_KEY: 5, c.LBP_NEIGHBORS_KEY: 8, c.LBP_RADIUS_KEY: 1 } fm = FaceModels(params) # Delete possible already existing models fm.delete_models() # Add face from first image to face models label = 0 tag = '' fm.add_face(label, tag, image_path_1) # Detect face in second image result = detect_faces_in_image( image_path_2, align_path, params, show_results=False) # Recognize aligned face detected in second image if result and c.FACES_KEY in result: faces = result[c.FACES_KEY] if len(faces) == 1:
def test_add_face(self): base_path = os.path.join('..', 'test_files', 'face_models') face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data')) params = {c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data} fm = FaceModels(params) fm.delete_models() label = 3812 tag = 'Mameli_Giacomo' image_path = os.path.join(base_path, '0000000.png') aligned_image_path = os.path.join(base_path, '0000000_aligned.png') aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE) eye_pos = (303, 131, 352, 134) bbox = (260, 76, 137, 137) fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox) label = 3813 tag = 'Fadda_Paolo' image_path = os.path.join(base_path, '0000001.png') aligned_image_path = os.path.join(base_path, '0000001_aligned.png') aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE) eye_pos = (323, 150, 376, 145) bbox = (267, 87, 166, 166) fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox) label = 3815 tag = 'Giannotta_Michele' image_path = os.path.join(base_path, '0000002.png') aligned_image_path = os.path.join(base_path, '0000002_aligned.png') aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE) eye_pos = (337, 190, 393, 183) bbox = (282, 121, 161, 161) fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox) label = 3814 tag = 'Leoni_Mario' image_path = os.path.join(base_path, '0000003.png') aligned_image_path = os.path.join(base_path, '0000003_aligned.png') aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE) eye_pos = (355, 148, 407, 152) bbox = (300, 89, 156, 156) fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox) label = 3814 tag = 'Leoni_Mario' image_path = os.path.join(base_path, '0000004.png') aligned_image_path = os.path.join(base_path, '0000004_aligned.png') aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE) eye_pos = (138, 150, 158, 151) bbox = (119, 128, 60, 60) fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox) label = 3812 tag = 'Mameli_Giacomo' image_path = os.path.join(base_path, '0000005.png') aligned_image_path = os.path.join(base_path, '0000005_aligned.png') aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE) eye_pos = (318, 128, 361, 126) bbox = (272, 86, 126, 126) fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox)
def main(argv): # Set path of images to be analyzed image_path_1 = argv[1] print "image_path_1 ", image_path_1 image_path_2 = argv[2] print "image_path_2 ", image_path_2 # Set path of directory where aligned faces will be saved align_path = '/tmp' # Set parameters params = { c.CHECK_EYE_POSITIONS_KEY: True, c.CLASSIFIERS_DIR_PATH_KEY: '/home/active/gitactive/ACTIVE/face_extractor/examples/haarcascades', c.CROPPED_FACE_HEIGHT_KEY: 250, c.CROPPED_FACE_WIDTH_KEY: 200, c.EYE_DETECTION_CLASSIFIER_KEY: 'haarcascade_mcs_lefteye.xml', c.FACE_DETECTION_ALGORITHM_KEY: 'HaarCascadeFrontalFaceAlt2', c.FLAGS_KEY: 'DoCannyPruning', c.MIN_NEIGHBORS_KEY: 5, c.MIN_SIZE_HEIGHT_KEY: 20, c.MIN_SIZE_WIDTH_KEY: 20, c.OFFSET_PCT_X_KEY: 0.30, c.OFFSET_PCT_Y_KEY: 0.42, c.SCALE_FACTOR_KEY: 1.1, c.MAX_EYE_ANGLE_KEY: 0.125, c.MIN_EYE_DISTANCE_KEY: 0.25, c.USE_EYES_POSITION_KEY: True, c.USE_NOSE_POS_IN_DETECTION_KEY: False, c.ALIGNED_FACES_PATH_KEY: align_path, c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: '/home/active/gitactive/ACTIVE/face_extractor/examples/face_rec_data2', c.LBP_GRID_X_KEY: 4, c.LBP_GRID_Y_KEY: 5, c.LBP_NEIGHBORS_KEY: 8, c.LBP_RADIUS_KEY: 1 } fm = FaceModels(params) # Delete possible already existing models fm.delete_models() # Add face from first image to face models label = 0 tag = '' fm.add_face(label, tag, image_path_1) # Detect face in second image result = detect_faces_in_image( image_path_2, align_path, params, show_results=False) # Recognize aligned face detected in second image if result and c.FACES_KEY in result: faces = result[c.FACES_KEY] if len(faces) == 1: # Get aligned face and calculate distance between faces file_name = faces[0][c.ALIGNED_FACE_FILE_NAME_KEY] file_name_complete = file_name + '_gray.png' file_path = os.path.join(align_path, file_name_complete) aligned_face = cv2.imread(file_path, cv2.IMREAD_GRAYSCALE) (label, conf) = fm.recognize_face(aligned_face) # Draw bounding box around face img = cv2.imread(image_path_2) (x, y, w, h) = faces[0][c.BBOX_KEY] cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 255), 3, 8, 0) # Write distance from reference image cv2.putText(img, str(conf), (x, y + h + 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2) print "distance ", conf cv2.imshow('Image', img) cv2.waitKey(0) image_path_2 = os.path.splitext(image_path_2)[0] image_path_2 = image_path_2 + '_comparison.png' cv2.imwrite(image_path_2, img)