def detect_deffects(file_name): new_file_name = 'uploads/' + file_name time = cv2.getTickCount() result_points, eyes_coordinates, nose_coordinates, mouth_coordinates, image = fd.get_param( new_file_name) roi = crop_face(image, result_points) roi = crop_limbs(roi, eyes_coordinates, nose_coordinates, mouth_coordinates) roi = get_otsu(roi, 200, 255) key_points = sift(roi, contrast_threshold=0.02, edge_threshold=15, sigma=2) key_points, score = delete_unused_keypoints(key_points, result_points, eyes_coordinates, nose_coordinates, mouth_coordinates, roi, image) result_image = cv2.drawKeypoints( image, key_points, flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS) print 'total score - ' + str(score) print 'total time - ' + str(print_time(time)) return_file_name = 'proc_' + file_name new_file_name = 'uploads/' + return_file_name save_image(result_image, new_file_name) return return_file_name, score
def process_photo_tests(file_name): """ Process photo, use one of the above algorithms, return processed image and skin score Input: fileName """ result_points, eyes_coordinates, nose_coordinates, mouth_coordinates, image = fd.get_param(file_name) roi = crop_face(image, result_points) limbs = [nose_coordinates, mouth_coordinates, eyes_coordinates] #result_image, score = otsu_grid_search(roi, image, result_points, limbs, # contrast_threshold=0.02, edge_threshold=10, sigma=1.6) result_image, score, key_points = sift_grid_search(roi, image, result_points, limbs, thresh_val=220, type=cv2.THRESH_TRUNC) #result_image, score = mono_search(roi, image, result_points, limbs, thresh_val=220, type=cv2.THRESH_TRUNC) #result_image = draw_face(result_image, result_points) return result_image, key_points
def detect_deffects(file_name): new_file_name = "uploads/" + file_name time = cv2.getTickCount() result_points, eyes_coordinates, nose_coordinates, mouth_coordinates, image = fd.get_param(new_file_name) roi = crop_face(image, result_points) roi = crop_limbs(roi, eyes_coordinates, nose_coordinates, mouth_coordinates) roi = get_otsu(roi, 200, 255) key_points = sift(roi, contrast_threshold=0.02, edge_threshold=15, sigma=2) key_points, score = delete_unused_keypoints( key_points, result_points, eyes_coordinates, nose_coordinates, mouth_coordinates, roi, image ) result_image = cv2.drawKeypoints(image, key_points, flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS) print "total score - " + str(score) print "total time - " + str(print_time(time)) return_file_name = "proc_" + file_name new_file_name = "uploads/" + return_file_name save_image(result_image, new_file_name) return return_file_name, score