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
