def otsu_grid_search(roi, image, result_points, limbs, **kwargs):
"""
Algorithm based on sorting parameters of otsu, return processed image and skin score
Input:
roi (cropped image)
image (original image)
result_points (array of points - contour)
limbs (array of face limbs coordinates)
"""
threshs = [190, 200, 210]
roi = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY)
alpha = contrast_val(roi)
roi = change_constrast(roi, alpha=alpha, beta=-70.0)
#roi = get_blur(roi, 3)
key_points = grid_otsu(roi, threshs, delta=2, **kwargs)
key_points = kpproc.delete_unused_keypoints(roi, key_points, result_points, limbs)
key_points = kpproc.delete_repeating_points(key_points)
score = 0.0
score = kpproc.get_score(image, key_points)
result_image = draw_circles(image, key_points)
return result_image, score
def mono_search(roi, image, result_points, limbs, **kwargs):
"""
Algorithm based on simple sift and otsu, return processed image and skin score
Input:
roi (cropped image)
image (original image)
result_points (array of points - contour)
limbs (array of face limbs coordinates)
kwargs (otsu parameters)
"""
roi = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY)
alpha = contrast_val(roi)
roi = change_constrast(roi, alpha=alpha, beta=-70.0)
#roi = get_blur(roi, 3)
roi = get_otsu(roi, **kwargs)
key_points = sift(roi, contrast_threshold=0.035, edge_threshold=5, sigma=1.0)
key_points = kpproc.delete_unused_keypoints(roi, key_points, result_points, limbs)
key_points = kpproc.delete_repeating_points(key_points)
score = 0.0
score = kpproc.get_score(image, key_points)
result_image = draw_circles(image, key_points)
#result_image = roi
#score = 0
return result_image, score
def sift_grid_search(roi, image, result_points, limbs, **kwargs):
"""
Algorithm based on sorting parameters of sift, return processed image and skin score
Input:
roi (cropped image)
image (original image)
result_points (array of points - contour)
limbs (array of face limbs coordinates)
kwargs (otsu parameters)
"""
roi = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY)
alpha = contrast_val(roi)
roi = change_constrast(roi, alpha=alpha, beta=-80.0)
roi_non_contrast = roi
roi = get_blur(roi, 3)
roi = get_otsu(roi, **kwargs)
contrast_thresholds = [0.02, 0.025]
edge_thresholds = [5]
sigmas = [1.2, 1.4]
key_points1 = grid_sift(roi, contrast_thresholds, edge_thresholds, sigmas, delta=3)
#key_points2 = sift(roi_non_contrast, contrast_threshold=0.035, edge_threshold=5, sigma=1.0)
key_points1 = kpproc.delete_unused_keypoints(roi, key_points1, result_points, limbs)
#key_points2 = kpproc.delete_unused_keypoints(roi_non_contrast, key_points2, result_points, limbs)
#key_points2 = kpproc.combine_points(key_points1, key_points2)
#key_points1 = key_points1 + key_points2
key_points1 = kpproc.delete_repeating_points(key_points1)
score = 0.0
score = kpproc.get_score(image, key_points1)
result_image = draw_circles(image, key_points1)
#score = 0
#result_image = roi
return result_image, score, key_points1