def proc_and_copy_image (src, dest) :
#print src
img = cv2.imread(src)
fore = 255 * np.ones([img.shape[0],img.shape[1]])
skinfore = 255 * np.ones([img.shape[0],img.shape[1]])
if args.remove_background :
fore = remove_background(src)
if args.remove_skin :
skinfore = skin_detect(img)
fore = cv2.bitwise_and(fore, fore, mask = skinfore) # the foreground mask
b = img[:,:,0]
g = img[:,:,1]
r = img[:,:,2]
img_merge = cv2.merge((b,g,r,fore))
dot_index = dest.rfind('.')
dest = dest[:dot_index] + '.png'
cv2.imwrite(dest,img_merge)
def proc_and_copy_image (src, dest) :
"""Process image from src and write the result to dest."""
if not args.remove_background and not args.remove_skin :
shutil.copyfile(src, dest)
return dest
img = cv2.imread(src)
fore = 255 * np.ones([img.shape[0],img.shape[1]])
skinfore = 255 * np.ones([img.shape[0],img.shape[1]])
if args.remove_background :
fore = remove_background(src)
if args.remove_skin :
skinfore = skin_detect(img)
fore = cv2.bitwise_and(fore, fore, mask = skinfore) # the foreground mask
b = img[:,:,0]
g = img[:,:,1]
r = img[:,:,2]
img_merge = cv2.merge((b,g,r,fore))
dot_index = dest.rfind('.')
dest = dest[:dot_index] + '.png'
cv2.imwrite(dest, img_merge)
return dest
def detect(self, image_file_path) :
img = cv2.imread(image_file_path)
start_time = time.time()
# generate the foreground
background_removed = remove_background(image_file_path) # background removal
skin_removed = skin_detect(img) # skin removal
foreground = cv2.bitwise_and(background_removed, background_removed, mask = skin_removed) # the foreground mask
skin_percentage = 1 - sum(map(sum, foreground))/1.0/(sum(map(sum, background_removed))+0.1)
# In case of clothes in skin color.
# print "%f skin detected." % skin_percentage
if skin_percentage > self._max_skin_percentage:
# print "Too much skin"
foreground = background_removed
# Find the nearest reference color for each pixel and count
color_histogram = [0] * self._color_num
image_foreground_pixel = 0
for i in range(len(foreground)):
for j in range(len(foreground[0])):
if foreground[i][j] != 255:
continue
image_foreground_pixel += 1
if self._color_table_builder.rgb_to_color[img[i][j][2], img[i][j][1], img[i][j][0]] < 0 :
self._color_table_builder.reset_color(img[i][j][2], img[i][j][1], img[i][j][0])
color_index = int(self._color_table_builder.rgb_to_color[img[i][j][2], img[i][j][1], img[i][j][0]])
color_histogram[color_index] += 1
# Decay colors.
for decay_color in self._decay_color_index :
color_histogram[decay_color] *= self._decay_percentage
max_color_count = max(color_histogram)
return (color_histogram.index(max_color_count),
color_histogram,
max_color_count / (float(image_foreground_pixel)+0.1),
foreground)
