def __compute_components_for_negative_images(self):
self.logger.log("Loading negative images")
images = general.load_images_from_folder(self.path_train + "/" +
"train_images_ns")
self.logger.log("\nExtracting values from negative images")
for current_index in range(len(images)):
self.logger.log_progress(current_index, len(images))
image = images[current_index]
image = general.convert_color(image, self.color_space)
mask = np.zeros(image.shape)
self.__get_components_from_image_mask(image, mask)
def detect(self, image, threshold):
new_image = general.generate_overlay_image(image)
image = general.convert_color(image, self.model.color_space)
rows = image.shape[0]
cols = image.shape[1]
for x_pixel in range(rows):
for y_pixel in range(cols):
self.logger.log_progress_pixel(x_pixel, y_pixel, rows, cols)
pixel = image[x_pixel, y_pixel]
prob = ProbabilityCalculator.calculate_for_pixel(pixel, self.model.components)
if prob > threshold:
new_image[x_pixel, y_pixel] = [0, 0, 0]
return new_image
def extract_non_skin_pixels(self):
self.logger.log("Calculating bayes spm components for nonskin images")
non_skin_images = general.load_images_from_folder(
self.path_negative_images)
for image in non_skin_images:
image = general.convert_color(image, self.color_space)
rows = image.shape[0]
cols = image.shape[1]
for x_pixel in range(rows):
for y_pixel in range(cols):
self.non_skin_pixels += 1
pixel = image[x_pixel, y_pixel]
p = Pixel(F1=pixel[0], F2=pixel[1], F3=pixel[2])
if p in self.appearances:
self.appearances[p] += 1
else:
self.appearances[p] = 1
def detect(self, image, superpixels, threshold):
new_image = general.generate_overlay_image(image)
image = general.convert_color(image, self.model.color_space)
pos = 0
for center in superpixels: # iterate superpixels
pos += 1
self.logger.log_progress(pos, len(superpixels))
superpixel = superpixels[center]
average_prob = self.__calculate_superpixel_average(superpixel, image)
# determine based on max probability if the region is classified as skin
if average_prob > threshold:
for pixel_pos in superpixel.get_pixels_pos():
x_pixel, y_pixel = pixel_pos[0], pixel_pos[1]
new_image[x_pixel, y_pixel] = [0, 0, 0]
return new_image
def __compute_components_for_positive_images(self):
self.logger.log("Loading positive images")
images = general.load_images_from_folder(self.path_train + "/" +
"train_images")
masks = general.load_images_from_folder(self.path_train + "/" +
"train_masks")
self.logger.log("\nExtracting values from positive images")
for current_index in range(len(images)):
self.logger.log_progress(current_index, len(images))
image = images[current_index]
mask = masks[current_index]
image = general.convert_color(image, self.color_space)
try:
self.__get_components_from_image_mask(image, mask)
except IndexError:
self.logger.log(str(current_index) + " mask is corrupted")