def transform(self, images, *args, **kwargs):
if self.selected:
if COLOR_IMAGE in images:
images[COLOR_IMAGE] = self.image_service.linear_scaling(images[COLOR_IMAGE], self.alpha, self.beta)
images[OUT_IMAGE] = COLOR_IMAGE
else:
raise TransformationError("Contrast and brightness transformation requires color image")
return images
def transform(self, images, *args, **kwargs):
if self.selected:
if GRAY_IMAGE in images:
images[OUT_IMAGE] = BIN_IMAGE
images[BIN_IMAGE] = self.image_service.otsu_binarization(images[GRAY_IMAGE])
else:
raise TransformationError("Otsu binarization requires grayscale image")
return images
def transform(self, images, *args, **kwargs):
if self.selected:
if COLOR_IMAGE in images:
images[OUT_IMAGE] = COLOR_IMAGE
images[COLOR_IMAGE] = self.image_service.brightness_equalizer(
images[COLOR_IMAGE], self.clip_limit, self.tile_grid_size)
else:
raise TransformationError(
"Brightness equalizer transformation requires color image")
return images
def transform(self, images, *args, **kwargs):
if self.selected:
if COLOR_IMAGE in images:
images[OUT_IMAGE] = GRAY_IMAGE
images[GRAY_IMAGE] = self.image_service.bgr_to_gray(
images[COLOR_IMAGE])
else:
raise TransformationError(
"RGB to gray transformation requires color image")
return images
def transform(self, images, *args, **kwargs):
if self.selected:
if GRAY_IMAGE in images:
images[GRAY_IMAGE] = self.image_service.gaussian_blur(
images[GRAY_IMAGE], self.kernel)
images[OUT_IMAGE] = GRAY_IMAGE
else:
raise TransformationError(
"Gaussian blur requires transformation grayscale image")
return images
def transform(self, images, *args, **kwargs):
if self.selected:
if BIN_IMAGE in images:
images[BIN_IMAGE] = self.image_service.morphology_closing(
images[BIN_IMAGE], self.kernel)
images[OUT_IMAGE] = BIN_IMAGE
else:
raise TransformationError(
"Morphology - closing transformation requires binary image"
)
return images
def transform(self, images, *args, **kwargs):
if self.selected:
if COLOR_IMAGE in images:
images[COLOR_IMAGE] = self.image_service.clip_and_rotate(
images[COLOR_IMAGE], self.gaussian_blur,
(self.lower_h, self.lower_s, self.lower_v),
(self.upper_h, self.upper_s, self.upper_v), self.canny_min,
self.canny_max)
images[OUT_IMAGE] = COLOR_IMAGE
images[CLIPPED_IMAGE] = images[COLOR_IMAGE]
else:
raise TransformationError("Clip requires color image")
return images
def gaussian_blur(self, image, kernel=(5, 5)):
if kernel[0] % 2 == 0 or kernel[1] % 2 == 0:
raise TransformationError(
"Gaussian kernel must have odd dimension")
return cv2.GaussianBlur(image, kernel, 0)