def _transform_image(self, image_path, areas, style, cloths):
segmentation_mask, _ = self._segmentation_model.predict(image_path)
# transformed_image = self._style_transformer.transform(image=image, style=style) FIXME
image = cv2.imread(image_path)
assert image is not None, image_path
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
# return image, None
if not cloths:
transformed_image = self._motion_blur(image, ksize=45)
else:
transformed_image = shift_hsv(image, 100, 50, 50)
return self._morph_transforms(initial_image=image,
transformed_image=transformed_image,
segmentation_mask=segmentation_mask,
areas=areas)
def apply(self, image, hue_shift=0, sat_shift=0, val_shift=0, label = None, **params):
print("apply")
if label is not None:
print('thread aug')
image = np.array(image)
output = image.copy()
hsv = image.copy()
hsv = F.shift_hsv(hsv, hue_shift, sat_shift, val_shift)
thread = np.where(label==self.thread_idx)
output[thread] = hsv[thread]
return output
else:
print('thread aug failed')
return image
def albumentations(self, img):
return albumentations.shift_hsv(img,
hue_shift=20,
sat_shift=20,
val_shift=20)
def test_shift_hsv_gray(img):
F.shift_hsv(img, 0.5, 0.5, 0.5)
def albumentations(self, img):
return albumentations.shift_hsv(img, hue_shift=20, sat_shift=20, val_shift=20)