def _return_std(image_path, mean):
img = np.array(load_pil_image(image_path)) / 255.0
m2 = np.square(
np.array([
img[:, :, 0] - mean[0], img[:, :, 1] - mean[1],
img[:, :, 2] - mean[2]
]))
return np.sum(np.sum(m2, axis=1), 1), m2.size / 3.0
def _return_mean(image_path):
img = np.array(load_pil_image(image_path))
mean = np.array([
np.mean(img[:, :, 0]),
np.mean(img[:, :, 1]),
np.mean(img[:, :, 2])
])
return mean / 255.0
def __getitem__(self, index: int):
# Load images and masks
img = load_pil_image(self.images_path[index])
target = self._map_annotation(index)
if self.convert_polygons is not None:
img, target = self.convert_polygons(img, target)
if self.transform is not None:
img, target = self.transform(img, target)
return img, target