def transform(self, pil_img, label, **kwargs):
pil_img = pil_img.copy()
degree = categorize_value(self.level, self.value_range, "int")
width, height = pil_img.size
x0 = np.random.uniform(width)
y0 = np.random.uniform(height)
x0 = int(max(0, x0 - degree / 2.0))
y0 = int(max(0, y0 - degree / 2.0))
x1 = min(width, x0 + degree)
y1 = min(height, y0 + degree)
xy = (x0, y0, x1, y1)
if self.color is not None:
color = self.color
elif pil_img.mode == "RGB":
color = (125, 123, 114)
elif pil_img.mode == "L":
color = 121
else:
raise ValueError(f"Unspported image mode {pil_img.mode}")
ImageDraw.Draw(pil_img).rectangle(xy, color)
return pil_img, label
def transform(self, pil_img, label, **kwargs):
degree = categorize_value(self.level, self.value_range, "float")
if random.random() > 0.5:
degree = -degree
return (
pil_img.transform(pil_img.size, Image.AFFINE, (1, 0, 0, degree, 1, 0)),
label,
)
def transform(self, pil_img, label, **kwargs):
degree = categorize_value(self.level, self.value_range, "float")
return ImageEnhance.Brightness(pil_img).enhance(degree), label
def transform(self, pil_img, label, **kwargs):
degree = categorize_value(self.level, self.value_range, "int")
return ImageOps.posterize(pil_img, degree), label
def transform(self, pil_img, label, **kwargs):
degree = categorize_value(self.level, self.value_range, "float")
if random.random() > 0.5:
degree = -degree
return pil_img.rotate(degree), label