def __call__(self, sample):
inputs, target = sample
h, w, _ = inputs.shape
applied_angle = random.uniform(-self.angle, self.angle)
diff = random.uniform(-self.diff_angle, self.diff_angle)
angle1 = applied_angle - diff / 2
angle1_rad = angle1 * np.pi / 180
inputs = F.rotate(inputs, angle1)
target = F.rotate(target, angle1)
# keep angle1 and angle2 within [0,pi/2] with a reflection at pi/2: -1rad is 1rad, 2rad is pi - 2 rad
angle1_rad = np.pi / 2 - np.abs(angle1_rad % np.pi - np.pi / 2)
c1 = np.cos(angle1_rad)
s1 = np.sin(angle1_rad)
c_diag = h / np.sqrt(h * h + w * w)
s_diag = w / np.sqrt(h * h + w * w)
ratio = 1. / (c1 + w / float(h) * s1)
crop = CropCenter((int(h * ratio), int(w * ratio)))
return crop(inputs, target)
def perform_transformation_operation(temp_x, temp_y):
threshold = 0.5
threshold_angle = 0.2
if threshold_angle <= random.random() == True:
angle = random.randint(-10, 10)
temp_x = F.rotate(temp_x, angle)
temp_y = F.rotate(temp_y, angle)
if threshold <= random.random() == True:
temp_x = transforms.functional.hflip(temp_x)
temp_y = transforms.functional.hflip(temp_y)
if threshold <= random.random() == True:
temp_x = transforms.functional.hflip(temp_x)
temp_y = transforms.functional.hflip(temp_y)
return (temp_x, temp_y)
def __call__(self, img):
"""
img (PIL Image): Image to be rotated.
Returns:
PIL Image: Rotated image.
"""
angle = self.get_params(self.degrees)
return F.rotate(img, angle, self.resample, self.expand, self.center)
def apply(self, image, mask, rand_h, rand_w, angle, **params):
h, w = image.shape[:2]
mask = F.rotate(mask, angle) if self.rotate[1] > 0 else mask
mask = mask[:, :, np.newaxis] if image.ndim == 3 else mask
image *= mask[rand_h:rand_h + h, rand_w:rand_w + w].astype(image.dtype)
return image