42418e10a68f534b939a125a9ccd60167f9a6633,torchsample/transforms/affine_transforms.py,Rotate,__call__,#Rotate#Any#Any#,252

Before Change

        if self.lazy:
            return rotation_matrix
        else:
            x_transformed = torch.from_numpy(apply_transform(x.numpy(), rotation_matrix,
                fill_mode=self.fill_mode, fill_value=self.fill_value))
            if y is not None:
                y_transformed = torch.from_numpy(apply_transform(y.numpy(), rotation_matrix,
                fill_mode=self.target_fill_mode, fill_value=self.target_fill_value))
                return x_transformed, y_transformed
            else:
                return x_transformed

After Change

    def __call__(self, x, y=None):
        degree = random.uniform(-self.rotation_range, self.rotation_range)
        theta = math.pi / 180 * degree
        rotation_matrix = torch.FloatTensor([[math.cos(theta), -math.sin(theta), 0],
                                             [math.sin(theta), math.cos(theta), 0],
                                             [0, 0, 1]])
        if self.lazy:
            return rotation_matrix
        else:
            x_transformed = _apply_transform(x, rotation_matrix, self.coords)
            if y is not None:
                y_transformed = _apply_transform(y, rotation_matrix, self.coords)
                return x_transformed, y_transformed
            else:
                return x_transformed

Instances