def transform(self, results):
        """
        Args:
            results (dict): Results dict from pipeline

        Returns:
            dict: Results after the transformation.
        """
        if self.random_disable():
            return results

        img = results['img']
        img_h, img_w = img.shape[:2]

        img = self._fill_pixels(img, *self.random_patch(img_h, img_w))

        results['img'] = img

        return results

        Args:
            results (dict): Results dict from pipeline

        Returns:
            dict: Results after the transformation.
        
mmpretrain/datasets/transforms/processing.py