[add] A PairRandomCrop for both input and target.

README.rst

@@ -332,6 +332,16 @@ integer, in which case the target will be of a square shape (size, size)
 If ``padding`` is non-zero, then the image is first zero-padded on each
 side with ``padding`` pixels.
 
+``PairRandomCrop(size, padding=0)``
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Crops the given PIL.Image at a random location to have a region of the
+given size for both input image and its target image. size can be a
+tuple (target\_height, target\_width) or an integer, in which case the
+target will be of a square shape (size, size)
+If ``padding`` is non-zero, then the image is first zero-padded on each
+side with ``padding`` pixels.
+
 ``RandomHorizontalFlip()``
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
 

torchvision/transforms.py

@@ -311,6 +311,51 @@ def __call__(self, img):
         return img.crop((x1, y1, x1 + tw, y1 + th))
 
 
+class PairRandomCrop(object):
+    """Crop the given PIL.Image at a random location for both input and target.
+
+    Args:
+        size (sequence or int): Desired output size of the crop. If size is an
+            int instead of sequence like (h, w), a square crop (size, size) is
+            made.
+        padding (int or sequence, optional): Optional padding on each border
+            of the image. Default is 0, i.e no padding. If a sequence of length
+            4 is provided, it is used to pad left, top, right, bottom borders
+            respectively.
+    """
+    last_position = None
+
+    def __init__(self, size, padding=0):
+        if isinstance(size, numbers.Number):
+            self.size = (int(size), int(size))
+        else:
+            self.size = size
+        self.padding = padding
+
+    def __call__(self, img):
+        """
+        Args:
+            img (PIL.Image): Image to be cropped.
+        Returns:
+            PIL.Image: Cropped image.
+        """
+        if self.padding > 0:
+            img = ImageOps.expand(img, border=self.padding, fill=0)
+
+        w, h = img.size
+        th, tw = self.size
+        if w == tw and h == th:
+            return img
+
+        if self.last_position is not None:
+            (x1, y1), self.last_position = self.last_position, None
+        else:
+            x1 = random.randint(0, w - tw)
+            y1 = random.randint(0, h - th)
+            self.last_position = (x1, y1)
+        return img.crop((x1, y1, x1 + tw, y1 + th))
+
+
 class RandomHorizontalFlip(object):
     """Horizontally flip the given PIL.Image randomly with a probability of 0.5."""