[Feature] Support CopyPaste when mask is not available

mmdet/datasets/transforms/transforms.py

@@ -2,6 +2,7 @@
 import copy
 import inspect
 import math
+import warnings
 from typing import List, Optional, Sequence, Tuple, Union
 
 import cv2
@@ -2930,6 +2931,9 @@ class CopyPaste(BaseTransform):
             all objects of the source image will be pasted to the
             destination image.
             Defaults to True.
+        paste_by_box (bool): Whether use boxes as masks when masks are not
+            available.
+            Defaults to False.
     """
 
     def __init__(
@@ -2938,11 +2942,13 @@ def __init__(
         bbox_occluded_thr: int = 10,
         mask_occluded_thr: int = 300,
         selected: bool = True,
+        paste_by_box: bool = False,
     ) -> None:
         self.max_num_pasted = max_num_pasted
         self.bbox_occluded_thr = bbox_occluded_thr
         self.mask_occluded_thr = mask_occluded_thr
         self.selected = selected
+        self.paste_by_box = paste_by_box
 
     @cache_randomness
     def get_indexes(self, dataset: BaseDataset) -> int:
@@ -2981,11 +2987,31 @@ def _get_selected_inds(self, num_bboxes: int) -> np.ndarray:
         num_pasted = np.random.randint(0, max_num_pasted)
         return np.random.choice(num_bboxes, size=num_pasted, replace=False)
 
+    def get_gt_masks(self, results: dict) -> BitmapMasks:
+        """Get gt_masks originally or generated based on bboxes.
+
+        If gt_masks is not contained in results,
+        it will be generated based on gt_bboxes.
+        Args:
+            results (dict): Result dict.
+        Returns:
+            BitmapMasks: gt_masks, originally or generated based on bboxes.
+        """
+        if results.get('gt_masks', None) is not None:
+            if self.paste_by_box:
+                warnings.warn('gt_masks is already contained in results, '
+                              'so paste_by_box is disabled.')
+            return results['gt_masks']
+        else:
+            if not self.paste_by_box:
+                raise RuntimeError('results does not contain masks.')
+            return results['gt_bboxes'].create_masks(results['img'].shape[:2])
+
     def _select_object(self, results: dict) -> dict:
         """Select some objects from the source results."""
         bboxes = results['gt_bboxes']
         labels = results['gt_bboxes_labels']
-        masks = results['gt_masks']
+        masks = self.get_gt_masks(results)
         ignore_flags = results['gt_ignore_flags']
 
         selected_inds = self._get_selected_inds(bboxes.shape[0])
@@ -3013,7 +3039,7 @@ def _copy_paste(self, dst_results: dict, src_results: dict) -> dict:
         dst_img = dst_results['img']
         dst_bboxes = dst_results['gt_bboxes']
         dst_labels = dst_results['gt_bboxes_labels']
-        dst_masks = dst_results['gt_masks']
+        dst_masks = self.get_gt_masks(dst_results)
         dst_ignore_flags = dst_results['gt_ignore_flags']
 
         src_img = src_results['img']
@@ -3071,7 +3097,8 @@ def __repr__(self):
         repr_str += f'(max_num_pasted={self.max_num_pasted}, '
         repr_str += f'bbox_occluded_thr={self.bbox_occluded_thr}, '
         repr_str += f'mask_occluded_thr={self.mask_occluded_thr}, '
-        repr_str += f'selected={self.selected})'
+        repr_str += f'selected={self.selected}), '
+        repr_str += f'paste_by_box={self.paste_by_box})'
         return repr_str
 
 

mmdet/structures/bbox/horizontal_boxes.py

@@ -335,6 +335,26 @@ def find_inside_points(self,
         return (points[..., 0] >= x_min) & (points[..., 0] <= x_max) & \
             (points[..., 1] >= y_min) & (points[..., 1] <= y_max)
 
+    def create_masks(self, img_shape: Tuple[int, int]) -> BitmapMasks:
+        """
+        Args:
+            img_shape (Tuple[int, int]): A tuple of image height and width.
+
+        Returns:
+            :obj:`BitmapMasks`: Converted masks
+        """
+        img_h, img_w = img_shape
+        boxes = self.tensor
+
+        xmin, ymin = boxes[:, 0:1], boxes[:, 1:2]
+        xmax, ymax = boxes[:, 2:3], boxes[:, 3:4]
+        gt_masks = np.zeros((len(boxes), img_h, img_w), dtype=np.uint8)
+        for i in range(len(boxes)):
+            gt_masks[i,
+                     int(ymin[i]):int(ymax[i]),
+                     int(xmin[i]):int(xmax[i])] = 1
+        return BitmapMasks(gt_masks, img_h, img_w)
+
     @staticmethod
     def overlaps(boxes1: BaseBoxes,
                  boxes2: BaseBoxes,

tests/test_datasets/test_transforms/test_transforms.py

@@ -1453,6 +1453,26 @@ def test_transform(self):
         }]
         results = transform(results)
 
+        # test copypaste with an empty mask results
+        transform = CopyPaste()
+        results = copy.deepcopy(self.dst_results)
+        results = {k: v for k, v in results.items() if 'mask' not in k}
+        results['mix_results'] = [copy.deepcopy(self.src_results)]
+        with self.assertRaises(RuntimeError):
+            results = transform(results)
+
+        # test copypaste with boxes as masks
+        transform = CopyPaste(paste_by_box=True)
+        results = copy.deepcopy(self.dst_results)
+        results = {k: v for k, v in results.items() if 'mask' not in k}
+        src_results = copy.deepcopy(self.src_results)
+        src_results = {k: v for k, v in src_results.items() if 'mask' not in k}
+        results['mix_results'] = [src_results]
+        results = transform(results)
+
+        self.assertEqual(results['img'].shape[:2],
+                         self.dst_results['img'].shape[:2])
+
     def test_transform_use_box_type(self):
         src_results = copy.deepcopy(self.src_results)
         src_results['gt_bboxes'] = HorizontalBoxes(src_results['gt_bboxes'])
@@ -1524,7 +1544,8 @@ def test_repr(self):
             repr(transform), ('CopyPaste(max_num_pasted=100, '
                               'bbox_occluded_thr=10, '
                               'mask_occluded_thr=300, '
-                              'selected=True)'))
+                              'selected=True), '
+                              'paste_by_box=False)'))
 
 
 class TestAlbu(unittest.TestCase):