update scales and img_shape (#1871)

mmcv/transforms/processing.py

@@ -438,8 +438,7 @@ class CenterCrop(BaseTransform):
     Modified Keys:
 
     - img
-    - height
-    - width
+    - img_shape
     - gt_seg_map (optional)
     - gt_bboxes (optional)
     - gt_keypoints (optional)
@@ -499,10 +498,9 @@ class CenterCrop(BaseTransform):
         """
         if results.get('img', None) is not None:
             img = mmcv.imcrop(results['img'], bboxes=bboxes)
-            img_shape = img.shape
+            img_shape = img.shape[:2]
             results['img'] = img
-            results['height'] = img_shape[0]
-            results['width'] = img_shape[1]
+            results['img_shape'] = img_shape
             results['pad_shape'] = img_shape
 
     def _crop_seg_map(self, results: dict, bboxes: np.ndarray) -> None:
@@ -725,7 +723,7 @@ class MultiScaleFlipAug(BaseTransform):
 
         dict(
             type='MultiScaleFlipAug',
-            img_scale=[(1333, 400), (1333, 800)],
+            scales=[(1333, 400), (1333, 800)],
             flip=True,
             transforms=[
                 dict(type='Normalize', **img_norm_cfg),
@@ -734,7 +732,7 @@ class MultiScaleFlipAug(BaseTransform):
                 dict(type='Collect', keys=['img'])
             ])
 
-    ``results`` will be resized using all the sizes in ``img_scale``.
+    ``results`` will be resized using all the sizes in ``scales``.
     If ``flip`` is True, then flipped results will also be added into output
     list.
 
@@ -769,7 +767,7 @@ class MultiScaleFlipAug(BaseTransform):
     Args:
         transforms (list[dict]): Transforms to be applied to each resized
             and flipped data.
-        img_scale (tuple | list[tuple] | None): Images scales for resizing.
+        scales (tuple | list[tuple] | None): Images scales for resizing.
         scale_factor (float or tuple[float]): Scale factors for resizing.
             Defaults to None.
         allow_flip (bool): Whether apply flip augmentation. Defaults to False.
@@ -787,7 +785,7 @@ class MultiScaleFlipAug(BaseTransform):
     def __init__(
         self,
         transforms: List[dict],
-        img_scale: Optional[Union[Tuple, List[Tuple]]] = None,
+        scales: Optional[Union[Tuple, List[Tuple]]] = None,
         scale_factor: Optional[Union[float, List[float]]] = None,
         allow_flip: bool = False,
         flip_direction: Union[str, List[str]] = 'horizontal',
@@ -797,17 +795,16 @@ class MultiScaleFlipAug(BaseTransform):
         super().__init__()
         self.transforms = Compose(transforms)  # type: ignore
 
-        if img_scale is not None:
-            self.img_scale = img_scale if isinstance(img_scale,
-                                                     list) else [img_scale]
+        if scales is not None:
+            self.scales = scales if isinstance(scales, list) else [scales]
             self.scale_key = 'scale'
-            assert mmcv.is_list_of(self.img_scale, tuple)
+            assert mmcv.is_list_of(self.scales, tuple)
         else:
-            # if ``img_scale`` and ``scale_factor`` both be ``None``
+            # if ``scales`` and ``scale_factor`` both be ``None``
             if scale_factor is None:
-                self.img_scale = [1.]
+                self.scales = [1.]
             else:
-                self.img_scale = scale_factor if isinstance(
+                self.scales = scale_factor if isinstance(
                     scale_factor, list) else [scale_factor]
             self.scale_key = 'scale_factor'
 
@@ -838,7 +835,7 @@ class MultiScaleFlipAug(BaseTransform):
         if self.allow_flip:
             flip_args += [(True, direction)
                           for direction in self.flip_direction]
-        for scale in self.img_scale:
+        for scale in self.scales:
             for flip, direction in flip_args:
                 _resize_cfg = self.resize_cfg.copy()
                 _resize_cfg.update({self.scale_key: scale})
@@ -864,7 +861,7 @@ class MultiScaleFlipAug(BaseTransform):
     def __repr__(self) -> str:
         repr_str = self.__class__.__name__
         repr_str += f', transforms={self.transforms}'
-        repr_str += f', img_scale={self.img_scale}'
+        repr_str += f', scales={self.scales}'
         repr_str += f', allow_flip={self.allow_flip}'
         repr_str += f', flip_direction={self.flip_direction}'
         return repr_str
@@ -933,8 +930,8 @@ class RandomChoiceResize(BaseTransform):
         """Randomly select an scale from given candidates.
 
         Returns:
-            (tuple, int): Returns a tuple ``(img_scale, scale_dix)``,
-            where ``img_scale`` is the selected image scale and
+            (tuple, int): Returns a tuple ``(scale, scale_dix)``,
+            where ``scale`` is the selected image scale and
             ``scale_idx`` is the selected index in the given candidates.
         """
 

tests/test_transforms/test_transforms_processing.py

@@ -291,8 +291,7 @@ class TestCenterCrop:
         transform = dict(type='CenterCrop', crop_size=224)
         center_crop_module = TRANSFORMS.build(transform)
         results = center_crop_module(results)
-        assert results['height'] == 224
-        assert results['width'] == 224
+        assert results['img_shape'] == (224, 224)
         assert (results['img'] == self.original_img[38:262, 88:312, ...]).all()
         assert (results['gt_seg_map'] == self.gt_semantic_map[38:262,
                                                               88:312]).all()
@@ -309,8 +308,7 @@ class TestCenterCrop:
         results = self.reset_results(results, self.original_img,
                                      self.gt_semantic_map)
         results = center_crop_module(results)
-        assert results['height'] == 224
-        assert results['width'] == 224
+        assert results['img_shape'] == (224, 224)
         assert (results['img'] == self.original_img[38:262, 88:312, ...]).all()
         assert (results['gt_seg_map'] == self.gt_semantic_map[38:262,
                                                               88:312]).all()
@@ -327,8 +325,7 @@ class TestCenterCrop:
         results = self.reset_results(results, self.original_img,
                                      self.gt_semantic_map)
         results = center_crop_module(results)
-        assert results['height'] == 256
-        assert results['width'] == 224
+        assert results['img_shape'] == (256, 224)
         assert (results['img'] == self.original_img[22:278, 88:312, ...]).all()
         assert (results['gt_seg_map'] == self.gt_semantic_map[22:278,
                                                               88:312]).all()
@@ -346,8 +343,7 @@ class TestCenterCrop:
         results = self.reset_results(results, self.original_img,
                                      self.gt_semantic_map)
         results = center_crop_module(results)
-        assert results['height'] == 300
-        assert results['width'] == 400
+        assert results['img_shape'] == (300, 400)
         assert (results['img'] == self.original_img).all()
         assert (results['gt_seg_map'] == self.gt_semantic_map).all()
         assert np.equal(results['gt_bboxes'],
@@ -364,8 +360,7 @@ class TestCenterCrop:
         results = self.reset_results(results, self.original_img,
                                      self.gt_semantic_map)
         results = center_crop_module(results)
-        assert results['height'] == 300
-        assert results['width'] == 400
+        assert results['img_shape'] == (300, 400)
         assert (results['img'] == self.original_img).all()
         assert (results['gt_seg_map'] == self.gt_semantic_map).all()
         assert np.equal(results['gt_bboxes'],
@@ -385,8 +380,7 @@ class TestCenterCrop:
         results = self.reset_results(results, self.original_img,
                                      self.gt_semantic_map)
         results = center_crop_module(results)
-        assert results['height'] == 600
-        assert results['width'] == 200
+        assert results['img_shape'] == (600, 200)
         assert results['img'].shape[:2] == results['gt_seg_map'].shape
         assert (results['img'][300:600, 100:300, ...] == 12).all()
         assert (results['gt_seg_map'][300:600, 100:300] == 255).all()
@@ -409,8 +403,7 @@ class TestCenterCrop:
         results = self.reset_results(results, self.original_img,
                                      self.gt_semantic_map)
         results = center_crop_module(results)
-        assert results['height'] == 600
-        assert results['width'] == 200
+        assert results['img_shape'] == (600, 200)
         assert (results['img'][300:600, 100:300, ...] == 13).all()
         assert (results['gt_seg_map'][300:600, 100:300] == 33).all()
         assert np.equal(results['gt_bboxes'],
@@ -427,8 +420,7 @@ class TestCenterCrop:
         results = self.reset_results(results, self.original_img,
                                      self.gt_semantic_map)
         results = center_crop_module(results)
-        assert results['height'] == img_height
-        assert results['width'] == img_width // 2
+        assert results['img_shape'] == (img_height, img_width // 2)
         assert (results['img'] == self.original_img[:, 100:300, ...]).all()
         assert (results['gt_seg_map'] == self.gt_semantic_map[:,
                                                               100:300]).all()
@@ -446,8 +438,7 @@ class TestCenterCrop:
         results = self.reset_results(results, self.original_img,
                                      self.gt_semantic_map)
         results = center_crop_module(results)
-        assert results['height'] == img_height // 2
-        assert results['width'] == img_width
+        assert results['img_shape'] == (img_height // 2, img_width)
         assert (results['img'] == self.original_img[75:225, ...]).all()
         assert (results['gt_seg_map'] == self.gt_semantic_map[75:225,
                                                               ...]).all()
@@ -557,17 +548,17 @@ class TestMultiScaleFlipAug:
         cls.original_img = copy.deepcopy(cls.img)
 
     def test_error(self):
-        # test assertion if img_scale is not tuple or list of tuple
+        # test assertion if scales is not tuple or list of tuple
         with pytest.raises(AssertionError):
             transform = dict(
-                type='MultiScaleFlipAug', img_scale=[1333, 800], transforms=[])
+                type='MultiScaleFlipAug', scales=[1333, 800], transforms=[])
             TRANSFORMS.build(transform)
 
         # test assertion if flip_direction is not str or list of str
         with pytest.raises(AssertionError):
             transform = dict(
                 type='MultiScaleFlipAug',
-                img_scale=[(1333, 800)],
+                scales=[(1333, 800)],
                 flip_direction=1,
                 transforms=[])
             TRANSFORMS.build(transform)
@@ -579,7 +570,7 @@ class TestMultiScaleFlipAug:
         transform = dict(
             type='MultiScaleFlipAug',
             transforms=[dict(type='MockPackTaskInputs')],
-            img_scale=[(1333, 800), (800, 600), (640, 480)],
+            scales=[(1333, 800), (800, 600), (640, 480)],
             allow_flip=True,
             flip_direction=['horizontal', 'vertical', 'diagonal'])
         multi_scale_flip_aug_module = TRANSFORMS.build(transform)
@@ -592,7 +583,7 @@ class TestMultiScaleFlipAug:
         transform = dict(
             type='MultiScaleFlipAug',
             transforms=[dict(type='MockPackTaskInputs')],
-            img_scale=[(1333, 800), (800, 600), (640, 480)],
+            scales=[(1333, 800), (800, 600), (640, 480)],
             allow_flip=False,
             flip_direction=['horizontal', 'vertical', 'diagonal'])
         multi_scale_flip_aug_module = TRANSFORMS.build(transform)
@@ -615,7 +606,7 @@ class TestMultiScaleFlipAug:
         transform = dict(
             type='MultiScaleFlipAug',
             transforms=transforms_cfg,
-            img_scale=[(1333, 800), (800, 600), (640, 480)],
+            scales=[(1333, 800), (800, 600), (640, 480)],
             allow_flip=True,
             flip_direction=['horizontal', 'vertical', 'diagonal'])
         multi_scale_flip_aug_module = TRANSFORMS.build(transform)