add tests for perspective start- / endpoints

test/prototype_transforms_kernel_infos.py

@@ -15,11 +15,14 @@
     get_num_channels,
     ImageLoader,
     InfoBase,
+    make_bounding_box_loader,
     make_bounding_box_loaders,
+    make_detection_mask_loader,
     make_image_loader,
     make_image_loaders,
     make_image_loaders_for_interpolation,
     make_mask_loaders,
+    make_video_loader,
     make_video_loaders,
     mark_framework_limitation,
     TestMark,
@@ -1168,12 +1171,18 @@ def reference_inputs_pad_bounding_box():
     [1.2405, 0.1772, -6.9113, 0.0463, 1.251, -5.235, 0.00013, 0.0018],
     [0.7366, -0.11724, 1.45775, -0.15012, 0.73406, 2.6019, -0.0072, -0.0063],
 ]
+_STARTPOINTS = [[0, 1], [2, 3], [4, 5], [6, 7]]
+_ENDPOINTS = [[9, 8], [7, 6], [5, 4], [3, 2]]
 
 
 def sample_inputs_perspective_image_tensor():
     for image_loader in make_image_loaders(sizes=["random"]):
         for fill in get_fills(num_channels=image_loader.num_channels, dtype=image_loader.dtype):
-            yield ArgsKwargs(image_loader, None, None, fill=fill, coefficients=_PERSPECTIVE_COEFFS[0])
+            yield ArgsKwargs(
+                image_loader, startpoints=None, endpoints=None, fill=fill, coefficients=_PERSPECTIVE_COEFFS[0]
+            )
+
+    yield ArgsKwargs(make_image_loader(), startpoints=_STARTPOINTS, endpoints=_ENDPOINTS)
 
 
 def reference_inputs_perspective_image_tensor():
@@ -1200,25 +1209,38 @@ def reference_inputs_perspective_image_tensor():
 def sample_inputs_perspective_bounding_box():
     for bounding_box_loader in make_bounding_box_loaders():
         yield ArgsKwargs(
-            bounding_box_loader, bounding_box_loader.format, None, None, coefficients=_PERSPECTIVE_COEFFS[0]
+            bounding_box_loader,
+            format=bounding_box_loader.format,
+            startpoints=None,
+            endpoints=None,
+            coefficients=_PERSPECTIVE_COEFFS[0],
         )
 
+    format = datapoints.BoundingBoxFormat.XYXY
+    yield ArgsKwargs(
+        make_bounding_box_loader(format=format), format=format, startpoints=_STARTPOINTS, endpoints=_ENDPOINTS
+    )
+
 
 def sample_inputs_perspective_mask():
     for mask_loader in make_mask_loaders(sizes=["random"]):
-        yield ArgsKwargs(mask_loader, None, None, coefficients=_PERSPECTIVE_COEFFS[0])
+        yield ArgsKwargs(mask_loader, startpoints=None, endpoints=None, coefficients=_PERSPECTIVE_COEFFS[0])
+
+    yield ArgsKwargs(make_detection_mask_loader(), startpoints=_STARTPOINTS, endpoints=_ENDPOINTS)
 
 
 def reference_inputs_perspective_mask():
     for mask_loader, perspective_coeffs in itertools.product(
         make_mask_loaders(extra_dims=[()], num_objects=[1]), _PERSPECTIVE_COEFFS
     ):
-        yield ArgsKwargs(mask_loader, None, None, coefficients=perspective_coeffs)
+        yield ArgsKwargs(mask_loader, startpoints=None, endpoints=None, coefficients=perspective_coeffs)
 
 
 def sample_inputs_perspective_video():
     for video_loader in make_video_loaders(sizes=["random"], num_frames=["random"]):
-        yield ArgsKwargs(video_loader, None, None, coefficients=_PERSPECTIVE_COEFFS[0])
+        yield ArgsKwargs(video_loader, startpoints=None, endpoints=None, coefficients=_PERSPECTIVE_COEFFS[0])
+
+    yield ArgsKwargs(make_video_loader(), startpoints=_STARTPOINTS, endpoints=_ENDPOINTS)
 
 
 KERNEL_INFOS.extend(

torchvision/prototype/datapoints/_bounding_box.py

@@ -176,7 +176,11 @@ def perspective(
         coefficients: Optional[List[float]] = None,
     ) -> BoundingBox:
         output = self._F.perspective_bounding_box(
-            self.as_subclass(torch.Tensor), startpoints, endpoints, self.format, coefficients=coefficients
+            self.as_subclass(torch.Tensor),
+            format=self.format,
+            startpoints=startpoints,
+            endpoints=endpoints,
+            coefficients=coefficients,
         )
         return BoundingBox.wrap_like(self, output)