Added missing typing annotations in datasets/_stereo_matching

torchvision/datasets/_stereo_matching.py

@@ -24,7 +24,7 @@ class StereoMatchingDataset(ABC, VisionDataset):
 
     _has_built_in_disparity_mask = False
 
-    def __init__(self, root: str, transforms: Optional[Callable] = None):
+    def __init__(self, root: str, transforms: Optional[Callable] = None) -> None:
         """
         Args:
             root(str): Root directory of the dataset.
@@ -58,7 +58,11 @@ def _read_img(self, file_path: Union[str, Path]) -> Image.Image:
             img = img.convert("RGB")
         return img
 
-    def _scan_pairs(self, paths_left_pattern: str, paths_right_pattern: Optional[str] = None):
+    def _scan_pairs(
+        self,
+        paths_left_pattern: str,
+        paths_right_pattern: Optional[str] = None,
+    ) -> List[Tuple[str, Optional[str]]]:
 
         left_paths = list(sorted(glob(paths_left_pattern)))
 
@@ -156,7 +160,7 @@ class CarlaStereo(StereoMatchingDataset):
         transforms (callable, optional): A function/transform that takes in a sample and returns a transformed version.
     """
 
-    def __init__(self, root: str, transforms: Optional[Callable] = None):
+    def __init__(self, root: str, transforms: Optional[Callable] = None) -> None:
         super().__init__(root, transforms)
 
         root = Path(root) / "carla-highres"
@@ -233,7 +237,7 @@ class Kitti2012Stereo(StereoMatchingDataset):
 
     _has_built_in_disparity_mask = True
 
-    def __init__(self, root: str, split: str = "train", transforms: Optional[Callable] = None):
+    def __init__(self, root: str, split: str = "train", transforms: Optional[Callable] = None) -> None:
         super().__init__(root, transforms)
 
         verify_str_arg(split, "split", valid_values=("train", "test"))
@@ -321,7 +325,7 @@ class Kitti2015Stereo(StereoMatchingDataset):
 
     _has_built_in_disparity_mask = True
 
-    def __init__(self, root: str, split: str = "train", transforms: Optional[Callable] = None):
+    def __init__(self, root: str, split: str = "train", transforms: Optional[Callable] = None) -> None:
         super().__init__(root, transforms)
 
         verify_str_arg(split, "split", valid_values=("train", "test"))
@@ -479,7 +483,7 @@ def __init__(
         use_ambient_views: bool = False,
         transforms: Optional[Callable] = None,
         download: bool = False,
-    ):
+    ) -> None:
         super().__init__(root, transforms)
 
         verify_str_arg(split, "split", valid_values=("train", "test", "additional"))
@@ -569,7 +573,7 @@ def _read_disparity(self, file_path: str) -> Tuple:
         valid_mask = (disparity_map > 0).squeeze(0)  # mask out invalid disparities
         return disparity_map, valid_mask
 
-    def _download_dataset(self, root: str):
+    def _download_dataset(self, root: str) -> None:
         base_url = "https://vision.middlebury.edu/stereo/data/scenes2014/zip"
         # train and additional splits have 2 different calibration settings
         root = Path(root) / "Middlebury2014"
@@ -670,7 +674,7 @@ def __init__(
         self,
         root: str,
         transforms: Optional[Callable] = None,
-    ):
+    ) -> None:
         super().__init__(root, transforms)
 
         root = Path(root) / "CREStereo"
@@ -755,7 +759,7 @@ class FallingThingsStereo(StereoMatchingDataset):
         transforms (callable, optional): A function/transform that takes in a sample and returns a transformed version.
     """
 
-    def __init__(self, root: str, variant: str = "single", transforms: Optional[Callable] = None):
+    def __init__(self, root: str, variant: str = "single", transforms: Optional[Callable] = None) -> None:
         super().__init__(root, transforms)
 
         root = Path(root) / "FallingThings"
@@ -874,7 +878,7 @@ def __init__(
         variant: str = "FlyingThings3D",
         pass_name: str = "clean",
         transforms: Optional[Callable] = None,
-    ):
+    ) -> None:
         super().__init__(root, transforms)
 
         root = Path(root) / "SceneFlow"
@@ -973,7 +977,7 @@ class SintelStereo(StereoMatchingDataset):
 
     _has_built_in_disparity_mask = True
 
-    def __init__(self, root: str, pass_name: str = "final", transforms: Optional[Callable] = None):
+    def __init__(self, root: str, pass_name: str = "final", transforms: Optional[Callable] = None) -> None:
         super().__init__(root, transforms)
 
         verify_str_arg(pass_name, "pass_name", valid_values=("final", "clean", "both"))
@@ -1080,7 +1084,7 @@ class InStereo2k(StereoMatchingDataset):
         transforms (callable, optional): A function/transform that takes in a sample and returns a transformed version.
     """
 
-    def __init__(self, root: str, split: str = "train", transforms: Optional[Callable] = None):
+    def __init__(self, root: str, split: str = "train", transforms: Optional[Callable] = None) -> None:
         super().__init__(root, transforms)
 
         root = Path(root) / "InStereo2k" / split
@@ -1095,7 +1099,7 @@ def __init__(self, root: str, split: str = "train", transforms: Optional[Callabl
         right_disparity_pattern = str(root / "*" / "right_disp.png")
         self._disparities = self._scan_pairs(left_disparity_pattern, right_disparity_pattern)
 
-    def _read_disparity(self, file_path: str) -> Tuple:
+    def _read_disparity(self, file_path: str) -> Tuple[np.ndarray, None]:
         disparity_map = np.asarray(Image.open(file_path), dtype=np.float32)
         # unsqueeze disparity to (C, H, W)
         disparity_map = disparity_map[None, :, :] / 1024.0
@@ -1169,7 +1173,7 @@ class ETH3DStereo(StereoMatchingDataset):
 
     _has_built_in_disparity_mask = True
 
-    def __init__(self, root: str, split: str = "train", transforms: Optional[Callable] = None):
+    def __init__(self, root: str, split: str = "train", transforms: Optional[Callable] = None) -> None:
         super().__init__(root, transforms)
 
         verify_str_arg(split, "split", valid_values=("train", "test"))