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[compatibility] Fix torchvision transforms NotImplementedError #104

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[compatibility] Fix torchvision transforms NotImplementedError #104

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d38b1eb
fix compatibility
Jun 28, 2025
c5b47c7
Refactor transform method for padding functionality
jjkkttnn Sep 26, 2025
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31 changes: 31 additions & 0 deletions engine/data/transforms/_transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -70,6 +70,10 @@ def _transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
fill = self._fill[type(inpt)]
padding = params['padding']
return F.pad(inpt, padding=padding, fill=fill, padding_mode=self.padding_mode) # type: ignore[arg-type]

# Compatibility with torchvision>0.20.0
def transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
return self._transform(inpt, params)

def __call__(self, *inputs: Any) -> Any:
outputs = super().forward(*inputs)
Expand All @@ -91,6 +95,7 @@ def __call__(self, *inputs: Any) -> Any:
return super().forward(*inputs)



@register()
class ConvertBoxes(T.Transform):
_transformed_types = (
Expand All @@ -112,6 +117,19 @@ def _transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
inpt = inpt / torch.tensor(spatial_size[::-1]).tile(2)[None]

return inpt

# Compatibility with torchvision>0.20.0
def transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
spatial_size = getattr(inpt, _boxes_keys[1])
if self.fmt:
in_fmt = inpt.format.value.lower()
inpt = torchvision.ops.box_convert(inpt, in_fmt=in_fmt, out_fmt=self.fmt.lower())
inpt = convert_to_tv_tensor(inpt, key='boxes', box_format=self.fmt.upper(), spatial_size=spatial_size)

if self.normalize:
inpt = inpt / torch.tensor(spatial_size[::-1]).tile(2)[None]

return inpt


@register()
Expand All @@ -135,3 +153,16 @@ def _transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
inpt = Image(inpt)

return inpt

# Compatibility with torchvision>0.20.0
def transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
inpt = F.pil_to_tensor(inpt)
if self.dtype == 'float32':
inpt = inpt.float()

if self.scale:
inpt = inpt / 255.

inpt = Image(inpt)

return inpt