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fix: resize can take list as input
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src/diffusers/image_processor.py

Lines changed: 15 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -467,17 +467,17 @@ def _resize_and_crop(
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def resize(
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self,
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image: Union[PIL.Image.Image, np.ndarray, torch.Tensor],
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image: PipelineImageInput,
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height: int,
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width: int,
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resize_mode: str = "default", # "default", "fill", "crop"
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) -> Union[PIL.Image.Image, np.ndarray, torch.Tensor]:
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) -> PipelineImageInput:
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"""
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Resize image.
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Args:
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image (`PIL.Image.Image`, `np.ndarray` or `torch.Tensor`):
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The image input, can be a PIL image, numpy array or pytorch tensor.
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image (`torch.Tensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.Tensor]`, `List[PIL.Image.Image]`, or `List[np.ndarray]`):
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The image batch input, can be a PIL image, numpy array or pytorch tensor, or a list of these elements.
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height (`int`):
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The height to resize to.
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width (`int`):
@@ -492,7 +492,7 @@ def resize(
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supported for PIL image input.
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Returns:
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`PIL.Image.Image`, `np.ndarray` or `torch.Tensor`:
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`torch.Tensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.Tensor]`, `List[PIL.Image.Image]`, or `List[np.ndarray]`:
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The resized image.
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"""
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if resize_mode != "default" and not isinstance(image, PIL.Image.Image):
@@ -523,6 +523,16 @@ def resize(
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size=(height, width),
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)
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image = self.pt_to_numpy(image)
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elif isinstance(image, list):
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image = [
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self.resize(
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img,
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height=height,
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width=width,
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resize_mode=resize_mode,
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)
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for img in image
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]
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return image
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def binarize(self, image: PIL.Image.Image) -> PIL.Image.Image:

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