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[fix] Flux Kontext resize method #11863

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[fix] Flux Kontext resize method #11863

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2a24a6f
fix: resize can take list as input
Net-Mist Jul 4, 2025
eb323d0
test: add test for the resize method with list argument
Net-Mist Jul 5, 2025
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20 changes: 15 additions & 5 deletions src/diffusers/image_processor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -467,17 +467,17 @@ def _resize_and_crop(

def resize(
self,
image: Union[PIL.Image.Image, np.ndarray, torch.Tensor],
image: PipelineImageInput,
height: int,
width: int,
resize_mode: str = "default", # "default", "fill", "crop"
) -> Union[PIL.Image.Image, np.ndarray, torch.Tensor]:
) -> PipelineImageInput:
"""
Resize image.
Args:
image (`PIL.Image.Image`, `np.ndarray` or `torch.Tensor`):
The image input, can be a PIL image, numpy array or pytorch tensor.
image (`torch.Tensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.Tensor]`, `List[PIL.Image.Image]`, or `List[np.ndarray]`):
The image batch input, can be a PIL image, numpy array or pytorch tensor, or a list of these elements.
height (`int`):
The height to resize to.
width (`int`):
Expand All @@ -492,7 +492,7 @@ def resize(
supported for PIL image input.
Returns:
`PIL.Image.Image`, `np.ndarray` or `torch.Tensor`:
`torch.Tensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.Tensor]`, `List[PIL.Image.Image]`, or `List[np.ndarray]`:
The resized image.
"""
if resize_mode != "default" and not isinstance(image, PIL.Image.Image):
Expand Down Expand Up @@ -523,6 +523,16 @@ def resize(
size=(height, width),
)
image = self.pt_to_numpy(image)
elif isinstance(image, list):
image = [
self.resize(
img,
height=height,
width=width,
resize_mode=resize_mode,
)
for img in image
]
return image

def binarize(self, image: PIL.Image.Image) -> PIL.Image.Image:
Expand Down
13 changes: 13 additions & 0 deletions tests/others/test_image_processor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -308,3 +308,16 @@ def test_vae_image_processor_resize_np(self):
assert out_np.shape == exp_np_shape, (
f"resized image output shape '{out_np.shape}' didn't match expected shape '{exp_np_shape}'."
)

def test_vae_image_processor_resize_list_pt(self):
image_processor = VaeImageProcessor(do_resize=True, vae_scale_factor=1)
input_pt = self.dummy_sample
b, c, h, w = input_pt.shape
scale = 2
input_pt_list = [input_pt]
out_pt_list = image_processor.resize(image=input_pt_list, height=h // scale, width=w // scale)
exp_pt_shape = (b, c, h // scale, w // scale)
for out_pt in out_pt_list:
assert out_pt.shape == exp_pt_shape, (
f"resized image output shape '{out_pt.shape}' didn't match expected shape '{exp_pt_shape}'."
)