fixed
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@@ -27,7 +27,9 @@ def get_max_size (width, height, max, upscale="false"):
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else:
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fit_width = int(max * aspect_ratio)
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return (fit_width, fit_height, aspect_ratio)
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new_width, new_height = octal_sizes(fit_width, fit_height)
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return (new_width, new_height, aspect_ratio)
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def get_image_size(IMAGE) -> tuple[int, int]:
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samples = IMAGE.movedim(-1, 1)
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@@ -121,8 +123,7 @@ class FitResizeImage:
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size = get_image_size(image)
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img = tensor2pil(image)
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octalwidth, octalheight = octal_sizes(size[0], size[1])
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new_width, new_height, aspect_ratio = get_max_size(octalwidth, octalheight, max_size, upscale)
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new_width, new_height, aspect_ratio = get_max_size(size[0], size[1], max_size, upscale)
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resized_image = img.resize((new_width, new_height), resample=Image.Resampling(resample_filters[resampling]))
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@@ -180,8 +181,7 @@ class FitResizeLatent():
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size = get_image_size(image)
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img = tensor2pil(image)
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octalwidth, octalheight = octal_sizes(size[0], size[1])
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new_width, new_height, aspect_ratio = get_max_size(octalwidth, octalheight, max_size, upscale)
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new_width, new_height, aspect_ratio = get_max_size(size[0], size[1], max_size, upscale)
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resized_image = img.resize((new_width, new_height), resample=Image.Resampling(resample_filters[resampling]))
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tensor_img = pil2tensor(resized_image)
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@@ -286,9 +286,8 @@ class LoadToFitResizeLatent():
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img = tensor2pil(got_image)
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new_width, new_height, aspect_ratio = get_max_size(size[0], size[1], max_size, upscale)
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octalwidth, octalheight = octal_sizes(new_width, new_height)
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resized_image = img.resize((octalwidth, octalheight), resample=Image.Resampling(resample_filters[resampling]))
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resized_image = img.resize((new_width, new_height), resample=Image.Resampling(resample_filters[resampling]))
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tensor_img = pil2tensor(resized_image)
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# vae encode the image
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@@ -301,7 +300,7 @@ class LoadToFitResizeLatent():
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return (
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{"samples":batched},
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tensor_img,
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octalwidth,
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octalheight,
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new_width,
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new_height,
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aspect_ratio,
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)
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