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Bug fix - tasks with an initial image were not resizing the initial image to the desired dimension
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@ -273,7 +273,7 @@ def mk_img(req: Request):
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else:
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else:
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handler = _img2img
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handler = _img2img
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init_image = load_img(req.init_image)
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init_image = load_img(req.init_image, opt_W, opt_H)
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init_image = init_image.to(device)
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init_image = init_image.to(device)
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if device != "cpu" and precision == "autocast":
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if device != "cpu" and precision == "autocast":
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@ -511,12 +511,15 @@ def load_model_from_config(ckpt, verbose=False):
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class UserInitiatedStop(Exception):
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class UserInitiatedStop(Exception):
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pass
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pass
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def load_img(img_str):
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def load_img(img_str, w0, h0):
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image = base64_str_to_img(img_str).convert("RGB")
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image = base64_str_to_img(img_str).convert("RGB")
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w, h = image.size
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w, h = image.size
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print(f"loaded input image of size ({w}, {h}) from base64")
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print(f"loaded input image of size ({w}, {h}) from base64")
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if h0 is not None and w0 is not None:
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h, w = h0, w0
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w, h = map(lambda x: x - x % 64, (w, h)) # resize to integer multiple of 64
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w, h = map(lambda x: x - x % 64, (w, h)) # resize to integer multiple of 64
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image = image.resize((w, h), resample=Image.LANCZOS)
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image = image.resize((w, h), resample=Image.Resampling.LANCZOS)
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image = np.array(image).astype(np.float32) / 255.0
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image = np.array(image).astype(np.float32) / 255.0
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image = image[None].transpose(0, 3, 1, 2)
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image = image[None].transpose(0, 3, 1, 2)
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image = torch.from_numpy(image)
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image = torch.from_numpy(image)
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