53 lines
1.7 KiB
Python
53 lines
1.7 KiB
Python
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import os
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from comfy_extras.chainner_models import model_loading
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from comfy.sd import load_torch_file
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import comfy.model_management
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from nodes import filter_files_extensions, recursive_search, supported_ckpt_extensions
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import torch
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class UpscaleModelLoader:
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models_dir = os.path.join(os.path.dirname(os.path.dirname(os.path.realpath(__file__))), "models")
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upscale_model_dir = os.path.join(models_dir, "upscale_models")
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "model_name": (filter_files_extensions(recursive_search(s.upscale_model_dir), supported_ckpt_extensions), ),
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}}
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RETURN_TYPES = ("UPSCALE_MODEL",)
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FUNCTION = "load_model"
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CATEGORY = "loaders"
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def load_model(self, model_name):
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model_path = os.path.join(self.upscale_model_dir, model_name)
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sd = load_torch_file(model_path)
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out = model_loading.load_state_dict(sd).eval()
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return (out, )
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class ImageUpscaleWithModel:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "upscale_model": ("UPSCALE_MODEL",),
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"image": ("IMAGE",),
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}}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "upscale"
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CATEGORY = "image"
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def upscale(self, upscale_model, image):
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device = comfy.model_management.get_torch_device()
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upscale_model.to(device)
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in_img = image.movedim(-1,-3).to(device)
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with torch.inference_mode():
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s = upscale_model(in_img).cpu()
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upscale_model.cpu()
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s = torch.clamp(s.movedim(-3,-1), min=0, max=1.0)
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return (s,)
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NODE_CLASS_MAPPINGS = {
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"UpscaleModelLoader": UpscaleModelLoader,
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"ImageUpscaleWithModel": ImageUpscaleWithModel
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}
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