| import os |
| import logging |
| from spandrel import ModelLoader, ImageModelDescriptor |
| from comfy import model_management |
| import torch |
| import comfy.utils |
| import folder_paths |
|
|
| try: |
| from spandrel_extra_arches import EXTRA_REGISTRY |
| from spandrel import MAIN_REGISTRY |
| MAIN_REGISTRY.add(*EXTRA_REGISTRY) |
| logging.info("Successfully imported spandrel_extra_arches: support for non commercial upscale models.") |
| except: |
| pass |
|
|
| class UpscaleModelLoader: |
| @classmethod |
| def INPUT_TYPES(s): |
| return {"required": { "model_name": (folder_paths.get_filename_list("upscale_models"), ), |
| }} |
| RETURN_TYPES = ("UPSCALE_MODEL",) |
| FUNCTION = "load_model" |
|
|
| CATEGORY = "loaders" |
|
|
| def load_model(self, model_name): |
| model_path = folder_paths.get_full_path_or_raise("upscale_models", model_name) |
| sd = comfy.utils.load_torch_file(model_path, safe_load=True) |
| if "module.layers.0.residual_group.blocks.0.norm1.weight" in sd: |
| sd = comfy.utils.state_dict_prefix_replace(sd, {"module.":""}) |
| out = ModelLoader().load_from_state_dict(sd).eval() |
|
|
| if not isinstance(out, ImageModelDescriptor): |
| raise Exception("Upscale model must be a single-image model.") |
|
|
| return (out, ) |
|
|
|
|
| class ImageUpscaleWithModel: |
| @classmethod |
| def INPUT_TYPES(s): |
| return {"required": { "upscale_model": ("UPSCALE_MODEL",), |
| "image": ("IMAGE",), |
| }} |
| RETURN_TYPES = ("IMAGE",) |
| FUNCTION = "upscale" |
|
|
| CATEGORY = "image/upscaling" |
|
|
| def upscale(self, upscale_model, image): |
| device = model_management.get_torch_device() |
|
|
| memory_required = model_management.module_size(upscale_model.model) |
| memory_required += (512 * 512 * 3) * image.element_size() * max(upscale_model.scale, 1.0) * 384.0 |
| memory_required += image.nelement() * image.element_size() |
| model_management.free_memory(memory_required, device) |
|
|
| upscale_model.to(device) |
| in_img = image.movedim(-1,-3).to(device) |
|
|
| tile = 512 |
| overlap = 32 |
|
|
| oom = True |
| while oom: |
| try: |
| steps = in_img.shape[0] * comfy.utils.get_tiled_scale_steps(in_img.shape[3], in_img.shape[2], tile_x=tile, tile_y=tile, overlap=overlap) |
| pbar = comfy.utils.ProgressBar(steps) |
| s = comfy.utils.tiled_scale(in_img, lambda a: upscale_model(a), tile_x=tile, tile_y=tile, overlap=overlap, upscale_amount=upscale_model.scale, pbar=pbar) |
| oom = False |
| except model_management.OOM_EXCEPTION as e: |
| tile //= 2 |
| if tile < 128: |
| raise e |
|
|
| upscale_model.to("cpu") |
| s = torch.clamp(s.movedim(-3,-1), min=0, max=1.0) |
| return (s,) |
|
|
| NODE_CLASS_MAPPINGS = { |
| "UpscaleModelLoader": UpscaleModelLoader, |
| "ImageUpscaleWithModel": ImageUpscaleWithModel |
| } |
|
|
