Release on 09.11.24

comfy_extras/nodes_upscale_model.py

@@ -0,0 +1,84 @@
+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 #The 384.0 is an estimate of how much some of these models take, TODO: make it more accurate
+        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
+}