Upload hr.py

ComfyUI/hr.py

@@ -0,0 +1,170 @@
+import os
+import random
+import sys
+from typing import Sequence, Mapping, Any, Union
+import torch
+
+
+def get_value_at_index(obj: Union[Sequence, Mapping], index: int) -> Any:
+    """Returns the value at the given index of a sequence or mapping.
+
+    If the object is a sequence (like list or string), returns the value at the given index.
+    If the object is a mapping (like a dictionary), returns the value at the index-th key.
+
+    Some return a dictionary, in these cases, we look for the "results" key
+
+    Args:
+        obj (Union[Sequence, Mapping]): The object to retrieve the value from.
+        index (int): The index of the value to retrieve.
+
+    Returns:
+        Any: The value at the given index.
+
+    Raises:
+        IndexError: If the index is out of bounds for the object and the object is not a mapping.
+    """
+    try:
+        return obj[index]
+    except KeyError:
+        return obj["result"][index]
+
+
+def find_path(name: str, path: str = None) -> str:
+    """
+    Recursively looks at parent folders starting from the given path until it finds the given name.
+    Returns the path as a Path object if found, or None otherwise.
+    """
+    # If no path is given, use the current working directory
+    if path is None:
+        path = os.getcwd()
+
+    # Check if the current directory contains the name
+    if name in os.listdir(path):
+        path_name = os.path.join(path, name)
+        print(f"{name} found: {path_name}")
+        return path_name
+
+    # Get the parent directory
+    parent_directory = os.path.dirname(path)
+
+    # If the parent directory is the same as the current directory, we've reached the root and stop the search
+    if parent_directory == path:
+        return None
+
+    # Recursively call the function with the parent directory
+    return find_path(name, parent_directory)
+
+
+def add_comfyui_directory_to_sys_path() -> None:
+    """
+    Add 'ComfyUI' to the sys.path
+    """
+    comfyui_path = find_path("ComfyUI")
+    if comfyui_path is not None and os.path.isdir(comfyui_path):
+        sys.path.append(comfyui_path)
+        print(f"'{comfyui_path}' added to sys.path")
+
+
+def add_extra_model_paths() -> None:
+    """
+    Parse the optional extra_model_paths.yaml file and add the parsed paths to the sys.path.
+    """
+    try:
+        from main import load_extra_path_config
+    except ImportError:
+        print(
+            "Could not import load_extra_path_config from main.py. Looking in utils.extra_config instead."
+        )
+        from utils.extra_config import load_extra_path_config
+
+    extra_model_paths = find_path("extra_model_paths.yaml")
+
+    if extra_model_paths is not None:
+        load_extra_path_config(extra_model_paths)
+    else:
+        print("Could not find the extra_model_paths config file.")
+
+
+add_comfyui_directory_to_sys_path()
+add_extra_model_paths()
+
+
+def import_custom_nodes() -> None:
+    """Find all custom nodes in the custom_nodes folder and add those node objects to NODE_CLASS_MAPPINGS
+
+    This function sets up a new asyncio event loop, initializes the PromptServer,
+    creates a PromptQueue, and initializes the custom nodes.
+    """
+    import asyncio
+    import execution
+    from nodes import init_extra_nodes
+    import server
+
+    # Creating a new event loop and setting it as the default loop
+    loop = asyncio.new_event_loop()
+    asyncio.set_event_loop(loop)
+
+    # Creating an instance of PromptServer with the loop
+    server_instance = server.PromptServer(loop)
+    execution.PromptQueue(server_instance)
+
+    # Initializing custom nodes
+    init_extra_nodes()
+
+
+from nodes import NODE_CLASS_MAPPINGS
+
+
+def main():
+    import_custom_nodes()
+    with torch.inference_mode():
+        checkpointloadersimple = NODE_CLASS_MAPPINGS["CheckpointLoaderSimple"]()
+        checkpointloadersimple_4 = checkpointloadersimple.load_checkpoint(
+            ckpt_name="DreamShaper_8_pruned.safetensors"
+        )
+
+        emptylatentimage = NODE_CLASS_MAPPINGS["EmptyLatentImage"]()
+        emptylatentimage_5 = emptylatentimage.generate(
+            width=512, height=512, batch_size=1
+        )
+
+        cliptextencode = NODE_CLASS_MAPPINGS["CLIPTextEncode"]()
+        cliptextencode_6 = cliptextencode.encode(
+            text="Indian Cricket Team is playing against Australia,",
+            clip=get_value_at_index(checkpointloadersimple_4, 1),
+        )
+
+        cliptextencode_7 = cliptextencode.encode(
+            text="text, watermark", clip=get_value_at_index(checkpointloadersimple_4, 1)
+        )
+
+        ksampler = NODE_CLASS_MAPPINGS["KSampler"]()
+        vaedecode = NODE_CLASS_MAPPINGS["VAEDecode"]()
+        saveimage = NODE_CLASS_MAPPINGS["SaveImage"]()
+
+        for q in range(1):
+            ksampler_3 = ksampler.sample(
+                seed=random.randint(1, 2**64),
+                steps=20,
+                cfg=8,
+                sampler_name="euler",
+                scheduler="normal",
+                denoise=1,
+                model=get_value_at_index(checkpointloadersimple_4, 0),
+                positive=get_value_at_index(cliptextencode_6, 0),
+                negative=get_value_at_index(cliptextencode_7, 0),
+                latent_image=get_value_at_index(emptylatentimage_5, 0),
+            )
+
+            vaedecode_8 = vaedecode.decode(
+                samples=get_value_at_index(ksampler_3, 0),
+                vae=get_value_at_index(checkpointloadersimple_4, 2),
+            )
+
+            saveimage_9 = saveimage.save_images(
+                filename_prefix="ComfyUI", images=get_value_at_index(vaedecode_8, 0)
+            )
+
+
+if __name__ == "__main__":
+    main()