Upload comfy_pulid.py

comfy_pulid.py

@@ -0,0 +1,288 @@
+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 generate_image(prompt, structure_image, style_image, depth_strength, style_strength):
+    import_custom_nodes()
+    with torch.inference_mode():
+        vaeloader = NODE_CLASS_MAPPINGS["VAELoader"]()
+        vaeloader_10 = vaeloader.load_vae(vae_name="FLUX1/ae.safetensors")
+
+        dualcliploader = NODE_CLASS_MAPPINGS["DualCLIPLoader"]()
+        dualcliploader_11 = dualcliploader.load_clip(
+            clip_name1="clip_l.safetensors",
+            clip_name2="t5xxl_fp8_e4m3fn.safetensors",
+            type="flux",
+        )
+
+        loadimage = NODE_CLASS_MAPPINGS["LoadImage"]()
+        loadimage_97 = loadimage.load_image(image=structure_image)
+
+        pulidfluxinsightfaceloader = NODE_CLASS_MAPPINGS["PulidFluxInsightFaceLoader"]()
+        pulidfluxinsightfaceloader_98 = pulidfluxinsightfaceloader.load_insightface(
+            provider="CUDA"
+        )
+
+        pulidfluxmodelloader = NODE_CLASS_MAPPINGS["PulidFluxModelLoader"]()
+        pulidfluxmodelloader_99 = pulidfluxmodelloader.load_model(
+            pulid_file="pulid_flux_v0.9.1.safetensors"
+        )
+
+        pulidfluxevacliploader = NODE_CLASS_MAPPINGS["PulidFluxEvaClipLoader"]()
+        pulidfluxevacliploader_100 = pulidfluxevacliploader.load_eva_clip()
+
+        cliptextencode = NODE_CLASS_MAPPINGS["CLIPTextEncode"]()
+        cliptextencode_121 = cliptextencode.encode(
+            text=prompt, clip=get_value_at_index(dualcliploader_11, 0)
+        )
+
+        conditioningzeroout = NODE_CLASS_MAPPINGS["ConditioningZeroOut"]()
+        conditioningzeroout_116 = conditioningzeroout.zero_out(
+            conditioning=get_value_at_index(cliptextencode_121, 0)
+        )
+
+        loadimage_129 = loadimage.load_image(
+            image=style_image
+        )
+
+        getimagesize = NODE_CLASS_MAPPINGS["GetImageSize+"]()
+        getimagesize_113 = getimagesize.execute(
+            image=get_value_at_index(loadimage_129, 0)
+        )
+
+        imageresize = NODE_CLASS_MAPPINGS["ImageResize+"]()
+        imageresize_112 = imageresize.execute(
+            width=get_value_at_index(getimagesize_113, 0),
+            height=get_value_at_index(getimagesize_113, 1),
+            interpolation="nearest",
+            method="keep proportion",
+            condition="always",
+            multiple_of=0,
+            image=get_value_at_index(loadimage_129, 0),
+        )
+
+        layermask_personmaskultra = NODE_CLASS_MAPPINGS["LayerMask: PersonMaskUltra"]()
+        layermask_personmaskultra_120 = layermask_personmaskultra.person_mask_ultra(
+            face=True,
+            hair=False,
+            body=False,
+            clothes=False,
+            accessories=False,
+            background=False,
+            confidence=0.4,
+            detail_range=16,
+            black_point=0.01,
+            white_point=0.99,
+            process_detail=True,
+            images=get_value_at_index(imageresize_112, 0),
+        )
+
+        growmask = NODE_CLASS_MAPPINGS["GrowMask"]()
+        growmask_118 = growmask.expand_mask(
+            expand=43,
+            tapered_corners=True,
+            mask=get_value_at_index(layermask_personmaskultra_120, 1),
+        )
+
+        maskblur = NODE_CLASS_MAPPINGS["MaskBlur+"]()
+        maskblur_119 = maskblur.execute(
+            amount=60, device="auto", mask=get_value_at_index(growmask_118, 0)
+        )
+
+        inpaintmodelconditioning = NODE_CLASS_MAPPINGS["InpaintModelConditioning"]()
+        inpaintmodelconditioning_110 = inpaintmodelconditioning.encode(
+            noise_mask=True,
+            positive=get_value_at_index(cliptextencode_121, 0),
+            negative=get_value_at_index(conditioningzeroout_116, 0),
+            vae=get_value_at_index(vaeloader_10, 0),
+            pixels=get_value_at_index(imageresize_112, 0),
+            mask=get_value_at_index(maskblur_119, 0),
+        )
+
+        unetloader = NODE_CLASS_MAPPINGS["UNETLoader"]()
+        unetloader_111 = unetloader.load_unet(
+            unet_name="FLUX1/flux1-dev.safetensors", weight_dtype="fp8_e4m3fn"
+        )
+
+        randomnoise = NODE_CLASS_MAPPINGS["RandomNoise"]()
+        randomnoise_114 = randomnoise.get_noise(noise_seed=random.randint(1, 2**64))
+
+        ksamplerselect = NODE_CLASS_MAPPINGS["KSamplerSelect"]()
+        ksamplerselect_115 = ksamplerselect.get_sampler(sampler_name="euler")
+
+        applypulidflux = NODE_CLASS_MAPPINGS["ApplyPulidFlux"]()
+        repeatlatentbatch = NODE_CLASS_MAPPINGS["RepeatLatentBatch"]()
+        basicguider = NODE_CLASS_MAPPINGS["BasicGuider"]()
+        basicscheduler = NODE_CLASS_MAPPINGS["BasicScheduler"]()
+        samplercustomadvanced = NODE_CLASS_MAPPINGS["SamplerCustomAdvanced"]()
+        vaedecode = NODE_CLASS_MAPPINGS["VAEDecode"]()
+        saveimage = NODE_CLASS_MAPPINGS["SaveImage"]()
+
+        applypulidflux_101 = applypulidflux.apply_pulid_flux(
+            weight=1.1,
+            start_at=0,
+            end_at=1,
+            fusion="max",
+            fusion_weight_max=1,
+            fusion_weight_min=0,
+            train_step=1000,
+            use_gray=True,
+            model=get_value_at_index(unetloader_111, 0),
+            pulid_flux=get_value_at_index(pulidfluxmodelloader_99, 0),
+            eva_clip=get_value_at_index(pulidfluxevacliploader_100, 0),
+            face_analysis=get_value_at_index(pulidfluxinsightfaceloader_98, 0),
+            image=get_value_at_index(loadimage_97, 0),
+            unique_id=12000670301720322250,
+        )
+
+        repeatlatentbatch_107 = repeatlatentbatch.repeat(
+            amount=1, samples=get_value_at_index(inpaintmodelconditioning_110, 2)
+        )
+
+        basicguider_117 = basicguider.get_guider(
+            model=get_value_at_index(applypulidflux_101, 0),
+            conditioning=get_value_at_index(inpaintmodelconditioning_110, 0),
+        )
+
+        basicscheduler_130 = basicscheduler.get_sigmas(
+            scheduler="normal",
+            steps=14,
+            denoise=0.6,
+            model=get_value_at_index(unetloader_111, 0),
+        )
+
+        samplercustomadvanced_109 = samplercustomadvanced.sample(
+            noise=get_value_at_index(randomnoise_114, 0),
+            guider=get_value_at_index(basicguider_117, 0),
+            sampler=get_value_at_index(ksamplerselect_115, 0),
+            sigmas=get_value_at_index(basicscheduler_130, 0),
+            latent_image=get_value_at_index(repeatlatentbatch_107, 0),
+        )
+
+        vaedecode_122 = vaedecode.decode(
+            samples=get_value_at_index(samplercustomadvanced_109, 0),
+            vae=get_value_at_index(vaeloader_10, 0),
+        )
+
+        saveimage_127 = saveimage.save_images(
+            filename_prefix="ComfyUI", images=get_value_at_index(vaedecode_122, 0)
+        )
+        saved_path = f"output/{saveimage_127['ui']['images'][0]['filename']}"
+        return saved_path
+
+
+#if __name__ == "__main__":
+#    main()