add github action

https://github.com/ltdrdata/ComfyUI-Impact-Subpack/issues/13

.github/workflows/publish.yml

@@ -0,0 +1,21 @@
+name: Publish to Comfy registry
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - main
+    paths:
+      - "pyproject.toml"
+
+jobs:
+  publish-node:
+    name: Publish Custom Node to registry
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v4
+      - name: Publish Custom Node
+        uses: Comfy-Org/publish-node-action@main
+        with:
+          ## Add your own personal access token to your Github Repository secrets and reference it here.
+          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}

README.md

@@ -15,6 +15,22 @@ This node pack provides nodes that complement the [ComfyUI Impact Pack](https://
 * civitai/[adetailer](https://civitai.com/search/models?sortBy=models_v5&query=adetailer) - You can download various types detection models....Many models are associated with NSFW content.
 
 
+## How To Install?
+
+### Install via ComfyUI-Manager (Recommended)
+* Search `ComfyUI Impact Subpack` in ComfyUI-Manager and click `Install` button.
+
+### Manual Install (Not Recommended)
+1. `cd custom_nodes`
+2. `git clone https://github.com/ltdrdata/ComfyUI-Impact-Subpack`
+3. `cd ComfyUI-Impact-Subpack`
+4. `pip install -r requirements.txt`
+    * **IMPORTANT**:
+        * You must install it within the Python environment where ComfyUI is running.
+        * For the portable version, use `<installed path>\python_embeded\python.exe -m pip` instead of `pip`. For a `venv`, activate the `venv` first and then use `pip`.
+5. Restart ComfyUI
+
+
 ## Credits
 
 ComfyUI/[ComfyUI](https://github.com/comfyanonymous/ComfyUI) - A powerful and modular stable diffusion GUI.

__init__.py

@@ -6,10 +6,11 @@
 """
 
 import importlib
+import logging
 
-version_code = [1, 0]
+version_code = [1, 2]
 version_str = f"V{version_code[0]}.{version_code[1]}" + (f'.{version_code[2]}' if len(version_code) > 2 else '')
-print(f"### Loading: ComfyUI-Impact-Subpack ({version_str})")
+logging.info(f"### Loading: ComfyUI-Impact-Subpack ({version_str})")
 
 node_list = [
     "subpack_nodes",

modules/subcore.py

@@ -1,12 +1,12 @@
-from pathlib import Path
 from PIL import Image
 
 import cv2
 import numpy as np
-from torchvision.transforms.functional import to_pil_image
 import torch
 from collections import namedtuple
 from . import utils
+import inspect
+import logging
 
 
 orig_torch_load = torch.load
@@ -39,27 +39,101 @@ def create_segmasks(results):
 
 try:
     from ultralytics import YOLO
+    from ultralytics.nn.tasks import DetectionModel
+    from ultralytics.nn.tasks import SegmentationModel
+    from ultralytics.utils import IterableSimpleNamespace
+    from ultralytics.utils.tal import TaskAlignedAssigner
+    import ultralytics.nn.modules as modules
+    import ultralytics.nn.modules.block as block_modules
+    import torch.nn.modules as torch_modules
+    import ultralytics.utils.loss as loss_modules
+    import dill._dill
+    from numpy.core.multiarray import scalar
+    from numpy import dtype
+    from numpy.dtypes import Float64DType
+
+    torch_whitelist = []
+
+    # https://github.com/comfyanonymous/ComfyUI/issues/5516#issuecomment-2466152838
+    def build_torch_whitelist():
+        """
+        For security, only a limited set of namespaces is allowed during loading.
+
+        Since the same module may be identified by different namespaces depending on the model,
+        some modules are additionally registered with aliases to ensure backward compatibility.
+        """
+        global torch_whitelist
+
+        for name, obj in inspect.getmembers(modules):
+            if inspect.isclass(obj) and obj.__module__.startswith("ultralytics.nn.modules"):
+                aliasObj = type(name, (obj,), {})
+                aliasObj.__module__ = "ultralytics.nn.modules"
+
+                torch_whitelist.append(obj)
+                torch_whitelist.append(aliasObj)
+
+        for name, obj in inspect.getmembers(block_modules):
+            if inspect.isclass(obj) and obj.__module__.startswith("ultralytics.nn.modules"):
+                aliasObj = type(name, (obj,), {})
+                aliasObj.__module__ = "ultralytics.nn.modules.block"
+
+                torch_whitelist.append(obj)
+                torch_whitelist.append(aliasObj)
+
+        for name, obj in inspect.getmembers(loss_modules):
+            if inspect.isclass(obj) and obj.__module__.startswith("ultralytics.utils.loss"):
+                aliasObj = type(name, (obj,), {})
+                aliasObj.__module__ = "ultralytics.yolo.utils.loss"
+
+                torch_whitelist.append(obj)
+                torch_whitelist.append(aliasObj)
+
+        for name, obj in inspect.getmembers(torch_modules):
+            if inspect.isclass(obj) and obj.__module__.startswith("torch.nn.modules"):
+                torch_whitelist.append(obj)
+
+        aliasIterableSimpleNamespace = type("IterableSimpleNamespace", (IterableSimpleNamespace,), {})
+        aliasIterableSimpleNamespace.__module__ = "ultralytics.yolo.utils"
+
+        aliasTaskAlignedAssigner = type("TaskAlignedAssigner", (TaskAlignedAssigner,), {})
+        aliasTaskAlignedAssigner.__module__ = "ultralytics.yolo.utils.tal"
+
+        aliasYOLOv10DetectionModel = type("YOLOv10DetectionModel", (DetectionModel,), {})
+        aliasYOLOv10DetectionModel.__module__ = "ultralytics.nn.tasks"
+        aliasYOLOv10DetectionModel.__name__ = "YOLOv10DetectionModel"
+
+        aliasv10DetectLoss = type("v10DetectLoss", (loss_modules.E2EDetectLoss,), {})
+        aliasv10DetectLoss.__name__ = "v10DetectLoss"
+        aliasv10DetectLoss.__module__ = "ultralytics.utils.loss"
+
+        torch_whitelist += [DetectionModel, aliasYOLOv10DetectionModel, SegmentationModel, IterableSimpleNamespace,
+                            aliasIterableSimpleNamespace, TaskAlignedAssigner, aliasTaskAlignedAssigner, aliasv10DetectLoss,
+                            getattr, dill._dill._load_type, scalar, dtype, Float64DType]
+
+    build_torch_whitelist()
+
 except Exception as e:
-    print(e)
-    print(f"\n!!!!!\n\n[ComfyUI-Impact-Subpack] If this error occurs, please check the following link:\n\thttps://github.com/ltdrdata/ComfyUI-Impact-Pack/blob/Main/troubleshooting/TROUBLESHOOTING.md\n\n!!!!!\n")
+    logging.error(e)
+    logging.error("\n!!!!!\n\n[ComfyUI-Impact-Subpack] If this error occurs, please check the following link:\n\thttps://github.com/ltdrdata/ComfyUI-Impact-Pack/blob/Main/troubleshooting/TROUBLESHOOTING.md\n\n!!!!!\n")
     raise e
 
 # HOTFIX: https://github.com/ltdrdata/ComfyUI-Impact-Pack/issues/754
 # importing YOLO breaking original torch.load capabilities
 def torch_wrapper(*args, **kwargs):
-    kwargs['weights_only'] = False
-    # https://github.com/comfyanonymous/ComfyUI/issues/5516#issuecomment-2466152838
     return orig_torch_load(*args, **kwargs)
 
 torch.load = torch_wrapper
 
+
 def load_yolo(model_path: str):
-    try:
-        return YOLO(model_path)
-    except ModuleNotFoundError:
-        # https://github.com/ultralytics/ultralytics/issues/3856
-        YOLO("yolov8n.pt")
-        return YOLO(model_path)
+    # https://github.com/comfyanonymous/ComfyUI/issues/5516#issuecomment-2466152838
+    with torch.serialization.safe_globals(torch_whitelist):
+        try:
+            return YOLO(model_path)
+        except ModuleNotFoundError:
+            # https://github.com/ultralytics/ultralytics/issues/3856
+            YOLO("yolov8n.pt")
+            return YOLO(model_path)
 
 
 def inference_bbox(

modules/subpack_nodes.py

@@ -2,11 +2,19 @@ import os
 import folder_paths
 from . import subcore
 from . import utils
+import logging
 
-model_path = folder_paths.models_dir
-utils.add_folder_path_and_extensions("ultralytics_bbox", [os.path.join(model_path, "ultralytics", "bbox")], folder_paths.supported_pt_extensions)
-utils.add_folder_path_and_extensions("ultralytics_segm", [os.path.join(model_path, "ultralytics", "segm")], folder_paths.supported_pt_extensions)
-utils.add_folder_path_and_extensions("ultralytics", [os.path.join(model_path, "ultralytics")], folder_paths.supported_pt_extensions)
+
+def update_model_paths(model_path):
+    utils.add_folder_path_and_extensions("ultralytics_bbox", [os.path.join(model_path, "ultralytics", "bbox")], folder_paths.supported_pt_extensions)
+    utils.add_folder_path_and_extensions("ultralytics_segm", [os.path.join(model_path, "ultralytics", "segm")], folder_paths.supported_pt_extensions)
+    utils.add_folder_path_and_extensions("ultralytics", [os.path.join(model_path, "ultralytics")], folder_paths.supported_pt_extensions)
+    logging.info(f'[Impact Subpack] ultralytics_bbox: {os.path.join(model_path, "ultralytics", "bbox")}')
+    logging.info(f'[Impact Subpack] ultralytics_segm: {os.path.join(model_path, "ultralytics", "segm")}')
+
+update_model_paths(folder_paths.models_dir)
+if 'download_model_base' in folder_paths.folder_names_and_paths:
+    update_model_paths(folder_paths.get_folder_paths('download_model_base')[0])
 
 
 class UltralyticsDetectorProvider:

modules/utils.py

@@ -2,6 +2,7 @@ import folder_paths
 from PIL import Image
 import numpy as np
 import cv2
+import torch
 
 
 def add_folder_path_and_extensions(folder_name, full_folder_paths, extensions):

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-impact-subpack"
 description = "This node pack provides nodes that complement the Impact Pack, such as the UltralyticsDetectorProvider."
-version = "1.0"
+version = "1.2"
 license = { file = "LICENSE.txt" }
 dependencies = ["matplotlib", "ultralytics==8.3.40"]