modified: release pinning ultralytics version

fixed: ruff check

.github/workflows/publish.yml

@@ -7,15 +7,19 @@ on:
     paths:
       - "pyproject.toml"
 
+permissions:
+  issues: write
+
 jobs:
   publish-node:
     name: Publish Custom Node to registry
     runs-on: ubuntu-latest
+    if: ${{ github.repository_owner == 'ltdrdata' }}
     steps:
       - name: Check out code
         uses: actions/checkout@v4
       - name: Publish Custom Node
-        uses: Comfy-Org/publish-node-action@main
+        uses: Comfy-Org/publish-node-action@v1
         with:
           ## Add your own personal access token to your Github Repository secrets and reference it here.
-          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}
+          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}

README.md

@@ -15,6 +15,13 @@ 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.
 
 
+## Paths
+* In `extra_model_paths.yaml`, you can add the following entries:
+- `ultralytics_bbox` - Specifies the paths for bbox YOLO models.
+- `ultralytics_segm` - Specifies the paths for segm YOLO models.
+- `ultralytics` - Allows the presence of `bbox/` and `segm/` subdirectories.
+
+
 ## How To Install?
 
 ### Install via ComfyUI-Manager (Recommended)

__init__.py

@@ -8,7 +8,7 @@
 import importlib
 import logging
 
-version_code = [1, 2, 1]
+version_code = [1, 2, 10]
 version_str = f"V{version_code[0]}.{version_code[1]}" + (f'.{version_code[2]}' if len(version_code) > 2 else '')
 logging.info(f"### Loading: ComfyUI-Impact-Subpack ({version_str})")
 

install.py

@@ -1,21 +1,22 @@
 import os
 import sys
 from torchvision.datasets.utils import download_url
+import logging
 
 subpack_path = os.path.join(os.path.dirname(__file__))
 
 comfy_path = os.environ.get('COMFYUI_PATH')
 if comfy_path is None:
     comfy_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
-    print(f"\nWARN: The `COMFYUI_PATH` environment variable is not set. Assuming `{comfy_path}` as the ComfyUI path.", file=sys.stderr)
-    
+    logging.warning(f"\nWARN: The `COMFYUI_PATH` environment variable is not set. Assuming `{comfy_path}` as the ComfyUI path.")
+
 sys.path.append(comfy_path)
 
 model_path = os.environ.get('COMFYUI_MODEL_PATH')
 if model_path is None:
     model_path = os.path.abspath(os.path.join(comfy_path, 'models'))
-    print(f"\nWARN: The `COMFYUI_MODEL_PATH` environment variable is not set. Assuming `{model_path}` as the ComfyUI path.", file=sys.stderr)
-    
+    logging.warning(f"\nWARN: The `COMFYUI_MODEL_PATH` environment variable is not set. Assuming `{model_path}` as the ComfyUI path.")
+
 
 ultralytics_bbox_path = os.path.join(model_path, "ultralytics", "bbox")
 ultralytics_segm_path = os.path.join(model_path, "ultralytics", "segm")

modules/subcore.py

@@ -37,6 +37,18 @@ def create_segmasks(results):
     return results
 
 
+# Limit the commands that can be executed through `getattr` to `ultralytics.nn.modules.head.Detect.forward`.
+def restricted_getattr(obj, name, *args):
+    if name != "forward":
+        logging.error(f"Access to potentially dangerous attribute '{obj.__module__}.{obj.__name__}.{name}' is blocked.\nIf you believe the use of this code is genuinely safe, please report it.\nhttps://github.com/ltdrdata/ComfyUI-Impact-Subpack/issues")
+        raise RuntimeError(f"Access to potentially dangerous attribute '{obj.__module__}.{obj.__name__}.{name}' is blocked.")
+
+    return getattr(obj, name, *args)
+
+restricted_getattr.__module__ = 'builtins'
+restricted_getattr.__name__ = 'getattr'
+
+
 try:
     from ultralytics import YOLO
     from ultralytics.nn.tasks import DetectionModel
@@ -49,8 +61,13 @@ try:
     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
+    try:
+        from numpy import dtype
+        from numpy.dtypes import Float64DType
+    except:
+        logging.error("[Impact Subpack] installed 'numpy' is outdated. Please update 'numpy' to 1.26.4")
+        raise Exception("[Impact Subpack] installed 'numpy' is outdated. Please update 'numpy' to 1.26.4")
+
 
     torch_whitelist = []
 
@@ -108,7 +125,7 @@ try:
 
         torch_whitelist += [DetectionModel, aliasYOLOv10DetectionModel, SegmentationModel, IterableSimpleNamespace,
                             aliasIterableSimpleNamespace, TaskAlignedAssigner, aliasTaskAlignedAssigner, aliasv10DetectLoss,
-                            getattr, dill._dill._load_type, scalar, dtype, Float64DType]
+                            restricted_getattr, dill._dill._load_type, scalar, dtype, Float64DType]
 
     build_torch_whitelist()
 
@@ -120,11 +137,25 @@ except Exception as e:
 # HOTFIX: https://github.com/ltdrdata/ComfyUI-Impact-Pack/issues/754
 # importing YOLO breaking original torch.load capabilities
 def torch_wrapper(*args, **kwargs):
-    if hasattr(torch.serialization, 'safe_globals'):
-        return orig_torch_load(*args, **kwargs)
+    # NOTE: A trick to support code based on `'weights_only' in torch.load.__code__.co_varnames`.
+    if 'weights_only' in kwargs:
+        weights_only = kwargs.pop('weights_only')
     else:
-        logging.warning("[Impact Subpack] Your torch version is outdated, and security features cannot be applied properly.")
-        return orig_torch_load(*args, **kwargs, weights_only=False)
+        weights_only = None
+
+    if hasattr(torch.serialization, 'safe_globals'):
+        if weights_only is not None:
+            kwargs['weights_only'] = weights_only
+
+        return orig_torch_load(*args, **kwargs)  # NOTE: This code simply delegates the call to torch.load, and any errors that occur here are not the responsibility of Subpack.
+    else:
+        if weights_only is not None:
+            kwargs['weights_only'] = weights_only
+        else:
+            logging.warning("[Impact Subpack] Your torch version is outdated, and security features cannot be applied properly.")
+            kwargs['weights_only'] = False
+
+        return orig_torch_load(*args, **kwargs)
 
 torch.load = torch_wrapper
 
@@ -354,4 +385,4 @@ class UltraSegmDetector:
         return utils.combine_masks(segmasks)
 
     def setAux(self, x):
-        pass
+        pass

modules/subpack_nodes.py

@@ -30,6 +30,22 @@ class UltralyticsDetectorProvider:
 
     def doit(self, model_name):
         model_path = folder_paths.get_full_path("ultralytics", model_name)
+
+        if model_path is None:
+            logging.error(f"[Impact Subpack] model file '{model_name}' is not found in one of the following directories:")
+
+            cands = []
+            cands.extend(folder_paths.get_folder_paths("ultralytics"))
+            if model_name.startswith('bbox/'):
+                cands.extend(folder_paths.get_folder_paths("ultralytics_bbox"))
+            elif model_name.startswith('segm/'):
+                cands.extend(folder_paths.get_folder_paths("ultralytics_segm"))
+
+            formatted_cands = "\n\t".join(cands)
+            logging.error(f'\t{formatted_cands}\n')
+
+            raise ValueError(f"[Impact Subpack] model file '{model_name}' is not found.")
+
         model = subcore.load_yolo(model_path)
 
         if model_name.startswith("bbox"):

modules/utils.py

@@ -133,7 +133,7 @@ def crop_ndarray2(npimg, crop_region):
 
     return cropped
 
-    
+
 def crop_ndarray4(npimg, crop_region):
     x1 = crop_region[0]
     y1 = crop_region[1]

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 = "1.2.1"
+version = "1.2.10"
 license = { file = "LICENSE.txt" }
 dependencies = ["matplotlib", "ultralytics==8.3.40"]
 

requirements.txt

@@ -1,4 +1,5 @@
 matplotlib
-ultralytics==8.3.40
-numpy<2
-opencv-python-headless
+ultralytics
+numpy==1.26.4
+opencv-python-headless
+dill