Merge pull request #4 from SameetAsadullah/master

Make facedetection models load from comfyui models if present
Fix torch version checking

__init__.py

@@ -15,10 +15,11 @@ from custom_nodes.facerestore_cf.basicsr.utils.registry import ARCH_REGISTRY
 # import codeformer_arch
 
 dir_facerestore_models = os.path.join(folder_paths.models_dir, "facerestore_models")
-dir_facedetection = os.path.join(folder_paths.models_dir, "facedetection")
+dir_facedetection_models = os.path.join(folder_paths.models_dir, "facedetection")
 os.makedirs(dir_facerestore_models, exist_ok=True)
-os.makedirs(dir_facedetection, exist_ok=True)
+os.makedirs(dir_facedetection_models, exist_ok=True)
 folder_paths.folder_names_and_paths["facerestore_models"] = ([dir_facerestore_models], folder_paths.supported_pt_extensions)
+folder_paths.folder_names_and_paths["facedetection_models"] = ([dir_facedetection_models], folder_paths.supported_pt_extensions)
 
 def img2tensor(imgs, bgr2rgb=True, float32=True):
     """Numpy array to tensor.

facelib/detection/yolov5face/face_detector.py

@@ -17,7 +17,9 @@ from custom_nodes.facerestore_cf.facelib.detection.yolov5face.utils.general impo
     scale_coords_landmarks,
 )
 
-IS_HIGH_VERSION = tuple(map(int, torch.__version__.split('+')[0].split('.'))) >= (1, 9, 0)
+from torch import torch_version
+
+IS_HIGH_VERSION = torch_version.__version__ >= "1.9.0"
 
 
 def isListempty(inList):

facelib/utils/misc.py

@@ -4,6 +4,8 @@ import os.path as osp
 import torch
 from torch.hub import download_url_to_file, get_dir
 from urllib.parse import urlparse
+import folder_paths
+
 # from custom_nodes.facerestore_cf.basicsr.utils.download_util import download_file_from_google_drive
 #import gdown
 
@@ -96,6 +98,11 @@ def load_file_from_url(url, model_dir=None, progress=True, file_name=None):
     filename = os.path.basename(parts.path)
     if file_name is not None:
         filename = file_name
+    
+    model_path = folder_paths.get_full_path("facedetection_models", filename)
+    if model_path:
+        return model_path
+
     cached_file = os.path.abspath(os.path.join(ROOT_DIR, model_dir, filename))
     if not os.path.exists(cached_file):
         print(f'Downloading: "{url}" to {cached_file}\n')