Update app.py

app.py

@@ -1,23 +1,25 @@
+import os
+import sys
+import types
+import cv2
 import gradio as gr
+import numpy as np
 from gfpgan import GFPGANer
 from huggingface_hub import hf_hub_download
-import cv2
-import numpy as np
-import torchvision.transforms.functional as F
-import sys
-import types
 
-# Patch برای حل مشکل 'functional_tensor' در basicsr
-sys.modules['torchvision.transforms.functional_tensor'] = types.SimpleNamespace(
-    rgb_to_grayscale=F.rgb_to_grayscale
-)
+# -------- Patch برای جلوگیری از ارور torchvision.transforms.functional_tensor --------
+try:
+    import torchvision.transforms.functional_tensor
+except ModuleNotFoundError:
+    # ساخت یک ماژول خالی به جای functional_tensor
+    sys.modules['torchvision.transforms.functional_tensor'] = types.ModuleType('functional_tensor')
 
-# کش مدل‌ها
+# -------- کش مدل‌ها --------
 loaded_models = {}
 
 def load_model(version):
-    if version == "v1.4 (original)":
-        if version not in loaded_models:
+    if version not in loaded_models:
+        if version == "v1.4 (original)":
             model_path = hf_hub_download("leonelhs/gfpgan", "GFPGANv1.4.pth")
             loaded_models[version] = GFPGANer(
                 model_path=model_path,
@@ -26,10 +28,7 @@ def load_model(version):
                 channel_multiplier=2,
                 bg_upsampler=None
             )
-        return loaded_models[version]
-
-    elif version == "v1.3 (clean)":
-        if version not in loaded_models:
+        elif version == "v1.3 (clean)":
             model_path = hf_hub_download("leonelhs/gfpgan", "GFPGANv1.3.pth")
             loaded_models[version] = GFPGANer(
                 model_path=model_path,
@@ -38,26 +37,25 @@ def load_model(version):
                 channel_multiplier=2,
                 bg_upsampler=None
             )
-        return loaded_models[version]
-
+    return loaded_models[version]
 
+# -------- تابع اصلی پردازش تصویر --------
 def enhance_face(image, version):
     restorer = load_model(version)
 
-    # تبدیل تصویر PIL/numpy به BGR
     if isinstance(image, np.ndarray):
         img = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
     else:
         raise ValueError("Invalid image format")
 
-    _, _, restored_img = restorer.enhance(img, has_aligned=False, only_center_face=False, paste_back=True)
+    _, _, restored_img = restorer.enhance(
+        img, has_aligned=False, only_center_face=False, paste_back=True
+    )
 
-    # تبدیل دوباره به RGB برای نمایش
     restored_img = cv2.cvtColor(restored_img, cv2.COLOR_BGR2RGB)
-
     return restored_img
 
-
+# -------- رابط کاربری Gradio --------
 iface = gr.Interface(
     fn=enhance_face,
     inputs=[