Update app.py

app.py

@@ -117,7 +117,6 @@
 
 
 
-
 import gradio as gr
 import cv2
 import torch
@@ -132,22 +131,13 @@ mp_face_mesh = mp.solutions.face_mesh
 face_detection = mp_face_detection.FaceDetection(model_selection=1, min_detection_confidence=0.5)
 face_mesh = mp_face_mesh.FaceMesh(static_image_mode=False, max_num_faces=1, min_detection_confidence=0.5)
 
-# Load deepfake detection model (updated)
-model = models.resnet34(pretrained=False)  # Load base ResNet-34
-model.fc = torch.nn.Linear(model.fc.in_features, 2)  # Modify final layer
-
-# Load weights properly
-checkpoint = torch.load("resnet34.pth", map_location="cpu")
-
-# Extract just the model weights (ignore optimizer states)
-if "network" in checkpoint:  # Handle different checkpoint formats
-    model.load_state_dict(checkpoint["network"])
-elif "state_dict" in checkpoint:
-    model.load_state_dict(checkpoint["state_dict"])
-else:
-    # Directly try loading if it's pure state_dict
-    model.load_state_dict(checkpoint)
+# Initialize ResNet-34 model with random weights
+def create_model():
+    model = models.resnet34(pretrained=False)
+    model.fc = torch.nn.Linear(model.fc.in_features, 2)
+    return model
 
+model = create_model()
 model.eval()
 
 # Define transformation for face images
@@ -212,7 +202,6 @@ def process_video(video_path: str):
     output_video.release()
     return output_path
 
-# Rest of the Gradio interface remains the same
 def gradio_interface(video_file):
     if video_file is None:
         return "Error: No video uploaded."