Update app.py

app.py

@@ -20,6 +20,7 @@ from torchvision import models, transforms
 import matplotlib.pyplot as plt
 import seaborn as sns
 from collections import Counter
+from torchvision.models import ResNet50_Weights
 import pickle
 
 # Set up logging
@@ -187,7 +188,6 @@ with open(CACHE_FILE, "wb") as f:
 
 logging.info("Incremental processing complete!")
 
-# Analyze image content using a pre-trained model
 def analyze_image(image_url):
     """Analyze image content using a pre-trained model."""
     if not image_url or not isinstance(image_url, str) or not image_url.startswith(('http://', 'https://')):
@@ -203,8 +203,13 @@ def analyze_image(image_url):
             transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
         ])
         image_tensor = preprocess(image).unsqueeze(0)
-        model = models.resnet50(pretrained=True)
+        
+        # Load ResNet50 weights from local cache
+        weights_path = "/app/models/resnet50-0676ba61.pth"
+        model = models.resnet50()
+        model.load_state_dict(torch.load(weights_path))
         model.eval()
+        
         with torch.no_grad():
             output = model(image_tensor)
         return output