Perfect! Now that you have your trained model, let me show you exactly how to connect it with the frontend and test it.

Step-by-Step Connection Guide

Step 1: Place Your Trained Model

Important: Make sure your model file is named exactly nepal_traffic_rcnn.pth

Step 2: Update Backend for Your Model

Step 3: Test Your Model

1. First, test if your model loads correctly:

2. Start the updated backend:

3. Test the API:

4. Start the frontend:

Step 4: Complete Testing Process

Backend Testing:

1. Model Loading Test:

   python test_model.py

   This will verify your model file loads correctly.

2. API Test:

   python quick_test.py

   This will test the complete API functionality.

Frontend Testing:

1. Open http://localhost:3000
2. Check if "Backend Status: Connected" appears
3. Upload a test image
4. Verify detection results appear

Step 5: Troubleshooting

Common Issues & Solutions:

1. Model not loading:

   # Check your model file import torch checkpoint = torch.load('models/nepal_traffic_rcnn.pth') print(checkpoint.keys()) # See what's in your model file

2. Wrong number of classes:

   • Update the classes dictionary in app_updated.py to match your trained classes

3. Detection not working:

   • Check confidence threshold (try lowering it to 0.3)
   • Verify image preprocessing matches training

4. Frontend connection issues:

   • Ensure backend runs on port 5000
   • Check browser console for errors

Step 6: Monitor Performance

The updated backend includes detailed logging:

• Model loading status
• Detection confidence scores
• Processing times
• Error messages

Expected Results:

Once everything is connected:

1. ✅ Backend loads your model successfully
2. ✅ Frontend connects to backend
3. ✅ Image upload works
4. ✅ Detection results appear with bounding boxes
5. ✅ Nepali labels display correctly

Quick Start Commands:

Your trained model is now connected and ready to test! 🇳🇵

I'll help you connect your trained model with the frontend! Let me create a comprehensive solution that will automatically detect your model structure and connect it properly.

Quick Setup Instructions

Step 1: Place Your Model

Step 2: Run Model Inspector

Step 3: Start Smart Backend

Step 4: Test Your Model

Step 5: Start Frontend

What This Does

1. 🔍 Smart Model Detection: Automatically finds and analyzes your model file
2. 🧠 Auto-Configuration: Adapts to your model's class structure
3. 📊 Detailed Logging: Shows exactly what's happening during detection
4. 🧪 Comprehensive Testing: Tests all aspects of your model
5. 🔄 Hot Reloading: Can reload models without restarting

Expected Output

When you run the model inspector, you'll see:

Ready to Test!

Once everything is running:

1. ✅ Backend auto-detects your model
2. ✅ Frontend connects automatically
3. ✅ Upload images to test detection
4. ✅ View results with Nepali labels
5. ✅ Use webcam for live detection

Your model is now fully integrated and ready for testing! 🇳🇵