converter.py

import torch
from models import ResNet9

# Load the existing model
try:
    old_model = torch.load("plant-disease-model.pth", map_location="cpu", weights_only=False)
    
    # Save only the state dict
    torch.save(old_model.state_dict(), "plant-disease-model-state-dict.pth")
    print("✅ Model converted to state dict format")
    
    # Test loading the new format
    new_model = ResNet9(3, 38)  # 38 classes based on your CLASS_NAMES
    new_model.load_state_dict(torch.load("plant-disease-model-state-dict.pth"))
    new_model.eval()
    print("✅ Converted model loads successfully")
    
except Exception as e:
    print(f"❌ Conversion failed: {e}")