```python
import os
import torch
import logging
from config import CONFIG

logger = logging.getLogger(__name__)

def setup_static_folder():
    """Ensure static folder and model weights are available."""
    static_dir = "static"
    output_dir = os.path.join(static_dir, "output")
    
    # Create static and output directories
    os.makedirs(static_dir, exist_ok=True)
    os.makedirs(output_dir, exist_ok=True)
    logger.info(f"Static directory ensured: {static_dir}")
    logger.info(f"Output directory ensured: {output_dir}")

    # Check for model weights
    model_path = CONFIG["MODEL_PATH"]
    fallback_model = CONFIG["FALLBACK_MODEL"]
    
    if not os.path.isfile(model_path):
        logger.warning(f"Custom model {model_path} not found. Falling back to {fallback_model}.")
        if not os.path.isfile(fallback_model):
            logger.info(f"Downloading fallback model: {fallback_model}")
            try:
                torch.hub.download_url_to_file(
                    'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8n.pt',
                    fallback_model
                )
                logger.info(f"Downloaded {fallback_model}")
            except Exception as e:
                logger.error(f"Failed to download {fallback_model}: {e}")
                raise
    else:
        logger.info(f"Using custom model: {model_path}")

    return model_path if os.path.isfile(model_path) else fallback_model

# Call this function before loading the model in app.py
model_path = setup_static_folder()
```

This code should be inserted in `app.py` before the `load_model()` function, replacing the existing model loading logic. Update the `load_model()` function to use `model_path`:

```python
def load_model(model_path):
    try:
        model = YOLO(model_path).to(device)
        if device.type == "cuda":
            model.model.half()
        logger.info(f"Model loaded: {model_path}, classes: {model.names}")
        return model
    except Exception as e:
        logger.error(f"Failed to load model: {e}")
        raise

model = load_model(model_path)
```