do this setup.md

Project Setup: Road Anomaly Detection

1. Prerequisites

• Python 3.9+ & pip
• Git

2. Create & Activate Virtual Environment

# Create venv
python -m venv venv

Activate

# macOS/Linux:
source venv/bin/activate
# Windows:     
venv\Scripts\activate

(Conda users: conda create -n yolo_env python=3.10 && conda activate yolo_env)

3. Install Dependencies

If you have GPU run this, then requirements.txt

pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128

# Installs everything, including CPU PyTorch (or GPU if detected & compatible)
pip install -r requirements.txt

• (Local GPU Only): If you need a specific CUDA version locally, install PyTorch first from pytorch.org, then run pip install -r requirements.txt.

4. Verify Installation(optional)

# Create a test.py file with this code to verify PyTorch GPU setup

import torch
print(f"Is CUDA available: {torch.cuda.is_available()}")
print(f"Current device: {torch.cuda.get_device_name(0)}" if torch.cuda.is_available() else "No CUDA device available")

5. Run the App

streamlit run main.py 

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Notes:

• Deactivate environment: deactivate (venv) or conda deactivate (conda).