Parking Spot Detection System

Overview

This application provides accurate parking spot detection using a combination of computer vision and machine learning. The system requires:

1. An image of a parking lot
2. A corresponding mask image where parking spots are marked in white

The system then identifies available and occupied parking spots, displaying the results visually.

Features

• Accurate detection using custom mask images
• Web interface for easy uploading and processing
• Real-time results showing available spots
• Simple mask creation process

Prerequisites

• Python 3.8+
• OpenCV
• scikit-image
• Flask
• scikit-learn

Installation

1. Clone the repository:

   git clone https://github.com/4444Harsh/Parking_lot_Area.git
   cd parking-system

2. Create and activate a virtual environment:

   python -m venv .venv
   source .venv/bin/activate  # Linux/Mac
   .venv\Scripts\activate     # Windows

3. Install dependencies:

   pip install -r requirements.txt

How to Use

1. Preparing Mask Images

Create mask images for your parking lots:

1. Open the parking lot image in an image editor
2. Paint all parking spots pure white (RGB 255,255,255)
3. Paint all non-parking areas black (RGB 0,0,0)
4. Save as PNG file

Example:

Parking Lot	Mask Image

2. Running the Application

python app.py

Access the web interface at: http://localhost:5000

3. Using the Web Interface

1. Upload a parking lot image
2. Upload its corresponding mask image
3. Click "Process Images"
4. View the results showing available (green) and occupied (red) spots

File Structure

parking-system/
├── static/
│   ├── masks/          # Predefined mask images
│   ├── uploads/        # User uploaded images
│   └── results/        # Processed results
├── templates/
│   └── index.html      # Frontend
├── parking_detector.py # Detection logic
├── app.py              # Flask backend
├── model.p             # Pretrained model
└── README.md

Troubleshooting

• Error processing images: Ensure your mask image has:

  • Pure white (255,255,255) parking spots
  • Pure black (0,0,0) non-parking areas
  • Same dimensions as the parking lot image

• Model not loading: Verify model.p exists in the root directory

Sample Data

Sample images are provided in:

• static/uploads/parking_image_test.png - Example parking lot
• static/masks/mask_1920_1080.png - Corresponding mask

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For questions or support, please contact [[email protected]].