Parking Lot Detection Dataset

Contents:

1. Images:
   • Various conditions (e.g., different times of the day).
   • Examples: image_001.jpg, image_002.jpg, etc.
2. Mask Image:
   • mask_1920_1080.png: Binary image indicating parking spots.
3. Video:
   • parking_1920_1080_loop.mp4: Real-time parking spot status.
4. Utility File (util.py):
   • empty_or_not: Classifies parking spots as empty or occupied.
   • get_parking_spots_bboxes: Extracts parking spot bounding boxes from the mask image.
5. Model File:
   • model.p: Pre-trained model for classifying parking spots.

Usage:

• Train and test machine learning models for detecting parking spot occupancy.
• Example workflow includes loading images, extracting parking spots using the mask, classifying spots, and counting empty spots.

Potential Applications:

• Automated parking management.
• Smart city infrastructure.
• Real-time parking guidance systems.

This dataset is sourced from Kaggle.