Parking Lot Detection Dataset

Parking Lot Detection Dataset

Datasets

Parking Lot Detection Dataset

File

Parking Lot Detection Dataset

Use Case

Parking Lot Detection

Description

Discover a versatile parking lot detection dataset designed for training and testing machine learning models. Includes images, mask image, video, utility file.

Description:

This dataset is created for detecting and counting empty and occupied parking spots in a parking area. It includes images, a mask image, a video, and a utility file (util.py) with functions for processing these resources.

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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.

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