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:
- Images:
- Various conditions (e.g., different times of the day).
- Examples: image_001.jpg, image_002.jpg, etc.
- Mask Image:
- mask_1920_1080.png: Binary image indicating parking spots.
- Video:
- parking_1920_1080_loop.mp4: Real-time parking spot status.
- 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.
- 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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