MoonshotAI
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Kimi-K3
Kimi K3 is an open-weight, 2.8T-parameter native multimodal agentic model with a 1M-token context window, designed for frontier coding, knowledge work, and reasoning tasks.
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FR-AI / ANALYSISWhy it is worth attention
It extends a popular tutorial by adding support for diagonal parking layouts, making it more applicable to real-world parking lots with angled spaces.
Who it is for
- Developers learning computer vision with OpenCV
- Hobbyists building smart parking monitoring systems
- Students working on real-time object detection projects
- Engineers prototyping parking management solutions
Use cases
- Monitoring parking lot occupancy in real time
- Providing a visual dashboard of free and occupied spots
- Learning interactive annotation and video processing with OpenCV
- Adapting the system to custom parking lot configurations
Strengths
- Real-time occupancy detection using OpenCV and NumPy
- Interactive tool for manual parking space annotation and storage via Pickle
- Support for diagonal and mirrored polygonal parking layouts
- Live counter display for free and occupied spots
Considerations
- Requires manual selection of parking spaces per video
- Not based on deep learning, so may struggle with varying lighting or occlusions
- Only processes video input; no integration with live camera feeds out of the box
README quick start
Smart Parking Spot Analyzer
A computer vision project for detecting available and occupied parking spaces using Python and OpenCV.
Overview
This project analyzes a parking lot video and detects available and occupied parking spaces in real time. Parking spaces are manually selected using an interactive annotation tool and stored for later use. Each video frame is processed with computer vision techniques to estimate the occupancy of every parking spot and display the number of free and occupied spaces.
Features
- Real-time parking space occupancy detection
- Interactive tool for selecting parking spaces
- Manual parking space annotation and storage using Pickle
- Support for diagonal parking layouts
- Visual indication of occupied and available spaces
- Live counter showing free and occupied parking spots
Technologies
- Python
- OpenCV
- NumPy
- Pickle
Improvements
Unlike the original tutorial, I adapted the project to support diagonal parking spaces (// and \ layouts) instead of only rectangular parking spots. The parking space selection tool was modified to create mirrored polygonal parking slots, allowing the system to analyze angled parking lots more accurately.
Credits
This project was inspired by and developed with the help of Murtaza's Workshop. The original tutorial can be found here: https://www.youtube.com/watch?v=caKnQlCMIYI
Description
A parking spot analyzer using computer vision and image processing.
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