> For the complete documentation index, see [llms.txt](https://modelforge-1.gitbook.io/modelforge-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://modelforge-1.gitbook.io/modelforge-docs/introduction-modelforge/project-homepage.md).

# Project homepage

### CA:HRSsrhJZ3NhPAgxxuq2bmm7TZ7X6KZjMT7TEdgwbpump <a href="#project-introduction" id="project-introduction"></a>

### Project Introduction <a href="#project-introduction" id="project-introduction"></a>

This project focuses on stereo vision in autonomous driving (ADAS). By generating disparity maps and using columnar pixel (Stixel) estimation and segmentation technology, obstacles and roads are detected and analyzed, providing basic functions for autonomous driving environment perception.

<figure><img src="/files/akqfPucsDGH0m2MJAWdo" alt=""><figcaption></figcaption></figure>

<figure><img src="/files/p4Cybw5dPcoU1bYUbhRw" alt=""><figcaption></figcaption></figure>

### Function Overview <a href="#function-overview" id="function-overview"></a>

* **Stereo Matching** Use OpenCV to match left and right binocular images and generate disparity maps.
* **Stixel Estimation** Extract the depth and height of each column of pixels based on disparity information.
* **Stixel Segmentation** Perform cluster analysis on Stixel data to identify candidate obstacle areas.
* **Scene Understanding** Combine the above technologies to complete the environmental perception of the scene.

### Project Structure <a href="#project-structure" id="project-structure"></a>

* **`main.cpp`**: Program entry, responsible for loading data and calling main modules.
* **`StereoMatching`**: disparity map generation and post-processing.
* **`StereoVisionForADAS`**: encapsulates the process of multiple functional modules.
* **`StixelEstimation`**: extract the core logic of ground and Stixel.
* **`StixelSegmentation`**: complete Stixel clustering and object area recognition.

### How to get started <a href="#how-to-get-started" id="how-to-get-started"></a>

Please refer to [Quick Start](https://modelforge-1.gitbook.io/modelforge-docs/introduction-modelforge/quick-start) to obtain environment dependencies and basic operations.

### Data and testing <a href="#data-and-testing" id="data-and-testing"></a>

Supports testing using stereo datasets such as KITTI. For detailed instructions, please refer to [Appendix B: Datasets and Test Cases](https://modelforge-1.gitbook.io/modelforge-docs/appendix-b-datasets-and-test-cases).

### Contribution <a href="#contribution" id="contribution"></a>

Any form of contribution is welcome, including code submission, problem feedback or improvement suggestions.