---
title: Geodect
emoji: 💻
colorFrom: gray
colorTo: green
sdk: gradio
sdk_version: 6.9.0
app_file: app.py
pinned: false
license: mit
short_description: AI-assisted computer vision for 3D geological modeling.
---

# ⚒️ Geodect: Geological 3D & Mapping

Geodect is an AI-assisted computer vision tool designed to convert field video of geological surfaces or rock samples into clean 3D models and high-resolution 2D orthomosaic maps. 

## 🌟 Key Features

* **2D Orthomosaic Mapping:** Automatically extract, align, and stitch video frames into a single, high-resolution undistorted map.
* **3D Sample Reconstruction:** Transform video orbits of rock samples into interactive `.obj` meshes using Structure from Motion (SfM).
* **Intelligent Background Removal:** Designed to segment and remove unwanted objects (like hands or tools) to focus on the geological surface.
* **CPU Optimized:** Built to run efficiently within a Hugging Face Space without requiring high-end GPU resources.

## 🚀 Technical Workflow

1.  **Extraction:** OpenCV extracts optimal frames from uploaded field video.
2.  **Processing:** * **Orthomosaic Mode:** Detects features via SIFT/ORB and estimates homography for seamless stitching.
    * **3D Mode:** Estimates camera poses and generates a dense point cloud converted into a surface mesh via Trimesh.
3.  **Visualization:** Interactive 3D rendering and high-res image downloads provided via the Gradio interface.

## 📂 Architecture

This project is implemented as a lightweight four-file Python application:

* `app.py`: The main Gradio interface and pipeline controller.
* `Orthomosaic.py`: The 2D stitching and blending engine.
* `ThreeDimagery.py`: The 3D reconstruction and SfM module.
* `requirements.txt`: Environment dependencies including OpenCV, SciPy, and Trimesh.

## 🤝 Credits & Acknowledgments

**Developer:** **Adedoyin Ifeoluwa James**

**X:** **https://x.com/IAdedoyin64700**

**portfolio website:** **https://adedoyinjames-portfolio.vercel.app**

**blog:** **https://theadedoyinjournal.wordpress.com**

**Technical Resources:** This project was developed with the technical support and computational resources of **NORA RESEARCH LAB**.

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