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Space Debris Yolov8

A YOLOv8-powered deep learning system for detecting space debris and satellites in orbital imagery — with real-time collision risk assessment.

KindOtherVersionRevision 3ed855d

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Other
File size
5.96 MB
Version
vRevision 3ed855d
Updated
Sep 27, 2026
Downloads
7
Tasks
Object detection
Source
Hugging Face

Source excerpt

A YOLOv8-powered deep learning system for detecting space debris and satellites in orbital imagery — with real-time collision risk assessment.

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Hugging FacePrimaryVersion 3ed855d9dd24e1e0f474832fc8a641e38f9ddc92
huggingface.co/tanveeerr/space-debris-yolov8/tree/3ed855d9dd24e1e0f474832fc8a641e38f9ddc92

Verified Sep 27

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best.pt

pt · 5.96 MB · SHA-256 c1688f31b50c…4bb0 · Hugging Face

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Source excerpts

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--- license: mit tags: - object-detection - yolov8 - space-debris - computer-vision - ultralytics language: - en --- <div align="center"> # 🛰️ Space Debris Detection & Risk Assessment **A YOLOv8-powered deep learning system for detecting space debris and satellites in orbital imagery — with real-time collision risk assessment.** ![Python](https://img.shields.io/badge/Python-3776AB?style=flat&logo=python&logoColor=white) ![YOLOv8](https://img.shields.io/badge/YOLOv8-FF4081?style=flat&logo=pytorch&logoColor=white) ![Streamlit](https://img.shields.io/badge/Streamlit-FF4B4B?style=flat&logo=streamlit&logoColor=white) ![PyTorch](https://img.shields.io/badge/PyTorch-EE4C2C?style=flat&logo=pytorch&logoColor=white) ![License](https://img.shields.io/badge/License-MIT-green?style=flat) </div> --- ## 📌 Overview Space debris poses a significant risk to operational satellites and future space missions. This project uses **YOLOv8 object detection** trained on orbital imagery to identify and classify **Satellites** and **Debris** in real time, and assess the **collision risk level** based on detected debris count. The project includes a **Streamlit web application** for easy image upload and visualization, along with the complete training notebook used to develop the model. --- ## 🎯 Key Features | Feature | Description | |---|---| | 🛸 **Object Detection** | Detects Satellites and Debris using YOLOv8 | | 🎨 **Confidence Tiers** | Color-coded bounding boxes (🟢 High ≥ 0.80 / 🟡 Medium 0.50–0.80 / 🔴 Low < 0.50) | | 📊 **Risk Assessment** | Collision risk score: LOW / MEDIUM / HIGH based on debris count | | ⚙️ **Adjustable Threshold** | Sidebar slider to control detection confidence | | ⚡ **Fast Inference** | FP16 half-precision model for faster predictions | | 🖥️ **Web Interface** | Clean Streamlit UI — no coding required to use | --- ## 🧠 Model Performance > Trained for **30 epochs** on orbital imagery dataset using **YOLOv8 (Ultralytics v8.4.27)** | Metric | Score | |---|---| | **Precision** | 0.930 | | **Recall** | 0.926 | | **mAP@50** | 0.931 | | **mAP@50-95** | 0.750 | | **Image Size** | 640 × 640 | | **Classes** | Satellite, Debris | | **Precision (Storage)** | FP16 (Half) | --- ## 📦 Project Structure ``` space-debris-detection/ ├── app.py # Streamlit web application ├── space_debris_v2-1.ipynb # Model training & experimentation notebook ├──...

Source context: 7 downloads · 1 likes · Pipeline object-detection · Library ultralytics · Repo tanveeerr/space-debris-yolov8