---
license: mit
language:
  - en
tags:
  - computer-vision
  - object-detection
  - yolov5
  - microscopy
  - microplastics
  - environmental-ai
  - industrial-ai
  - pytorch
  - ViBOT
pipeline_tag: object-detection
---

# 🔬 YOLOv5 — Microparticle Detection & Classification

> Automated detection and classification of microplastics from microscopy images.
> Developed for industrial deployment at **IZONICS** — achieving **>90% accuracy in production**.

---

## 📌 Model Summary

| Property | Details |
|---|---|
| 🏗️ Architecture | YOLOv5 |
| 🎯 Task | Object Detection + Classification |
| 📊 Accuracy | **>90% in production** |
| ⚡ Speedup | **30% faster** than classical image processing pipeline |
| 🏭 Deployment | Fully industrialized — prototype to production |
| ⚙️ Framework | PyTorch |
| 📜 License | MIT |

---

## 🧠 What This Model Does

This model detects and classifies **microplastic particles** in microscopy images, enabling automated environmental monitoring and industrial quality control.

It was developed at **IZONICS** as a complete refactoring of an existing classical computer vision pipeline into a deep learning architecture — resulting in higher reliability, better accuracy, and significantly faster inference in real production environments.

**Origin:** Extended from a Master's thesis (VIBOT program, Université de Bourgogne) into a fully deployed industrial product.

---

## 📈 Performance

| Metric | Score |
|---|---|
| Production accuracy | **>90%** |
| Processing speedup vs. classical pipeline | **30%** |
| Deployment status | ✅ Fully industrialized |

---

## 🚀 How to Use

```python
import torch

# Load the model
model = torch.hub.load("ultralytics/yolov5", "custom", path="best.pt")
model.conf = 0.35  # confidence threshold

# Run inference
results = model("microscopy_image.jpg")

# Show results
results.show()

# Get detections as dataframe
df = results.pandas().xyxy[0]
print(df)
```

---

## 🗂️ Training Data

- **Domain:** Environmental microscopy images of microplastic particles
- **Task:** Multi-class detection and classification of particle types
- **Augmentation:** Custom augmentation tailored for microscopy image characteristics

---

## ⚠️ Limitations

- Optimized for specific microscopy imaging conditions used at IZONICS
- Performance may vary on microscopy setups with different magnification or lighting
- Not validated for clinical or regulatory use

---

## 🔗 Related Resources

- 🤗 [Live Demo Space](https://huggingface.co/spaces/martinbadrous/Microparticle-Detection-YOLOv5)
- 💻 [GitHub Repository](https://github.com/martinbadrous/Microparticle-Detection)

---

## 👤 Author

**Martin Badrous** — Computer Vision & Deep Learning Engineer

[![LinkedIn](https://img.shields.io/badge/LinkedIn-%230077B5.svg?style=flat&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/martinbadrous)
[![GitHub](https://img.shields.io/badge/GitHub-181717.svg?style=flat&logo=github&logoColor=white)](https://github.com/martinbadrous)
[![HuggingFace](https://img.shields.io/badge/HuggingFace-FFD21E.svg?style=flat&logo=huggingface&logoColor=000)](https://huggingface.co/martinbadrous)