---
license: mit
language: en
tags:
- pytorch
- image-classification
- computer-vision
- pothole-detection
---

# 🧠 Pothole Detection Model (ResNet18)

This repository contains a fine-tuned **ResNet18** model for classifying whether a road image contains a **pothole** or not.  
The model was developed as part of the **Zindi MIIA Pothole Image Classification Challenge**, focused on improving road safety in South Africa.

## 📚 Project Overview
- **Task:** Binary image classification (`pothole` / `no_pothole`)
- **Framework:** PyTorch + torchvision
- **Model:** ResNet18 (pretrained on ImageNet, fine-tuned)
- **Evaluation Metric:** AUC (Area Under the Curve)
- **Dataset Source:** [rupesh002/Patholes_Dataset](https://huggingface.co/datasets/rupesh002/Patholes_Dataset)

---

## 🔗 Full Project Code
The complete project (training, inference, and notebook) is available on GitHub:  
👉 [MIIA Pothole Image Classification on GitHub](https://github.com/Rupeshbhardwaj002/MIIA_Pothole_Image_Classification_SouthAfrica)

It includes:
- Data preprocessing  
- Model training pipeline (`train.py`)  
- Prediction and submission script (`predict.py`)  
- Notebook used for Zindi competition submission  

---

## ⚙️ How to Load This Model

```python
from huggingface_hub import hf_hub_download
import joblib

model_path = hf_hub_download(
    repo_id="rupesh002/pothole_detection_model",
    filename="model.pkl",
    repo_type="model"
)

model = joblib.load(model_path)
---
🏷️ Author

Rupesh Bhardwaj
Machine Learning Enthusiast