🧠 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

🔗 Full Project Code

The complete project (training, inference, and notebook) is available on GitHub:
👉 MIIA Pothole Image Classification on GitHub

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

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)
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🏷️ Author

Rupesh Bhardwaj
Machine Learning Enthusiast

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