---
license: mit
language:
- en
tags:
- materials_engineering
- materials
- steel
---
# UHCS Microstructure CNN Classifier

A CNN model for classifying ultra-high carbon steel (UHCS) microstructures from microscopy images.

## Model Description

Trained on the UHCS Microstructure dataset (Kaggle). Classifies grayscale microscopy images into 4 classes:
- spheroidite
- network
- pearlite
- martensite

## Architecture

- 3 convolutional blocks (16/32/64 filters)
- MaxPooling after each block
- Fully connected layers (16384 -> 256 -> 4)
- Dropout (p=0.5)
- Input size: 128x128 grayscale

## Performance

| Model | Test Accuracy |
|---|---|
| Logistic Regression (baseline) | 51.3% |
| **CNN** | **84.7%** |

## Usage

Model was trained with PyTorch. To load:
```python
import torch
model = MicrostructureCNN()
model.load_state_dict(torch.load("best_model.pth"))
model.eval()
```

## Dataset

[UHCS Microstructure dataset on Kaggle](https://www.kaggle.com/datasets/sagarupsc/uhcs-microstructure-01)

## Full Project

Full code and notebook available on [GitHub](https://github.com/xJadzix/microstructure-classification).

---
license: mit
language:
- en
---