metadata
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:
import torch
model = MicrostructureCNN()
model.load_state_dict(torch.load("best_model.pth"))
model.eval()
Dataset
UHCS Microstructure dataset on Kaggle
Full Project
Full code and notebook available on GitHub.