---
license: apache-2.0
tags:
- image-classification
- medical-imaging
- cervical-cancer
- pap-smear
- pytorch
---

# AlexNet Fine-Tuned on HERLEV Dataset

This repository provides a fine-tuned AlexNet model trained on the HERLEV cervical cytology dataset for multi-class cervical cell classification.

## Model Details
- Architecture: AlexNet
- Framework: PyTorch
- Input size: 224x224 RGB
- Classes: 5

## Classes
0: Superficial–Intermediate  
1: Parabasal  
2: Koilocytotic  
3: Dyskeratotic  
4: Metaplastic  

## How to Use

```python
import torch
from PIL import Image
from torchvision import transforms
from model import load_model

device = "cuda" if torch.cuda.is_available() else "cpu"
model = load_model("best_alexnet.pth", device=device)

transform = transforms.Compose([
    transforms.Resize((224,224)),
    transforms.ToTensor(),
    transforms.Normalize(
        mean=[0.485, 0.456, 0.406],
        std=[0.229, 0.224, 0.225]
    )
])

img = Image.open("cell_image.jpg").convert("RGB")
img = transform(img).unsqueeze(0).to(device)

with torch.no_grad():
    pred = model(img).argmax(1)

print("Prediction:", pred.item())

Intended Use

Research and educational purposes only.