README.md

metadata

title: Malaria Classification
emoji: 🧬
colorFrom: green
colorTo: red
sdk: streamlit
sdk_version: 1.45.1
app_file: app/app.py
pinned: false

🧬 Malaria Cell Classifier with Grad-CAM & Streamlit UI

A deep learning-based malaria detection system using ResNet50 and Grad-CAM explainability.

🚀 Features

• ✅ Binary classification of blood smear images (Infected / Uninfected)
• 🔍 Grad-CAM visualizations to highlight infected regions
• 🌐 Interactive Streamlit web interface
• 📦 Easy-to-deploy structure

🛠️ Built With

• PyTorch
• Streamlit
• Grad-CAM
• ResNet50

📦 Dataset

Uses the Malaria Cell Images Dataset

📁 Folder Structure

Place raw images in: data/cell_images/ ├── Parasitized/ └── Uninfected/

Here's a quick preview of the app in action:

🧪 Usage

🛠️ Requirements

Install dependencies:

pip install torch torchvision streamlit opencv-python matplotlib scikit-learn