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# Brain Tumor Classification using VGG16 (Colorized MRI)
This repository contains a PyTorch-based VGG16 transfer learning model for automated brain tumor classification from MRI images. The model is trained on enhanced colorized MRI scans and classifies images into three tumor categories: Glioma, Meningioma, and Pituitary tumors.
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## 🧠 Model Overview
- **Architecture:** VGG16 (Transfer Learning)
- **Framework:** PyTorch
- **Task:** Image Classification
- **Classes:** 3 (Glioma, Meningioma, Pituitary)
- **Input Type:** Colorized MRI images
- **Best Test Accuracy:** **88.70%**
- **Device Used:** GPU (CUDA)
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## 📊 Dataset Details
- **Dataset Type:** Enhanced Colorized MRI Images
- **Total Samples:** 3,600 images
- **Class Distribution:**
- Glioma
- Meningioma
- Pituitary
- **Data Split:**
- Training: 70%
- Validation: 15%
- Testing: 15%
> Note: The dataset is preprocessed and not hosted publicly on Hugging Face.
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## ⚙️ Training & Methodology
- Pre-t…
