Spaces:
Build error
Build error
File size: 1,416 Bytes
e75df92 c84c4ba e75df92 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | ---
title: GoGenix MRI Brain Tumor Classifier
emoji: ⚡
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 6.8.0
python_version: '3.10'
app_file: app.py
pinned: true
license: mit
short_description: quick-predictions
---
# GoGenix MRI Brain Tumor Classifier
Fine-tuned version of `Falconsai/nsfw_image_detection` for Brain Tumor MRI classification.
## 🚀 Model Information
- **Base Model**: [Falconsai/nsfw_image_detection](https://huggingface.co/Falconsai/nsfw_image_detection)
- **Custom Model**: GoGenix_MRI_Brain
- **Number of Classes**: 4 (Glioma, Meningioma, No Tumor, Pituitary Tumor)
- **Dataset**: Brain Tumor MRI 4-class Dataset
## 📊 Dataset Information
The model is trained on a comprehensive Brain Tumor MRI dataset containing:
- **Glioma Tumors**
- **Meningioma Tumors**
- **Pituitary Tumors**
- **No Tumor** (Healthy brains)
## 🎯 Usage
### Training
1. Navigate to the **"🚀 Train Model"** tab
2. Click **"Start Training"** to begin fine-tuning
3. Monitor the training progress in the status box
### Classification
1. Go to the **"🔍 Classify MRI"** tab
2. Upload a Brain MRI image
3. Click **"Classify"** to get tumor classification results
## 🔧 Technical Details
- **Framework**: PyTorch + Hugging Face Transformers
- **Image Size**: 224x224 pixels
- **Architecture**: Based on Vision Transformer (ViT)
- **Training Time**: ~10-30 minutes on T4 GPU
## 📁 Files Structure |