| # Tuberculosis CNN Model | |
| This repository contains a CNN model for classifying chest X-ray images as **Normal** or **Tuberculosis**. | |
| ## Dataset | |
| - **Source**: TB Chest Radiography Database | |
| - **Input**: 256x256 grayscale images | |
| - **Classes**: Normal, Tuberculosis | |
| - **Accuracy**: ~93% | |
| ## Usage | |
| ```python | |
| from handler import TBClassifier | |
| import cv2 | |
| classifier = TBClassifier() | |
| image = cv2.imread("path/to/xray.jpg") | |
| result = classifier.predict(image) | |
| print(f"Prediction: {result['prediction']}, Confidence: {result['confidence']:.4f}") | |
| ``` | |
| ## Model Details | |
| - **Framework**: TensorFlow 2.17.0 | |
| - **Format**: SavedModel | |
| - **Preprocessing**: Grayscale, 256x256, normalized | |
| ## Medical Disclaimer | |
| For educational use only. Consult healthcare professionals. | |
| ## Tags | |
| Medical Imaging, Deep Learning, TensorFlow, Tuberculosis | |