TBtector is a deep learning project aimed at diagnosing and classifying lung conditions from medical images. This repository contains the code for training, evaluating, and running inference with our machine learning models.
data/: Directory for storing the datasets (images and labels). Note: Datasets are excluded from version control.venv/: Python virtual environment.models/: Directory where trained model weights (.pth/.h5) are saved.
To run this project, you need Python installed on your machine. The project uses PyTorch / TensorFlow for model training and inference.
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Clone the repository:
git clone <your-repository-url> cd TBtector
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Create a virtual environment:
python -m venv venv
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Activate the virtual environment:
- On Windows:
.\venv\Scripts\activate
- On macOS and Linux:
source venv/bin/activate
- On Windows:
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Install dependencies:
pip install -r requirements.txt
(Add instructions here on how to train the model, evaluate it, or run inference on new images.)
MIT License