This project provides a suite of tools for histopathology image analysis, including feature extraction, model training, and data visualization. It is designed to be modular and extensible, allowing for easy integration of new models and datasets.

• Feature Extraction: Tools for extracting features from histopathology images.
• Model Training: Support for training various deep learning models.
• Data Visualization: Utilities for visualizing images and model results.
• Experiment Tracking: Integrated with Weights & Biases for experiment tracking and logging.

1. Clone the repository:

   git clone https://github.com/your-username/histopathology-project.git
   cd histopathology-project

2. Create a virtual environment and install dependencies:

   python -m venv .venv
   source .venv/bin/activate
   pip install -r requirements.txt

To train a model, you can use the train.py script located in the scripts directory. You will need to provide a configuration file specifying the model architecture, dataset, and training parameters.

python scripts/train.py --config-path configs/your_config.yaml

The launch_tmux_experiments.py script can be used to launch multiple experiments in parallel using tmux.

python launch_tmux_experiments.py --config configs/experiment_config.yaml

Contributions are welcome! Please follow these steps to contribute:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them with a descriptive message.
4. Push your changes to your fork.
5. Create a pull request to the main repository.

This project is licensed under the MIT License. See the LICENSE file for more details.