BiaPy

Accessible deep learning on bioimages

Latest release notes

🔥NEWS🔥: BiaPy's paper is finally out in Nature Methods!
[Preprint in bioRxiv]

  •   Download
    Get Additional Installers   |  

    Please install Docker to use the GUI following these instructions.
    Find instructions on how to use the GUI in this video.

    You can also install previous versions of BiaPy's graphical user interface.

  • For each workflow we have both 2D and 3D versions:

    Image classification
    (2D)
    Image denoising
    (2D)
    Image to image
    (2D)
    Instance segmentation
    (2D)
    Object detection
    (2D)
    Self-supervision
    (2D)
    Semantic segmentation
    (2D)
    Super-resolution
    (2D)
    Image classification
    (3D)
    Image denoising
    (3D)
    Image to image
    (3D)
    Instance segmentation
    (3D)
    Object detection
    (3D)
    Self supervision
    (3D)
    Semantic segmentation
    (3D)
    Super-resolution
    (3D)

    For just predicting/inference you can use the following notebook:

    Inference
    (2D/3D)

  • We have a container prepared to run BiaPy:

    latest-11.8
    Pytorch 2.4.0
    CUDA 11.8
    Ubuntu 22.04

    Docker Engine is available for Windows, macOS, and Linux, through Docker Desktop. For instructions on how to install Docker Desktop, see:

  • You have three different options to install BiaPy. Choose one or another depending on your preferences:

    • To use BiaPy via the command line, you will need to set up a conda environment. To do this, you will first need to install Conda. Then you need to create a conda environment through a terminal:

      conda create -n biapy-env -c conda-forge biapy

    • Before you begin, ensure you have Mamba installed. Mamba is a faster alternative to Conda and can be used to manage your conda environments. Install mamba in the base conda environment, allowing you to use it across all your environments.

      If you don’t have conda installed you can download the miniforge installer specific to your OS and run it. Otherwise, if you have conda already installed just type:

      conda install mamba -n base -c conda-forge

      Afterwards, create a new Conda environment with BiaPy:

      mamba create -n biapy-env -c conda-forge biapy

    • Set up a conda environment first by installing Conda. Then you need to create a conda environment through a terminal:

      conda create -n BiaPy_env python=3.10
conda activate BiaPy_env

      To clone the repository you will need to install git, a free and open source distributed version control system. Git will allow you to easily download the code with a single command. You can download and install it here. For detailed installation instructions based on your operating system, please see the following links: Windows, macOS and Linux.

      Once you have installed Anaconda and git, you will need to open a terminal to complete the following steps. Then, you are prepared to download BiaPy repository by running this command in the terminal:

      git clone https://github.com/BiaPyX/BiaPy.git

      This will create a folder called BiaPy that contains all the files of the library’s official repository. Then you will need to install BiaPy dependencies:

      # Install Pytorch and GPU dependencies
pip install torch==2.4.0 torchvision==0.19.0 --index-url https://download.pytorch.org/whl/cu118 

# Then install BiaPy
cd BiaPy
pip install --editable .

    Verify installation:

    python -c 'import torch; print(torch.__version__)'
>>> 2.4.0
python -c 'import torch; print(torch.cuda.is_available())'
>>> True