Installation

Please first install TensorFlow (either TensorFlow 1 or 2) by following the official instructions. For GPU support, it is very important to install the specific versions of CUDA and cuDNN that are compatible with the respective version of TensorFlow.

Note

We strongly recommend to use TensorFlow on a Linux or Windows system with a modern CUDA-enabled GPU from Nvidia, since TensorFlow currently does not support GPUs on the Mac. Without a GPU, training and prediction will be much slower (~30-60 times, even when using a computer with 40 CPU cores).

Second, we suggest to install Jupyter to be able to run our provided example notebooks that contain step-by-step instructions on how to use this package.

Finally, install the latest stable version of the CSBDeep package with pip.

  • If you installed TensorFlow 2 (version 2.x.x):

    pip install csbdeep

  • If you installed TensorFlow 1 (version 1.x.x):

    pip install "csbdeep[tf1]"

Note

  • The package is compatible with Python 2 and 3, but mainly developed and tested with Python 3 (which we recommend to use).

  • If you use Python 3, you may need to use pip3 instead of pip.

  • You can find out which version of TensorFlow is installed via pip show tensorflow.

Alternative GPU-enabled Installation (Linux only)

Since installing TensorFlow with its dependencies (CUDA, cuDNN) can be challenging, we offer a ready-to-use Docker container as an alternative to get started more quickly. (What is Docker?)