Installation
tfaip is available on pypi and can thus be installed with pip:
pip install tfaip
Prerequisites
You need to install the following on your system:
Python 3.7 or later, including
the python development packages (on Ubuntu
apt install python3.7 python3.7-dev
, if not available in your distribution, use the deadsnakes repo for ubuntu based distros)a gcc compiler and all other build essentials (on Ubuntu
apt install build-essential
)(optional) cuda/cudnn libs for GPU support, see tensorflow for the versions which are required/compatible.
Setup in a Virtual Environment
Setup your venv and install:
<python>
must be replaced with python3.7
or later (check <python> --version
before):
virtualenv -p <python> PATH_TO_VENV
source PATH_TO_VENV/bin/activate
pip install -U pip # recommended to get the latest version of pip
pip install tfaip
Possible bugs
pycocotools
Currently as of numpy 1.20, pycocotools are falsely compiled, run
pip uninstall -y pycocotools
pip install --no-cache-dir pycocotools
to fix your venv by reinstalling and recompiling the pycocotools.
Tests
tfaip provides a set of tests which are listed in the test directory using the unittest framework.
Run the tests
Call python -m unittest
or pytest
to run the tests from the command line.
In PyCharm: Right-click on test
select Run 'Unittests in test'
, or “Shift-Shift”, write “run” and choose Run 'Unittests in test'
CI/CD
All tests will automatically run for CI/CD.
Development Setup
For development support, clone the code, install the requirements in a fresh virtual environment, and link the tfaip source to the virtualenv:
git clone https://github.com/Planet-AI-GmbH/tfaip.git # or git clone git@github.com:Planet-AI-GmbH/tfaip.git
cd tfaip
virtualenv -p python3 venv
source venv/bin/activate
pip install -U pip # recommended to get the latest version of pip
pip install -r requirements.txt
pip install -r devel_requirements.txt # Requirements only required for testing and development
python setup.py develop