Metadata-Version: 2.1
Name: vidtrain
Version: 0.2.0
Summary: Deep learning annotation training and prediction workflow for microscopy video data
Home-page: https://gitlab.com/Thawn/vidtrain
Author: Thawn
Author-email: webmaster@korten.at
License: UNKNOWN
Description: # VidTrain
        
        Train deep neural networks to analyze video data.
        
        ## Installation
        
        1. [Install anaconda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html)
        2. (Optional) Install a python-capable IDE like [Visual Studio Code](https://code.visualstudio.com/)
        3. Open a command line terminal to install `vidtrain`: 
           1. Create a python 3.7 environment: `conda create --name vidtrain`. Note, the python version must be >= 3.7 [[1]](#Notes)
           2. Activate the environment `conda activate vidtrain`
           3. Install tensorflow `conda install tensorflow`. Note we use conda so that all dependencies are installed as well. If you like you can manually install the tensorflow dependencies instead and skip this step (in that case pip installs tensorflow as a dependency of vidtrain in the next step).
           3. Install vidtrain `pip install vidtrain`
           
        ## Run
        
        Execute the following code in python:
        ```python
        import vidtrain
        
        
        if __name__ == '__main__':
            vidtrain.workflow.JunctionAnalysis().run()
        ```
        
        
        ## Notes
        [1]  The code uses some features that were introduced in 3.7 (dictionaries that are ordered by default), meaning it will not work properly with python <3.7.
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >3.7.0
Description-Content-Type: text/markdown
Provides-Extra: bioformats
