This is a sample starting kit for the Data Science Africa challenge. It uses the Microscopy dataset from http://air.ug/microscopy/.
Prerequisites: Install Anaconda Python 3.6.6, Tensorflow (2.0.0), opencv-python (4.0.1), scikit-image (0.15.0)
or
run your code within the Codalab docker (inside the docker, python 3.6 is called python3):
`docker run -it -p 8888:8888 -v `pwd`:/home/aux herilalaina/dsa:2.0`
`DockerPrompt# cd /home/aux`
`DockerPrompt# python3 ingestion_program/ingestion.py sample_data sample_result_submission ingestion_program sample_code_submission`
`DockerPrompt# python3 scoring_program/score.py sample_data sample_result_submission scoring_output`
`DockerPrompt# exit`
Usage:
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The two files sample_*_submission.zip are sample submissions ready to go!
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The file README.ipynb contains step-by-step instructions on how to create a sample submission for the challenge. At the prompt type: jupyter-notebook README.ipynb
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modify sample_code_submission to provide a better model
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zip the contents of sample_code_submission (without the directory, but with metadata), or
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download the public_data and run (double check you are running the correct version of python):
python ingestion_program/ingestion.py public_data sample_result_submission ingestion_program sample_code_submission
then zip the contents of sample_result_submission (without the directory).