This incorporates the TensorFlow Reader and Predictor filters into pycinema. It currently works with the MNIST dataset.
Given trained ML models (included in data/MNIST_models), the 2 new filters read and predict the values of MNIST numerical images (samples included in data/mnist.cdb). An example workflow is provided in examples/MLScatterPlot.py with documentation in doc/ml_prediction.md and screenshot in doc/MLScatterPlot.png. New tests were added (and passed) with testing/MLPredictTest.py, testing/gold/MLOutputTest.csv and .github/workflow/MLPredictionTest.yml.
This incorporates the TensorFlow Reader and Predictor filters into pycinema. It currently works with the MNIST dataset.
Given trained ML models (included in data/MNIST_models), the 2 new filters read and predict the values of MNIST numerical images (samples included in data/mnist.cdb). An example workflow is provided in examples/MLScatterPlot.py with documentation in doc/ml_prediction.md and screenshot in doc/MLScatterPlot.png. New tests were added (and passed) with testing/MLPredictTest.py, testing/gold/MLOutputTest.csv and .github/workflow/MLPredictionTest.yml.