AutoAiLib 0.3.2.dev0

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AutoAI

This repository is a compilation of scripts that I have created in my time working with machine learning. These scripts aim to automate the annoying and silly parts of ML, allowing you to focus on what is important. PyPi: https://pypi.org/project/AutoAILib/
$ pip install autoailib

AutoAi.manual_test(model, testing_dir, labels)

This function tests a model given labels and testing data. It then compiles the results in a CSV file, and groups the results by class, and by correct and incorrect.

• Model - Path of model that you want to test or model object.
• Testing_dir - Path to the directory with your testing data.
• Labels - Dictionary of the classes, in form (index:class_name)

AutoAi.compile_data(src, dest, num_imgs_per_class=0, train_ratio=.7, validation_ratio=.2, test_ratio=.1)

• Src - Path to a folder that contains a folder for each class and then data examples in those class folders.
• Dest - Path to a folder where you want the data to end up.
• Num_imgs_per_class - This number of images will be added to the original set for each class through transforms. The theoretical limit for this would be 3! * original images per class

Demo:

Given the a path to the following folder: If augmentation used the following results will be yielded: Then these images will be copied to the dest folder with copied file structure, but an added upper layer: Example showing the images made it: