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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. 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
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