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BrookRaindle/Image_Classification_CNN
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The entire point of my study is that it explores the effects of different sizes of data sets. - i have left all my files in there, you can just delete the 2 datasets and the saved models. Changes to make to the System for functionality: tensor, keras, os, matplotlib, numpy are required For testing purposes: - Uncomment Line 150 (there is also a commented guide) For Training: if you want to use small dataset: - change line 108 parameter with 'data_dir_small' - change String in line 90 to "SmallSavedModel" - change String in line 129 to "SmallSavedModel" if you want to use Large dataset: - change line 108 parameter with 'data_dir_large' - change String in line 90 to "LargeSavedModel" - change String in line 129 to "LargeSavedModel" alternatively, if you have your own folder of images that will be used for training: - add directory to String in line 105 - change line 108 parameter with 'data_set' if the images you want to test with are png: - on line 11, add png to that list of extentions if you want to test without training: - comment out line108 - uncomment line 150
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A small 4 category image classification CNN built from scratch
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