Is this cheese?
Image recognition software that trains to detect images of cheese using SciKit-Learn models
Trains with images of cheese and not cheese then makes predictions on a fraction of the sample photos
Usage: py cheeser.py [init|load|test]
Train software with photos of cheese and photos of not cheese
Use the directores data\Cheese\ and data\NotCheese\ to train the AI
Optional init commandline argument will reload all the images into the .pkl file before training. This only needs to be run if there new photos have been added. Without the init flag, cheeser.py will attempt to read from a .pkl file composed of the base name and the dimensions
Optional load flag will not train a new HOG SGD model, but instead read one in from hog_sgd_model.pkl
Optional test flag will read in testing data from indir\. When called, the program will try to find a fully trained model under the name full_train_model.pkl. If does not exist, it will train one with all the images in data\ and create a .pkl file for it
Specifying no flags will split the data from data\ to 90% for training and 10% for testing. Then it will create a CLF and Grid Search model, compare the two and display the results. Lastly, the program will give you the option to save the trained model as hog_sgd_model.pkl