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.gitmodules
Main.ipynb
Main2.ipynb
README
colorizer.py
featurizer.py
index.html
main.py

README

To run the code used to get results for this project, open the ipython notebook : Main.ipynb

To run parameter sweeps for given images:

open Main2.ipynb and run the cells
	* test image - choose a test image from the images folder and replace the string in the imread function
	* training_images - choose a set of training images from the images folder and replace the strings in the list



- featurizer.py = creates feature vectors and labels for a given training set
	- compute_k_means = computes the discretized colors for a given k
	- compute_features = creates feature,label matrices for the training data
- colorizer.py = trains the SVMs and colorizes a test image
	* takes in a featurizer which presumably has called the functions described above
	- train = trains the SVM classifiers for each color in the featurizer
	- color_image = takes in a grayscale image and colors it in