# SparkIP ###Workflow ___________ Listed are the steps below to achieve Image Classification * Training Set * Key Descriptors generation using SIFT/SURF * K Means algorithms to "k" clusters (Called as Vocabulary) * Use Vocabulary to generate Histograms for each image from the Training Set * Label the Histograms * Use Naive Bayes to generate Model * Choose a test image and generate the Histogram image and predict it using the Naive Bayes model generated above. ###Data Set ------------ [CMU Description] (https://archive.ics.uci.edu/ml/machine-learning-databases/faces-mld/faces.data.html) [CMU Data Set] (https://archive.ics.uci.edu/ml/machine-learning-databases/faces-mld/)