Image classification using Bag of Words concept
python codebook.py -i [images_dir] -o [output_file] -a [sift|kaze] -s [vocab_size] --verbose(optional)
python codebook.py -i /home/agumbira/dev/data/dog_cat_kaggle/train -o /home/agumbira/dev/python/BOWImageClassifier/model/dog_cat_kaggle/codebook_kaze_200.pkl -a kaze -s 200 --verbose
python preprocess.py -p [uiuc|kaggle] -a [sift|kaze] -i [root_image_dir] -c [codebook_file] -o [output_file]
python preprocess.py -p kaggle -a kaze -i /home/akbar/dev/data/dog_cat_kaggle/test_1/ -c /home/akbar/dev/python/BOWImageClassifier/model/dog_cat_kaggle/codebook_kaze_test_200.pkl -o /home/akbar/dev/python/BOWImageClassifier/model/dog_cat_kaggle/training_data_kaze_200.dat
python training.py -a [svm|ann] -d [serialized_dataset_file] -o [trained_model_file] -t [test_size_percentage]
python training.py -a svm -d model/dataset.dat -o model/model_svm.xml -t 0.1
python classify.py -a [svm|ann] -m [model_file] -d [serialized_dataset_file]
python classify.py -a svm -m model/model_svm.xml -d model/test_data.dat