def load_fv(fv='fv0'): if fv == 'fv0': gmm_data = fvloader.load_train_data(size=0, balance=False) weights, means, covs = load_gmm(gmm_data, gmmdir='gmm/fv0') train_data = fvloader.load_train_data(size=0, balance=True) val_data = fvloader.load_val_data(size=0) test_data = fvloader.load_test_data(size=0) elif fv == 'matlab': gmm_data = matloader.load_train_data(size=0, balance=False) weights, means, covs = load_gmm(gmm_data, gmmdir='gmm/matlab') train_data = matloader.load_train_data(size=0, balance=True) val_data = matloader.load_val_data(size=0) test_data = matloader.load_test_data(size=0) train_items = data2fisher(train_data, weights, means, covs) val_items = data2fisher(val_data, weights, means, covs) test_items = data2fisher(test_data, weights, means, covs) return train_items, val_items, test_items
def load_fv(fv='fv0'): if fv == 'fv0': kmean_data = fvloader.load_train_data(size=0, balance=False) kmeans = cluster(kmean_data) train_data = fvloader.load_train_data(size=0, balance=True) val_data = fvloader.load_val_data(size=0) test_data = fvloader.load_test_data(size=0) bovdir = 'bov/fv0' elif fv == 'matlab': kmean_data = matloader.load_train_data(size=0, balance=False) kmeans = cluster(kmean_data) train_data = matloader.load_train_data(size=0, balance=True) val_data = matloader.load_val_data(size=0) test_data = matloader.load_test_data(size=0) bovdir = 'bov/matlab' train_items = data2bov(train_data, kmeans, bovdir=bovdir) val_items = data2bov(val_data, kmeans, bovdir=bovdir) test_items = data2bov(test_data, kmeans, bovdir=bovdir) return train_items, val_items, test_items
def load_fv(fv='fv0'): if fv == 'fv0': vlad_data = fvloader.load_train_data(size=0, balance=False) kmeans = cluster(vlad_data) train_data = fvloader.load_train_data(size=0, balance=True) val_data = fvloader.load_val_data(size=0) test_data = fvloader.load_test_data(size=0) vladdir = 'vlad/fv0' elif fv == 'matlab': vlad_data = matloader.load_train_data(size=0, balance=False) kmeans = cluster(vlad_data) train_data = matloader.load_train_data(size=0, balance=True) val_data = matloader.load_val_data(size=0) test_data = matloader.load_test_data(size=0) vladdir = 'vlad/matlab' train_items = data2vlad(train_data, kmeans, vladdir=vladdir) val_items = data2vlad(val_data, kmeans, vladdir=vladdir) test_items = data2vlad(test_data, kmeans, vladdir=vladdir) return train_items, val_items, test_items