def get_train_data(): data1, width1, height1 = load_image.loadimage("Knights") data2, width2, height2 = load_image.loadimage("Bunny") data3, width3, height3 = load_image.loadimage("Amethyst") data4, width4, height4 = load_image.loadimage("Jelly Beans") data5, width5, height5 = load_image.loadimage("dice") data_1 = np.r_[data1[:, :, 0], data1[:, :, 1], data1[:, :, 2]] data_2 = np.r_[data2[:, :, 0], data2[:, :, 1], data2[:, :, 2]] data_3 = np.r_[data3[:, :, 0], data3[:, :, 1], data3[:, :, 2]] data_4 = np.r_[data4[:, :, 0], data4[:, :, 1], data4[:, :, 2]] data_5 = np.r_[data4[:, :, 0], data4[:, :, 1], data4[:, :, 2]] train_data = np.r_[data_1, data_2, data_3, data_4, data_5] train_length = len(train_data) return train_data, train_length
def get_train_data(): data1, width1, height1 = load_image.loadimage("Knights") data2, width2, height2 = load_image.loadimage("Bunny") data3, width3, height3 = load_image.loadimage("Amethyst") data4, width4, height4 = load_image.loadimage("Jelly Beans") data5, width5, height5 = load_image.loadimage("dice") data_1 = np.r_[data1[:,:,0],data1[:,:,1],data1[:,:,2]] data_2 = np.r_[data2[:,:,0],data2[:,:,1],data2[:,:,2]] data_3 = np.r_[data3[:,:,0],data3[:,:,1],data3[:,:,2]] data_4 = np.r_[data4[:,:,0],data4[:,:,1],data4[:,:,2]] data_5 = np.r_[data4[:,:,0],data4[:,:,1],data4[:,:,2]] train_data = np.r_[data_1, data_2, data_3, data_4, data_5] train_length = len(train_data) return train_data, train_length
def get_test_data(): test, width, height = load_image.loadimage("DragonsAndBunnies") test_data = np.r_[test[:,:,0], test[:,:,1], test[:,:,2]] test_length = len(test_data) return test_data, test_length, width, height
def get_test_data(): test, width, height = load_image.loadimage("DragonsAndBunnies") test_data = np.r_[test[:, :, 0], test[:, :, 1], test[:, :, 2]] test_length = len(test_data) return test_data, test_length, width, height