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