無法使用tflearn

Question

的圖像數據集加載到蟒蛇我不能夠將圖像數據集加載到使用tflearn 它顯示了我的錯誤蟒蛇...

TypeError: image_preloader() got an unexpected keyword argument 'categorical_lables' 

是代碼..

from __future__ import division, print_function, absolute_import 

import tflearn 
import tensorflow as tf 
from tflearn.data_utils import shuffle 
from tflearn.layers.core import input_data, dropout, fully_connected 
from tflearn.layers.conv import conv_2d, max_pool_2d 
from tflearn.layers.estimator import regression 
from tflearn.data_preprocessing import ImagePreprocessing 
from tflearn.data_augmentation import ImageAugmentation 
import pickle 

dataset_file = 'data.txt' 
from tflearn.data_utils import image_preloader 
X,Y=image_preloader(dataset_file, image_shape=(100,100),mode=file,categorical_lables=True,normalize=True) 
img_prep = ImagePreprocessing() 
img_prep.add_featurewise_zero_center() 
img_prep.add_featurewise_stdnorm() 
network = input_data(shape=[None, 32, 32, 3], 
        data_preprocessing=img_prep, 
       data_augmentation=img_aug) 
network = conv_2d(network, 32, 3, activation='relu') 
network = max_pool_2d(network, 2) 
network = conv_2d(network, 64, 3, activation='relu') 
network = conv_2d(network, 64, 3, activation='relu') 
network = max_pool_2d(network, 2) 
network = fully_connected(network, 512, activation='relu') 
network = dropout(network, 0.5) 
network = fully_connected(network, 2, activation='softmax') 
network = regression(network, optimizer='adam', 
       loss='categorical_crossentropy', 
       learning_rate=0.001) 
model = tflearn.DNN(network, tensorboard_verbose=0, checkpoint_path='bird-classifier.tfl.ckpt') 
model.fit(X, Y, n_epoch=100, shuffle=True, validation_set=(X_test, Y_test), 
     show_metric=True, batch_size=96, 
     snapshot_epoch=True, 
     run_id='bird-classifier') 

和的data.txt文件constains /路徑/到/圖像類

例如 img1.jpeg 0 img2.jpeg 1 。 。 。 。 。 。 。

Answer 1

也許檢查categorical_labels上的拼寫。