pas en mesure de charger l'ensemble de données d'image en python utilisant tflearn

Question

je ne suis pas en mesure de charger un ensemble de données d'image en python utilisant tflearn il me montre une erreur ...

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

Voici le code ..

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') 

et data.txt fichier constains /chemin/vers/image classe

exemple img1.jpeg 0 img2.jpeg 1 . . . . . . .

Answer 1

Peut-être vérifier l'orthographe sur categorical_labels.