LiangjunFeng / Create-dataset-for-Tensorflow

create yourself dataset for tensorflow

Create-dataset-for-Tensorflow

create yourself dataset for tensorflow

test code

getTrianList()
dataroad = "/Users/zhuxiaoxiansheng/Desktop/Yaledata.txt"
outputdir = "/Users/zhuxiaoxiansheng/Desktop/Yaledata"
trainroad = trans2tfRecord(dataroad,outputdir)
traindata,trainlabel = read_tfRecord(trainroad)

image_batch,label_batch = tf.train.shuffle_batch([traindata,trainlabel],
                                        batch_size=100,capacity=2000,min_after_dequeue = 1000) 

with tf.Session() as sess:
    sess.run(tf.local_variables_initializer())
    sess.run(tf.global_variables_initializer())
    coord = tf.train.Coordinator()
    threads = tf.train.start_queue_runners(sess=sess,coord = coord)
    train_steps = 10  
    # Retrieve a single instance:  
    try:  
        while not coord.should_stop(): 
            example,label = sess.run([image_batch,label_batch])  
            print(example.shape,label)  

            train_steps -= 1  
            print(train_steps)  
            if train_steps <= 0:  
                coord.request_stop()    

    except tf.errors.OutOfRangeError:  
        print ('Done training -- epoch limit reached')  
    finally:  
        # When done, ask the threads to stop. 
        coord.request_stop()  
        # And wait for them to actually do it.  
        coord.join(threads)      

output