import tensorflow as tf
import numpy as np
import glob
from numpy import array
fq=glob.glob("*.jpg")
from PIL import Image

filename_queue = tf.train.string_input_producer(fq)
reader = tf.WholeFileReader()
key, value = reader.read(filename_queue)
my_img = tf.image.decode_jpeg(value,channels=3)
my_img=tf.cast(my_img,tf.float32)
resized_image = tf.image.resize_images(my_img, [50, 50])
labels = tf.placeholder(tf.int32, [None])
images=tf.placeholder(tf.float32,[None,50,50,3])
la=[0,0,0,0,0,0,1,1,1,1]
onehot =tf.one_hot(la, depth=2)
image_batch,label_batch=tf.train.batch([resized_image,onehot],enqueue_many=True,dynamic_pad=True,allow_smaller_final_batch=True,batch_size=2,num_threads=1)