import tensorflow as tf

    
    # Read image
    img = Image.open(image_path)
    img = img.resize([width,height], Image.ANTIALIAS)
    img = np.array(img).astype('float32')
    img = np.expand_dims(np.asarray(img), axis = 0)
   
    # Create a placeholder for the input image
    input_node = tf.placeholder(tf.float32, shape=(None, height, width, channels))
    
    # Construct the network
    net = models.ResNet50UpProj({'data': input_node}, batch_size)
        
    with tf.Session() as sess:

        # Load the converted parameters
