Tensorflow Inception resnet v2 input tensor
<p>I'm trying to run this code</p>

<pre><code>import os
import tensorflow as tf
from datasets import imagenet
from nets import inception_resnet_v2
from preprocessing import inception_preprocessing

checkpoints_dir = 'model'

slim = tf.contrib.slim

batch_size = 3
image_size = 299

with tf.Graph().as_default():

with slim.arg_scope(inception_resnet_v2.inception_resnet_v2_arg_scope()):
    logits, _ = inception_resnet_v2.inception_resnet_v2([1, 299, 299, 3], num_classes=1001, is_training=False)
    probabilities = tf.nn.softmax(logits)

    init_fn = slim.assign_from_checkpoint_fn(
    os.path.join(checkpoints_dir, 'inception_resnet_v2_2016_08_30.ckpt'),
    slim.get_model_variables('InceptionResnetV2'))

    with tf.Session() as sess:
        init_fn(sess)

        imgPath = '.../image_3.jpeg'
        testImage_string = tf.gfile.FastGFile(imgPath, 'rb').read()
        testImage = tf.image.decode_jpeg(testImage_string, channels=3)

        np_image, probabilities = sess.run([testImage, probabilities])
        probabilities = probabilities[0, 0:]
        sorted_inds = [i[0] for i in sorted(enumerate(-probabilities), key=lambda x:x[1])]

        names = imagenet.create_readable_names_for_imagenet_labels()
        for i in range(15):
            index = sorted_inds[i]
            print((probabilities[index], names[index]))
</code></pre>

<p>But TF displays an error: <code>ValueError: rank of shape must be at least 4 not: 1</code> </p>

<p>I believe that problem is in input tensor shape <code>[1, 299, 299, 3]</code>. How to  input tensor for 3 channel JPEG image??? </p>

<p>there is an also one similar question (<a href="https://stackoverflow.com/questions/39582703/using-pre-trained-inception-resnet-v2-with-tensorflow">Using pre-trained inception_resnet_v2 with Tensorflow</a>). I saw in code input_tensor - unfortunatelly there is explanation what is <code>input_tensor</code>. Maybe I'm asking something  self-evident but i stuck! Thanks a lot in advance for any advice!</p>