How can I add labels to TensorBoard Images?

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TensorBoard is a great tool, but can it be more robust? The image below shows the visualization in TensorBoard.

It's called by the following code:

tf.image_summary('images', images, max_images=100)

As the API suggests, the last digit is the "image number", from 0 to 99 in this case since I specified max_images = 100. I would like to ask, if I can append the label of this image into the text? This would be a great functionality to have as it allows users to see in real time the images and their respective labels during training. In the event whereby some images are totally mislabelled, a fix can be implemented. In other words, I would like the corresponding text in the image below to be:

images/image/9/5
images/image/39/6
images/image/31/0
images/image/30/2
where last digit is the label.

Thanks!

enter image description here

tensorboard tensorflow python
2 Answers

Here is a small improvement for approach proposed by Vince Gatto. We can use tf.py_func to avoid creating extra placeholders and doing extra session.run.

First, we define these function (you will need opencv-python installed):

import cv2
import tensorflow as tf

def put_text(imgs, texts):
    result = np.empty_like(imgs)
    for i in range(imgs.shape[0]):
        text = texts[i]
        if isinstance(text, bytes):
            text = text.decode()
        # You may need to adjust text size and position and size.
        # If your images are in [0, 255] range replace (0, 0, 1) with (0, 0, 255)
        result[i, :, :, :] = cv2.putText(imgs[i, :, :, :], str(text), (0, 30), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 1), 2)
    return result

def tf_put_text(imgs, texts):
    return tf.py_func(put_text, [imgs, texts], Tout=imgs.dtype)

Now we can use tf_put_text to print labels on top images just before feeding them to image summary:

annotated_images = tf_put_text(images, labels)
tf.summary.image('annotated_images', annotated_images, 4)
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