Good way to input PASCAL-VOC 2012 training data and labels with tensorflow
<p>I want to do object detection of <a href="http://host.robots.ox.ac.uk/pascal/VOC/voc2012/index.html#introduction" rel="nofollow">PASCAL-VOC 2012 dataset</a> with tensorflow. </p>

<p>I want to input <strong>the whole image</strong> with <strong>object labels</strong> and the corresponding <strong>bounding boxes</strong> into the tensorflow for training. </p>

<p>Is there any good way to write a data file for tensorflow to read? Or just read the original XML file in tensorflow?</p>

<p>Thank you very much.</p>

<p>Here is an image example:
<a href="http://i.stack.imgur.com/1i0O1.jpg" rel="nofollow"><img src="http://i.stack.imgur.com/1i0O1.jpg" alt="enter image description here"></a> </p>

<p>It seems that TF have no support of xml files yet. </p>

<ol>
<li><p>You can try to make batches by yourself and feed them to TF placeholders. 
<a href="https://www.tensorflow.org/versions/r0.10/how_tos/reading_data/index.html#feeding" rel="nofollow">https://www.tensorflow.org/versions/r0.10/how_tos/reading_data/index.html#feeding</a></p></li>
<li><p>You can write your own file format and your own decoder. Then you can read file and get file bytes with <code>tf.decode_raw</code> function and do whatever you whant. Related question if you whant to read multiple files simultaneously: <a href="http://stackoverflow.com/questions/34340489/tensorflow-read-images-with-labels">Tensorflow read images with labels</a></p></li>
</ol>

<p>I think that first option is easier to implement.</p>

python tensorflow deep-learning