Is it possible to have bounding boxes prediction using TensorFlow? I found TensorBox on github but I'm looking for a better supported or maybe official way to address this problem.

I need to retrain the model for my own classes.

  • Hi @BernardoGO I have the same concern, have you find any solution for this? – M David Dec 16 '16 at 4:35

It is unclear what exactly do you mean. Do you need object detection? I assume it from the 'bounding boxes'. If so, inception networks are not directly applicable for your task, they are classification networks. You should look for object detection models, like Single Shot Detector (SSD) or You Only Look Once (YOLO). They often use pre-trained convolutional layers from classification networks, but have additional layers on the top of it. If you want Inception (aka GoogLeNet), YOLO is based on that. Take a look at this implementation: https://github.com/thtrieu/darkflow or any other you can find in Google.

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  • Have you tried Darkflow? I consider the documentation terrible. – Olha Jan 17 '17 at 15:35

The COCO2016 winner for object detection was implemented in tensorflow. Some state of the art techniques are Faster R-CNN, R-FCN and SSD. Check the slides from http://image-net.org/challenges/talks/2016/GRMI-COCO-slidedeck.pdf (Slide 14 has key tensorflow ops for you to recreate this pipeline).

Edit 6/19/2017: Tensorflow released some techniques to predict bboxes: https://research.googleblog.com/2017/06/supercharge-your-computer-vision-models.html

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