Live data from Hacker News

Supercharge your Computer Vision models with the TensorFlow Object Detection API

research.googleblog.com

41–50 of 66 posts

Re: Supercharge your Computer Vision models with the TensorFlow Object Detection API

#43
post #20

Is this a new Google API for use through their cloud offering or is it a set of tensorflow artifacts one can download and use freely without ever contacting Google Cloud?

Clicking through the two layers of links, it is a GitHub repository containing pre-trained models, training scripts, and scripts for running the models on Google Cloud: https://github.com/tensorflow/models/tree/master/object_dete...

Holy moly, I can't believe I didn't know about https://github.com/tensorflow/models

Re: Supercharge your Computer Vision models with the TensorFlow Object Detection API

#44
Their repository is pretty neat! It includes three state-of-the-art architectures in object detection: Faster-RCNN, RFCN, and SSD. It is missing YOLO [1][2], though, which shares some similarities with SSD. Another detector is the recently released Mask-RCNN [3], which of course wouldn't be possible to be included in this publication as we can't travel through time yet.

[1]: https://arxiv.org/abs/1506.02640

[2]: https://arxiv.org/abs/1612.08242

[3]: https://arxiv.org/abs/1703.06870

Re: Supercharge your Computer Vision models with the TensorFlow Object Detection API

#45

Just spent the last 6 months making anpr camera. Now just need to put Python on it. Fun times.

My sentiment exactly. For my full-time startup, we've been trying, testing (many), and productionizing (one) object detection network for the past nine months. It was a tedious effort of implementing papers from last year's CVPR conference. This makes some of our MOJO go away, but in the scheme of things we can focus more closely on our business. Mixed bag.

Re: Supercharge your Computer Vision models with the TensorFlow Object Detection API

#49
post #35

Earlier quoted context omitted.

I missed I/O -- what's particular to Tensorflow Lite? Is that distinct from the CPU target?

Mobile focused version of tensorflow.

Lol. Parallel data computations across resource (including battery) constrained devices? Good news, the owner of the device is now the product. The device is also the product. Can't wait.

Re: Supercharge your Computer Vision models with the TensorFlow Object Detection API

#50
post #22

Earlier quoted context omitted.

We still have a ways to go, to completely eliminating false positives, but these tools will help us get there. For example, you can recognize different types of objects now but we still need to figure out which are meaningful or not (like a person or animal vs a tree blowing in the wind). Even certain classes, some are benign while others or not, for example pedestrians walking by the front of my house versus a guy w…

Even a confidence level would go a long way. If I get a notification that says "motion detected" I have to look at it, but if it said "motion detected, person with 75% confidence" that suddenly becomes much more valuable.

Digital cameras pick up different parts of the spectrum. My curiosity is raised. Could that be used to increase confidence levels?
Post reply on HN