Google AI Blog: Supercharge your Computer Vision models with the TensorFlow Object Detection API

Supercharge your Computer Vision models with the TensorFlow Object Detection API

Thursday, June 15, 2017

Posted by Jonathan Huang, Research Scientist and Vivek Rathod, Software Engineer(Cross-posted on the Google Open Source Blog)spur progress in the research community

Detected objects in a sample image (from the COCO dataset) made by one of our models. Image credit: Michael Miley, original image.

COCO detection challenge1,2,3,4,5,6,7NestCamsimilar items and style ideasstreet number and name detectionTensorFlow Object Detection APITensorFlow

A selection of trainable detection models, including:

Single Shot Multibox Detector (SSD) with MobileNets
SSD with Inception V2
Region-Based Fully Convolutional Networks (R-FCN) with Resnet 101
Faster RCNN with Resnet 101
Faster RCNN with Inception Resnet v2

Frozen weights (trained on the COCO dataset) for each of the above models to be used for out-of-the-box inference purposes.

A Jupyter notebook for performing out-of-the-box inference with one of our released models

Convenient local training scripts as well as distributed training and evaluation pipelines via Google Cloud

CVPR 2017 paperAre you ready to get started?hereJupyter notebooktraining your own pet detector on Cloud ML engine
AcknowledgementsCore Contributors:Derek Chow, Chen Sun, Menglong Zhu, Matthew Tang, Anoop Korattikara, Alireza Fathi, Ian Fischer, Zbigniew Wojna, Yang Song, Sergio Guadarrama, Jasper Uijlings, Viacheslav Kovalevskyi, Kevin MurphyAlso special thanks to:Andrew Howard, Rahul Sukthankar, Vittorio Ferrari, Tom Duerig, Chuck Rosenberg, Hartwig Adam, Jing Jing Long, Victor Gomes, George Papandreou, Tyler ZhuReferences

Speed/accuracy trade-offs for modern convolutional object detectors, Huang et al., CVPR 2017 (paper describing this framework)

Towards Accurate Multi-person Pose Estimation in the Wild, Papandreou et al., CVPR 2017

YouTube-BoundingBoxes: A Large High-Precision Human-Annotated Data Set for Object Detection in Video, Real et al., CVPR 2017 (see also our blog post)

Beyond Skip Connections: Top-Down Modulation for Object Detection, Shrivastava et al., arXiv preprint arXiv:1612.06851, 2016

Spatially Adaptive Computation Time for Residual Networks, Figurnov et al., CVPR 2017

AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions, Gu et al., arXiv preprint arXiv:1705.08421, 2017

MobileNets: Efficient convolutional neural networks for mobile vision applications, Howard et al., arXiv preprint arXiv:1704.04861, 2017

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Supercharge your Computer Vision models with the TensorFlow Object Detection API

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