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Objects Detection Machine Learning TensorFlow Demo.

Uses the Google TensorFlow Machine Learning Library Inception model to detect object with camera frames in real-time, displaying the label and overlay on the camera image.

Detect 1001 objects in this model

more info

http://androidcontrol.blogspot.com

What is TensorFlow?

TensorFlow is open source machine learning library from Google. Computation code is written in C++, but programmers can write their TensorFlow software in either C++ or Python and implemented for CPUs ,GPUs or both.

In November 2015, Google announced and open sourced TensorFlow, its latest and greatest machine learning library. This is a big deal for three reasons:

 

1.Machine Learning expertise: Google is a dominant force in machine learning. Its prominence in search owes a lot to the strides it achieved in machine learning.

2.Scalable : the announcement noted that TensorFlow was initially designed for internal use and that it’s already in production for some live product features.

3.Ability to run on Mobile.

 

This last reason is the operating reason for this post since we’ll be focusing on Android. If you examine the tensorflow repo on GitHub, you’ll find a little tensorflow/examples/android directory. I’ll try to shed some light on the Android TensorFlow example and some of the things going on under the hood.

original code 

https://github.com/tensorflow/tensorflow/tree/master/tensorflow/examples/android

My Website

http://softpowergroup.net/

My Blog

https://androidcontrol.blogspot.com

email : info@softpowergroup.net 

amphancm@gmail.com

Tel .6681-6452400 ( Thailand )

 

Google+  https://plus.google.com/+SoftpowergroupNetThailand/

Facebook : https://www.facebook.com/softpowergroup/

目标检测机器学习TensorFlow演示。

采用谷歌TensorFlow机器学习库盗梦空间模型来检测对象与实时摄像头帧，显示摄像机图像上的标签和覆盖。

检测在这个模型1001级的对象

更多信息

http://androidcontrol.blogspot.com

什么是TensorFlow？

TensorFlow是开源的机器从谷歌学习型图书馆。计算代码是用C ++编写，但程序员可以在任何C ++或Python编写他们TensorFlow软件和的CPU，GPU或两者实现。

在2015年11月，谷歌宣布与开源TensorFlow，其最新和最伟大的机器学习库。这是一个大问题，原因有三：

 

1.机器学习专业知识：谷歌是机器学习中的主导力量。其在搜索突出很大程度上要归功于它在机器学习所取得的进展。

2.Scalable：公告指出，TensorFlow最初设计用于内部使用，并且它已经在生产现场的一些产品功能。

3.Ability在移动设备上运行。

 

这最后一个原因是这个职位的工作的原因，因为我们将专注于Android系统。如果您检查在GitHub上tensorflow回购，你会发现一个小tensorflow /例子/ Android的目录。我会尽力摆脱对Android TensorFlow例子和某些引擎盖下的事情在进行一些轻。

原代码

https://github.com/tensorflow/tensorflow/tree/master/tensorflow/examples/android

我的网站

http://softpowergroup.net/

我的博客

https://androidcontrol.blogspot.com

电子邮件：info@softpowergroup.net

amphancm@gmail.com

电话.6681-6452400（泰国）

 

Google+的https://plus.google.com/+SoftpowergroupNetThailand/

Facebook的：https://www.facebook.com/softpowergroup/

Objects Detection Machine Learning TensorFlow Demo

Objects Detection Machine Learning TensorFlow Demo的最新版本