About Objects Detection Machine Learning TensorFlow Demo
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...
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
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Previous Versions
Here you can find the changelog of Objects Detection Machine Learning TensorFlow Demo since it was posted on our website on 2019-07-11 08:10:06.
The latest version is 0.2 and it was updated on 2024-03-28 19:57:32. See below the changes in each version.
Objects Detection Machine Learning TensorFlow Demo version 0.2
Updated At: 2017-10-09
Changes: Version 0.2
Disclaimer
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