Objects Detection Machine Learning TensorFlow Demo APK
Version 0.2 - org.tensorflow.detecttensorflow,detect,libraries,demo,object,detection
Objects Detection Machine Learning TensorFlow with Realtime Camera Demo
APP Information
| Download Version | 0.2 (2) |
| Apk Size | 87.62 MB |
| App Developer | Amphan |
| Malware Check | TRUSTED |
| Install on Android | 5.0 and up |
| App Package | org.tensorflow.detect.apk |
| MD5 | 088273aba5b18f06327f3eb877d0535d |
| Rate | 4.5 |
| Website | http://softpowergroup.net |
Table of Contents
Download Objects Detection Machine Learning TensorFlow Demo 0.2 APK
App Description
Objects Detection Machine Learning TensorFlow Demo is tensorflow,detect,libraries,demo,object,detection, content rating is Everyone (PEGI-3). This app is rated 4.5 by 2 users who are using this app. To know more about the company/developer, visit Amphan website who developed it. org.tensorflow.detect.apk apps can be downloaded and installed on Android 5.0 and higher Android devices. The Latest Version of 0.2 Available for download. Download the app using your favorite browser and click Install to install the application. Please note that we provide both basic and pure APK files and faster download speeds than APK Mirror. This app APK has been downloaded 186+ times on store. You can also download org.tensorflow.detect APK and run it with the popular Android Emulators.
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 itβs 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 weβll be focusing on Android. If you examine the tensorflow repo on GitHub, youβll find a little tensorflow/examples/android directory. Iβll 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 : [email protected] [email protected] Tel .6681-6452400 ( Thailand ) Google+ https://plus.google.com/+SoftpowergroupNetThailand/ Facebook : https://www.facebook.com/softpowergroup/
App ChangeLog
- Version 0.2
App Screens
Name:base.apk
Apk scan results
Apk Scaned By TotalVirus Antivirus,org.tensorflow.detect.apk Was Pure And Safe. Scan Stats:harmless:0|type-unsupported:11|suspicious:0|confirmed-timeout:0|timeout:0|failure:0|malicious:0|undetected:64| Name:TensorFlow_Object_Detection.apk
Name:base.apk SHA-1:790b3e637e791872e45fad1e97ea460d83d45dd8 SHA-256:fe3dab4d5780537b15fa1027fbdf3532321bbcf74522c9519de57adaf751ec7d SSDEEP:1572864:j6VaN6tjEa0yFgCF2BT31W3Aw4Vgx7uNAjPWW62tWoBLbgtnFslTZEIFWEf15H7f:zMEa0rBT31OKVYJjPd6dELktnFs5ZHHr File type:Android Magic:Zip archive data, at least v2.0 to extract, compression method=deflate File size:91876295 Uncompressed Size:110037036 Contained Files :123 Contained Files By Type:xml:19,dex:1,MF:1,RSA:1,jpg:26,pb:3,so:2,txt:2,SF:1,png:64,
Older Versions
More Android Apps to Consider
mattizzle Soda
Good as a benchmark for object detection on your phone. If you are interested in this stuff it is good just to try out, however it mostly shows that mobile phones still lack the processing power to do this well. I have a top of the line phone and speed/accuracy are not that great. I have tried video streaming from the phone to a high powered server with an nvidia gpu and it performs way better than this, but then it needs a net connection to an expensive server so pros/cons to both approaches.
Stephen Adamson
A nice demo that, while not 100 accurate, does the job to a certain degree. A fun experience more than a technical demonstration. One small issue is that it makes my popup front camera pop up despite not visibly.using any of its functionality. Perhaps trying work on both front and back camera simultaneously? Either way that needs fixed.
Anthony Dawson
Brilliant... I can see that privacy in the future will be a thing of the past. When I pointed it to my ceiling fan it said aeroplane 79% sure... Some more learning required π
Daniel Kawalsky
amazing feature of tracking items as they move! but the identification of said items needs improvement
Gerard Virgona
amusing, it said that a footpath was a apple, a phone box a car & a shopfront was a train. Very funny
Chan Wai Hung
Accuracy very low and the rate of false detection very high.
chi Ming chang
Great trial for the first machine learning app
Tiger Zuo
Great app, more object class will be appreciated
Sunny Kumar
It tells different names for the same object every time
X
wants access not only to camera, but also to files