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Tensorflow Lite Object Detection Demo App 2019 1.1

8.3 MB / 0+ Downloads / Rating 5.0 - 2 reviews


See previous versions

Tensorflow Lite Object Detection Demo App 2019, developed and published by CodeDunK, has released its latest version, 1.1, on 2024-01-06. This app falls under the Libraries & Demo category on the Google Play Store and has achieved over 1 installs. It currently holds an overall rating of 5.0, based on 2 reviews.

Tensorflow Lite Object Detection Demo App 2019 APK available on this page is compatible with all Android devices that meet the required specifications (Android 5.0+). It can also be installed on PC and Mac using an Android emulator such as Bluestacks, LDPlayer, and others.

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App Screenshot

App Screenshot

App Details

Package name: org.tensorflow.lite.codedunks.detection

Updated: 1 year ago

Developer Name: CodeDunK

Category: Libraries & Demo

New features: Show more

App Permissions: Show more

Installation Instructions

This article outlines two straightforward methods for installing Tensorflow Lite Object Detection Demo App 2019 on PC Windows and Mac.

Using BlueStacks

  1. Download the APK/XAPK file from this page.
  2. Install BlueStacks by visiting http://bluestacks.com.
  3. Open the APK/XAPK file by double-clicking it. This action will launch BlueStacks and begin the application's installation. If the APK file does not automatically open with BlueStacks, right-click on it and select 'Open with...', then navigate to BlueStacks. Alternatively, you can drag-and-drop the APK file onto the BlueStacks home screen.
  4. Wait a few seconds for the installation to complete. Once done, the installed app will appear on the BlueStacks home screen. Click its icon to start using the application.

Using LDPlayer

  1. Download and install LDPlayer from https://www.ldplayer.net.
  2. Drag the APK/XAPK file directly into LDPlayer.

If you have any questions, please don't hesitate to contact us.

App Rating

5.0
Total 2 reviews

Reviews

5 ★, on 2019-09-03
Wow!!! Amazing to see how fast the objects are detected on a smart phone. Machine learning has pushed the limits. Interesting App. Easy to use

5 ★, on 2019-09-03
Very fast for detecting objects bounding boxes are amazing. It's an useful application for developing object detection using tensorflow lite.

Previous Versions

Tensorflow Lite Object Detection Demo App 2019 1.1
2024-01-06 / 8.3 MB / Android 5.0+

About this app

Launch the TensorflowLite demo app and start viewing different objects in camera preview to see the bounding boxes and live tracking in action.

TensorFlow Lite provides all the tools you need to convert and run TensorFlow models on mobile, embedded, and IoT devices.

The source code of the app is open source and can be found on Github using the link below:
https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/examples

TensorFlow Lite allows you to run TensorFlow models on a wide range of devices. A TensorFlow model is a data structure that contains the logic and knowledge of a machine learning network trained to solve a particular problem.

What is object detection?
Given an image or a video stream, an object detection model can identify which of a known set of objects might be present and provide information about their positions within the image.

An object detection model is trained to detect the presence and location of multiple classes of objects. For example, a model might be trained with images that contain various pieces of fruit, along with a label that specifies the class of fruit they represent (e.g. an apple, a banana, or a strawberry), and data specifying where each object appears in the image.

When we subsequently provide an image to the model, it will output a list of the objects it detects, the location of a bounding box that contains each object, and a score that indicates the confidence that detection was correct.

New features

- TensorflowLite Object Detection And Tracking
- Checkout the amazing detection speed of TensorflowLite on any Android Device

App Permissions

Required to be able to access the camera device.
Allows applications to open network sockets.
Allows applications to access information about networks.
Allows using PowerManager WakeLocks to keep processor from sleeping or screen from dimming.