Dog Breed Identifier Application icon

Dog Breed Identifier 1.15

93.3 MB / 1+ Downloads / Rating 5.0 - 1 reviews


See previous versions

Dog Breed Identifier, developed and published by Larry GOYEAU, has released its latest version, 1.15, on 2024-09-22. This app falls under the Tools category on the Google Play Store and has achieved over 50 installs. It currently holds an overall rating of 5.0, based on 1 reviews.

Dog Breed Identifier APK available on this page is compatible with all Android devices that meet the required specifications (Android 4.1+). 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: com.dog.vision.demo

Updated: 5 months ago

Developer Name: Larry GOYEAU

Category: Tools

App Permissions: Show more

Installation Instructions

This article outlines two straightforward methods for installing Dog Breed Identifier 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.

Reviews

1 ★, on 2021-02-06
IT dot tell you what your dog is?!

Previous Versions

Dog Breed Identifier 1.15
2024-09-22 / 93.3 MB / Android 4.1+

About this app

This app allow you to automatically detect the breed of a dog on images. The model, EfficientNetB3, is trained on 70428 labeled images from 130 different breeds. It got a validation accuracy of 84%.
The source code of the app can be found in the GitHub repository:
https://github.com/larrygoyeau/dog_friendly
The description of the model, the training data and the training process is described in this notebook:
https://colab.research.google.com/drive/1j76-FNYwVtWzUEYKj7oxBsvxHUJ-pkNA?usp=sharing

App Permissions

Allows applications to open network sockets.
Allows an application to write to external storage.
Allows an application to read from external storage.
Required to be able to access the camera device.