Ml android app | image recognition android app | machine learning | deploy ml android

in this video we have created a android app which can recognize the images it means if you show the image of dog it is going to tell you the breed of dog and if you show any fruit is it going to tell you which fruit it is.
similarly it can predict 1000 categories.
In this video we have also learnt how to deploy deep learning model on the android app by using android studio. Specifically we learnt to deploy tfilte models.
I have tried to show everything step wise and we have first seen how to get the model and then building gui for the app and after all deploying the model.

we have used latest version of Android studio to deploy TF lite it also we used kotlin language to back our app.

timestamps
0:00 - what exactly we’ll develop
0:40 - Getting model
1:40 - lets start new project
2:25 - Build GUI
4:28 - adding model and label
6:20 - BACKEND Selecting and showing the image
10:35 - coding PREDICTION part
14:30 - TESTING 1
15:10 - Getting Max category
18:40 - FINAL TESTING

password - 1234

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tags:
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image classification,
image recognition,
tensorflow lite android,
android app,
image recognition machine learning,
machine learning,
machine learning projects,
object detection android studio,
tensorflow lite android tutorial,
android studio,
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instruction set of 8086 microprocessor,
object detection,
tensorflow image recognition,
tensorflow lite

[andrewkozhemyakin]

you can say you saved my life, thank you very much !!

[josephemeraldmayangao]

I just want to thank you bro you saved my life <3

[m.ilhamsyah]

you are very helpful thanks. keep going :)

[kybal]

Hi, may I ask if adding confidence would make the output better? Thank you!

[prakatneupane]

Hi, how can i convert the kotlin file to java? could you provide a source code in java?

[Senanyakar]

sir i have an issue, i have mine own project for image classification i wrote on jupyterlab and saved it. i dont know how can i integrate it with mobile app can u help me please??

[sainathingle]

their is error of flatbuffer when we are using tflite and sceneform simultaneosly can you suggest any solution

[the-rebooted-coder]

How can I play an audio when a certain label gets above a certain confidence % level?

[ainal]

I have followed the video step by step, but when the application is run, the label / is classified as not the same as the confidence value, the highest value should be the label, can you help me, thank you

[gururajkotian]

Hey there !! I have a svm model to classify medicinal plants which predicts the species of plants, now i want a android app to implement my model in it and predict the species using the pics captured by the camera. Can you please tell me how this can be done ?

[rizwanabibi]

Sir I have no separate file for label on model so what should I do? Whenever I click on prediction button it show me number

[gee]

Hi! Can you do herbal plants classification and recognition

[Rudrixx]

Hi! This was an amazing video. I just want to ask on how can it predict without selecting photos, instead you, yourself would capture it?

[mujahidrasool]

Can you make a video on Image Segmentation on android using tflite because model provided by Tensorflow giving us some errors.

[DinanathLad]

I have a sample code wihich is do not content bytebufffer and data type etc.
So, what should i do?

[ruthvikparate]

Sir which language you have used for coding in this Project

[mahamahi-gf]

Can you create one video for Yolo object detection

[tantrydivya]

if i select other images rather than in the labels, it should display as unknown how should I implement that ?

[merickutan]

Hello sir when i import my tflite file it says TensorBuffer.createFixedSize(intArrayOf(1, 1, 1, 3), what should i do to make it 1, 224, 224, 3 like yours?

[mandeepraaj]

Hello Sir,
Thank you so much for uploading this content, it is very usefull for me.
I have done it But the problem is, I am unable to add Accuracy
My requirement is to display match accuracy of item
can you please give me any idea to do this
Any help will be Highly Appreciated.