Hello and welcome back.
In this section we're going to build an application that uses pre-trained machine learning model.
So we're going to use third party machine learning model and implement it with our Android application.
For this purpose I want from you to focus with me to understand every step that I made.
Okay, there are a lot of websites online that provides you with many models and many pre-trained models.
The most important and the best website is Kaggle.com.
This is a website by Google that provides a huge repository of community published models, data and
codes.
Okay, so go to kaggle.com.
Sign in and there are a lot of things you can do in this website.
It's amazing community for machine learning models and data sets.
Okay, in order to benefit from this website and download an object detection model.
Go to models, search for object detection and hit enter.
There are a lot of results you can download YOLO version eight.
MobileNet version two.
Uh, actually we're going we're going to use the MobileNet version one.
If we go to mobile version two, scroll down.
There are a lot of variants, but there are there is no tflite okay.
So if you select you can download them, but they are of type BB.
We don't need to go and convert these models.
We can download ready made Tflite model okay if you prefer downloading it and then converting the model
into Tflite you can go with.
Okay, so select SSD mobile.
Net version one.
This is a very important object detection and very popular object detection model trained on Coco dataset.
If you want to learn about Coco dataset, you can click on this link Coco dataset org and Coco refers
for common objects in context.
There are a lot of objects you can discover in this data set, but we are.
The thing that you should pay attention to is that those data sets and are, um, are imported and added
to the model.
TensorFlow model SSD mobile.
Net version one okay scroll down.
There are a lot of model variations.
You can download them.
You can download TensorFlow two, TensorFlow JS or JavaScript and light RT.
Light RT by the way, is TF Lite.
TF Lite is the old version of R of models by TensorFlow, and the new name of TF Lite is light RT.
You can download the default, select default, and click download.
You can go to Google Colab and import this, or you can download the model and start.
We are interested in loading it as zip file.
Click open and here is our model.
Copy it.
And here create a new folder called model.
Paste it here and extract the model.
Here we get TF Lite file.
Rename it as SSD underscore mobile.
Net version one.
Okay this is our model, our pre-trained model.
You can read about this model if you scroll down.
There are a lot of things you should pay attention to it.
You can download it from here one dot Tflite the metadata.
The data sets, the input output of the model and so on.
Okay, so this is our model.
You see guys are detecting persons kite and others okay.
This is a very important model.
And uh maybe it's around 90 objects we can detect.
And it supports um multiple model detection and multiple object detection okay.
So please guys pay attention.
Tflite is similar to light art in this way.
We downloaded our model and now we can add it to our Android Studio project.