Welcome back.
We validate and test our model.
And this is the result on a new image.
Now let's export the model as Tflite in order to use it in Android Studio.
Okay.
So create a new cell here.
In order to export it as Tflite we need to use the TensorFlow.
So install ultra and TensorFlow.
TensorFlow from ultra.
Import yolo.
Create.
This model equals to YOLO and you can copy the previous model copy selection run okay so this is from
runs detect train runs detect train waits.
And best this is our model okay.
We need to convert it to Tflite in order to convert it.
Go and use model dot export.
And here set the format Equals do the f light.
We talked about this extension which is for Android and microcontrollers in light version.
Okay.
Let me run this cell and wait for the result.
And congratulations guys.
We succeeded in exporting this model into Tflite.
Okay so let me check where is the the model here runs detect a train.
Wait.
Saved.
You see there is a new file and a new folder.
This is best dot Onnx.
We don't need the Onnx extension.
We need the Tflite.
So go and open best saved model.
And here we have best Float16 Tflite and best Float32 Tflite versions.
Okay, let me download both.
And congratulations guys.
We created the TF Lite version of our model.