Custom Machine learning code to import in the android studio - firebase

Question

I am creating a project of fake news detection in android. I have trained the model and converted into the tensorflow lite. I tried to import it into the android studio in asset folder but it showed the message "This is not valid tensorflow lite model file".
enter image description here
can anyone help me to deploy it into android studio and to generate the input/output.
NOTE: I have tried export to firebase custom ML, I have run this code and didn't get any error
CustomModelDownloadConditions conditions = new CustomModelDownloadConditions.Builder().requireWifi().build();
FirebaseModelDownloader.getInstance().getModel("NewsCheckModel",
DownloadType.LOCAL_MODEL_UPDATE_IN_BACKGROUND, conditions)
.addOnSuccessListener(new OnSuccessListener<CustomModel>() {
#Override
public void onSuccess(CustomModel customModel) {
File modelFile = customModel.getFile();
if (modelFile != null) {
Interpreter interpreter = new Interpreter(modelFile);
}
}
});
I don't know the further steps.
.
.
.
if anyone can help in any way using asset folder or firebase way. I would be very thankful to you

Answer 1

Could you make sure that no compression option is enabled as follows while experimenting on the asset dir case?
android {
// ...
aaptOptions {
noCompress "tflite" // Your model's file extension: "tflite", "lite", etc.
}
}
See more details at this guide page.

Answer 2

There's not much information on your post. It would be useful to know if:
Are you able to deploy it on android?
Does the model initialize?
If yes, Can you perform inference?
If no, what is the exception you get?
In the past, I've had the same problem. So here are some basic steps:
Add Firebase to your project
2a. Make sure you are using the correct dependencies :
They have been updated recently so better follow this guide: here
Basically:
dependencies {
// Import the BoM for the Firebase platform
implementation platform('com.google.firebase:firebase-bom:28.0.1')
// Declare the dependency for the Firebase ML model downloader library
// When using the BoM, you don't specify versions in Firebase library dependencies
implementation 'com.google.firebase:firebase-ml-modeldownloader'
// Also declare the dependency for the TensorFlow Lite library and specify its version
implementation 'org.tensorflow:tensorflow-lite:2.3.0'
}
2b. Add to Manifest:
<uses-permission android:name="android.permission.INTERNET" />
3a. Double check the way you convert your model. Luckily you can convert and deploy to firebase easily:
3b. Convert the model to TensorFlow Lite and upload it to Cloud Storage
source = ml.TFLiteGCSModelSource.from_saved_model('./model_directory')
3c. Create the model object
tflite_format = ml.TFLiteFormat(model_source=source)
model = ml.Model(
display_name="example_model", # This is the name you use from your app to load the model.
tags=["examples"], # Optional tags for easier management.
model_format=tflite_format)
3d. Add the model to your Firebase project and publish it
new_model = ml.create_model(model)
ml.publish_model(new_model.model_id)
3a bis: If your model is already in .tflite:
source = ml.TFLiteGCSModelSource.from_tflite_model_file('example.tflite')
The guide is here
Regarding the inputs/outputs, I can't say much as it depends on your model. Also, be careful with the data types of input and output. Be aware of the type that your model requires (INT32, UINT8, FLOAT32....)
Another important thing is to have some metadata embedded in your model: here
Android Studio uses that metadata to display information when you open a .tflite file.
IMO is very likely that your issue is during your model conversion or lack of metadata.