使用android studio应用程序获取python生成的数据

Question

I have a python script that runs a Linear Regression model:

import sklearn
import pandas
import numpy
from sklearn import linear_model

#Get Data from data set
data = pandas.read_csv("dataset.csv", sep=";")
data = data[["Red", "Green", "Blue", "T"]]

#Define Variables
x = numpy.array(data.drop(["T"], 1))  # Data set
y = numpy.array(data["T"])  # Correct values


#Set training sets
x_train, x_test, y_train, y_test = sklearn.model_selection.train_test_split(x, y, test_size=0.2)
linear = linear_model.LinearRegression()
linear.fit(x_train, y_train)

#Random Value
a = [[145, 131, 125, 35], [0, 0, 0, 0]]

#Predictions
p = linear.predict(a)

The linear.predict() function returns exactly the value I need. But I need to be able to access this function and the model through an Android Studio Application.

Any suggestions??

Answer 1

assume your model is named 'model', then you can export it like this:

import tensorflow as tf
from tensorflow.keras import models

keras_file='cf.h5'
models.save_model(model,keras_file)
converter=tf.compat.v1.lite.TFLiteConverter.from_keras_model_file(keras_file)
tfmodel = converter.convert()
open("degree.tflite","wb").write(tfmodel)

and in android studio you can predict using the sample input futures by calling doInterface method after you put the exported model file degree.tflite in your project assets

here is a full tutorial on this

import org.tensorflow.lite.Interpreter;

private MappedByteBuffer loadModelFile(){
 AssetFileDescriptor fileDescriptor= null;
 try {
 fileDescriptor = this.getAssets().openFd("degree.tflite");

 FileInputStream inputStream=new FileInputStream(fileDescriptor.getFileDescriptor());
 FileChannel fileChannel=inputStream.getChannel();
 long startOffset=fileDescriptor.getStartOffset();
 long declareLength=fileDescriptor.getDeclaredLength();
 return fileChannel.map(FileChannel.MapMode.READ_ONLY,startOffset,declareLength);
 } catch (IOException e) {
 e.printStackTrace();
 }
 return null;
}

private double[] doInference (double[] input) {
 Interpreter tflite;
 double[] output = new double[1]; //depending on your output shape
 try {
 tflite = new Interpreter(loadModelFile());
 tflite.run(input,output);
 return output;
 }catch (Exception ex){
 ex.printStackTrace();
 }
 return output;
}