Key points detection 구현

 apply plugin: 'com.android.application'
 apply plugin: 'com.android.application'
+apply plugin: 'kotlin-android-extensions'
+apply plugin: 'kotlin-android'
 
 
 android {
 android {
     compileSdkVersion 29
     compileSdkVersion 29
@@ -17,6 +19,9 @@ android {
             proguardFiles getDefaultProguardFile('proguard-android-optimize.txt'), 'proguard-rules.pro'
             proguardFiles getDefaultProguardFile('proguard-android-optimize.txt'), 'proguard-rules.pro'
         }
         }
     }
     }
+    aaptOptions {
+        noCompress "tflite"
+    }
 }
 }
 
 
 dependencies {
 dependencies {
@@ -26,4 +31,11 @@ dependencies {
     testImplementation 'junit:junit:4.12'
     testImplementation 'junit:junit:4.12'
     androidTestImplementation 'androidx.test.ext:junit:1.1.0'
     androidTestImplementation 'androidx.test.ext:junit:1.1.0'
     androidTestImplementation 'androidx.test.espresso:espresso-core:3.1.1'
     androidTestImplementation 'androidx.test.espresso:espresso-core:3.1.1'
+    compile "androidx.core:core-ktx:+"
+    implementation 'org.tensorflow:tensorflow-lite:2.2.0'
+    implementation 'org.tensorflow:tensorflow-lite-gpu:2.2.0'
+    implementation "org.jetbrains.kotlin:kotlin-stdlib-jdk7:$kotlin_version"
+}
+repositories {
+    mavenCentral()
 }
 }

@@ -7,25 +7,39 @@ import androidx.core.app.ActivityCompat;
 import android.Manifest;
 import android.Manifest;
 import android.content.Context;
 import android.content.Context;
 import android.content.pm.PackageManager;
 import android.content.pm.PackageManager;
+import android.graphics.Bitmap;
+import android.graphics.Canvas;
+import android.graphics.Color;
+import android.graphics.ImageFormat;
+import android.graphics.Matrix;
+import android.graphics.Paint;
+import android.graphics.Rect;
 import android.hardware.camera2.CameraAccessException;
 import android.hardware.camera2.CameraAccessException;
 import android.hardware.camera2.CameraCaptureSession;
 import android.hardware.camera2.CameraCaptureSession;
 import android.hardware.camera2.CameraDevice;
 import android.hardware.camera2.CameraDevice;
 import android.hardware.camera2.CameraManager;
 import android.hardware.camera2.CameraManager;
 import android.hardware.camera2.CaptureRequest;
 import android.hardware.camera2.CaptureRequest;
+import android.media.Image;
+import android.media.ImageReader;
 import android.os.Bundle;
 import android.os.Bundle;
+import android.util.Log;
 import android.view.SurfaceHolder;
 import android.view.SurfaceHolder;
 import android.view.SurfaceView;
 import android.view.SurfaceView;
 import android.widget.Toast;
 import android.widget.Toast;
 
 
+import java.nio.ByteBuffer;
 import java.util.Arrays;
 import java.util.Arrays;
 
 
-public class ExerciseActivity extends AppCompatActivity implements SurfaceHolder.Callback {
+public class ExerciseActivity extends AppCompatActivity implements SurfaceHolder.Callback, ImageReader.OnImageAvailableListener {
 
 
     private static final int REQUEST_CAMERA = 1000;
     private static final int REQUEST_CAMERA = 1000;
 
 
     private SurfaceView surfaceView;
     private SurfaceView surfaceView;
     private CameraDevice camera;
     private CameraDevice camera;
     private CaptureRequest.Builder previewBuilder;
     private CaptureRequest.Builder previewBuilder;
+    private Posenet posenet;
+    private ImageReader imageReader;
+    private byte[][] yuvBytes = new byte[3][];
 
 
     @Override
     @Override
     protected void onCreate(Bundle savedInstanceState) {
     protected void onCreate(Bundle savedInstanceState) {
@@ -36,6 +50,18 @@ public class ExerciseActivity extends AppCompatActivity implements SurfaceHolder
         surfaceView.getHolder().addCallback(this);
         surfaceView.getHolder().addCallback(this);
     }
     }
 
 
+    @Override
+    protected void onStart() {
+        super.onStart();
+        posenet = new Posenet(this, "posenet_model.tflite", Device.GPU);
+    }
+
+    @Override
+    protected void onDestroy() {
+        super.onDestroy();
+        posenet.close();
+    }
+
     // 카메라 활성화
     // 카메라 활성화
     private void openCamera() {
     private void openCamera() {
         if (ActivityCompat.checkSelfPermission(this, Manifest.permission.CAMERA) != PackageManager.PERMISSION_GRANTED) {
         if (ActivityCompat.checkSelfPermission(this, Manifest.permission.CAMERA) != PackageManager.PERMISSION_GRANTED) {
@@ -99,10 +125,13 @@ public class ExerciseActivity extends AppCompatActivity implements SurfaceHolder
     // 카메라 Capture 시작
     // 카메라 Capture 시작
     private void startCapture() {
     private void startCapture() {
         try {
         try {
+            imageReader = ImageReader.newInstance(640, 480, ImageFormat.YUV_420_888, 2);
+            imageReader.setOnImageAvailableListener(this, null);
+
             previewBuilder = camera.createCaptureRequest(CameraDevice.TEMPLATE_PREVIEW);
             previewBuilder = camera.createCaptureRequest(CameraDevice.TEMPLATE_PREVIEW);
-            previewBuilder.addTarget(surfaceView.getHolder().getSurface());
+            previewBuilder.addTarget(imageReader.getSurface());
 
 
-            camera.createCaptureSession(Arrays.asList(surfaceView.getHolder().getSurface()), new CameraCaptureSession.StateCallback() {
+            camera.createCaptureSession(Arrays.asList(imageReader.getSurface()), new CameraCaptureSession.StateCallback() {
                 @Override
                 @Override
                 public void onConfigured(@NonNull CameraCaptureSession session) {
                 public void onConfigured(@NonNull CameraCaptureSession session) {
                     try {
                     try {
@@ -125,4 +154,110 @@ public class ExerciseActivity extends AppCompatActivity implements SurfaceHolder
             e.printStackTrace();
             e.printStackTrace();
         }
         }
     }
     }
+
+    @Override
+    public void onImageAvailable(ImageReader reader) {
+        Image image = reader.acquireLatestImage();
+        if(image == null)
+            return;
+
+        fillBytes(image.getPlanes(), yuvBytes);
+        int[] rgbBytes = new int[640 * 480];
+
+        ImageUtils.INSTANCE.convertYUV420ToARGB8888(yuvBytes[0], yuvBytes[1], yuvBytes[2],
+                640, 480,
+                image.getPlanes()[0].getRowStride(),
+                image.getPlanes()[1].getRowStride(),
+                image.getPlanes()[1].getPixelStride(), rgbBytes);
+
+        Bitmap imageBitmap = Bitmap.createBitmap(rgbBytes, 640, 480, Bitmap.Config.ARGB_8888);
+
+        Matrix rotateMatrix = new Matrix();
+        rotateMatrix.postRotate(90);
+
+        Bitmap rotatedBitmap = Bitmap.createBitmap(imageBitmap,
+                0, 0, 640, 480, rotateMatrix, true);
+        image.close();
+
+        processImage(rotatedBitmap);
+    }
+
+    private void fillBytes(Image.Plane[] planes, byte[][] yuvBytes) {
+        // Row stride is the total number of bytes occupied in memory by a row of an image.
+        // Because of the variable row stride it's not possible to know in
+        // advance the actual necessary dimensions of the yuv planes.
+        for (int i = 0; i < planes.length; i++) {
+            ByteBuffer buffer = planes[i].getBuffer();
+            if (yuvBytes[i] == null) {
+                yuvBytes[i] = new byte[buffer.capacity()];
+            }
+            buffer.get(yuvBytes[i]);
+        }
+    }
+
+    private Bitmap cropBitmap(Bitmap bitmap) {
+        float bitmapRatio = (float) bitmap.getHeight() / bitmap.getWidth();
+        float modelInputRatio = 257.0f / 257.0f;
+        Bitmap croppedBitmap = bitmap;
+
+        // Acceptable difference between the modelInputRatio and bitmapRatio to skip cropping.
+        double maxDifference = 1e-5;
+
+        // Checks if the bitmap has similar aspect ratio as the required model input.
+        if(Math.abs(modelInputRatio - bitmapRatio) < maxDifference)
+            return croppedBitmap;
+
+        if(modelInputRatio < bitmapRatio) {
+            // New image is taller so we are height constrained.
+            float cropHeight = bitmap.getHeight() - bitmap.getWidth() / modelInputRatio;
+            croppedBitmap = Bitmap.createBitmap(
+                    bitmap,
+                    0,
+                    (int) cropHeight / 2,
+                    bitmap.getWidth(),
+                    (int) (bitmap.getHeight() - cropHeight)
+            );
+        }
+        else {
+            float cropWidth = bitmap.getWidth() - bitmap.getHeight() * modelInputRatio;
+            croppedBitmap = Bitmap.createBitmap(
+                    bitmap,
+                    (int) (cropWidth / 2),
+                    0,
+                    (int) (bitmap.getWidth() - cropWidth),
+                    bitmap.getHeight()
+            );
+        }
+        return croppedBitmap;
+    }
+
+    private void processImage(Bitmap bitmap) {
+        Log.d("Capture", "Process");
+
+        // Crop bitmap.
+        Bitmap croppedBitmap = cropBitmap(bitmap);
+
+        // Created scaled version of bitmap for model input.
+        Bitmap scaledBitmap = Bitmap.createScaledBitmap(croppedBitmap, 257, 257, true);
+
+        // Perform inference.
+        Person person = posenet.estimateSinglePose(scaledBitmap);
+
+        Paint paint = new Paint();
+        Canvas canvas = surfaceView.getHolder().lockCanvas();
+
+        // 이미지 그리기
+        canvas.drawBitmap(croppedBitmap, new Rect(0, 0, croppedBitmap.getWidth(), croppedBitmap.getHeight()), new Rect(0, 0, canvas.getWidth(), canvas.getWidth()), paint);
+
+        // Key points 그리기
+        paint.setColor(Color.RED);
+        for(KeyPoint keyPoint : person.getKeyPoints()) {
+            if(keyPoint.getScore() < 0.7)
+                continue;
+
+            canvas.drawCircle((float) keyPoint.getPosition().getX() / scaledBitmap.getWidth() * canvas.getWidth(), (float) keyPoint.getPosition().getY() / scaledBitmap.getWidth() * canvas.getWidth(), 5, paint);
+        }
+
+        surfaceView.getHolder().unlockCanvasAndPost(canvas);
+    }
 }
 }

+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.khuhacker.pocketgym
+
+/** Utility class for manipulating images.  */
+object ImageUtils {
+  // This value is 2 ^ 18 - 1, and is used to hold the RGB values together before their ranges
+  // are normalized to eight bits.
+  private const val MAX_CHANNEL_VALUE = 262143
+
+  /** Helper function to convert y,u,v integer values to RGB format */
+  private fun convertYUVToRGB(y: Int, u: Int, v: Int): Int {
+    // Adjust and check YUV values
+    val yNew = if (y - 16 < 0) 0 else y - 16
+    val uNew = u - 128
+    val vNew = v - 128
+    val expandY = 1192 * yNew
+    var r = expandY + 1634 * vNew
+    var g = expandY - 833 * vNew - 400 * uNew
+    var b = expandY + 2066 * uNew
+
+    // Clipping RGB values to be inside boundaries [ 0 , MAX_CHANNEL_VALUE ]
+    val checkBoundaries = { x: Int ->
+      when {
+        x > MAX_CHANNEL_VALUE -> MAX_CHANNEL_VALUE
+        x < 0 -> 0
+        else -> x
+      }
+    }
+    r = checkBoundaries(r)
+    g = checkBoundaries(g)
+    b = checkBoundaries(b)
+    return -0x1000000 or (r shl 6 and 0xff0000) or (g shr 2 and 0xff00) or (b shr 10 and 0xff)
+  }
+
+  /** Converts YUV420 format image data (ByteArray) into ARGB8888 format with IntArray as output. */
+  fun convertYUV420ToARGB8888(
+    yData: ByteArray,
+    uData: ByteArray,
+    vData: ByteArray,
+    width: Int,
+    height: Int,
+    yRowStride: Int,
+    uvRowStride: Int,
+    uvPixelStride: Int,
+    out: IntArray
+  ) {
+    var outputIndex = 0
+    for (j in 0 until height) {
+      val positionY = yRowStride * j
+      val positionUV = uvRowStride * (j shr 1)
+
+      for (i in 0 until width) {
+        val uvOffset = positionUV + (i shr 1) * uvPixelStride
+
+        // "0xff and" is used to cut off bits from following value that are higher than
+        // the low 8 bits
+        out[outputIndex] = convertYUVToRGB(
+          0xff and yData[positionY + i].toInt(), 0xff and uData[uvOffset].toInt(),
+          0xff and vData[uvOffset].toInt()
+        )
+        outputIndex += 1
+      }
+    }
+  }
+}

+/*
+ * Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *       http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package com.khuhacker.pocketgym
+
+import android.content.Context
+import android.graphics.Bitmap
+import android.os.SystemClock
+import android.util.Log
+import java.io.FileInputStream
+import java.nio.ByteBuffer
+import java.nio.ByteOrder
+import java.nio.MappedByteBuffer
+import java.nio.channels.FileChannel
+import kotlin.math.exp
+import org.tensorflow.lite.Interpreter
+import org.tensorflow.lite.gpu.GpuDelegate
+
+enum class BodyPart {
+  NOSE,
+  LEFT_EYE,
+  RIGHT_EYE,
+  LEFT_EAR,
+  RIGHT_EAR,
+  LEFT_SHOULDER,
+  RIGHT_SHOULDER,
+  LEFT_ELBOW,
+  RIGHT_ELBOW,
+  LEFT_WRIST,
+  RIGHT_WRIST,
+  LEFT_HIP,
+  RIGHT_HIP,
+  LEFT_KNEE,
+  RIGHT_KNEE,
+  LEFT_ANKLE,
+  RIGHT_ANKLE
+}
+
+class Position {
+  var x: Int = 0
+  var y: Int = 0
+}
+
+class KeyPoint {
+  var bodyPart: BodyPart = BodyPart.NOSE
+  var position: Position = Position()
+  var score: Float = 0.0f
+}
+
+class Person {
+  var keyPoints = listOf<KeyPoint>()
+  var score: Float = 0.0f
+}
+
+enum class Device {
+  CPU,
+  NNAPI,
+  GPU
+}
+
+class Posenet(
+  val context: Context,
+  val filename: String = "posenet_model.tflite",
+  val device: Device = Device.GPU
+) : AutoCloseable {
+  var lastInferenceTimeNanos: Long = -1
+    private set
+
+  /** An Interpreter for the TFLite model.   */
+  private var interpreter: Interpreter? = null
+  private var gpuDelegate: GpuDelegate? = null
+  private val NUM_LITE_THREADS = 4
+
+  private fun getInterpreter(): Interpreter {
+    if (interpreter != null) {
+      return interpreter!!
+    }
+    val options = Interpreter.Options()
+    options.setNumThreads(NUM_LITE_THREADS)
+    when (device) {
+      Device.CPU -> { }
+      Device.GPU -> {
+        gpuDelegate = GpuDelegate()
+        options.addDelegate(gpuDelegate)
+      }
+      Device.NNAPI -> options.setUseNNAPI(true)
+    }
+    interpreter = Interpreter(loadModelFile(filename, context), options)
+    return interpreter!!
+  }
+
+  override fun close() {
+    interpreter?.close()
+    interpreter = null
+    gpuDelegate?.close()
+    gpuDelegate = null
+  }
+
+  /** Returns value within [0,1].   */
+  private fun sigmoid(x: Float): Float {
+    return (1.0f / (1.0f + exp(-x)))
+  }
+
+  /**
+   * Scale the image to a byteBuffer of [-1,1] values.
+   */
+  private fun initInputArray(bitmap: Bitmap): ByteBuffer {
+    val bytesPerChannel = 4
+    val inputChannels = 3
+    val batchSize = 1
+    val inputBuffer = ByteBuffer.allocateDirect(
+      batchSize * bytesPerChannel * bitmap.height * bitmap.width * inputChannels
+    )
+    inputBuffer.order(ByteOrder.nativeOrder())
+    inputBuffer.rewind()
+
+    val mean = 128.0f
+    val std = 128.0f
+    for (row in 0 until bitmap.height) {
+      for (col in 0 until bitmap.width) {
+        val pixelValue = bitmap.getPixel(col, row)
+        inputBuffer.putFloat(((pixelValue shr 16 and 0xFF) - mean) / std)
+        inputBuffer.putFloat(((pixelValue shr 8 and 0xFF) - mean) / std)
+        inputBuffer.putFloat(((pixelValue and 0xFF) - mean) / std)
+      }
+    }
+    return inputBuffer
+  }
+
+  /** Preload and memory map the model file, returning a MappedByteBuffer containing the model. */
+  private fun loadModelFile(path: String, context: Context): MappedByteBuffer {
+    val fileDescriptor = context.assets.openFd(path)
+    val inputStream = FileInputStream(fileDescriptor.fileDescriptor)
+    return inputStream.channel.map(
+      FileChannel.MapMode.READ_ONLY, fileDescriptor.startOffset, fileDescriptor.declaredLength
+    )
+  }
+
+  /**
+   * Initializes an outputMap of 1 * x * y * z FloatArrays for the model processing to populate.
+   */
+  private fun initOutputMap(interpreter: Interpreter): HashMap<Int, Any> {
+    val outputMap = HashMap<Int, Any>()
+
+    // 1 * 9 * 9 * 17 contains heatmaps
+    val heatmapsShape = interpreter.getOutputTensor(0).shape()
+    outputMap[0] = Array(heatmapsShape[0]) {
+      Array(heatmapsShape[1]) {
+        Array(heatmapsShape[2]) { FloatArray(heatmapsShape[3]) }
+      }
+    }
+
+    // 1 * 9 * 9 * 34 contains offsets
+    val offsetsShape = interpreter.getOutputTensor(1).shape()
+    outputMap[1] = Array(offsetsShape[0]) {
+      Array(offsetsShape[1]) { Array(offsetsShape[2]) { FloatArray(offsetsShape[3]) } }
+    }
+
+    // 1 * 9 * 9 * 32 contains forward displacements
+    val displacementsFwdShape = interpreter.getOutputTensor(2).shape()
+    outputMap[2] = Array(offsetsShape[0]) {
+      Array(displacementsFwdShape[1]) {
+        Array(displacementsFwdShape[2]) { FloatArray(displacementsFwdShape[3]) }
+      }
+    }
+
+    // 1 * 9 * 9 * 32 contains backward displacements
+    val displacementsBwdShape = interpreter.getOutputTensor(3).shape()
+    outputMap[3] = Array(displacementsBwdShape[0]) {
+      Array(displacementsBwdShape[1]) {
+        Array(displacementsBwdShape[2]) { FloatArray(displacementsBwdShape[3]) }
+      }
+    }
+
+    return outputMap
+  }
+
+  /**
+   * Estimates the pose for a single person.
+   * args:
+   *      bitmap: image bitmap of frame that should be processed
+   * returns:
+   *      person: a Person object containing data about keypoint locations and confidence scores
+   */
+  fun estimateSinglePose(bitmap: Bitmap): Person {
+    val estimationStartTimeNanos = SystemClock.elapsedRealtimeNanos()
+    val inputArray = arrayOf(initInputArray(bitmap))
+    Log.i(
+      "posenet",
+      String.format(
+        "Scaling to [-1,1] took %.2f ms",
+        1.0f * (SystemClock.elapsedRealtimeNanos() - estimationStartTimeNanos) / 1_000_000
+      )
+    )
+
+    val outputMap = initOutputMap(getInterpreter())
+
+    val inferenceStartTimeNanos = SystemClock.elapsedRealtimeNanos()
+    getInterpreter().runForMultipleInputsOutputs(inputArray, outputMap)
+    lastInferenceTimeNanos = SystemClock.elapsedRealtimeNanos() - inferenceStartTimeNanos
+    Log.i(
+      "posenet",
+      String.format("Interpreter took %.2f ms", 1.0f * lastInferenceTimeNanos / 1_000_000)
+    )
+
+    val heatmaps = outputMap[0] as Array<Array<Array<FloatArray>>>
+    val offsets = outputMap[1] as Array<Array<Array<FloatArray>>>
+
+    val height = heatmaps[0].size
+    val width = heatmaps[0][0].size
+    val numKeypoints = heatmaps[0][0][0].size
+
+    // Finds the (row, col) locations of where the keypoints are most likely to be.
+    val keypointPositions = Array(numKeypoints) { Pair(0, 0) }
+    for (keypoint in 0 until numKeypoints) {
+      var maxVal = heatmaps[0][0][0][keypoint]
+      var maxRow = 0
+      var maxCol = 0
+      for (row in 0 until height) {
+        for (col in 0 until width) {
+          if (heatmaps[0][row][col][keypoint] > maxVal) {
+            maxVal = heatmaps[0][row][col][keypoint]
+            maxRow = row
+            maxCol = col
+          }
+        }
+      }
+      keypointPositions[keypoint] = Pair(maxRow, maxCol)
+    }
+
+    // Calculating the x and y coordinates of the keypoints with offset adjustment.
+    val xCoords = IntArray(numKeypoints)
+    val yCoords = IntArray(numKeypoints)
+    val confidenceScores = FloatArray(numKeypoints)
+    keypointPositions.forEachIndexed { idx, position ->
+      val positionY = keypointPositions[idx].first
+      val positionX = keypointPositions[idx].second
+      yCoords[idx] = (
+        position.first / (height - 1).toFloat() * bitmap.height +
+          offsets[0][positionY][positionX][idx]
+        ).toInt()
+      xCoords[idx] = (
+        position.second / (width - 1).toFloat() * bitmap.width +
+          offsets[0][positionY]
+          [positionX][idx + numKeypoints]
+        ).toInt()
+      confidenceScores[idx] = sigmoid(heatmaps[0][positionY][positionX][idx])
+    }
+
+    val person = Person()
+    val keypointList = Array(numKeypoints) { KeyPoint() }
+    var totalScore = 0.0f
+    enumValues<BodyPart>().forEachIndexed { idx, it ->
+      keypointList[idx].bodyPart = it
+      keypointList[idx].position.x = xCoords[idx]
+      keypointList[idx].position.y = yCoords[idx]
+      keypointList[idx].score = confidenceScores[idx]
+      totalScore += confidenceScores[idx]
+    }
+
+    person.keyPoints = keypointList.toList()
+    person.score = totalScore / numKeypoints
+
+    return person
+  }
+}

 // Top-level build file where you can add configuration options common to all sub-projects/modules.
 // Top-level build file where you can add configuration options common to all sub-projects/modules.
 
 
 buildscript {
 buildscript {
+    ext.kotlin_version = '1.3.72'
     repositories {
     repositories {
         google()
         google()
         jcenter()
         jcenter()
@@ -8,7 +9,8 @@ buildscript {
     }
     }
     dependencies {
     dependencies {
         classpath 'com.android.tools.build:gradle:3.5.1'
         classpath 'com.android.tools.build:gradle:3.5.1'
-        
+        classpath "org.jetbrains.kotlin:kotlin-gradle-plugin:$kotlin_version"
+
         // NOTE: Do not place your application dependencies here; they belong
         // NOTE: Do not place your application dependencies here; they belong
         // in the individual module build.gradle files
         // in the individual module build.gradle files
     }
     }