android mediapipe如何实现手势识别

要实现手势识别，可以使用MediaPipe库中的Hand Tracking和Hand Landmark模块。以下是一个简单的示例代码，演示如何使用MediaPipe实现手势识别：

import android.os.Bundle;
import androidx.annotation.NonNull;
import androidx.appcompat.app.AppCompatActivity;
import com.google.mediapipe.components.CameraHelper;
import com.google.mediapipe.components.PermissionHelper;
import com.google.mediapipe.formats.proto.LandmarkProto.NormalizedLandmarkList;
import com.google.mediapipe.formats.proto.LandmarkProto.NormalizedLandmark;
import com.google.mediapipe.solutions.hands.HandLandmark;
import com.google.mediapipe.solutions.hands.Hands;
import com.google.mediapipe.solutions.hands.HandsResult;
import com.google.mediapipe.solutions.hands.HandsOptions;
import com.google.mediapipe.framework.AndroidAssetUtil;
import com.google.mediapipe.framework.Packet;
import com.google.mediapipe.framework.PacketGetter;
import com.google.mediapipe.framework.TextureFrame;
import com.google.mediapipe.glutil.EglManager;
import com.google.mediapipe.glutil.GlTextureFrame;
import com.google.mediapipe.components.TextureFrameConsumer;

public class MainActivity extends AppCompatActivity {
    private static final String TAG = "MainActivity";
    private static final String BINARY_GRAPH_NAME = "hand_tracking_mobile.pb";
    private static final String INPUT_VIDEO_STREAM_NAME = "input_video";
    private static final String OUTPUT_VIDEO_STREAM_NAME = "output_video";
    private static final String LANDMARKS_STREAM_NAME = "hand_landmarks";
    private static final CameraHelper.CameraFacing CAMERA_FACING = CameraHelper.CameraFacing.FRONT;
    private Hands hands;
    private CameraHelper cameraHelper;
    private TextureFrameConsumer videoConsumer;

    @Override
    protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.activity_main);

        EglManager eglManager = new EglManager(null);
        hands = new Hands(this, HandsOptions.builder().build());
        hands.setInputSidePackets(new Packet[] {});

        cameraHelper = new CameraHelper(this, CAMERA_FACING,  /*surfaceTexture=*/ null,  /*previewDisplayView=*/ null);
        cameraHelper.setOnCameraStartedListener(surfaceTexture -> {
            videoConsumer = new TextureFrameConsumer() {
                @Override
                public void onNewFrame(TextureFrame textureFrame) {
                    processFrame(textureFrame);
                }
            };
            cameraHelper.setFrameProcessor(videoConsumer, eglManager);
        });

        cameraHelper.startCamera();
    }

    private void processFrame(TextureFrame textureFrame) {
        HandsResult handsResult = hands.process(textureFrame);
        if (handsResult.hasHandLandmarks()) {
            NormalizedLandmarkList landmarks = handsResult.getHandLandmarks();
            processHandLandmarks(landmarks);
        }
    }

    private void processHandLandmarks(NormalizedLandmarkList landmarks) {
        for (NormalizedLandmark landmark : landmarks.getLandmarkList()) {
            float x = landmark.getX();
            float y = landmark.getY();
            float z = landmark.getZ();
            // Do something with the landmark coordinates
        }
    }

    @Override
    protected void onResume() {
        super.onResume();
        cameraHelper.startCamera();
    }

    @Override
    protected void onPause() {
        super.onPause();
        cameraHelper.stopCamera();
    }

    @Override
    protected void onDestroy() {
        super.onDestroy();
        hands.close();
    }
}

在这个示例代码中，我们首先创建了一个Hands实例，并设置了HandTracking的参数。然后通过CameraHelper来获取摄像头的帧，将每一帧传递给Hands实例的process方法进行手势识别。最后，我们可以从HandsResult中获取手部的关键点坐标，并进行进一步的处理。

请注意，此示例只是一个简单的演示，实际项目中可能需要根据具体的需求进行调整和优化。您可以查阅MediaPipe的官方文档以获取更多详细信息和示例代码。