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。