Camerax ImageCapture 传递给 Chaquopy 太慢

如何解决Camerax ImageCapture 传递给 Chaquopy 太慢

我用 Chaquopy 制作了 Camerax 应用程序：

ImageCapture 用例捕获图像(jpg)
将其转换为位图
将位图转换为字符串
将字符串传递给 Python
Python OpenCV 获取图像分辨率并将其返回给 Android（如字符串）
在 Textview 上显示

应用程序正在运行，但问题是：

应用速度太慢：15-20 秒（字符串转换？）
它显示错误的分辨率（分辨率在 ImageCapture 配置中设置）

如何加速我的应用程序？
除了base64字符串之外，还有其他方法可以将图像传递给python吗？？

Android CameraAtivity 代码：

'''

public class CameraActivity extends AppCompatActivity {
    private PreviewView previewView;
    private ImageCapture imageCapture;
    private ListenableFuture<ProcessCameraProvider> cameraProviderFuture;
    private TextView textView;
    private Button button;



    @Override
    protected void onCreate(@Nullable Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.activity_camera);
        previewView = findViewById(R.id.previewView);
        cameraProviderFuture = ProcessCameraProvider.getInstance(this);
        textView = findViewById(R.id.length);
        button = findViewById(R.id.button);


        cameraProviderFuture.addListener(new Runnable() {
            @Override
            public void run() {
                try {
                    ProcessCameraProvider cameraProvider = cameraProviderFuture.get();
                    bindImageAnalysis(cameraProvider);
                } catch (ExecutionException | InterruptedException e) {
                    e.printStackTrace();
                }
            }
        },ContextCompat.getMainExecutor(this));
    }


    private void bindImageAnalysis(@NonNull ProcessCameraProvider cameraProvider) {

        Preview preview = new Preview.Builder().build();
        CameraSelector cameraSelector = new CameraSelector.Builder()
                .requireLensFacing(CameraSelector.LENS_FACING_BACK).build();
        preview.setSurfaceProvider(previewView.createSurfaceProvider());

        Executor cameraexecutor = ContextCompat.getMainExecutor(this);
        ImageCapture imageCapture = new ImageCapture.Builder().setTargetResolution(new Size(1200,1600)).build();
        button.setOnClickListener(new View.OnClickListener() {
            @Override
            public void onClick(View view) {
                imageCapture.takePicture(cameraexecutor,new ImageCapture.OnImageCapturedCallback() {
                    @Override
                    public void onCaptureSuccess(@NonNull ImageProxy image){
                        ByteBuffer byteBuffer = image.getPlanes()[0].getBuffer();

                        byte[] bytes = new byte[byteBuffer.capacity()];
                        byteBuffer.get(bytes);

                        Bitmap bitmap = BitmapFactory.decodeByteArray(bytes,bytes.length);
                        ByteArrayOutputStream baos = new ByteArrayOutputStream();
                        bitmap.compress(Bitmap.CompressFormat.PNG,100,baos);
                        byte[] imageBytes = baos.toByteArray();
                        String imgString = Base64.encodeToString(imageBytes,Base64.DEFAULT);


                        PyObject obj = pythonn(imgString);

                        textView.setText(obj.toString());

                    }

                    @Override
                    public void onError(@NonNull ImageCaptureException error) {
                        error.printStackTrace();
                    }
                });
            }

        });


        cameraProvider.bindToLifecycle((LifecycleOwner)this,cameraSelector,imageCapture,preview);
    }

    private PyObject pythonn(String imgString) {
        if(!Python.isStarted())
            Python.start(new AndroidPlatform(this ));
        Python py = Python.getInstance();

        final PyObject pyobj = py.getModule("shape");
        PyObject obj = pyobj.callAttr("main",imgString);
        return obj;
    }
}

'''

Python 代码；

import cv2
import numpy as np
import base64

def main(imgString):

    decoded_data = base64.b64decode(imgString)
    np_data = np.fromstring(decoded_data,np.uint8)
    img = cv2.imdecode(np_data,cv2.IMREAD_UNCHANGED)

    if img.shape[0] > img.shape[1]:
        img = cv2.transpose(img)
    
    return str(str(img.shape[0]) + "_"  + str(img.shape[1]))

所有代码都在 Github 上： https://github.com/kintipu/Camerax_ImageCapture_Chaquopy_OpenCV_ImageResolution/tree/master

2021 年 3 月 29 日更新。：我会尝试使用 bytearray，就像 mhsmith 建议的那样。与此同时，我尝试了另一件事：

捕获图片并保存为jpg

然后直接从python读取图片应用程序可以在模拟器上运行，但不能在真手机上运行安卓代码： '''

公共类 CameraActivity 扩展 AppCompatActivity { 私人预览视图预览视图；私有 ImageCapture imageCapture; 私人 ListenableFuture cameraProviderFuture; 私有文本视图文本视图；私人按钮按钮；私有上下文上下文；

  @Override
  protected void onCreate(@Nullable Bundle savedInstanceState) {
      super.onCreate(savedInstanceState);
      setContentView(R.layout.activity_camera);
      previewView = findViewById(R.id.previewView);
      cameraProviderFuture = ProcessCameraProvider.getInstance(this);
      textView = findViewById(R.id.length);
      button = findViewById(R.id.button);


      cameraProviderFuture.addListener(new Runnable() {
          @Override
          public void run() {
              try {
                  ProcessCameraProvider cameraProvider = cameraProviderFuture.get();
                  bindImageAnalysis(cameraProvider);
              } catch (ExecutionException | InterruptedException e) {
                  e.printStackTrace();
              }
          }
      },ContextCompat.getMainExecutor(this));
  }


  private void bindImageAnalysis(@NonNull ProcessCameraProvider cameraProvider) {

      Preview preview = new Preview.Builder().build();
      CameraSelector cameraSelector = new CameraSelector.Builder()
              .requireLensFacing(CameraSelector.LENS_FACING_BACK).build();
      preview.setSurfaceProvider(previewView.createSurfaceProvider());

      Executor cameraexecutor = ContextCompat.getMainExecutor(this);
      ImageCapture imageCapture = new ImageCapture.Builder().setTargetResolution(new Size(1200,1600)).build();


      button.setOnClickListener(new View.OnClickListener() {
          @Override
          public void onClick(View v) {


              File file = new File(getBatchDirectoryName(),"photo"+ ".jpg");

              ImageCapture.OutputFileOptions outputFileOptions = new ImageCapture.OutputFileOptions.Builder(file).build();
              imageCapture.takePicture(outputFileOptions,cameraexecutor,new ImageCapture.OnImageSavedCallback () {
                  @Override
                  public void onImageSaved(@NonNull ImageCapture.OutputFileResults outputFileResults) {
                      new Handler().post(new Runnable() {
                          @Override
                          public void run() {
                              Toast.makeText(CameraActivity.this,"Image Saved successfully" + file.getAbsolutePath(),Toast.LENGTH_LONG).show();

                              PyObject obj = pythonn();
                              textView.setText(obj.toString());
                          }


                      });

                  }
                  @Override
                  public void onError(@NonNull ImageCaptureException error) {
                      error.printStackTrace();
                  }
              });
          }
      });


      cameraProvider.bindToLifecycle((LifecycleOwner)this,preview);
  }




  public String getBatchDirectoryName() {

      String app_folder_path = "";
      app_folder_path = Environment.getExternalStorageDirectory().toString() + "/images";
      File dir = new File(app_folder_path);
      if (!dir.exists() && !dir.mkdirs()) {

      }

      return app_folder_path;
  }





  private PyObject pythonn() {
      if(!Python.isStarted())
          Python.start(new AndroidPlatform(this ));
      Python py = Python.getInstance();

      final PyObject pyobj = py.getModule("shape");
      PyObject obj = pyobj.callAttr("main");

      return obj;
  }

}

'''

Python 代码：

'''

import cv2
import numpy as np
from android.os import Environment


path = str(str(Environment.getExternalStorageDirectory()) + "/images" + "/photo.jpg")


def main():
    

    img = cv2.imread(path)
    
    return str(str(img.shape[0]) + "_"  + str(img.shape[1]))

'''

2021 年 4 月 4 日更新：

我通过一些修改使它更快：

将像字节数组这样的图像传递给 python（而不是字符串和 base64 转换） - 根据 Malcom Smith 的建议
位图压缩设置为 JPEG（而不是 PNG）
Python 从 Create 开始

安卓代码； '''

public class CameraActivity extends AppCompatActivity {
    private PreviewView previewView;
    private ImageCapture imageCapture;
    private ListenableFuture<ProcessCameraProvider> cameraProviderFuture;
    private TextView textView;
    private Button button;



    @Override
    protected void onCreate(@Nullable Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.activity_camera);
        previewView = findViewById(R.id.previewView);
        cameraProviderFuture = ProcessCameraProvider.getInstance(this);
        textView = findViewById(R.id.length);
        button = findViewById(R.id.button);
        
        if(!Python.isStarted())
              Python.start(new AndroidPlatform(this ));


        cameraProviderFuture.addListener(new Runnable() {
            @Override
            public void run() {
                try {
                    ProcessCameraProvider cameraProvider = cameraProviderFuture.get();
                    bindImageAnalysis(cameraProvider);
                } catch (ExecutionException | InterruptedException e) {
                    e.printStackTrace();
                }
            }
        },bytes.length);
                        ByteArrayOutputStream baos = new ByteArrayOutputStream();
                        bitmap.compress(Bitmap.CompressFormat.JPEG,baos);
                        byte[] imageBytes = baos.toByteArray();

//                        String length = String.valueOf((imgString.length()));
//                        textView.setText(length);

                        PyObject obj = pythonn(imageBytes);

                        textView.setText(obj.toString());

                    }

                    @Override
                    public void onError(@NonNull ImageCaptureException error) {
                        error.printStackTrace();
                    }
                });
            }

        });


        cameraProvider.bindToLifecycle((LifecycleOwner)this,preview);
    }

    private PyObject pythonn(byte[] imageBytes) {

        Python py = Python.getInstance();

        final PyObject pyobj = py.getModule("shape");
        PyObject obj = pyobj.callAttr("main",imageBytes);
        return obj;
    }
}

蟒蛇： '''

import cv2
import numpy as np



def main(imageBytes):
         np_data = np.asarray(imageBytes,np.uint8)
         img = cv2.imdecode(np_data,cv2.IMREAD_UNCHANGED)
         if img.shape[0] > img.shape[1]:
                img = cv2.transpose(img)

         img = cv2.resize(img,(1600,1200))
    
         return str(str(img.shape[0]) + "_"  + str(img.shape[1]))

更新的 github：https://github.com/kintipu/Camerax_ImageCapture_Chaquopy_OpenCV_ImageResolution/blob/master/README.md

解决方法

不需要使用 base64，您可以发送 PNG 编码的 byte[] 数组，它会在 Python 中作为字节对象接收。我不确定这个对象是否会被 cv2.imdecode 直接接受，但它肯定会被 np.array 或 np.frombuffer 接受。（不推荐将二进制数据传递给 np.fromstring，正如其 documentation page 解释的那样。）

如果您不确定是哪一行代码导致了延迟，您可以在各行之间添加 Log 调用（或 Python 中的 print 调用），然后检查 {{1}} 中的时间戳{3}}。

Camerax ImageCapture 传递给 Chaquopy 太慢

如何解决Camerax ImageCapture 传递给 Chaquopy 太慢

解决方法

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