gpt4 book ai didi

java - MLKit 对象检测未检测到对象

转载 作者:行者123 更新时间:2023-12-05 00:16:02 31 4
gpt4 key购买 nike

Google 的 MLKit(没有 Firebase)是新的,所以我遇到了麻烦。我在这里尝试遵循此示例:https://developers.google.com/ml-kit/vision/object-detection/custom-models/android

应用程序可以正常打开,并且相机可以正常工作(例如,我可以看到东西)。但是实际检测好像不行。

我是否遗漏了实际检测对象的部分代码?还是 CameraX 或 ImageInput 的实现有问题?

package com.example.mlkitobjecttest;

import androidx.annotation.NonNull;
import androidx.appcompat.app.AppCompatActivity;
import androidx.camera.core.Camera;
import androidx.camera.core.CameraSelector;
import androidx.camera.core.CameraX;
import androidx.camera.core.ImageAnalysis;
import androidx.camera.core.ImageProxy;
import androidx.camera.core.Preview;
import androidx.camera.core.impl.PreviewConfig;
import androidx.camera.lifecycle.ProcessCameraProvider;
import androidx.camera.view.PreviewView;
import androidx.core.app.ActivityCompat;
import androidx.core.content.ContextCompat;
import androidx.lifecycle.LifecycleOwner;

import android.content.pm.PackageManager;
import android.graphics.Rect;
import android.media.Image;
import android.os.Bundle;
import android.text.Layout;
import android.util.Rational;
import android.util.Size;
import android.view.View;
import android.widget.TextView;
import android.widget.Toast;

import com.google.android.gms.tasks.OnFailureListener;
import com.google.android.gms.tasks.OnSuccessListener;
import com.google.common.util.concurrent.ListenableFuture;
import com.google.mlkit.common.model.LocalModel;
import com.google.mlkit.vision.common.InputImage;
import com.google.mlkit.vision.objects.DetectedObject;
import com.google.mlkit.vision.objects.ObjectDetection;
import com.google.mlkit.vision.objects.ObjectDetector;
import com.google.mlkit.vision.objects.custom.CustomObjectDetectorOptions;

import org.w3c.dom.Text;

import java.util.List;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

public class MainActivity extends AppCompatActivity {

private class YourAnalyzer implements ImageAnalysis.Analyzer {

@Override
@androidx.camera.core.ExperimentalGetImage
public void analyze(ImageProxy imageProxy) {

Image mediaImage = imageProxy.getImage();
if (mediaImage != null) {
InputImage image =
InputImage.fromMediaImage(mediaImage, imageProxy.getImageInfo().getRotationDegrees());
// Pass image to an ML Kit Vision API
// ...
LocalModel localModel =
new LocalModel.Builder()
.setAssetFilePath("mobilenet_v1_1.0_128_quantized_1_default_1.tflite")
// or .setAbsoluteFilePath(absolute file path to tflite model)
.build();

CustomObjectDetectorOptions customObjectDetectorOptions =
new CustomObjectDetectorOptions.Builder(localModel)
.setDetectorMode(CustomObjectDetectorOptions.SINGLE_IMAGE_MODE)
.enableMultipleObjects()
.enableClassification()
.setClassificationConfidenceThreshold(0.5f)
.setMaxPerObjectLabelCount(3)
.build();

ObjectDetector objectDetector =
ObjectDetection.getClient(customObjectDetectorOptions);

objectDetector
.process(image)
.addOnFailureListener(new OnFailureListener() {
@Override
public void onFailure(@NonNull Exception e) {
//Toast.makeText(getApplicationContext(), "Fail. Sad!", Toast.LENGTH_SHORT).show();
//textView.setText("Fail. Sad!");
imageProxy.close();
}
})
.addOnSuccessListener(new OnSuccessListener<List<DetectedObject>>() {
@Override
public void onSuccess(List<DetectedObject> results) {

for (DetectedObject detectedObject : results) {
Rect box = detectedObject.getBoundingBox();


for (DetectedObject.Label label : detectedObject.getLabels()) {
String text = label.getText();
int index = label.getIndex();
float confidence = label.getConfidence();
textView.setText(text);



}}
imageProxy.close();
}
});

}
//ImageAnalysis.Builder.fromConfig(new ImageAnalysisConfig).setBackpressureStrategy(ImageAnalysis.STRATEGY_KEEP_ONLY_LATEST);

}

}


PreviewView prevView;
private ListenableFuture<ProcessCameraProvider> cameraProviderFuture;
private ExecutorService executor = Executors.newSingleThreadExecutor();
TextView textView;

private int REQUEST_CODE_PERMISSIONS = 101;
private String[] REQUIRED_PERMISSIONS = new String[]{"android.permission.CAMERA"};
/* @NonNull
@Override
public CameraXConfig getCameraXConfig() {
return CameraXConfig.Builder.fromConfig(Camera2Config.defaultConfig())
.setCameraExecutor(ContextCompat.getMainExecutor(this))
.build();
}
*/
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);

prevView = findViewById(R.id.viewFinder);
textView = findViewById(R.id.scan_button);

if(allPermissionsGranted()){
startCamera();
}else{
ActivityCompat.requestPermissions(this, REQUIRED_PERMISSIONS, REQUEST_CODE_PERMISSIONS);
}

}

private void startCamera() {
cameraProviderFuture = ProcessCameraProvider.getInstance(this);
cameraProviderFuture.addListener(new Runnable() {
@Override
public void run() {
try {
ProcessCameraProvider cameraProvider = cameraProviderFuture.get();
bindPreview(cameraProvider);
} catch (ExecutionException | InterruptedException e) {
// No errors need to be handled for this Future.
// This should never be reached.
}
}
}, ContextCompat.getMainExecutor(this));


}

void bindPreview(@NonNull ProcessCameraProvider cameraProvider) {

Preview preview = new Preview.Builder()
.build();

CameraSelector cameraSelector = new CameraSelector.Builder()
.requireLensFacing(CameraSelector.LENS_FACING_BACK)
.build();

preview.setSurfaceProvider(prevView.createSurfaceProvider());

ImageAnalysis imageAnalysis =
new ImageAnalysis.Builder()
.setTargetResolution(new Size(1280, 720))
.setBackpressureStrategy(ImageAnalysis.STRATEGY_KEEP_ONLY_LATEST)
.build();
imageAnalysis.setAnalyzer(ContextCompat.getMainExecutor(this), new YourAnalyzer());

Camera camera = cameraProvider.bindToLifecycle((LifecycleOwner)this, cameraSelector, preview, imageAnalysis);


}



private boolean allPermissionsGranted() {
for(String permission: REQUIRED_PERMISSIONS){
if(ContextCompat.checkSelfPermission(this, permission) != PackageManager.PERMISSION_GRANTED){
return false;
}
}
return true;
}

@Override
public void onRequestPermissionsResult(int requestCode, @NonNull String[] permissions, @NonNull int[] grantResults) {

if(requestCode == REQUEST_CODE_PERMISSIONS){
if(allPermissionsGranted()){
startCamera();
} else{
Toast.makeText(this, "Permissions not granted by the user.", Toast.LENGTH_SHORT).show();
this.finish();
}
}
}

}

最佳答案

未检测到任何内容,因为您定义了错误的 tflite 模型文件路径。您的模拟器或物理设备无法解析给定路径,因为它在移动设备上不存在:C:\\Users\\dude\\Documents\\mlkitobjecttest\\app\\src\\main\\assets\\mobilenet_v1_1.0_128_quantized_1_default_1.tflite

将模型 mobilenet_v1_1.0_128_quantized_1_default_1.tflite 复制到应用程序项目 src/main 目录下的 assets 目录中。

如果您没有该目录,只需创建一个名为 assets 的新目录即可。

最后应该是这样的:

project's src directory strucutre

之后修复LocalModel初始化代码:

LocalModel localModel =
new LocalModel.Builder()
.setAssetFilePath("mobilenet_v1_1.0_128_quantized_1_default_1.tflite")
// or .setAbsoluteFilePath(absolute file path to tflite model)
.build();

更新:又发现一个问题

ImageAnalysis 实例未绑定(bind)到 CameraProvider:

...
ImageAnalysis imageAnalysis = ...

Camera camera = cameraProvider.bindToLifecycle((LifecycleOwner)this, cameraSelector, preview); // imageAnalysis is not used

要修复它,只需将 imageAnalysis 变量作为最后一个参数传递给 bindToLifecycle 方法:

Camera camera = cameraProvider.bindToLifecycle((LifecycleOwner)this, cameraSelector, preview, imageAnalysis);

第二次更新:发现另一个问题

MLKit 无法处理图像,因为它在处理时或处理开始前关闭。我说的是 imageProxy.close()public void analyze(ImageProxy imageProxy) 中声明的代码行。

close() 方法的 Java 文档:

/**
* Free up this frame for reuse.
* <p>
* After calling this method, calling any methods on this {@code Image} will
* result in an {@link IllegalStateException}, and attempting to read from
* or write to {@link ByteBuffer ByteBuffers} returned by an earlier
* {@link Plane#getBuffer} call will have undefined behavior. If the image
* was obtained from {@link ImageWriter} via
* {@link ImageWriter#dequeueInputImage()}, after calling this method, any
* image data filled by the application will be lost and the image will be
* returned to {@link ImageWriter} for reuse. Images given to
* {@link ImageWriter#queueInputImage queueInputImage()} are automatically
* closed.
* </p>
*/

要解决此问题,请将 imageProxy.close() 移至失败和成功监听器中:

objectDetector
.process(image)
.addOnFailureListener(new OnFailureListener() {
@Override
public void onFailure(@NonNull Exception e) {
Toast.makeText(getApplicationContext(), "Fail. Sad!", Toast.LENGTH_LONG).show();
...
imageProxy.close();
}
})
.addOnSuccessListener(new OnSuccessListener<List<DetectedObject>>() {
@Override
public void onSuccess(List<DetectedObject> results) {
Toast.makeText(getBaseContext(), "Success...", Toast.LENGTH_LONG).show();
...
imageProxy.close();
}
});

已使用 image classification model 测试固定解决方案来自 Tensorflow,测试成功。

关于java - MLKit 对象检测未检测到对象,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/62606320/

31 4 0
Copyright 2021 - 2024 cfsdn All Rights Reserved 蜀ICP备2022000587号
广告合作:1813099741@qq.com 6ren.com