更新opencv到4.8.0，增加onnxruntime用于推理onnx模型

apkbuilder/src/main/java/com/stardust/autojs/apkbuilder/ApkUnpackUtil.java

@@ -35,10 +35,19 @@ public class ApkUnpackUtil {
                 if (!e.isDirectory() && !TextUtils.isEmpty(name)) {
                     File file = new File(mWorkspacePath, name);
                     System.out.println(file);
-                    if (file.getParentFile() != null && file.getParentFile().mkdirs()) {
+                    File parentFile = file.getParentFile();
+                    if (parentFile != null && (parentFile.exists() || parentFile.mkdirs())) {
                         try (FileOutputStream fos = new FileOutputStream(file)) {
+                            System.out.println(file.getName() + " has been written");
                             StreamUtils.write(zis, fos);
                         }
+                    } else {
+                        System.out.println(file.getName() + " can not write");
+                        System.out.println("is parent null? " + (parentFile != null));
+                        if (file.getParentFile() != null) {
+                            System.out.println("is parent exists? " + parentFile.exists());
+                            System.out.println("can parent mkdirs? " + parentFile.mkdirs());
+                        }
                     }
                 } else {
                     System.out.println("file or empty：" + name);

app/src/main/java/org/autojs/autojs/build/ApkBuilder.java

@@ -76,6 +76,7 @@ public class ApkBuilder {
         Boolean usePaddleOcr = false;
         Boolean useMlKitOcr = false;
         Boolean useTessTwo = false;
+        Boolean useOnnx = false;
         Set<String> enabledPermission = new HashSet<>();
 
         public static AppConfig fromProjectConfig(String projectDir, ProjectConfig projectConfig) {
@@ -187,6 +188,14 @@ public class ApkBuilder {
             this.useTessTwo = useTessTwo;
         }
 
+        public Boolean getUseOnnx() {
+            return useOnnx;
+        }
+
+        public void setUseOnnx(Boolean useOnnx) {
+            this.useOnnx = useOnnx;
+        }
+
         public Set<String> getEnabledPermission() {
             return enabledPermission;
         }
@@ -237,6 +246,9 @@ public class ApkBuilder {
         if (!mAppConfig.useTessTwo) {
             removeSoList.addAll(Arrays.asList("libtess.so", "liblept.so", "libjpgt.so", "libpngt.so"));
         }
+        if (!mAppConfig.useOnnx) {
+            removeSoList.addAll(Arrays.asList("libonnxruntime.so", "libonnxruntime4j_jni.so"));
+        }
         if (!mAppConfig.useOpenCv) {
             removeSoList.add("libopencv_java4.so");
         }

app/src/main/java/org/autojs/autojs/ui/project/BuildActivity.java

@@ -108,6 +108,9 @@ public class BuildActivity extends BaseActivity implements ApkBuilder.ProgressCa
     @ViewById(R.id.use_tess_two)
     CheckBox mUseTessTwo;
 
+    @ViewById(R.id.use_onnx_runtime)
+    CheckBox mUseOnnx;
+
     @ViewById(R.id.recycler_view)
     RecyclerView recyclerView;
 
@@ -202,6 +205,7 @@ public class BuildActivity extends BaseActivity implements ApkBuilder.ProgressCa
                 "https://i.autojs.org/autojs/plugin/%d.apk", ApkBuilderPluginHelper.getSuitablePluginVersion()));
     }
 
+    @SuppressLint("StringFormatInvalid")
     private void setupWithSourceFile(ScriptFile file) {
         String dir = file.getParent();
         if (dir.startsWith(getFilesDir().getPath())) {
@@ -349,6 +353,7 @@ public class BuildActivity extends BaseActivity implements ApkBuilder.ProgressCa
         appConfig.setUsePaddleOcr(mUsePaddleOcr.isChecked());
         appConfig.setUseMlKitOcr(mUseMlKitOcr.isChecked());
         appConfig.setUseTessTwo(mUseTessTwo.isChecked());
+        appConfig.setUseOnnx(mUseOnnx.isChecked());
         Set<String> enabledPermission = new HashSet<>();
         for (Option option : options) {
             if (option.isSelected()) {
@@ -387,6 +392,7 @@ public class BuildActivity extends BaseActivity implements ApkBuilder.ProgressCa
         Log.e(LOG_TAG, "Build failed", error);
     }
 
+    @SuppressLint("StringFormatInvalid")
     private void onBuildSuccessful(File outApk) {
         mProgressDialog.dismiss();
         mProgressDialog = null;

app/src/main/java/org/autojs/autojs/ui/project/ProjectConfigActivity.java

@@ -195,7 +195,7 @@ public class ProjectConfigActivity extends BaseActivity {
     @Click(R.id.icon)
     void selectIcon() {
         ShortcutIconSelectActivity_.intent(this)
-                .flags(Intent.FLAG_ACTIVITY_NEW_TASK)
+                .flags(Intent.FLAG_ACTIVITY_MULTIPLE_TASK)
                 .startForResult(REQUEST_CODE);
     }
 
@@ -249,6 +249,7 @@ public class ProjectConfigActivity extends BaseActivity {
     @SuppressLint("CheckResult")
     @Override
     protected void onActivityResult(int requestCode, int resultCode, Intent data) {
+        super.onActivityResult(requestCode, resultCode, data);
         if (resultCode != RESULT_OK) {
             return;
         }

app/src/main/res/layout/activity_build.xml

@@ -280,6 +280,13 @@
                             android:checked="true"
                             android:text="@string/text_use_ml_kit_ocr" />
 
+                        <CheckBox
+                            android:id="@+id/use_onnx_runtime"
+                            android:layout_width="wrap_content"
+                            android:layout_height="wrap_content"
+                            android:checked="false"
+                            android:text="@string/text_use_onnx_runtime" />
+
                         <CheckBox
                             android:id="@+id/use_tess_two"
                             android:layout_width="wrap_content"

app/src/main/res/values/strings.xml

@@ -423,6 +423,7 @@
     <string name="text_use_opencv">使用OpenCV</string>
     <string name="text_use_paddle_ocr">使用PaddleOCR</string>
     <string name="text_use_ml_kit_ocr">使用ML-KitOCR</string>
+    <string name="text_use_onnx_runtime">使用OnnxRuntime</string>
     <string name="text_use_tess_two">使用TessTwoOCR</string>
     <plurals name="air_error_short_description" key="air_error_short_description">
         <item quantity="one">描述至少要 %d 个字.</item>

autojs-aar/opencv/build.gradle

@@ -1,2 +1,2 @@
 configurations.maybeCreate("default")
-artifacts.add("default", file('opencv-4.5.5.aar'))
+artifacts.add("default", file('opencv-4.8.0.aar'))

autojs-aar/paddleocr/build.gradle

@@ -50,11 +50,11 @@ def archives = [
 //    ],
 ]
 /**
- * 下载opencv4.5.5源码包 默认为4.2.0 和 AutoJS中的版本不匹配会产生冲突 这里进行修改
+ * 下载opencv4.8.0源码包 默认为4.2.0 和 AutoJS中的版本不匹配会产生冲突 这里进行修改
  */
 def zipArchives = [
     [
-        'src' : 'https://github.com/opencv/opencv/releases/download/4.5.5/opencv-4.5.5-android-sdk.zip',
+        'src' : 'https://github.com/opencv/opencv/releases/download/4.8.0/opencv-4.8.0-android-sdk.zip',
         'dest': 'OpenCV'
     ]
 ]

autojs/build.gradle

@@ -76,6 +76,7 @@ dependencies {
     api project(path: ':common')
     api project(path: ':automator')
     implementation 'com.rmtheis:tess-two:9.1.0'
-    implementation 'com.google.mlkit:text-recognition-chinese:16.0.0-beta6'
+    implementation 'com.google.mlkit:text-recognition-chinese:16.0.0'
+    implementation 'com.microsoft.onnxruntime:onnxruntime-android:1.15.1'
 }
 

autojs/src/main/java/com/stardust/autojs/onnx/YoloV8Predictor.java

@@ -0,0 +1,306 @@
+package com.stardust.autojs.onnx;
+
+import android.os.Build;
+import android.util.Log;
+
+import com.google.gson.Gson;
+import com.stardust.autojs.onnx.domain.DetectResult;
+import com.stardust.autojs.onnx.domain.Detection;
+import com.stardust.autojs.onnx.util.Letterbox;
+
+import org.opencv.android.OpenCVLoader;
+import org.opencv.core.Mat;
+import org.opencv.core.Size;
+import org.opencv.imgcodecs.Imgcodecs;
+import org.opencv.imgproc.Imgproc;
+
+import java.nio.FloatBuffer;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Comparator;
+import java.util.EnumSet;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+
+import ai.onnxruntime.OnnxTensor;
+import ai.onnxruntime.OrtEnvironment;
+import ai.onnxruntime.OrtException;
+import ai.onnxruntime.OrtSession;
+import ai.onnxruntime.providers.NNAPIFlags;
+import androidx.annotation.RequiresApi;
+
+/**
+ * @author TonyJiangWJ
+ * @since 2023/8/20
+ */
+@RequiresApi(api = Build.VERSION_CODES.N)
+public class YoloV8Predictor {
+    private static final String TAG = "YoloV8Predictor";
+
+    static {
+        OpenCVLoader.initDebug();
+    }
+
+    private final String modelPath;
+
+    private float confThreshold = 0.35F;
+    private float nmsThreshold = 0.55F;
+    private boolean tryNpu;
+    private Size shapeSize = new Size(640, 640);
+    private Letterbox letterbox;
+
+    private List<String> labels = new ArrayList<>();
+    private List<String> apiFlags = Arrays.asList("CPU_DISABLED");
+
+    public YoloV8Predictor(String modelPath) {
+        this.modelPath = modelPath;
+    }
+
+    public YoloV8Predictor(String modelPath, float confThreshold, float nmsThreshold) {
+        this.modelPath = modelPath;
+        this.confThreshold = confThreshold;
+        this.nmsThreshold = nmsThreshold;
+    }
+
+    public void setConfThreshold(float confThreshold) {
+        this.confThreshold = confThreshold;
+    }
+
+    public void setNmsThreshold(float nmsThreshold) {
+        this.nmsThreshold = nmsThreshold;
+    }
+
+    public void setLabels(List<String> labels) {
+        this.labels = labels;
+    }
+
+    public void setShapeSize(double width, double height) {
+        this.shapeSize = new Size(width, height);
+    }
+
+    public void setTryNpu(boolean tryNpu) {
+        this.tryNpu = tryNpu;
+    }
+
+    public void setApiFlags(List<String> apiFlags) {
+        this.apiFlags = apiFlags;
+    }
+
+    private OrtSession session;
+    private OrtEnvironment environment;
+
+    private void prepareSession() throws OrtException {
+        if (environment != null) {
+            return;
+        }
+        // 加载ONNX模型
+        environment = OrtEnvironment.getEnvironment();
+        OrtSession.SessionOptions sessionOptions = new OrtSession.SessionOptions();
+        addNNApiProvider(sessionOptions);
+
+        session = environment.createSession(modelPath, sessionOptions);
+        // 输出基本信息
+        session.getInputInfo().keySet().forEach(x -> {
+            try {
+                System.out.println("input name = " + x);
+                System.out.println(session.getInputInfo().get(x).getInfo().toString());
+            } catch (OrtException e) {
+                throw new RuntimeException(e);
+            }
+        });
+    }
+
+    private void addNNApiProvider(OrtSession.SessionOptions sessionOptions) {
+        if (!tryNpu) {
+            return;
+        }
+        try {
+            List<NNAPIFlags> flags = new ArrayList<>();
+            if (apiFlags.contains("USE_FP16")) {
+                flags.add(NNAPIFlags.USE_FP16);
+            }
+            if (apiFlags.contains("USE_NCHW")) {
+                flags.add(NNAPIFlags.USE_NCHW);
+            }
+            if (apiFlags.contains("CPU_ONLY")) {
+                flags.add(NNAPIFlags.CPU_ONLY);
+            }
+            if (apiFlags.contains("CPU_DISABLED")) {
+                flags.add(NNAPIFlags.CPU_DISABLED);
+            }
+            Log.d(TAG, "addNNApiProvider: 当前启用nnapiFlags:" + new Gson().toJson(apiFlags));
+            sessionOptions.addNnapi(EnumSet.copyOf(flags));
+            Log.d(TAG, "prepareSession: 启用nnapi成功");
+        } catch (Exception e) {
+            Log.e(TAG, "prepareSession: 无法启用nnapi");
+        }
+    }
+
+    private HashMap<String, OnnxTensor> preprocessImage(Mat img) throws OrtException {
+
+        // 读取 image
+        Mat image = img.clone();
+        // 将四通道转换为三通道
+        if (image.channels() == 4) {
+            Imgproc.cvtColor(image, image, Imgproc.COLOR_RGBA2BGR);
+        }
+        Log.d(TAG, "preprocessImage: image's channels: " + image.channels());
+        Imgproc.cvtColor(image, image, Imgproc.COLOR_BGR2RGB);
+        // 更改 image 尺寸
+        letterbox = new Letterbox();
+        letterbox.setNewShape(this.shapeSize);
+        image = letterbox.letterbox(image);
+
+        int rows = letterbox.getHeight();
+        int cols = letterbox.getWidth();
+        int channels = image.channels();
+
+        // 将Mat对象的像素值赋值给Float[]对象
+        float[] pixels = new float[channels * rows * cols];
+        for (int i = 0; i < rows; i++) {
+            for (int j = 0; j < cols; j++) {
+                double[] pixel = image.get(j, i);
+                for (int k = 0; k < channels; k++) {
+                    // 这样设置相当于同时做了image.transpose((2, 0, 1))操作
+                    pixels[rows * cols * k + j * cols + i] = (float) pixel[k] / 255.0f;
+                }
+            }
+        }
+        image.release();
+        // 创建OnnxTensor对象
+        long[] shape = {1L, (long) channels, (long) rows, (long) cols};
+        OnnxTensor tensor = OnnxTensor.createTensor(environment, FloatBuffer.wrap(pixels), shape);
+        HashMap<String, OnnxTensor> stringOnnxTensorHashMap = new HashMap<>();
+        stringOnnxTensorHashMap.put(session.getInputInfo().keySet().iterator().next(), tensor);
+        return stringOnnxTensorHashMap;
+    }
+
+    private List<Detection> postProcessOutput(OrtSession.Result output) throws OrtException {
+        float[][] outputData = ((float[][][]) output.get(0).getValue())[0];
+
+        outputData = transposeMatrix(outputData);
+        Map<Integer, List<float[]>> class2Bbox = new HashMap<>();
+
+        for (float[] bbox : outputData) {
+            float[] conditionalProbabilities = Arrays.copyOfRange(bbox, 4, outputData.length);
+            int label = argmax(conditionalProbabilities);
+            float conf = conditionalProbabilities[label];
+            if (conf < confThreshold) {
+                continue;
+            }
+
+            bbox[4] = conf;
+
+            // xywh to (x1, y1, x2, y2)
+            xywh2xyxy(bbox);
+
+            // skip invalid predictions
+            if (bbox[0] >= bbox[2] || bbox[1] >= bbox[3]) {
+                continue;
+            }
+
+            class2Bbox.putIfAbsent(label, new ArrayList<>());
+            class2Bbox.get(label).add(bbox);
+        }
+
+        List<Detection> detections = new ArrayList<>();
+        for (Map.Entry<Integer, List<float[]>> entry : class2Bbox.entrySet()) {
+            int label = entry.getKey();
+            List<float[]> bboxes = entry.getValue();
+            bboxes = nonMaxSuppression(bboxes, nmsThreshold);
+            for (float[] bbox : bboxes) {
+                String labelString = "";
+                if (labels.size() - 1 < label) {
+                    labelString = String.valueOf(label);
+                } else {
+                    labelString = labels.get(label);
+                }
+                detections.add(new Detection(labelString, entry.getKey(), Arrays.copyOfRange(bbox, 0, 4), bbox[4]));
+            }
+        }
+        return detections;
+    }
+
+    public List<DetectResult> predictYolo(String imagePath) throws OrtException {
+        return predictYolo(Imgcodecs.imread(imagePath));
+    }
+
+    public List<DetectResult> predictYolo(Mat image) throws OrtException {
+        prepareSession();
+        long start_time = System.currentTimeMillis();
+        // 运行推理
+        OrtSession.Result output = session.run(preprocessImage(image));
+        List<Detection> detections = postProcessOutput(output);
+        System.out.printf("time：%d ms.\n", (System.currentTimeMillis() - start_time));
+        return detections.stream().map(detection -> new DetectResult(detection, letterbox))
+                .collect(Collectors.toList());
+    }
+
+    public static void xywh2xyxy(float[] bbox) {
+        float x = bbox[0];
+        float y = bbox[1];
+        float w = bbox[2];
+        float h = bbox[3];
+
+        bbox[0] = x - w * 0.5f;
+        bbox[1] = y - h * 0.5f;
+        bbox[2] = x + w * 0.5f;
+        bbox[3] = y + h * 0.5f;
+    }
+
+    public static float[][] transposeMatrix(float[][] m) {
+        float[][] temp = new float[m[0].length][m.length];
+        for (int i = 0; i < m.length; i++) {
+            for (int j = 0; j < m[0].length; j++) {
+                temp[j][i] = m[i][j];
+            }
+        }
+        return temp;
+    }
+
+    public static List<float[]> nonMaxSuppression(List<float[]> bboxes, float iouThreshold) {
+
+        List<float[]> bestBboxes = new ArrayList<>();
+
+        bboxes.sort(Comparator.comparing(a -> a[4]));
+
+        while (!bboxes.isEmpty()) {
+            float[] bestBbox = bboxes.remove(bboxes.size() - 1);
+            bestBboxes.add(bestBbox);
+            bboxes = bboxes.stream().filter(a -> computeIOU(a, bestBbox) < iouThreshold).collect(Collectors.toList());
+        }
+
+        return bestBboxes;
+    }
+
+    public static float computeIOU(float[] box1, float[] box2) {
+
+        float area1 = (box1[2] - box1[0]) * (box1[3] - box1[1]);
+        float area2 = (box2[2] - box2[0]) * (box2[3] - box2[1]);
+
+        float left = Math.max(box1[0], box2[0]);
+        float top = Math.max(box1[1], box2[1]);
+        float right = Math.min(box1[2], box2[2]);
+        float bottom = Math.min(box1[3], box2[3]);
+
+        float interArea = Math.max(right - left, 0) * Math.max(bottom - top, 0);
+        float unionArea = area1 + area2 - interArea;
+        return Math.max(interArea / unionArea, 1e-8f);
+
+    }
+
+    //返回最大值的索引
+    public static int argmax(float[] a) {
+        float re = -Float.MAX_VALUE;
+        int arg = -1;
+        for (int i = 0; i < a.length; i++) {
+            if (a[i] >= re) {
+                re = a[i];
+                arg = i;
+            }
+        }
+        return arg;
+    }
+}

autojs/src/main/java/com/stardust/autojs/onnx/domain/DetectResult.java

@@ -0,0 +1,89 @@
+package com.stardust.autojs.onnx.domain;
+
+import com.stardust.autojs.onnx.util.Letterbox;
+
+/**
+ * @author TonyJiangWJ
+ * @since 2023/8/20
+ */
+public class DetectResult {
+
+    private String label;
+    private Integer clsId;
+    private double left;
+    private double top;
+    private double right;
+    private double bottom;
+    private float confidence;
+
+    public DetectResult() {
+    }
+
+    public DetectResult(Detection detection, Letterbox letterbox) {
+        this.label = detection.label;
+        this.confidence = detection.confidence;
+        double dw = letterbox.getDw();
+        double dh = letterbox.getDh();
+        double ratio = letterbox.getRatio();
+        left = (detection.getBbox()[0] - dw) / ratio;
+        right = (detection.getBbox()[2] - dw) / ratio;
+        top = (detection.getBbox()[1] - dh) / ratio;
+        bottom = (detection.getBbox()[3] - dh) / ratio;
+    }
+
+    public String getLabel() {
+        return label;
+    }
+
+    public void setLabel(String label) {
+        this.label = label;
+    }
+
+    public Integer getClsId() {
+        return clsId;
+    }
+
+    public void setClsId(Integer clsId) {
+        this.clsId = clsId;
+    }
+
+    public double getLeft() {
+        return left;
+    }
+
+    public void setLeft(double left) {
+        this.left = left;
+    }
+
+    public double getTop() {
+        return top;
+    }
+
+    public void setTop(double top) {
+        this.top = top;
+    }
+
+    public double getRight() {
+        return right;
+    }
+
+    public void setRight(double right) {
+        this.right = right;
+    }
+
+    public double getBottom() {
+        return bottom;
+    }
+
+    public void setBottom(double bottom) {
+        this.bottom = bottom;
+    }
+
+    public float getConfidence() {
+        return confidence;
+    }
+
+    public void setConfidence(float confidence) {
+        this.confidence = confidence;
+    }
+}

autojs/src/main/java/com/stardust/autojs/onnx/domain/Detection.java

@@ -0,0 +1,62 @@
+package com.stardust.autojs.onnx.domain;
+
+/**
+ * @author TonyJiangWJ
+ * @since 2023/8/20
+ */
+public class Detection {
+    public String label;
+
+    private Integer clsId;
+
+    public float[] bbox;
+
+    public float confidence;
+
+
+    public Detection(String label,Integer clsId, float[] bbox, float confidence){
+        this.clsId = clsId;
+        this.label = label;
+        this.bbox = bbox;
+        this.confidence = confidence;
+    }
+
+    public Detection(){
+
+    }
+
+    public Integer getClsId() {
+        return clsId;
+    }
+
+    public void setClsId(Integer clsId) {
+        this.clsId = clsId;
+    }
+
+    public String getLabel() {
+        return label;
+    }
+
+    public void setLabel(String label) {
+        this.label = label;
+    }
+
+    public float[] getBbox() {
+        return bbox;
+    }
+
+    public void setBbox(float[] bbox) {
+    }
+
+
+    @Override
+    public String toString() {
+        return "  label="+label +
+                " \t clsId="+clsId +
+                " \t x0="+bbox[0] +
+                " \t y0="+bbox[1] +
+                " \t x1="+bbox[2] +
+                " \t y1="+bbox[3] +
+                " \t score="+confidence;
+    }
+}

autojs/src/main/java/com/stardust/autojs/onnx/util/Letterbox.java

@@ -0,0 +1,87 @@
+package com.stardust.autojs.onnx.util;
+
+import org.opencv.core.Core;
+import org.opencv.core.Mat;
+import org.opencv.core.Size;
+import org.opencv.imgproc.Imgproc;
+
+/**
+ * @author TonyJiangWJ
+ * @since 2023/8/20
+ */
+public class Letterbox {
+
+    private Size newShape = new Size(640, 640);
+    private final double[] color = new double[]{114, 114, 114};
+    private final Boolean auto = false;
+    private final Boolean scaleUp = true;
+    private Integer stride = 32;
+
+    private double ratio;
+    private double dw;
+    private double dh;
+
+    public double getRatio() {
+        return ratio;
+    }
+
+    public double getDw() {
+        return dw;
+    }
+
+    public Integer getWidth() {
+        return (int) this.newShape.width;
+    }
+
+    public Integer getHeight() {
+        return (int) this.newShape.height;
+    }
+
+    public double getDh() {
+        return dh;
+    }
+
+    public void setNewShape(Size newShape) {
+        this.newShape = newShape;
+    }
+
+    public void setStride(Integer stride) {
+        this.stride = stride;
+    }
+
+    public Mat letterbox(Mat im) { // 调整图像大小和填充图像，使满足步长约束，并记录参数
+
+        // 当前形状 [height, width]
+        int[] shape = {im.rows(), im.cols()};
+        // Scale ratio (new / old)
+        double r = Math.min(this.newShape.height / shape[0], this.newShape.width / shape[1]);
+        // 仅缩小，不扩大（一且为了mAP）
+        if (!this.scaleUp) {
+            r = Math.min(r, 1.0);
+        }
+        // Compute padding
+        Size newUnpad = new Size(Math.round(shape[1] * r), Math.round(shape[0] * r));
+        // wh 填充
+        double dw = this.newShape.width - newUnpad.width, dh = this.newShape.height - newUnpad.height;
+        // 最小矩形
+        if (this.auto) {
+            dw = dw % this.stride;
+            dh = dh % this.stride;
+        }
+        // 填充的时候两边都填充一半，使图像居于中心
+        dw /= 2;
+        dh /= 2;
+        // resize
+        if (shape[1] != newUnpad.width || shape[0] != newUnpad.height) {
+            Imgproc.resize(im, im, newUnpad, 0, 0, Imgproc.INTER_LINEAR);
+        }
+        int top = (int) Math.round(dh - 0.1), bottom = (int) Math.round(dh + 0.1);
+        int left = (int) Math.round(dw - 0.1), right = (int) Math.round(dw + 0.1);
+        // 将图像填充为正方形
+        Core.copyMakeBorder(im, im, top, bottom, left, right, Core.BORDER_CONSTANT, new org.opencv.core.Scalar(this.color));
+        this.ratio = r;
+        this.dh = dh;
+        this.dw = dw;
+        return im;
+    }
+}

inrt/build.gradle

@@ -15,6 +15,7 @@ android {
 
     signingConfigs {
         if (file(homePath + '/auto-js-t-pkcs12.jks').exists()) {
+            signSupport = true
             release {
                 storeFile file(homePath + '/auto-js-t-pkcs12.jks')
                 storePassword storePasswd