Merge branch 'dygraph' of https://github.com/PaddlePaddle/PaddleOCR into new_branch

deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/MainActivity.java

@@ -13,6 +13,7 @@ import android.graphics.BitmapFactory;
 import android.graphics.drawable.BitmapDrawable;
 import android.media.ExifInterface;
 import android.content.res.AssetManager;
+import android.media.FaceDetector;
 import android.net.Uri;
 import android.os.Bundle;
 import android.os.Environment;
@@ -27,7 +28,9 @@ import android.view.Menu;
 import android.view.MenuInflater;
 import android.view.MenuItem;
 import android.view.View;
+import android.widget.CheckBox;
 import android.widget.ImageView;
+import android.widget.Spinner;
 import android.widget.TextView;
 import android.widget.Toast;
 
@@ -68,23 +71,24 @@ public class MainActivity extends AppCompatActivity {
     protected ImageView ivInputImage;
     protected TextView tvOutputResult;
     protected TextView tvInferenceTime;
+    protected CheckBox cbOpencl;
+    protected Spinner spRunMode;
 
-    // Model settings of object detection
+    // Model settings of ocr
     protected String modelPath = "";
     protected String labelPath = "";
     protected String imagePath = "";
     protected int cpuThreadNum = 1;
     protected String cpuPowerMode = "";
-    protected String inputColorFormat = "";
-    protected long[] inputShape = new long[]{};
-    protected float[] inputMean = new float[]{};
-    protected float[] inputStd = new float[]{};
+    protected int detLongSize = 960;
     protected float scoreThreshold = 0.1f;
     private String currentPhotoPath;
-    private AssetManager assetManager =null;
+    private AssetManager assetManager = null;
 
     protected Predictor predictor = new Predictor();
 
+    private Bitmap cur_predict_image = null;
+
     @Override
     protected void onCreate(Bundle savedInstanceState) {
         super.onCreate(savedInstanceState);
@@ -98,10 +102,12 @@ public class MainActivity extends AppCompatActivity {
 
         // Setup the UI components
         tvInputSetting = findViewById(R.id.tv_input_setting);
+        cbOpencl = findViewById(R.id.cb_opencl);
         tvStatus = findViewById(R.id.tv_model_img_status);
         ivInputImage = findViewById(R.id.iv_input_image);
         tvInferenceTime = findViewById(R.id.tv_inference_time);
         tvOutputResult = findViewById(R.id.tv_output_result);
+        spRunMode = findViewById(R.id.sp_run_mode);
         tvInputSetting.setMovementMethod(ScrollingMovementMethod.getInstance());
         tvOutputResult.setMovementMethod(ScrollingMovementMethod.getInstance());
 
@@ -111,26 +117,26 @@ public class MainActivity extends AppCompatActivity {
             public void handleMessage(Message msg) {
                 switch (msg.what) {
                     case RESPONSE_LOAD_MODEL_SUCCESSED:
-                        if(pbLoadModel!=null && pbLoadModel.isShowing()){
+                        if (pbLoadModel != null && pbLoadModel.isShowing()) {
                             pbLoadModel.dismiss();
                         }
                         onLoadModelSuccessed();
                         break;
                     case RESPONSE_LOAD_MODEL_FAILED:
-                        if(pbLoadModel!=null && pbLoadModel.isShowing()){
+                        if (pbLoadModel != null && pbLoadModel.isShowing()) {
                             pbLoadModel.dismiss();
                         }
                         Toast.makeText(MainActivity.this, "Load model failed!", Toast.LENGTH_SHORT).show();
                         onLoadModelFailed();
                         break;
                     case RESPONSE_RUN_MODEL_SUCCESSED:
-                        if(pbRunModel!=null && pbRunModel.isShowing()){
+                        if (pbRunModel != null && pbRunModel.isShowing()) {
                             pbRunModel.dismiss();
                         }
                         onRunModelSuccessed();
                         break;
                     case RESPONSE_RUN_MODEL_FAILED:
-                        if(pbRunModel!=null && pbRunModel.isShowing()){
+                        if (pbRunModel != null && pbRunModel.isShowing()) {
                             pbRunModel.dismiss();
                         }
                         Toast.makeText(MainActivity.this, "Run model failed!", Toast.LENGTH_SHORT).show();
@@ -175,71 +181,47 @@ public class MainActivity extends AppCompatActivity {
         super.onResume();
         SharedPreferences sharedPreferences = PreferenceManager.getDefaultSharedPreferences(this);
         boolean settingsChanged = false;
+        boolean model_settingsChanged = false;
         String model_path = sharedPreferences.getString(getString(R.string.MODEL_PATH_KEY),
                 getString(R.string.MODEL_PATH_DEFAULT));
         String label_path = sharedPreferences.getString(getString(R.string.LABEL_PATH_KEY),
                 getString(R.string.LABEL_PATH_DEFAULT));
         String image_path = sharedPreferences.getString(getString(R.string.IMAGE_PATH_KEY),
                 getString(R.string.IMAGE_PATH_DEFAULT));
-        settingsChanged |= !model_path.equalsIgnoreCase(modelPath);
+        model_settingsChanged |= !model_path.equalsIgnoreCase(modelPath);
         settingsChanged |= !label_path.equalsIgnoreCase(labelPath);
         settingsChanged |= !image_path.equalsIgnoreCase(imagePath);
         int cpu_thread_num = Integer.parseInt(sharedPreferences.getString(getString(R.string.CPU_THREAD_NUM_KEY),
                 getString(R.string.CPU_THREAD_NUM_DEFAULT)));
-        settingsChanged |= cpu_thread_num != cpuThreadNum;
+        model_settingsChanged |= cpu_thread_num != cpuThreadNum;
         String cpu_power_mode =
                 sharedPreferences.getString(getString(R.string.CPU_POWER_MODE_KEY),
                         getString(R.string.CPU_POWER_MODE_DEFAULT));
-        settingsChanged |= !cpu_power_mode.equalsIgnoreCase(cpuPowerMode);
-        String input_color_format =
-                sharedPreferences.getString(getString(R.string.INPUT_COLOR_FORMAT_KEY),
-                        getString(R.string.INPUT_COLOR_FORMAT_DEFAULT));
-        settingsChanged |= !input_color_format.equalsIgnoreCase(inputColorFormat);
-        long[] input_shape =
-                Utils.parseLongsFromString(sharedPreferences.getString(getString(R.string.INPUT_SHAPE_KEY),
-                        getString(R.string.INPUT_SHAPE_DEFAULT)), ",");
-        float[] input_mean =
-                Utils.parseFloatsFromString(sharedPreferences.getString(getString(R.string.INPUT_MEAN_KEY),
-                        getString(R.string.INPUT_MEAN_DEFAULT)), ",");
-        float[] input_std =
-                Utils.parseFloatsFromString(sharedPreferences.getString(getString(R.string.INPUT_STD_KEY)
-                        , getString(R.string.INPUT_STD_DEFAULT)), ",");
-        settingsChanged |= input_shape.length != inputShape.length;
-        settingsChanged |= input_mean.length != inputMean.length;
-        settingsChanged |= input_std.length != inputStd.length;
-        if (!settingsChanged) {
-            for (int i = 0; i < input_shape.length; i++) {
-                settingsChanged |= input_shape[i] != inputShape[i];
-            }
-            for (int i = 0; i < input_mean.length; i++) {
-                settingsChanged |= input_mean[i] != inputMean[i];
-            }
-            for (int i = 0; i < input_std.length; i++) {
-                settingsChanged |= input_std[i] != inputStd[i];
-            }
-        }
+        model_settingsChanged |= !cpu_power_mode.equalsIgnoreCase(cpuPowerMode);
+
+        int det_long_size = Integer.parseInt(sharedPreferences.getString(getString(R.string.DET_LONG_SIZE_KEY),
+                getString(R.string.DET_LONG_SIZE_DEFAULT)));
+        settingsChanged |= det_long_size != detLongSize;
         float score_threshold =
                 Float.parseFloat(sharedPreferences.getString(getString(R.string.SCORE_THRESHOLD_KEY),
                         getString(R.string.SCORE_THRESHOLD_DEFAULT)));
         settingsChanged |= scoreThreshold != score_threshold;
         if (settingsChanged) {
-            modelPath = model_path;
             labelPath = label_path;
             imagePath = image_path;
+            detLongSize = det_long_size;
+            scoreThreshold = score_threshold;
+            set_img();
+        }
+        if (model_settingsChanged) {
+            modelPath = model_path;
             cpuThreadNum = cpu_thread_num;
             cpuPowerMode = cpu_power_mode;
-            inputColorFormat = input_color_format;
-            inputShape = input_shape;
-            inputMean = input_mean;
-            inputStd = input_std;
-            scoreThreshold = score_threshold;
             // Update UI
-            tvInputSetting.setText("Model: " + modelPath.substring(modelPath.lastIndexOf("/") + 1) + "\n" + "CPU" +
-                    " Thread Num: " + Integer.toString(cpuThreadNum) + "\n" + "CPU Power Mode: " + cpuPowerMode);
+            tvInputSetting.setText("Model: " + modelPath.substring(modelPath.lastIndexOf("/") + 1) + "\nOPENCL: " + cbOpencl.isChecked() + "\nCPU Thread Num: " + cpuThreadNum + "\nCPU Power Mode: " + cpuPowerMode);
             tvInputSetting.scrollTo(0, 0);
             // Reload model if configure has been changed
-//            loadModel();
-            set_img();
+            loadModel();
         }
     }
 
@@ -254,20 +236,28 @@ public class MainActivity extends AppCompatActivity {
     }
 
     public boolean onLoadModel() {
-        return predictor.init(MainActivity.this, modelPath, labelPath, cpuThreadNum,
+        if (predictor.isLoaded()) {
+            predictor.releaseModel();
+        }
+        return predictor.init(MainActivity.this, modelPath, labelPath, cbOpencl.isChecked() ? 1 : 0, cpuThreadNum,
                 cpuPowerMode,
-                inputColorFormat,
-                inputShape, inputMean,
-                inputStd, scoreThreshold);
+                detLongSize, scoreThreshold);
     }
 
     public boolean onRunModel() {
-        return predictor.isLoaded() && predictor.runModel();
+        String run_mode = spRunMode.getSelectedItem().toString();
+        int run_det = run_mode.contains("检测") ? 1 : 0;
+        int run_cls = run_mode.contains("分类") ? 1 : 0;
+        int run_rec = run_mode.contains("识别") ? 1 : 0;
+        return predictor.isLoaded() && predictor.runModel(run_det, run_cls, run_rec);
     }
 
     public void onLoadModelSuccessed() {
         // Load test image from path and run model
+        tvInputSetting.setText("Model: " + modelPath.substring(modelPath.lastIndexOf("/") + 1) + "\nOPENCL: " + cbOpencl.isChecked() + "\nCPU Thread Num: " + cpuThreadNum + "\nCPU Power Mode: " + cpuPowerMode);
+        tvInputSetting.scrollTo(0, 0);
         tvStatus.setText("STATUS: load model successed");
+
     }
 
     public void onLoadModelFailed() {
@@ -290,20 +280,13 @@ public class MainActivity extends AppCompatActivity {
         tvStatus.setText("STATUS: run model failed");
     }
 
-    public void onImageChanged(Bitmap image) {
-        // Rerun model if users pick test image from gallery or camera
-        if (image != null && predictor.isLoaded()) {
-            predictor.setInputImage(image);
-            runModel();
-        }
-    }
-
     public void set_img() {
         // Load test image from path and run model
         try {
-            assetManager= getAssets();
-            InputStream in=assetManager.open(imagePath);
-            Bitmap bmp=BitmapFactory.decodeStream(in);
+            assetManager = getAssets();
+            InputStream in = assetManager.open(imagePath);
+            Bitmap bmp = BitmapFactory.decodeStream(in);
+            cur_predict_image = bmp;
             ivInputImage.setImageBitmap(bmp);
         } catch (IOException e) {
             Toast.makeText(MainActivity.this, "Load image failed!", Toast.LENGTH_SHORT).show();
@@ -430,7 +413,7 @@ public class MainActivity extends AppCompatActivity {
                         Cursor cursor = managedQuery(uri, proj, null, null, null);
                         cursor.moveToFirst();
                         if (image != null) {
-//                            onImageChanged(image);
+                            cur_predict_image = image;
                             ivInputImage.setImageBitmap(image);
                         }
                     } catch (IOException e) {
@@ -451,7 +434,7 @@ public class MainActivity extends AppCompatActivity {
                         Bitmap image = BitmapFactory.decodeFile(currentPhotoPath);
                         image = Utils.rotateBitmap(image, orientation);
                         if (image != null) {
-//                            onImageChanged(image);
+                            cur_predict_image = image;
                             ivInputImage.setImageBitmap(image);
                         }
                     } else {
@@ -464,28 +447,28 @@ public class MainActivity extends AppCompatActivity {
         }
     }
 
-    public void btn_load_model_click(View view) {
-        if (predictor.isLoaded()){
-            tvStatus.setText("STATUS: model has been loaded");
-        }else{
-            tvStatus.setText("STATUS: load model ......");
-            loadModel();
-        }
+    public void btn_reset_img_click(View view) {
+        ivInputImage.setImageBitmap(cur_predict_image);
+    }
+
+    public void cb_opencl_click(View view) {
+        tvStatus.setText("STATUS: load model ......");
+        loadModel();
     }
 
     public void btn_run_model_click(View view) {
-        Bitmap image =((BitmapDrawable)ivInputImage.getDrawable()).getBitmap();
-        if(image == null) {
+        Bitmap image = ((BitmapDrawable) ivInputImage.getDrawable()).getBitmap();
+        if (image == null) {
             tvStatus.setText("STATUS: image is not exists");
-        }
-        else if (!predictor.isLoaded()){
+        } else if (!predictor.isLoaded()) {
             tvStatus.setText("STATUS: model is not loaded");
-        }else{
+        } else {
             tvStatus.setText("STATUS: run model ...... ");
             predictor.setInputImage(image);
             runModel();
         }
     }
+
     public void btn_choice_img_click(View view) {
         if (requestAllPermissions()) {
             openGallery();
@@ -506,4 +489,32 @@ public class MainActivity extends AppCompatActivity {
         worker.quit();
         super.onDestroy();
     }
+
+    public int get_run_mode() {
+        String run_mode = spRunMode.getSelectedItem().toString();
+        int mode;
+        switch (run_mode) {
+            case "检测+分类+识别":
+                mode = 1;
+                break;
+            case "检测+识别":
+                mode = 2;
+                break;
+            case "识别+分类":
+                mode = 3;
+                break;
+            case "检测":
+                mode = 4;
+                break;
+            case "识别":
+                mode = 5;
+                break;
+            case "分类":
+                mode = 6;
+                break;
+            default:
+                mode = 1;
+        }
+        return mode;
+    }
 }

deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/MiniActivity.java

-package com.baidu.paddle.lite.demo.ocr;
-
-import android.graphics.Bitmap;
-import android.graphics.BitmapFactory;
-import android.os.Build;
-import android.os.Bundle;
-import android.os.Handler;
-import android.os.HandlerThread;
-import android.os.Message;
-import android.util.Log;
-import android.view.View;
-import android.widget.Button;
-import android.widget.ImageView;
-import android.widget.TextView;
-import android.widget.Toast;
-
-import androidx.appcompat.app.AppCompatActivity;
-
-import java.io.IOException;
-import java.io.InputStream;
-
-public class MiniActivity extends AppCompatActivity {
-
-
-    public static final int REQUEST_LOAD_MODEL = 0;
-    public static final int REQUEST_RUN_MODEL = 1;
-    public static final int REQUEST_UNLOAD_MODEL = 2;
-    public static final int RESPONSE_LOAD_MODEL_SUCCESSED = 0;
-    public static final int RESPONSE_LOAD_MODEL_FAILED = 1;
-    public static final int RESPONSE_RUN_MODEL_SUCCESSED = 2;
-    public static final int RESPONSE_RUN_MODEL_FAILED = 3;
-
-    private static final String TAG = "MiniActivity";
-
-    protected Handler receiver = null; // Receive messages from worker thread
-    protected Handler sender = null; // Send command to worker thread
-    protected HandlerThread worker = null; // Worker thread to load&run model
-    protected volatile Predictor predictor = null;
-
-    private String assetModelDirPath = "models/ocr_v2_for_cpu";
-    private String assetlabelFilePath = "labels/ppocr_keys_v1.txt";
-
-    private Button button;
-    private ImageView imageView; // image result
-    private TextView textView; // text result
-
-    @Override
-    protected void onCreate(Bundle savedInstanceState) {
-        super.onCreate(savedInstanceState);
-        setContentView(R.layout.activity_mini);
-
-        Log.i(TAG, "SHOW in Logcat");
-
-        // Prepare the worker thread for mode loading and inference
-        worker = new HandlerThread("Predictor Worker");
-        worker.start();
-        sender = new Handler(worker.getLooper()) {
-            public void handleMessage(Message msg) {
-                switch (msg.what) {
-                    case REQUEST_LOAD_MODEL:
-                        // Load model and reload test image
-                        if (!onLoadModel()) {
-                            runOnUiThread(new Runnable() {
-                                @Override
-                                public void run() {
-                                    Toast.makeText(MiniActivity.this, "Load model failed!", Toast.LENGTH_SHORT).show();
-                                }
-                            });
-                        }
-                        break;
-                    case REQUEST_RUN_MODEL:
-                        // Run model if model is loaded
-                        final boolean isSuccessed = onRunModel();
-                        runOnUiThread(new Runnable() {
-                            @Override
-                            public void run() {
-                                if (isSuccessed){
-                                    onRunModelSuccessed();
-                                }else{
-                                    Toast.makeText(MiniActivity.this, "Run model failed!", Toast.LENGTH_SHORT).show();
-                                }
-                            }
-                        });
-                        break;
-                }
-            }
-        };
-        sender.sendEmptyMessage(REQUEST_LOAD_MODEL); // corresponding to REQUEST_LOAD_MODEL， to call onLoadModel()
-
-        imageView = findViewById(R.id.imageView);
-        textView = findViewById(R.id.sample_text);
-        button = findViewById(R.id.button);
-        button.setOnClickListener(new View.OnClickListener() {
-            @Override
-            public void onClick(View v) {
-                sender.sendEmptyMessage(REQUEST_RUN_MODEL);
-            }
-        });
-
-
-    }
-
-    @Override
-    protected void onDestroy() {
-        onUnloadModel();
-        if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.JELLY_BEAN_MR2) {
-            worker.quitSafely();
-        } else {
-            worker.quit();
-        }
-        super.onDestroy();
-    }
-
-    /**
-     * call in onCreate, model init
-     *
-     * @return
-     */
-    private boolean onLoadModel() {
-        if (predictor == null) {
-            predictor = new Predictor();
-        }
-        return predictor.init(this, assetModelDirPath, assetlabelFilePath);
-    }
-
-    /**
-     * init engine
-     * call in onCreate
-     *
-     * @return
-     */
-    private boolean onRunModel() {
-        try {
-            String assetImagePath = "images/0.jpg";
-            InputStream imageStream = getAssets().open(assetImagePath);
-            Bitmap image = BitmapFactory.decodeStream(imageStream);
-            // Input is Bitmap
-            predictor.setInputImage(image);
-            return predictor.isLoaded() && predictor.runModel();
-        } catch (IOException e) {
-            e.printStackTrace();
-            return false;
-        }
-    }
-
-    private void onRunModelSuccessed() {
-        Log.i(TAG, "onRunModelSuccessed");
-        textView.setText(predictor.outputResult);
-        imageView.setImageBitmap(predictor.outputImage);
-    }
-
-    private void onUnloadModel() {
-        if (predictor != null) {
-            predictor.releaseModel();
-        }
-    }
-}

deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/OCRPredictorNative.java

@@ -29,22 +29,22 @@ public class OCRPredictorNative {
     public OCRPredictorNative(Config config) {
         this.config = config;
         loadLibrary();
-        nativePointer = init(config.detModelFilename, config.recModelFilename,config.clsModelFilename,
+        nativePointer = init(config.detModelFilename, config.recModelFilename, config.clsModelFilename, config.useOpencl,
                 config.cpuThreadNum, config.cpuPower);
         Log.i("OCRPredictorNative", "load success " + nativePointer);
 
     }
 
 
-    public ArrayList<OcrResultModel> runImage(float[] inputData, int width, int height, int channels, Bitmap originalImage) {
-        Log.i("OCRPredictorNative", "begin to run image " + inputData.length + " " + width + " " + height);
-        float[] dims = new float[]{1, channels, height, width};
-        float[] rawResults = forward(nativePointer, inputData, dims, originalImage);
+    public ArrayList<OcrResultModel> runImage(Bitmap originalImage, int max_size_len, int run_det, int run_cls, int run_rec) {
+        Log.i("OCRPredictorNative", "begin to run image ");
+        float[] rawResults = forward(nativePointer, originalImage, max_size_len, run_det, run_cls, run_rec);
         ArrayList<OcrResultModel> results = postprocess(rawResults);
         return results;
     }
 
     public static class Config {
+        public int useOpencl;
         public int cpuThreadNum;
         public String cpuPower;
         public String detModelFilename;
@@ -53,16 +53,16 @@ public class OCRPredictorNative {
 
     }
 
-    public void destory(){
+    public void destory() {
         if (nativePointer > 0) {
             release(nativePointer);
             nativePointer = 0;
         }
     }
 
-    protected native long init(String detModelPath, String recModelPath,String clsModelPath, int threadNum, String cpuMode);
+    protected native long init(String detModelPath, String recModelPath, String clsModelPath, int useOpencl, int threadNum, String cpuMode);
 
-    protected native float[] forward(long pointer, float[] buf, float[] ddims, Bitmap originalImage);
+    protected native float[] forward(long pointer, Bitmap originalImage,int max_size_len, int run_det, int run_cls, int run_rec);
 
     protected native void release(long pointer);
 
@@ -73,9 +73,9 @@ public class OCRPredictorNative {
         while (begin < raw.length) {
             int point_num = Math.round(raw[begin]);
             int word_num = Math.round(raw[begin + 1]);
-            OcrResultModel model = parse(raw, begin + 2, point_num, word_num);
-            begin += 2 + 1 + point_num * 2 + word_num;
-            results.add(model);
+            OcrResultModel res = parse(raw, begin + 2, point_num, word_num);
+            begin += 2 + 1 + point_num * 2 + word_num + 2;
+            results.add(res);
         }
 
         return results;
@@ -83,19 +83,22 @@ public class OCRPredictorNative {
 
     private OcrResultModel parse(float[] raw, int begin, int pointNum, int wordNum) {
         int current = begin;
-        OcrResultModel model = new OcrResultModel();
-        model.setConfidence(raw[current]);
+        OcrResultModel res = new OcrResultModel();
+        res.setConfidence(raw[current]);
         current++;
         for (int i = 0; i < pointNum; i++) {
-            model.addPoints(Math.round(raw[current + i * 2]), Math.round(raw[current + i * 2 + 1]));
+            res.addPoints(Math.round(raw[current + i * 2]), Math.round(raw[current + i * 2 + 1]));
         }
         current += (pointNum * 2);
         for (int i = 0; i < wordNum; i++) {
             int index = Math.round(raw[current + i]);
-            model.addWordIndex(index);
+            res.addWordIndex(index);
         }
+        current += wordNum;
+        res.setClsIdx(raw[current]);
+        res.setClsConfidence(raw[current + 1]);
         Log.i("OCRPredictorNative", "word finished " + wordNum);
-        return model;
+        return res;
     }
 
 

deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/OcrResultModel.java

@@ -10,6 +10,9 @@ public class OcrResultModel {
     private List<Integer> wordIndex;
     private String label;
     private float confidence;
+    private float cls_idx;
+    private String cls_label;
+    private float cls_confidence;
 
     public OcrResultModel() {
         super();
@@ -49,4 +52,28 @@ public class OcrResultModel {
     public void setConfidence(float confidence) {
         this.confidence = confidence;
     }
+
+    public float getClsIdx() {
+        return cls_idx;
+    }
+
+    public void setClsIdx(float idx) {
+        this.cls_idx = idx;
+    }
+
+    public String getClsLabel() {
+        return cls_label;
+    }
+
+    public void setClsLabel(String label) {
+        this.cls_label = label;
+    }
+
+    public float getClsConfidence() {
+        return cls_confidence;
+    }
+
+    public void setClsConfidence(float confidence) {
+        this.cls_confidence = confidence;
+    }
 }

deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/Predictor.java

@@ -31,23 +31,19 @@ public class Predictor {
     protected float inferenceTime = 0;
     // Only for object detection
     protected Vector<String> wordLabels = new Vector<String>();
-    protected String inputColorFormat = "BGR";
-    protected long[] inputShape = new long[]{1, 3, 960};
-    protected float[] inputMean = new float[]{0.485f, 0.456f, 0.406f};
-    protected float[] inputStd = new float[]{1.0f / 0.229f, 1.0f / 0.224f, 1.0f / 0.225f};
+    protected int detLongSize = 960;
     protected float scoreThreshold = 0.1f;
     protected Bitmap inputImage = null;
     protected Bitmap outputImage = null;
     protected volatile String outputResult = "";
-    protected float preprocessTime = 0;
     protected float postprocessTime = 0;
 
 
     public Predictor() {
     }
 
-    public boolean init(Context appCtx, String modelPath, String labelPath) {
-        isLoaded = loadModel(appCtx, modelPath, cpuThreadNum, cpuPowerMode);
+    public boolean init(Context appCtx, String modelPath, String labelPath, int useOpencl, int cpuThreadNum, String cpuPowerMode) {
+        isLoaded = loadModel(appCtx, modelPath, useOpencl, cpuThreadNum, cpuPowerMode);
         if (!isLoaded) {
             return false;
         }
@@ -56,49 +52,18 @@ public class Predictor {
     }
 
 
-    public boolean init(Context appCtx, String modelPath, String labelPath, int cpuThreadNum, String cpuPowerMode,
-                        String inputColorFormat,
-                        long[] inputShape, float[] inputMean,
-                        float[] inputStd, float scoreThreshold) {
-        if (inputShape.length != 3) {
-            Log.e(TAG, "Size of input shape should be: 3");
-            return false;
-        }
-        if (inputMean.length != inputShape[1]) {
-            Log.e(TAG, "Size of input mean should be: " + Long.toString(inputShape[1]));
-            return false;
-        }
-        if (inputStd.length != inputShape[1]) {
-            Log.e(TAG, "Size of input std should be: " + Long.toString(inputShape[1]));
-            return false;
-        }
-        if (inputShape[0] != 1) {
-            Log.e(TAG, "Only one batch is supported in the image classification demo, you can use any batch size in " +
-                    "your Apps!");
-            return false;
-        }
-        if (inputShape[1] != 1 && inputShape[1] != 3) {
-            Log.e(TAG, "Only one/three channels are supported in the image classification demo, you can use any " +
-                    "channel size in your Apps!");
-            return false;
-        }
-        if (!inputColorFormat.equalsIgnoreCase("BGR")) {
-            Log.e(TAG, "Only  BGR color format is supported.");
-            return false;
-        }
-        boolean isLoaded = init(appCtx, modelPath, labelPath);
+    public boolean init(Context appCtx, String modelPath, String labelPath, int useOpencl, int cpuThreadNum, String cpuPowerMode,
+                        int detLongSize, float scoreThreshold) {
+        boolean isLoaded = init(appCtx, modelPath, labelPath, useOpencl, cpuThreadNum, cpuPowerMode);
         if (!isLoaded) {
             return false;
         }
-        this.inputColorFormat = inputColorFormat;
-        this.inputShape = inputShape;
-        this.inputMean = inputMean;
-        this.inputStd = inputStd;
+        this.detLongSize = detLongSize;
         this.scoreThreshold = scoreThreshold;
         return true;
     }
 
-    protected boolean loadModel(Context appCtx, String modelPath, int cpuThreadNum, String cpuPowerMode) {
+    protected boolean loadModel(Context appCtx, String modelPath, int useOpencl, int cpuThreadNum, String cpuPowerMode) {
         // Release model if exists
         releaseModel();
 
@@ -118,12 +83,13 @@ public class Predictor {
         }
 
         OCRPredictorNative.Config config = new OCRPredictorNative.Config();
+        config.useOpencl = useOpencl;
         config.cpuThreadNum = cpuThreadNum;
-        config.detModelFilename = realPath + File.separator + "ch_ppocr_mobile_v2.0_det_opt.nb";
-        config.recModelFilename = realPath + File.separator + "ch_ppocr_mobile_v2.0_rec_opt.nb";
-        config.clsModelFilename = realPath + File.separator + "ch_ppocr_mobile_v2.0_cls_opt.nb";
-        Log.e("Predictor", "model path" + config.detModelFilename + " ; " + config.recModelFilename + ";" + config.clsModelFilename);
         config.cpuPower = cpuPowerMode;
+        config.detModelFilename = realPath + File.separator + "det_db.nb";
+        config.recModelFilename = realPath + File.separator + "rec_crnn.nb";
+        config.clsModelFilename = realPath + File.separator + "cls.nb";
+        Log.i("Predictor", "model path" + config.detModelFilename + " ; " + config.recModelFilename + ";" + config.clsModelFilename);
         paddlePredictor = new OCRPredictorNative(config);
 
         this.cpuThreadNum = cpuThreadNum;
@@ -170,82 +136,29 @@ public class Predictor {
     }
 
 
-    public boolean runModel() {
+    public boolean runModel(int run_det, int run_cls, int run_rec) {
         if (inputImage == null || !isLoaded()) {
             return false;
         }
 
-        // Pre-process image, and feed input tensor with pre-processed data
-
-        Bitmap scaleImage = Utils.resizeWithStep(inputImage, Long.valueOf(inputShape[2]).intValue(), 32);
-
-        Date start = new Date();
-        int channels = (int) inputShape[1];
-        int width = scaleImage.getWidth();
-        int height = scaleImage.getHeight();
-        float[] inputData = new float[channels * width * height];
-        if (channels == 3) {
-            int[] channelIdx = null;
-            if (inputColorFormat.equalsIgnoreCase("RGB")) {
-                channelIdx = new int[]{0, 1, 2};
-            } else if (inputColorFormat.equalsIgnoreCase("BGR")) {
-                channelIdx = new int[]{2, 1, 0};
-            } else {
-                Log.i(TAG, "Unknown color format " + inputColorFormat + ", only RGB and BGR color format is " +
-                        "supported!");
-                return false;
-            }
-
-            int[] channelStride = new int[]{width * height, width * height * 2};
-            int[] pixels=new int[width*height];
-            scaleImage.getPixels(pixels,0,scaleImage.getWidth(),0,0,scaleImage.getWidth(),scaleImage.getHeight());
-            for (int i = 0; i < pixels.length; i++) {
-                int color = pixels[i];
-                float[] rgb = new float[]{(float) red(color) / 255.0f, (float) green(color) / 255.0f,
-                        (float) blue(color) / 255.0f};
-                inputData[i] = (rgb[channelIdx[0]] - inputMean[0]) / inputStd[0];
-                inputData[i + channelStride[0]] = (rgb[channelIdx[1]] - inputMean[1]) / inputStd[1];
-                inputData[i+ channelStride[1]] = (rgb[channelIdx[2]] - inputMean[2]) / inputStd[2];
-            }
-        } else if (channels == 1) {
-            int[] pixels=new int[width*height];
-            scaleImage.getPixels(pixels,0,scaleImage.getWidth(),0,0,scaleImage.getWidth(),scaleImage.getHeight());
-            for (int i = 0; i < pixels.length; i++) {
-                int color = pixels[i];
-                float gray = (float) (red(color) + green(color) + blue(color)) / 3.0f / 255.0f;
-                inputData[i] = (gray - inputMean[0]) / inputStd[0];
-            }
-        } else {
-            Log.i(TAG, "Unsupported channel size " + Integer.toString(channels) + ",  only channel 1 and 3 is " +
-                    "supported!");
-            return false;
-        }
-        float[] pixels = inputData;
-        Log.i(TAG, "pixels " + pixels[0] + " " + pixels[1] + " " + pixels[2] + " " + pixels[3]
-                + " " + pixels[pixels.length / 2] + " " + pixels[pixels.length / 2 + 1] + " " + pixels[pixels.length - 2] + " " + pixels[pixels.length - 1]);
-        Date end = new Date();
-        preprocessTime = (float) (end.getTime() - start.getTime());
-
         // Warm up
         for (int i = 0; i < warmupIterNum; i++) {
-            paddlePredictor.runImage(inputData, width, height, channels, inputImage);
+            paddlePredictor.runImage(inputImage, detLongSize, run_det, run_cls, run_rec);
         }
         warmupIterNum = 0; // do not need warm
         // Run inference
-        start = new Date();
-        ArrayList<OcrResultModel> results = paddlePredictor.runImage(inputData, width, height, channels, inputImage);
-        end = new Date();
+        Date start = new Date();
+        ArrayList<OcrResultModel> results = paddlePredictor.runImage(inputImage, detLongSize, run_det, run_cls, run_rec);
+        Date end = new Date();
         inferenceTime = (end.getTime() - start.getTime()) / (float) inferIterNum;
 
         results = postprocess(results);
-        Log.i(TAG, "[stat] Preprocess Time: " + preprocessTime
-                + " ; Inference Time: " + inferenceTime + " ;Box Size " + results.size());
+        Log.i(TAG, "[stat] Inference Time: " + inferenceTime + " ;Box Size " + results.size());
         drawResults(results);
 
         return true;
     }
 
-
     public boolean isLoaded() {
         return paddlePredictor != null && isLoaded;
     }
@@ -282,10 +195,6 @@ public class Predictor {
         return outputResult;
     }
 
-    public float preprocessTime() {
-        return preprocessTime;
-    }
-
     public float postprocessTime() {
         return postprocessTime;
     }
@@ -310,6 +219,7 @@ public class Predictor {
                 }
             }
             r.setLabel(word.toString());
+            r.setClsLabel(r.getClsIdx() == 1 ? "180" : "0");
         }
         return results;
     }
@@ -319,14 +229,22 @@ public class Predictor {
         for (int i = 0; i < results.size(); i++) {
             OcrResultModel result = results.get(i);
             StringBuilder sb = new StringBuilder("");
-            sb.append(result.getLabel());
-            sb.append(" ").append(result.getConfidence());
-            sb.append("; Points: ");
-            for (Point p : result.getPoints()) {
-                sb.append("(").append(p.x).append(",").append(p.y).append(") ");
+            if(result.getPoints().size()>0){
+                sb.append("Det: ");
+                for (Point p : result.getPoints()) {
+                    sb.append("(").append(p.x).append(",").append(p.y).append(") ");
+                }
+            }
+            if(result.getLabel().length() > 0){
+                sb.append("\n Rec: ").append(result.getLabel());
+                sb.append(",").append(result.getConfidence());
+            }
+            if(result.getClsIdx()!=-1){
+                sb.append(" Cls: ").append(result.getClsLabel());
+                sb.append(",").append(result.getClsConfidence());
             }
             Log.i(TAG, sb.toString()); // show LOG in Logcat panel
-            outputResultSb.append(i + 1).append(": ").append(result.getLabel()).append("\n");
+            outputResultSb.append(i + 1).append(": ").append(sb.toString()).append("\n");
         }
         outputResult = outputResultSb.toString();
         outputImage = inputImage;
@@ -344,6 +262,9 @@ public class Predictor {
         for (OcrResultModel result : results) {
             Path path = new Path();
             List<Point> points = result.getPoints();
+            if(points.size()==0){
+                continue;
+            }
             path.moveTo(points.get(0).x, points.get(0).y);
             for (int i = points.size() - 1; i >= 0; i--) {
                 Point p = points.get(i);

deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/SettingsActivity.java

@@ -20,16 +20,13 @@ public class SettingsActivity extends AppCompatPreferenceActivity implements Sha
     ListPreference etImagePath = null;
     ListPreference lpCPUThreadNum = null;
     ListPreference lpCPUPowerMode = null;
-    ListPreference lpInputColorFormat = null;
-    EditTextPreference etInputShape = null;
-    EditTextPreference etInputMean = null;
-    EditTextPreference etInputStd = null;
+    EditTextPreference etDetLongSize = null;
     EditTextPreference etScoreThreshold = null;
 
     List<String> preInstalledModelPaths = null;
     List<String> preInstalledLabelPaths = null;
     List<String> preInstalledImagePaths = null;
-    List<String> preInstalledInputShapes = null;
+    List<String> preInstalledDetLongSizes = null;
     List<String> preInstalledCPUThreadNums = null;
     List<String> preInstalledCPUPowerModes = null;
     List<String> preInstalledInputColorFormats = null;
@@ -50,7 +47,7 @@ public class SettingsActivity extends AppCompatPreferenceActivity implements Sha
         preInstalledModelPaths = new ArrayList<String>();
         preInstalledLabelPaths = new ArrayList<String>();
         preInstalledImagePaths = new ArrayList<String>();
-        preInstalledInputShapes = new ArrayList<String>();
+        preInstalledDetLongSizes = new ArrayList<String>();
         preInstalledCPUThreadNums = new ArrayList<String>();
         preInstalledCPUPowerModes = new ArrayList<String>();
         preInstalledInputColorFormats = new ArrayList<String>();
@@ -63,10 +60,7 @@ public class SettingsActivity extends AppCompatPreferenceActivity implements Sha
         preInstalledImagePaths.add(getString(R.string.IMAGE_PATH_DEFAULT));
         preInstalledCPUThreadNums.add(getString(R.string.CPU_THREAD_NUM_DEFAULT));
         preInstalledCPUPowerModes.add(getString(R.string.CPU_POWER_MODE_DEFAULT));
-        preInstalledInputColorFormats.add(getString(R.string.INPUT_COLOR_FORMAT_DEFAULT));
-        preInstalledInputShapes.add(getString(R.string.INPUT_SHAPE_DEFAULT));
-        preInstalledInputMeans.add(getString(R.string.INPUT_MEAN_DEFAULT));
-        preInstalledInputStds.add(getString(R.string.INPUT_STD_DEFAULT));
+        preInstalledDetLongSizes.add(getString(R.string.DET_LONG_SIZE_DEFAULT));
         preInstalledScoreThresholds.add(getString(R.string.SCORE_THRESHOLD_DEFAULT));
 
         // Setup UI components
@@ -89,11 +83,7 @@ public class SettingsActivity extends AppCompatPreferenceActivity implements Sha
                 (ListPreference) findPreference(getString(R.string.CPU_THREAD_NUM_KEY));
         lpCPUPowerMode =
                 (ListPreference) findPreference(getString(R.string.CPU_POWER_MODE_KEY));
-        lpInputColorFormat =
-                (ListPreference) findPreference(getString(R.string.INPUT_COLOR_FORMAT_KEY));
-        etInputShape = (EditTextPreference) findPreference(getString(R.string.INPUT_SHAPE_KEY));
-        etInputMean = (EditTextPreference) findPreference(getString(R.string.INPUT_MEAN_KEY));
-        etInputStd = (EditTextPreference) findPreference(getString(R.string.INPUT_STD_KEY));
+        etDetLongSize = (EditTextPreference) findPreference(getString(R.string.DET_LONG_SIZE_KEY));
         etScoreThreshold = (EditTextPreference) findPreference(getString(R.string.SCORE_THRESHOLD_KEY));
     }
 
@@ -112,11 +102,7 @@ public class SettingsActivity extends AppCompatPreferenceActivity implements Sha
                 editor.putString(getString(R.string.IMAGE_PATH_KEY), preInstalledImagePaths.get(modelIdx));
                 editor.putString(getString(R.string.CPU_THREAD_NUM_KEY), preInstalledCPUThreadNums.get(modelIdx));
                 editor.putString(getString(R.string.CPU_POWER_MODE_KEY), preInstalledCPUPowerModes.get(modelIdx));
-                editor.putString(getString(R.string.INPUT_COLOR_FORMAT_KEY),
-                        preInstalledInputColorFormats.get(modelIdx));
-                editor.putString(getString(R.string.INPUT_SHAPE_KEY), preInstalledInputShapes.get(modelIdx));
-                editor.putString(getString(R.string.INPUT_MEAN_KEY), preInstalledInputMeans.get(modelIdx));
-                editor.putString(getString(R.string.INPUT_STD_KEY), preInstalledInputStds.get(modelIdx));
+                editor.putString(getString(R.string.DET_LONG_SIZE_KEY), preInstalledDetLongSizes.get(modelIdx));
                 editor.putString(getString(R.string.SCORE_THRESHOLD_KEY),
                         preInstalledScoreThresholds.get(modelIdx));
                 editor.apply();
@@ -129,10 +115,7 @@ public class SettingsActivity extends AppCompatPreferenceActivity implements Sha
         etImagePath.setEnabled(enableCustomSettings);
         lpCPUThreadNum.setEnabled(enableCustomSettings);
         lpCPUPowerMode.setEnabled(enableCustomSettings);
-        lpInputColorFormat.setEnabled(enableCustomSettings);
-        etInputShape.setEnabled(enableCustomSettings);
-        etInputMean.setEnabled(enableCustomSettings);
-        etInputStd.setEnabled(enableCustomSettings);
+        etDetLongSize.setEnabled(enableCustomSettings);
         etScoreThreshold.setEnabled(enableCustomSettings);
         modelPath = sharedPreferences.getString(getString(R.string.MODEL_PATH_KEY),
                 getString(R.string.MODEL_PATH_DEFAULT));
@@ -144,14 +127,8 @@ public class SettingsActivity extends AppCompatPreferenceActivity implements Sha
                 getString(R.string.CPU_THREAD_NUM_DEFAULT));
         String cpuPowerMode = sharedPreferences.getString(getString(R.string.CPU_POWER_MODE_KEY),
                 getString(R.string.CPU_POWER_MODE_DEFAULT));
-        String inputColorFormat = sharedPreferences.getString(getString(R.string.INPUT_COLOR_FORMAT_KEY),
-                getString(R.string.INPUT_COLOR_FORMAT_DEFAULT));
-        String inputShape = sharedPreferences.getString(getString(R.string.INPUT_SHAPE_KEY),
-                getString(R.string.INPUT_SHAPE_DEFAULT));
-        String inputMean = sharedPreferences.getString(getString(R.string.INPUT_MEAN_KEY),
-                getString(R.string.INPUT_MEAN_DEFAULT));
-        String inputStd = sharedPreferences.getString(getString(R.string.INPUT_STD_KEY),
-                getString(R.string.INPUT_STD_DEFAULT));
+        String detLongSize = sharedPreferences.getString(getString(R.string.DET_LONG_SIZE_KEY),
+                getString(R.string.DET_LONG_SIZE_DEFAULT));
         String scoreThreshold = sharedPreferences.getString(getString(R.string.SCORE_THRESHOLD_KEY),
                 getString(R.string.SCORE_THRESHOLD_DEFAULT));
         etModelPath.setSummary(modelPath);
@@ -164,14 +141,8 @@ public class SettingsActivity extends AppCompatPreferenceActivity implements Sha
         lpCPUThreadNum.setSummary(cpuThreadNum);
         lpCPUPowerMode.setValue(cpuPowerMode);
         lpCPUPowerMode.setSummary(cpuPowerMode);
-        lpInputColorFormat.setValue(inputColorFormat);
-        lpInputColorFormat.setSummary(inputColorFormat);
-        etInputShape.setSummary(inputShape);
-        etInputShape.setText(inputShape);
-        etInputMean.setSummary(inputMean);
-        etInputMean.setText(inputMean);
-        etInputStd.setSummary(inputStd);
-        etInputStd.setText(inputStd);
+        etDetLongSize.setSummary(detLongSize);
+        etDetLongSize.setText(detLongSize);
         etScoreThreshold.setText(scoreThreshold);
         etScoreThreshold.setSummary(scoreThreshold);
     }

deploy/android_demo/app/src/main/res/layout/activity_main.xml

@@ -23,13 +23,7 @@
                 android:layout_height="wrap_content"
                 android:orientation="horizontal">
 
-                <Button
-                    android:id="@+id/btn_load_model"
-                    android:layout_width="0dp"
-                    android:layout_height="wrap_content"
-                    android:layout_weight="1"
-                    android:onClick="btn_load_model_click"
-                    android:text="加载模型" />
+
                 <Button
                     android:id="@+id/btn_run_model"
                     android:layout_width="0dp"
@@ -52,7 +46,45 @@
                     android:onClick="btn_choice_img_click"
                     android:text="选取图片" />
 
+                <Button
+                    android:id="@+id/btn_reset_img"
+                    android:layout_width="0dp"
+                    android:layout_height="wrap_content"
+                    android:layout_weight="1"
+                    android:onClick="btn_reset_img_click"
+                    android:text="清空绘图" />
+
             </LinearLayout>
+            <LinearLayout
+                android:id="@+id/run_mode_layout"
+                android:layout_width="fill_parent"
+                android:layout_height="wrap_content"
+                android:orientation="horizontal">
+
+                <CheckBox
+                    android:id="@+id/cb_opencl"
+                    android:layout_width="0dp"
+                    android:layout_weight="1"
+                    android:layout_height="wrap_content"
+                    android:text="开启OPENCL"
+                    android:onClick="cb_opencl_click"
+                    android:visibility="gone"/>
+                <TextView
+                    android:layout_width="0dp"
+                    android:layout_weight="0.5"
+                    android:layout_height="wrap_content"
+                    android:text="运行模式:"/>
+
+                <Spinner
+                    android:id="@+id/sp_run_mode"
+                    android:layout_width="0dp"
+                    android:layout_weight="1.5"
+                    android:layout_height="wrap_content"
+                    android:entries="@array/run_Model"
+                    />
+
+            </LinearLayout>
+
             <TextView
                     android:id="@+id/tv_input_setting"
                     android:layout_width="wrap_content"
@@ -60,7 +92,7 @@
                     android:scrollbars="vertical"
                     android:layout_marginLeft="12dp"
                     android:layout_marginRight="12dp"
-                    android:layout_marginTop="10dp"
+                    android:layout_marginTop="5dp"
                     android:layout_marginBottom="5dp"
                     android:lineSpacingExtra="4dp"
                     android:singleLine="false"

deploy/android_demo/app/src/main/res/layout/activity_mini.xml

-<?xml version="1.0" encoding="utf-8"?>
-<!-- for MiniActivity Use Only -->
-<androidx.constraintlayout.widget.ConstraintLayout xmlns:android="http://schemas.android.com/apk/res/android"
-    xmlns:app="http://schemas.android.com/apk/res-auto"
-    xmlns:tools="http://schemas.android.com/tools"
-    android:layout_width="match_parent"
-    android:layout_height="match_parent"
-    app:layout_constraintLeft_toLeftOf="parent"
-    app:layout_constraintLeft_toRightOf="parent"
-    tools:context=".MainActivity">
-
-    <TextView
-        android:id="@+id/sample_text"
-        android:layout_width="0dp"
-        android:layout_height="wrap_content"
-        android:text="Hello World!"
-        app:layout_constraintLeft_toLeftOf="parent"
-        app:layout_constraintRight_toRightOf="parent"
-        app:layout_constraintTop_toBottomOf="@id/imageView"
-        android:scrollbars="vertical"
-        />
-
-    <ImageView
-        android:id="@+id/imageView"
-        android:layout_width="wrap_content"
-        android:layout_height="wrap_content"
-        android:paddingTop="20dp"
-        android:paddingBottom="20dp"
-        app:layout_constraintBottom_toTopOf="@id/imageView"
-        app:layout_constraintLeft_toLeftOf="parent"
-        app:layout_constraintRight_toRightOf="parent"
-        app:layout_constraintTop_toTopOf="parent"
-        tools:srcCompat="@tools:sample/avatars" />
-
-    <Button
-        android:id="@+id/button"
-        android:layout_width="wrap_content"
-        android:layout_height="wrap_content"
-        android:layout_marginBottom="4dp"
-        android:text="Button"
-        app:layout_constraintBottom_toBottomOf="parent"
-        app:layout_constraintLeft_toLeftOf="parent"
-        app:layout_constraintRight_toRightOf="parent"
-        tools:layout_editor_absoluteX="161dp" />
-
-</androidx.constraintlayout.widget.ConstraintLayout>
\ No newline at end of file

deploy/slim/prune/README.md

@@ -45,7 +45,7 @@ python3 setup.py install
             'conv10_expand_weights': {0.1: 0.006509952684312718, 0.2: 0.01827734339798862, 0.3: 0.014528405644659832, 0.6: 0.06536008804270439, 0.8: 0.11798612250664964, 0.7: 0.12391408417493704, 0.4: 0.030615754498018757, 0.5: 0.047105205602406594}
             'conv10_linear_weights': {0.1: 0.05113190831455035, 0.2: 0.07705573833558801, 0.3: 0.12096721757739311, 0.6: 0.5135061352930738, 0.8: 0.7908166677143281, 0.7: 0.7272187676899062, 0.4: 0.1819252083008504, 0.5: 0.3728054727792405}
         }
-加载敏感度文件后会返回一个字典，字典中的keys为网络模型参数模型的名字，values为一个字典，里面保存了相应网络层的裁剪敏感度信息。例如在例子中，conv10_expand_weights所对应的网络层在裁掉10%的卷积核后模型性能相较原模型会下降0.65%，详细信息可见[PaddleSlim](https://github.com/PaddlePaddle/PaddleSlim/blob/develop/docs/zh_cn/algo/algo.md#2-%E5%8D%B7%E7%A7%AF%E6%A0%B8%E5%89%AA%E8%A3%81%E5%8E%9F%E7%90%86)
+加载敏感度文件后会返回一个字典，字典中的keys为网络模型参数模型的名字，values为一个字典，里面保存了相应网络层的裁剪敏感度信息。例如在例子中，conv10_expand_weights所对应的网络层在裁掉10%的卷积核后模型性能相较原模型会下降0.65%，详细信息可见[PaddleSlim](https://github.com/PaddlePaddle/PaddleSlim/blob/release/2.0-alpha/docs/zh_cn/algo/algo.md)
 
 进入PaddleOCR根目录，通过以下命令对模型进行敏感度分析训练：
 ```bash