amelioration de l'affichage des resultats de prediction et integrations deu nom et logo de l'app

app/src/main/java/com/example/myapplication/OutputPredictedImage.java

+package com.example.myapplication;
+
+import android.graphics.Bitmap;
+import android.graphics.BitmapFactory;
+
+import java.util.Map;
+
+/**
+ * this class purpose is to store information of the output of the recognation species
+ */
+public class OutputPredictedImage {
+    private Bitmap annotatedImage;
+    private Map<String, Integer> predictionResults;
+
+    public OutputPredictedImage(Bitmap annotatedImage, Map<String,Integer> predictionResults){
+        this.annotatedImage = annotatedImage;
+        this.predictionResults = predictionResults;
+    }
+
+    @Override
+    public String toString(){
+        StringBuilder result = new StringBuilder();
+        for (Map.Entry<String, Integer> entry : predictionResults.entrySet()) {
+            // Append the key (species) and value (probability) in the specified format
+            result.append(entry.getKey())
+                    .append(" : ")
+                    .append(entry.getValue()) // Format the float to 2 decimal places
+                    .append("\n"); // Add a newline for separation
+        }
+
+        // Return the concatenated string
+        return result.toString(); // Remove the last newline
+    }
+
+    public Bitmap getAnnotatedImage() {
+        return annotatedImage;
+    }
+
+    public Map<String, Integer> getPredictionResults() {
+        return predictionResults;
+    }
+
+}

app/src/main/java/com/example/myapplication/PhotoPage.java

@@ -123,22 +123,14 @@ public class PhotoPage extends Fragment {
         try {
             TestModeleTflite testModeleTflite = new TestModeleTflite(this.getContext());
 
-            /*
-            List<String> speciesDetected =  testModeleTflite.recognizeSpeciesClass(scaledBitmap);
-
-            StringBuilder recognationOutput = new StringBuilder("Espèces détectées : ");
-            for(String specie:speciesDetected){
-                recognationOutput.append(specie).append("\t");
-            }
-
-            TextView textView = getView().findViewById(R.id.textView2);
-            textView.setText(recognationOutput);*/
-            Bitmap annotatedImage = testModeleTflite.recognizeSpecies(bitmap);
+            OutputPredictedImage outputPredictedImage = testModeleTflite.recognizeSpeciesClass(bitmap);
+            Bitmap annotatedImage = outputPredictedImage.getAnnotatedImage();
             double height = 1.5 * annotatedImage.getHeight();
             double width = 1.5 * annotatedImage.getWidth();
             scaledBitmap = Bitmap.createScaledBitmap(annotatedImage, (int) width, (int) height, true);
             imageView.setImageBitmap(scaledBitmap);
-
+            //TextView textView = getView().findViewById(R.id.textView2);
+            textView.setText(outputPredictedImage.toString());
 
         } catch (IOException e) {
             throw new RuntimeException(e);

app/src/main/java/com/example/myapplication/TestModeleTflite.java

@@ -27,7 +27,9 @@ import java.io.InputStream;
 import java.io.InputStreamReader;
 import java.nio.MappedByteBuffer;
 import java.util.ArrayList;
+import java.util.HashMap;
 import java.util.List;
+import java.util.Map;
 
 public class TestModeleTflite {
     private static final String MODEL_PATH = "model_float32.tflite";
@@ -217,6 +219,7 @@ public class TestModeleTflite {
             );
             canvas.drawRect(rect, paint);
             canvas.drawText(box.clsName, rect.left, rect.bottom, textPaint);
+            canvas.drawText(new StringBuilder().append("prob : ").append(String.format("%.2f", box.cnf)).toString(), rect.left, rect.top, textPaint);
         }
 
         return mutableBitmap;
@@ -243,14 +246,22 @@ public class TestModeleTflite {
         return annotateImage(inputImage, boxes);
     }
 
-    public List<String> recognizeSpeciesClass(Bitmap inputImage){
-        ArrayList<String> speciesNames = new ArrayList<>();
+    public OutputPredictedImage recognizeSpeciesClass(Bitmap inputImage){
+        //ArrayList<String> speciesNames = new ArrayList<>();
+        Map<String, Integer> predictionResults = new HashMap<>();
         TensorBuffer outputBuffer = predict(inputImage);
         List<BoundingBox> boxes = processOutput(outputBuffer);
         for(BoundingBox box:boxes){
-            if(!speciesNames.contains(box.clsName)) speciesNames.add(box.clsName);
+            if(predictionResults.containsKey(box.clsName)){
+                int previousNumber = predictionResults.get(box.clsName);
+                predictionResults.put(box.clsName, previousNumber + 1);
+            }else{
+                predictionResults.put(box.clsName, 1);
+            }
+
         }
-        return speciesNames;
+        Bitmap annotatedImage =  annotateImage(inputImage, boxes);
+        return new OutputPredictedImage(annotatedImage, predictionResults);
     }
 
 

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

@@ -7,11 +7,14 @@
     tools:context=".PhotoPage">
 
     <!-- Prediction Text -->
+
+    <!-- Accuracy Text -->
+
     <TextView
         android:id="@+id/textView"
-        android:layout_width="9dp"
-        android:layout_height="0dp"
-        android:layout_marginBottom="200dp"
+        android:layout_width="351dp"
+        android:layout_height="28dp"
+        android:layout_marginBottom="196dp"
         android:text=""
         android:textColor="#F12B2B"
         android:textSize="17sp"
@@ -20,7 +23,6 @@
         app:layout_constraintEnd_toEndOf="parent"
         app:layout_constraintStart_toStartOf="parent" />
 
-    <!-- Accuracy Text -->
     <TextView
         android:id="@+id/txtView"
         android:layout_width="wrap_content"