Fix Memory error / Messy code

Assets/Brains/CozmoLearningBrain.asset

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     cameraResolutions:
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-      height: 120
+    - width: 80
+      height: 30
       blackAndWhite: 0
     vectorActionDescriptions:
     - 

Assets/Scenes/CozmoTraining.unity

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-    width: 84
-    height: 84
+    width: 80
+    height: 30
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     targetFrameRate: -1
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-    width: 84
-    height: 84
+    width: 320
+    height: 120
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Assets/Scripts/CannyEdgeDetection/ImageProcessor.cs

     public RenderTexture renderTextureCropped;
 
     [Header("Debug Helper")]
-    //[Tooltip("Reference to the MeshRenderer that will show the processed Image from Cozmo")]
-    //public MeshRenderer processedImageRenderer;
+    [Tooltip("Reference to the MeshRenderer that will show the processed Image from Cozmo")]
+    public MeshRenderer processedImageRenderer;
     [Tooltip("Reference to the MeshRenderer that will show the processed and cropped Image from Cozmo")]
     public MeshRenderer processedImageRendererCropped;
 
     private int croppedImHeight = 120;  // Height of the cropped camera image from the virtual cozmo 
     private Camera textureCamera;       // Virtual Cozmo camera
 
+
+    private Texture2D firstTexture;
+
+
     private void Start()
     {
         // Get reference to the cozmo camera
         // Set image widths and heights based on the given RenderTextures
         imWidth = textureCamera.targetTexture.width;
         imHeight = textureCamera.targetTexture.height;
-        croppedImHeight = renderTextureCropped.height;
+        //croppedImHeight = renderTextureCropped.height;
 
         //assign the processed targetTexture to the renderer to display the image
-        //processedImageRenderer.material.mainTexture = textureCamera.targetTexture;
+        processedImageRenderer.material.mainTexture = textureCamera.targetTexture;
         processedImageRendererCropped.material.mainTexture = renderTextureCropped;
 
         // initialize video / image with given size
         videoSourceImageData = new Vec3b[imHeight * imWidth];
         cannyImage = new Mat(imHeight, imWidth, MatType.CV_8UC1);
         cannyImageData = new byte[croppedImHeight * imWidth];
+
+
+        firstTexture = new Texture2D(imWidth, imHeight, TextureFormat.RGBA32, true, true);
+        processedTexture = new Texture2D(imWidth, croppedImHeight, TextureFormat.RGBA32, true, true);
     }
 
-    /// <summary>
-    /// Gets called when a new image arrives from the camera this script lies on
-    /// </summary>
-    /// <param name="source"></param>
-    /// <param name="destination"></param>
-    private void OnRenderImage(RenderTexture source, RenderTexture destination)
+    ///// <summary>
+    ///// Gets called when a new image arrives from the camera this script lies on
+    ///// </summary>
+    ///// <param name="source"></param>
+    ///// <param name="destination"></param>
+    //private void OnRenderImage(RenderTexture source, RenderTexture destination)
+    //{
+    //    Texture2D tex = RenderTextureToTexture2D(source);
+    //    videoSourceImage = TextureToMat(tex);
+    //    cannyImage = ProcessImage(videoSourceImage);
+    //    cannyImage = CropImage(cannyImage);
+    //    CenterOfGravityTest(cannyImage);
+    //    processedTexture = MatToTexture(cannyImage);
+    //    //processedTexture.Resize(80, 30);
+    //    //processedTexture.Apply();
+    //    //Graphics.Blit(processedTexture, destination);
+    //    Graphics.Blit(processedTexture, renderTextureCropped);
+    //}
+
+    public void ProcessRenderTexture(RenderTexture source)
+    {
+        ProcessRenderTexture(source, source);
+    }
+
+    public void ProcessRenderTexture(RenderTexture source, RenderTexture target)
     {
         Texture2D tex = RenderTextureToTexture2D(source);
         videoSourceImage = TextureToMat(tex);
         cannyImage = CropImage(cannyImage);
         CenterOfGravityTest(cannyImage);
         processedTexture = MatToTexture(cannyImage);
+        //processedTexture.Resize(80, 30);
+        //processedTexture.Apply();
         //Graphics.Blit(processedTexture, destination);
+        Graphics.Blit(processedTexture, target);
+    }
+
+    //public void ProcessRenderTexture_NEW(RenderTexture source, RenderTexture target)
+    //{
+    //    RenderTextureToTexture2D_NEW(source);
+    //    TextureToMat_NEW(firstTexture);
+    //    ProcessImage_NEW(videoSourceImage);
+    //    cannyImage = CropImage(cannyImage);
+    //    CenterOfGravityTest(cannyImage);
+    //    MatToTexture_NEW(cannyImage);
+    //    //processedTexture.Resize(80, 30);
+    //    //processedTexture.Apply();
+    //    //Graphics.Blit(processedTexture, destination);
+    //    Graphics.Blit(processedTexture, target);
+    //}
+
+    public void OnRenderImage(RenderTexture source, RenderTexture destination)
+    {
+        RenderTextureToTexture2D_NEW(source);
+        TextureToMat_NEW(firstTexture);
+        ProcessImage_NEW(videoSourceImage);
+        cannyImage = CropImage(cannyImage);
+        CenterOfGravityTest(cannyImage);
+        MatToTexture_NEW(cannyImage);
+        Graphics.Blit(processedTexture, destination);
         Graphics.Blit(processedTexture, renderTextureCropped);
     }
 
         return croppedImage;
     }
 
+    //// Crop image to just see the middle of the original image 
+    //private Mat CropImage_NEW(Mat image)
+    //{
+    //    //cut a fourth out of the top and bottom of the image 
+    //    OpenCvSharp.Rect rectCroped = new OpenCvSharp.Rect(0, image.Height / 4, image.Width, image.Height / 2);
+    //    Mat croppedImage = new Mat(image, rectCroped);
+    //    return croppedImage;
+    //}
+
     private Texture2D RenderTextureToTexture2D(RenderTexture rTex)
     {
         Texture2D tex = new Texture2D(imWidth, imHeight, TextureFormat.RGBA32, true, true);
         return tex;
     }
 
+    private void RenderTextureToTexture2D_NEW(RenderTexture rTex)
+    {
+        RenderTexture.active = rTex;
+        firstTexture.ReadPixels(new UnityEngine.Rect(0, 0, rTex.width, rTex.height), 0, 0);
+        firstTexture.Apply();
+    }
+
     // Convert Unity Texture2D object to OpenCVSharp Mat object
     private Mat TextureToMat(Texture2D source)
     {
         return tmpMat;
     }
 
+    // Convert Unity Texture2D object to OpenCVSharp Mat object
+    private void TextureToMat_NEW(Texture2D source)
+    {
+        // Color32 array : r, g, b, a
+        Color32[] c = source.GetPixels32();
+
+        // Parallel for loop
+        // convert Color32 object to Vec3b object
+        // Vec3b is the representation of pixel for Mat
+        Parallel.For(0, imHeight, i =>
+        {
+            for (var j = 0; j < imWidth; j++)
+            {
+                var col = c[j + i * imWidth];
+                var vec3 = new Vec3b
+                {
+                    Item0 = col.b,
+                    Item1 = col.g,
+                    Item2 = col.r
+                };
+                // set pixel to an array
+                videoSourceImageData[j + i * imWidth] = vec3;
+            }
+        });
+
+        // assign the Vec3b array to Mat
+
+        videoSourceImage.SetArray(0, 0, videoSourceImageData);
+    }
+
     // Simple example of canny edge detect
     private Mat ProcessImage(Mat _image)
     {
         return cannyImg;
     }
 
+    // Simple example of canny edge detect
+    private void ProcessImage_NEW(Mat _image)
+    {
+        Cv2.Canny(_image, cannyImage, 100, 100);
+    }
+
     // Convert OpenCVSharp Mat object to Unity Texture2D object
     private Texture2D MatToTexture(Mat mat)
     {
         return texture;
     }
 
+    // Convert OpenCVSharp Mat object to Unity Texture2D object
+    private void MatToTexture_NEW(Mat mat)
+    {
+        // cannyImageData is byte array, because canny image is grayscale
+        mat.GetArray(0, 0, cannyImageData);
+        // create Color32 array that can be assigned to Texture2D directly
+        Color32[] c = new Color32[croppedImHeight * imWidth];
+
+        // parallel for loop
+        Parallel.For(0, croppedImHeight, i =>
+        {
+            for (var j = 0; j < imWidth; j++)
+            {
+                byte vec = cannyImageData[j + i * imWidth];
+                var color32 = new Color32
+                {
+                    r = vec,
+                    g = vec,
+                    b = vec,
+                    a = 0
+                };
+                c[j + i * imWidth] = color32;
+            }
+        });
+
+
+        processedTexture.SetPixels32(c);
+        // to update the texture, OpenGL manner
+        processedTexture.Apply();
+    }
+
 
     private void CenterOfGravityTest(Mat processedImage)
     {

Assets/Scripts/ML Cozmo/CozmoAcademy.cs

     public override void AcademyReset()
     {
         cozmo.transform.position = startPoint.position;
+        cozmo.transform.rotation = startPoint.rotation;
     }
 
     //private void Update()

Assets/Scripts/ML Cozmo/CozmoAgent.cs

         if (renderCamera != null)
         {
             renderCamera.Render();
+            //onRenderImageTest.ProcessRenderTexture_NEW(renderCamera.targetTexture, onRenderImageTest.renderTextureCropped);
         }
 
 
             SetReward(-1);
             print("Reward: -1");
         }
+
+        onRenderImageTest.enabled = false;
     }
 
     // to be implemented by the developer
 
         if (!academy.GetIsInference())
         {
+            //onRenderImageTest.ProcessRenderTexture_NEW(renderCamera.targetTexture, onRenderImageTest.renderTextureCropped);
             RequestDecision();
         }
         else
             if (timeSinceDecision >= timeBetweenDecisionsAtInference)
             {
                 timeSinceDecision = 0f;
+                //onRenderImageTest.ProcessRenderTexture_NEW(renderCamera.targetTexture, onRenderImageTest.renderTextureCropped);
                 RequestDecision();
             }
             else

Assets/Textures/RenderTextures/CozmoCannyCroped.renderTexture

     Hash: 00000000000000000000000000000000
   m_ForcedFallbackFormat: 4
   m_DownscaleFallback: 0
-  m_Width: 320
-  m_Height: 120
+  m_Width: 80
+  m_Height: 30
   m_AntiAliasing: 1
   m_DepthFormat: 2
   m_ColorFormat: 0

Notebooks/getting-started.ipynb

     },
     {
      "data": {
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+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Total reward this episode: -699.7999988794327\n"
+      "Total reward this episode: -366.90000158548355\n"
      ]
     },
     {