Coding #71.

joaopauloschuler · Oct 14, 2021 · d2d073a · d2d073a
1 parent b68cb14
commit d2d073a
Showing 1 changed file with 29 additions and 0 deletions.
diff --git a/neural/neuralfit.pas b/neural/neuralfit.pas
@@ -140,12 +140,15 @@   TNeuralFitWithImageBase = class(TNeuralFitBase)
       FHasFlipY: boolean;
       FHasResizing: boolean;
       FColorEncoding: integer;
+      FChannelShiftRate: TNeuralFloat;
     public
       constructor Create(); override;
       destructor Destroy(); override;
       procedure ClassifyImage(pNN: TNNet; pImgInput, pOutput: TNNetVolume);
       procedure EnableDefaultImageTreatment(); virtual;
 
+      // ChannelShiftRate: 0 means no augmentation. 0.1 means 10% of maximum change per channel.
+      property ChannelShiftRate: TNeuralFloat read FChannelShiftRate write FChannelShiftRate;
       property HasImgCrop: boolean read FHasImgCrop write FHasImgCrop;
       property HasMakeGray: boolean read FHasMakeGray write FHasMakeGray;
       property HasFlipX: boolean read FHasFlipX write FHasFlipX;
@@ -468,6 +471,7 @@ constructor TNeuralFitWithImageBase.Create();
   FHasMakeGray := false;
   FColorEncoding := 0;
   FMultipleSamplesAtValidation := false;
+  FChannelShiftRate := 0;
 end;
 
 destructor TNeuralFitWithImageBase.Destroy();
@@ -892,6 +896,8 @@ procedure TNeuralDataLoadingFit.RunNNThread(index, threadnum: integer);
   InitialWeightSum, FinalWeightSum: TNeuralFloat;
   {$ENDIF}
   CropSizeX, CropSizeY: integer;
+  DepthCnt: integer;
+  LocalChannelShiftRate: TNeuralFloat;
 begin
   vInput     := TNNetVolume.Create();
   pOutput    := TNNetVolume.Create();
@@ -952,6 +958,16 @@ procedure TNeuralDataLoadingFit.RunNNThread(index, threadnum: integer);
         vInput.CopyResizing(vInputCopy, vInput.SizeX, vInput.SizeY);
       end;
 
+      if FChannelShiftRate > 0 then
+      begin
+        for DepthCnt := 0 to vInput.Depth - 1 do
+        begin
+          LocalChannelShiftRate := ((random(10000) - 5000) / 5000);
+          LocalChannelShiftRate := 1 + (LocalChannelShiftRate * LocalChannelShiftRate);
+          vInput.MulAtDepth(DepthCnt, LocalChannelShiftRate);
+        end;
+      end;
+
       if (vInput.Depth = 3) then
       begin
         if FHasMakeGray and (Random(1000) > 750) then
@@ -1504,6 +1520,7 @@ constructor TNeuralImageFit.Create();
   FColorEncoding := 0;
   FMultipleSamplesAtValidation := true;
   FTrainingSampleProcessedCnt := TNNetVolume.Create;
+  FChannelShiftRate := 0;
 end;
 
 destructor TNeuralImageFit.Destroy();
@@ -1905,6 +1922,8 @@ procedure TNeuralImageFit.RunNNThread(index, threadnum: integer);
   OutputValue, CurrentLoss: TNeuralFloat;
   LocalHit, LocalMiss: integer;
   LocalTotalLoss, LocalErrorSum: TNeuralFloat;
+  DepthCnt: integer;
+  LocalChannelShiftRate: TNeuralFloat;
 begin
   ImgInput := TNNetVolume.Create();
   ImgInputCp := TNNetVolume.Create();
@@ -1951,6 +1970,16 @@ procedure TNeuralImageFit.RunNNThread(index, threadnum: integer);
         ImgInput.Copy(FImgVolumes[ImgIdx]);
       end;
 
+      if FChannelShiftRate > 0 then
+      begin
+        for DepthCnt := 0 to ImgInput.Depth - 1 do
+        begin
+          LocalChannelShiftRate := ((random(10000) - 5000) / 5000);
+          LocalChannelShiftRate := 1 + (LocalChannelShiftRate * FChannelShiftRate);
+          ImgInput.MulAtDepth(DepthCnt, LocalChannelShiftRate);
+        end;
+      end;
+
       if (ImgInput.Depth = 3) then
       begin
         if FHasMakeGray and (Random(1000) > 750) then