Object detection

[warthecatalyst]

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This PR is about my current progress on Object Detection work. Currently, I think I've successfully built the network structure of YOLOv3 and get started with loss function

[warthecatalyst]

emm,this is just a test pr for my mentor Zack to get a view on my current progress and make suggestions

At 2022-08-29 13:50:35, "Frank Liu" @.***> wrote:

@frankfliu commented on this pull request.

In api/src/main/java/ai/djl/training/loss/SingleShotDetectionLoss.java:

@@ -48,6 +48,8 @@ public SingleShotDetectionLoss() { @Override protected Pair<NDList, NDList> inputForComponent( int componentIndex, NDList labels, NDList predictions) {

•    System.out.println(labels.singletonOrThrow());  //print labels for test
  

Remove testing code

In api/src/main/java/ai/djl/training/loss/YOLOv3Loss.java:

@@ -0,0 +1,275 @@ +package ai.djl.training.loss;

Add license header

In api/src/main/java/ai/djl/training/loss/YOLOv3Loss.java:

+import ai.djl.modality.cv.output.Rectangle; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDArrays; +import ai.djl.ndarray.NDList; +import ai.djl.ndarray.NDManager; +import ai.djl.ndarray.index.NDIndex; +import ai.djl.ndarray.types.DataType; +import ai.djl.ndarray.types.Shape; +import ai.djl.nn.Activation; +import ai.djl.util.Pair; +import ai.djl.util.PairList;

+import java.util.ArrayList; +import java.util.Arrays; + +public class YOLOv3Loss extends Loss{

./gradlew formatJava

In api/src/main/java/ai/djl/training/loss/YOLOv3Loss.java:

•            boxBTrue.get(":,2:").expandDims(0).broadcast(A,B,2));
  

•    NDArray minXY = NDArrays.maximum(boxATrue.get(":,:2").expandDims(1).broadcast(A,B,2),
  

•            boxBTrue.get(":,:2").expandDims(0).broadcast(A,B,2));
  

•    NDArray inter = NDArrays.minimum(maxXY.sub(minXY),0);
  

•    inter = inter.get(":,:,0").mul(inter.get(":,:,1"));
  

•    //to calculate the area of prediction bbox and true bbox
  

•    NDArray areaA = boxATrue.get(":,2").sub(boxATrue.get(":,0")).mul(boxATrue.get(":,3").sub(boxATrue.get(":,1"))).expandDims( 1).broadcast(inter.getShape()),
  

•            areaB = boxBTrue.get(":,2").sub(boxBTrue.get(":,0")).mul(boxBTrue.get(":,3").sub(boxBTrue.get(":,1"))).expandDims( 0).broadcast(inter.getShape());
  

•    NDArray union = areaA.add(areaB).sub(inter);
  

•    return inter.div(union);
  

• }
• public ArrayList<PairList<Long,Rectangle>> getTargetFromCurrentLabel(NDArray labels){

Use List instead of ArrayList in function declaration

In api/src/main/java/ai/djl/training/loss/YOLOv3Loss.java:

•                float interHeight = Math.min(trueBottom,predBottom)-Math.max(trueTop,predTop);
  

•                float inter = interWidth*interHeight, union = wgt.get(i).getFloat()*inW*hgt.get(i).getFloat()*inH
  

•                        + anchors.get(j,0).getFloat()*anchors.get(j,1).getFloat()-inter;
  

•                iou.set(new NDIndex(curIndex),inter/union);
  

•            }
  

•        }
  

•        return new NDList(iou,boxLossScale,groundTruth);
  

•    }
  

•    return null;
  

• }
• //calculate IOU is already defined in Rectangle
• public NDArray calculateIOU(NDArray boxA,NDArray boxB){

javadoc

In examples/src/main/java/ai/djl/examples/training/TrainPikachu.java:

@@ -87,7 +87,7 @@ public static TrainingResult runExample(String[] args) throws IOException, Trans try (Trainer trainer = model.newTrainer(config)) { trainer.setMetrics(new Metrics());

•            Shape inputShape = new Shape(arguments.getBatchSize(), 3, 256, 256);
  

•            Shape inputShape = new Shape(1, 3, 256, 256);
  

Why?

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