change more arraySync

src/ssdMobilenetv1/SsdMobilenetv1.ts

@@ -85,15 +85,16 @@ export class SsdMobilenetv1 extends NeuralNetwork<NetParams> {
     const padX = inputSize / reshapedDims.width
     const padY = inputSize / reshapedDims.height
 
+    const boxesData = boxes.arraySync()
     const results = indices
       .map(idx => {
         const [top, bottom] = [
-          Math.max(0, boxes.arraySync()[idx][0]),
-          Math.min(1.0, boxes.arraySync()[idx][2])
+          Math.max(0, boxesData[idx][0]),
+          Math.min(1.0, boxesData[idx][2])
         ].map(val => val * padY)
         const [left, right] = [
-          Math.max(0, boxes.arraySync()[idx][1]),
-          Math.min(1.0, boxes.arraySync()[idx][3])
+          Math.max(0, boxesData[idx][1]),
+          Math.min(1.0, boxesData[idx][3])
         ].map(val => val * padX)
         return new FaceDetection(
           scoresData[idx],

src/ssdMobilenetv1/nonMaxSuppression.ts

@@ -49,14 +49,15 @@ export function nonMaxSuppression(
 }
 
 function IOU(boxes: tf.Tensor2D, i: number, j: number) {
-  const yminI = Math.min(boxes.arraySync()[i][0], boxes.arraySync()[i][2])
-  const xminI = Math.min(boxes.arraySync()[i][1], boxes.arraySync()[i][3])
-  const ymaxI = Math.max(boxes.arraySync()[i][0], boxes.arraySync()[i][2])
-  const xmaxI = Math.max(boxes.arraySync()[i][1], boxes.arraySync()[i][3])
-  const yminJ = Math.min(boxes.arraySync()[j][0], boxes.arraySync()[j][2])
-  const xminJ = Math.min(boxes.arraySync()[j][1], boxes.arraySync()[j][3])
-  const ymaxJ = Math.max(boxes.arraySync()[j][0], boxes.arraySync()[j][2])
-  const xmaxJ = Math.max(boxes.arraySync()[j][1], boxes.arraySync()[j][3])
+  const boxesData = boxes.arraySync()
+  const yminI = Math.min(boxesData[i][0], boxesData[i][2])
+  const xminI = Math.min(boxesData[i][1], boxesData[i][3])
+  const ymaxI = Math.max(boxesData[i][0], boxesData[i][2])
+  const xmaxI = Math.max(boxesData[i][1], boxesData[i][3])
+  const yminJ = Math.min(boxesData[j][0], boxesData[j][2])
+  const xminJ = Math.min(boxesData[j][1], boxesData[j][3])
+  const ymaxJ = Math.max(boxesData[j][0], boxesData[j][2])
+  const xmaxJ = Math.max(boxesData[j][1], boxesData[j][3])
   const areaI = (ymaxI - yminI) * (xmaxI - xminI)
   const areaJ = (ymaxJ - yminJ) * (xmaxJ - xminJ)
   if (areaI <= 0 || areaJ <= 0) {