fix optimized bwlabel, bump tfjs to current (4.18)

brainchop.js

@@ -1682,12 +1682,7 @@ async function inferenceFullVolumeSeqCovLayerPhase2(
         const seqConvLayer = await new SequentialConvLayer(res, 10, isChannelLast, callbackUI)
 
         // Apply the last output tensor to the seq. instance
-        let outputTensor = null
-        const profileInfo = await tf.profile(async () => {
-          // Your tensor operations here
-          outputTensor = await seqConvLayer.apply(curTensor[i])
-        })
-        console.log('profileInfo : ', profileInfo)
+        let outputTensor = await seqConvLayer.apply(curTensor[i])
 
         // -- document.getElementById("progressBarChild").style.width = 0 + "%";;
 
@@ -2048,7 +2043,6 @@ async function inferenceFullVolumePhase2(
     // ???? subsequent await are required
     const timer = window.setInterval(async function () {
       try {
-        // -- curTensor[i] = res.layers[i].apply( curTensor[i-1])
         curTensor[i] = res.layers[i].apply(curTensor[i - 1])
       } catch (err) {
         callbackUI(err.message, -1, err.message)
@@ -2082,10 +2076,6 @@ async function inferenceFullVolumePhase2(
       if (i === layersLength - 1) {
         window.clearInterval(timer)
 
-        // prediction = res.layers[res.layers.length-1].apply(curTensor[i])
-        // curTensor[i].print()
-        // outputDataBeforArgmx = Array.from(curTensor[i].dataSync())
-
         const axis = isChannelLast ? -1 : 1
         console.log(' find argmax ')
         console.log('last Tensor shape : ', curTensor[i].shape)

bwlabels.js

@@ -80,8 +80,8 @@ export class BWLabeler {
 
   // provisionally label all voxels in volume
   do_initial_labelling(bw, dim, conn) {
-    const naboPS = new Uint32Array(27)
-    const tn = new Uint32Array(27 + 5)
+    const naboPS = new Uint32Array(32)
+    const tn = new Uint32Array(32)
     let label = 1
     const kGrowArrayBy = 8192
     let ttn = kGrowArrayBy
@@ -157,19 +157,20 @@ export class BWLabeler {
 
   // translation table unifies a region that has been assigned multiple classes
   fill_tratab(tt, nabo, nr_set, tn) {
-    let cntr = 0
+    // let cntr = 0
+    tn.fill(0)
     const INT_MAX = 2147483647
     let ltn = INT_MAX
     for (let i = 0; i < nr_set; i++) {
       let j = nabo[i]
-      cntr = 0
+      // cntr = 0
       while (tt[j - 1] !== j) {
         j = tt[j - 1]
-        cntr++
+        /* cntr++
         if (cntr > 100) {
           console.log('\nOoh no!!')
           break
-        }
+        } */
       }
       tn[i] = j
       ltn = Math.min(ltn, j)

main.js

@@ -13,7 +13,6 @@ async function main() {
   nv1.opts.multiplanarForceRender = true
   nv1.opts.yoke3Dto2DZoom = true
   await nv1.loadVolumes([{ url: "./t1_crop.nii.gz" }])
-
   aboutBtn.onclick = function () {
     window.alert("BrainChop models https://github.com/neuroneural/brainchop")
   }
@@ -32,14 +31,18 @@ async function main() {
     nv1.removeVolume(nv1.volumes[0])
     nv1.addVolume(nii2)
   }
-
+  async function closeAllOverlays() {
+    while (nv1.volumes.length > 1) {
+      await nv1.removeVolume(nv1.volumes[1])
+    }
+  }
   modelSelect.onchange = async function () {
+    await closeAllOverlays()
     await ensureConformed()
     let model = inferenceModelsList[this.selectedIndex]
     let opts = brainChopOpts
     runInference(opts, model, nv1.volumes[0].hdr, nv1.volumes[0].img, callbackImg, callbackUI)
   }
-
   saveBtn.onclick = function () {
     nv1.volumes[1].saveToDisk("Custom.nii")
   }
@@ -49,9 +52,7 @@ async function main() {
     return js
   }
   async function callbackImg(img, opts, modelEntry) {
-    while (nv1.volumes.length > 1) {
-      await nv1.removeVolume(nv1.volumes[1])
-    }
+    closeAllOverlays()
     let overlayVolume = await nv1.volumes[0].clone()
     overlayVolume.zeroImage()
     overlayVolume.hdr.scl_inter = 0

package.json

@@ -10,7 +10,7 @@
   },
   "dependencies": {
     "@niivue/niivue":"^0.42.0",
-    "@tensorflow/tfjs": "3.9.0",
+    "@tensorflow/tfjs": "^4.18.0",
     "gl-matrix": "^3.4.3"
   },
   "devDependencies": {