src/pages/camera-mixin.js

@@ -25,12 +25,14 @@ export default {
     },
     closeCamera () {
       this.cameraStream.getTracks().forEach( t => t.stop())
+      this.cameraStream = null
       this.videoAvailable = false
     },
     captureVidFrame() {
       const vidViewer = this.$refs.vid_viewer
       vidViewer.pause()
       let tempCVS = document.createElement('canvas')
+      tempCVS.id = 'temp-video-canvas'
       tempCVS.height = vidViewer.videoHeight || parseInt(vidViewer.style.height)
       tempCVS.width = vidViewer.videoWidth || parseInt(vidViewer.style.width)
       const tempCtx = tempCVS.getContext('2d')

src/pages/detect.vue

@@ -10,7 +10,7 @@
     </f7-navbar>
     <f7-block class="detect-grid">
       <div class="image-container" ref="image_container">
-        <SvgIcon v-if="!imageView && !videoAvailable" :icon="f7route.params.region" fill-color="var(--avn-theme-color)" @click="selectImage" />
+        <SvgIcon v-if="!imageView.src && !videoAvailable" :icon="f7route.params.region" fill-color="var(--avn-theme-color)" @click="selectImage" />
         <div class="vid-container" :style="`display: ${videoAvailable ? 'block' : 'none'}; position: absolute; width: 100%; height: 100%;`">
           <video id="vid-view" ref="vid_viewer" :srcObject="cameraStream" :autoPlay="true" style="width: 100%; height: 100%"></video>
           <f7-button @click="captureVidFrame()" style="position: absolute; bottom: 32px; left: 50%; transform: translateX(-50%); z-index: 3;" fill large>Capture</f7-button>
@@ -120,7 +120,6 @@
   import submitMixin from './submit-mixin'
   import detectionMixin from './detection-mixin'
   import cameraMixin from './camera-mixin'
-import { Conv2DBackpropFilter } from '@tensorflow/tfjs'
 
   export default {
     mixins: [submitMixin, detectionMixin, cameraMixin],
@@ -139,7 +138,7 @@ import { Conv2DBackpropFilter } from '@tensorflow/tfjs'
         activeRegion: 4,
         classesList: [],
         imageLoaded: false,
-        imageView: null,
+        imageView: new Image(),
         imageLoadMode: "environment",
         detecting: false,
         detectPanel: false,
@@ -300,7 +299,7 @@ import { Conv2DBackpropFilter } from '@tensorflow/tfjs'
           this.videoAvailable = await this.openCamera(this.$refs.image_container)
           if (this.videoAvailable) {
             this.imageLoaded = false
-            this.imageView = null
+            this.imageView.src = null
             this.$refs.image_cvs.style['background-image'] = 'none'
             this.resultData = {}
             var trackDetails = this.cameraStream.getVideoTracks()[0].getSettings()
@@ -384,11 +383,11 @@ import { Conv2DBackpropFilter } from '@tensorflow/tfjs'
             this.detecting = true
             resolve('data:image/jpg;base64,' + searchImage)
           }
-          var reader = new FileReader()
+          const reader = new FileReader()
           reader.addEventListener("load", () => {
             this.detecting = true
             resolve(reader.result)
-          })
+          },{once: true})
           if (this.imageLoadMode == 'sample') {
             fetch(`${this.isCordova ? 'https://localhost' : '.'}/samples/${this.detectorName}-${searchImage}.jpeg`).then( resp => {
               return resp.blob()
@@ -408,7 +407,6 @@ import { Conv2DBackpropFilter } from '@tensorflow/tfjs'
           this.imageLoaded = true
           this.resultData = {}
           this.selectedChip = -1
-          this.imageView = new Image()
           this.imageView.src = imgData
           return(this.imageView.decode())
         }).then( () => {

src/pages/detection-mixin.js

@@ -1,7 +1,7 @@
 import * as tf  from '@tensorflow/tfjs'
 import { f7 } from 'framework7-vue'
 
-var model = null
+let model = null
 
 export default {
   methods: {
@@ -9,7 +9,7 @@ export default {
       if (model && model.modelURL == weights) {
         return model
       } else if (model) {
-        model.dispose()
+        tf.dispose(model)
       }
       model = await tf.loadGraphModel(weights)
       const [modelWidth, modelHeight] = model.inputs[0].shape.slice(1, 3)
@@ -34,7 +34,8 @@ export default {
 
       console.time('run prediction')
       const res = model.predict(input)
-      const rawRes = tf.transpose(res,[0,2,1]).arraySync()[0]
+      const tRes = tf.transpose(res,[0,2,1])
+      const rawRes = tRes.arraySync()[0]
       console.timeEnd('run prediction')
 
       console.time('post-process')
@@ -59,6 +60,8 @@ export default {
       if (rawBoxes.length > 0) {
         const tBoxes = tf.tensor2d(rawBoxes)
         let tScores = null
+        let resBoxes = null
+        let validBoxes = []
         let structureScores = null
         let boxes_data = []
         let scores_data = []
@@ -66,8 +69,9 @@ export default {
         for (var c = 0; c < outputSize - 4; c++) {
           structureScores = rawScores.map(x => x[c])
           tScores = tf.tensor1d(structureScores)
-          var validBoxes = await tf.image.nonMaxSuppressionAsync(tBoxes,tScores,10,0.5,.05)
+          resBoxes = await tf.image.nonMaxSuppressionAsync(tBoxes,tScores,10,0.5,.05)
-          validBoxes = validBoxes.dataSync()
+          validBoxes = resBoxes.dataSync()
+          tf.dispose(resBoxes)
           if (validBoxes) {
             boxes_data.push(...rawBoxes.filter( (_, idx) => validBoxes.includes(idx)))
             var outputScores = structureScores.filter( (_, idx) => validBoxes.includes(idx))
@@ -76,8 +80,10 @@ export default {
           }
         }
 
+        validBoxes = []
         tf.dispose(tBoxes)
         tf.dispose(tScores)
+        tf.dispose(tRes)
         const valid_detections_data = classes_data.length
         var output = {
           detections: []