Fix tensor cleanup and orphan event listener (#171)

Closes: #166

Signed-off-by: Justin Georgi <justin.georgi@gmail.com>

Reviewed-on: #171

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)
-          validBoxes = validBoxes.dataSync()
+          resBoxes = await tf.image.nonMaxSuppressionAsync(tBoxes,tScores,10,0.5,.05)
+          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: []