From b09cff2a2bc49ba13621a3412cf3fcbb92764667 Mon Sep 17 00:00:00 2001
From: Justin Georgi <justin.georgi@gmail.com>
Date: Tue, 19 Mar 2024 15:14:17 -0700
Subject: [PATCH] Clean up new video code

Signed-off-by: Justin Georgi <justin.georgi@gmail.com>
---
 src/pages/camera-mixin.js    | 20 --------------------
 src/pages/detection-mixin.js |  7 ++++---
 2 files changed, 4 insertions(+), 23 deletions(-)

diff --git a/src/pages/camera-mixin.js b/src/pages/camera-mixin.js
index c801246..f04e288 100644
--- a/src/pages/camera-mixin.js
+++ b/src/pages/camera-mixin.js
@@ -1,5 +1,3 @@
-import * as tf  from '@tensorflow/tfjs'
-
 export default {
   methods: {
     async openCamera(imContain) {
@@ -38,24 +36,6 @@ export default {
       const tempCtx = tempCVS.getContext('2d')
       tempCtx.drawImage(vidViewer, 0, 0)
       this.getImage(tempCVS.toDataURL())
-    },
-    async videoStream () {
-      const vidElement = this.$refs.vid_viewer
-      this.videoAvailable = false
-      const devicesList = await navigator.mediaDevices.enumerateDevices()
-      this.videoDeviceAvailable = devicesList.some( d => d.kind == "videoinput")
-      if (this.videoDeviceAvailable) {
-        var vidConstraint = {
-          //resizeWidth: 640,
-          //resizeHeight: 640,
-          facingMode: 'environment'
-          }
-        tf.data.webcam(vidElement, vidConstraint).then( webData => {
-          this.videoAvailable = true
-          this.cameraStream = vidElement.captureStream()
-          this.videoFrameDetect(webData)
-        })
-      }
     }
   }
 }
\ No newline at end of file
diff --git a/src/pages/detection-mixin.js b/src/pages/detection-mixin.js
index 7de057a..c3f6129 100644
--- a/src/pages/detection-mixin.js
+++ b/src/pages/detection-mixin.js
@@ -1,7 +1,5 @@
 import * as tf  from '@tensorflow/tfjs'
-import { image } from '@tensorflow/tfjs'
 import { f7 } from 'framework7-vue'
-import { nextTick } from 'vue'
 
 var model = null
 
@@ -11,7 +9,10 @@ export default {
       model = await tf.loadGraphModel(weights)
       const [modelWidth, modelHeight] = model.inputs[0].shape.slice(1, 3)
       const dummyT = tf.ones([1,modelWidth,modelHeight,3])
-      model.predict(dummyT) //Run model once to preload weights for better response time
+      /*****************
+       * Run model once to preload weights for better response time
+       *****************/
+      model.predict(dummyT)
       return model
     },
     async localDetect(imageData) {