Update thorax model and improve model performance

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

src/css/detect.css

@@ -3,7 +3,7 @@
 .detect-grid {
   display: grid;
   grid-template-columns: 1fr;
-  grid-template-rows: 1fr 56px auto min-content;
+  grid-template-rows: 1fr minmax(calc(var(--f7-chip-height) + 33px), auto) auto min-content;
   grid-template-areas: 
     "image-view"
     "result-view"
@@ -51,6 +51,7 @@
   --f7-chip-media-size: 32px;
   --f7-chip-font-weight: normal;
   overflow-y: auto;
+  overflow-x: hidden;
   max-height: 100%;
 }
 
@@ -58,6 +59,10 @@
   padding-left: 8px;
 }
 
+.progress-hide {
+  display: hidden;
+}
+
 .selected-chip {
   font-weight: 500;
   box-shadow: 4px 4px 1px var(--avn-theme-color);

src/models/thorax/metadata.yaml

@@ -1,14 +1,14 @@
 description: Ultralytics best model trained on /data/ALVINN/Thorax/Thorax 0.1.0/thorax.yaml
 author: Ultralytics
 license: AGPL-3.0 https://ultralytics.com/license
-date: '2024-03-05T17:01:14.129654'
+date: '2024-03-07T16:03:03.296997'
 version: 8.1.20
 stride: 32
 task: detect
 batch: 1
 imgsz:
-- 992
+- 640
-- 992
+- 640
 names:
   0: Abdominal diaphragm
   1: Aorta

src/pages/detect.vue

@@ -13,7 +13,7 @@
           <f7-button @click="captureVidFrame()" style="position: absolute; bottom: 32px; left: 50%; transform: translateX(-50%);" fill>Capture</f7-button>
         </div>
       </div>
-      <div v-if="(resultData && resultData.detections) || detecting" class="chip-results" style="grid-area: result-view; flex: 0 0 auto; align-self: center;">
+      <div class="chip-results" style="grid-area: result-view; flex: 0 0 auto; align-self: center;">
         <f7-chip v-for="result in showResults.filter( r => { return r.aboveThreshold && r.isSearched && !r.isDeleted })"
           :class="(result.resultIndex == selectedChip) ? 'selected-chip' : ''"
           :text="result.label"
@@ -24,8 +24,8 @@
           @delete="deleteChip(result.resultIndex)"
           :style="chipGradient(result.confidence)"
         />
-        <span v-if="numResults == 0 && !detecting" style="height: var(--f7-chip-height); font-size: calc(var(--f7-chip-height) - 4px); font-weight: bolder; margin: 2px;">No results.</span>
+        <div v-if="!numResults" style="height: var(--f7-chip-height); width: 100%; text-align: center; font-size: calc(var(--f7-chip-height) - 4px); font-weight: bolder; margin: 2px;">{{  message }}</div>
-        <f7-preloader v-if="detecting || modelLoading" size="32" style="color: var(--avn-theme-color);" />
+        <f7-progressbar v-if="(detecting || modelLoading)" style="width: 100%;" :infinite="true" />
       </div>
       <div v-if="showDetectSettings" class="detect-inputs" style="grid-area: detect-settings;">
         <f7-range class="level-slide-horz" :min="0" :max="100" :step="1" @range:change="onLevelChange" v-model:value="detectorLevel" type="range" style="flex: 1 1 100%"/>
@@ -41,7 +41,7 @@
         <f7-button popover-open="#region-popover">
           <RegionIcon :region="activeRegion" />
         </f7-button>
-        <f7-button popover-open="#capture-popover">
+        <f7-button :class="(!modelLoading) ? '' : 'disabled'" popover-open="#capture-popover">
           <SvgIcon icon="camera_add"/>
         </f7-button>
         <f7-button @click="() => showDetectSettings = !showDetectSettings" :class="(imageLoaded) ? '' : 'disabled'">
@@ -144,7 +144,7 @@
         uploadUid: null,
         uploadDirty: false,
         modelLocation: '',
-        modelLoading: false,
+        modelLoading: true,
         videoDeviceAvailable: false,
         videoAvailable: false,
         cameraStream: null
@@ -179,8 +179,11 @@
       }
       var loadServerSettings = localStorage.getItem('serverSettings')
       if (loadServerSettings) this.serverSettings = JSON.parse(loadServerSettings)
+    },
+    mounted () {
       if (this.serverSettings && this.serverSettings.use) {
         this.getRemoteLabels()
+        this.modelLoading = false
       } else {
         this.modelLoading = true
         this.detectorLabels = this.classesList.map( l => { return {'name': l, 'detect': true} } )
@@ -189,11 +192,23 @@
         }).catch((e) => {
           console.log(e.message)
           f7.dialog.alert(`ALVINN AI model error: ${e.message}`)
+          this.modelLoading = false
         })
       }
       window.onresize = (e) => { this.selectChip('redraw') }
     },
     computed: {
+      message () {
+        if (this.modelLoading) {
+          return "Preparing ALVINN..."
+        } else if (this.detecting) {
+          return "Finding structures..."
+        } else if (this.numResults == 0 && this.imageLoaded) {
+          return "No results."
+        } else {
+          return "ALVINN is ready."
+        }
+      },
       showResults () {
         var filteredResults = this.resultData.detections
         if (!filteredResults) return []

src/pages/detection-mixin.js

@@ -1,18 +1,22 @@
 import * as tf  from '@tensorflow/tfjs'
 import { f7 } from 'framework7-vue'
+import { nextTick } from 'vue'
 
 var model = null
 
 export default {
   methods: {
     async loadModel(weights) {
-      model = await tf.loadGraphModel(weights).then(graphModel => {
+      await nextTick()
-        return graphModel
+      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
+      return model
+    },
     async localDetect(imageData) {
       console.time('pre-process')
-      const [modelWidth, modelHeight] = model.inputs[0].shape.slice(1, 3);
+      const [modelWidth, modelHeight] = model.inputs[0].shape.slice(1, 3)
       const input = tf.tidy(() => {
         return tf.image.resizeBilinear(tf.browser.fromPixels(imageData), [modelWidth, modelHeight]).div(255.0).expandDims(0)
       })