Thorax 0.3.0 test

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

public/models/head/descript.json

@@ -1,10 +1,10 @@
 {
-  "version": "0.2.1-m1",
+  "version": "0.3.0-s1",
   "region": "Thorax",
-  "size": 640,
+  "size": 960,
   "epochs": 1000,
-  "name": "med1",
+  "name": "small1",
   "yolo-version": "8.2.16 docker",
-  "date": "2024-05-16",
+  "date": "2024-05-29",
-  "export": "0.2.1-th"
+  "export": "0.3.0-th"
 }

public/models/head/metadata.yaml

@@ -1,14 +1,14 @@
-description: Ultralytics best model trained on /data/ALVINN/Thorax/Thorax 0.2.1/thorax.yaml
+description: Ultralytics best model trained on /data/ALVINN/Thorax/Thorax 0.3.0/thorax_g.yaml
 author: Ultralytics
 license: AGPL-3.0 https://ultralytics.com/license
-date: '2024-05-28T16:18:09.394705'
+date: '2024-05-29T22:49:38.649823'
 version: 8.1.20
 stride: 32
 task: detect
 batch: 1
 imgsz:
-- 640
+- 960
-- 640
+- 960
 names:
   0: Abdominal diaphragm
   1: Aorta

src/pages/detection-mixin.js

@@ -28,7 +28,8 @@ export default {
       console.time('pre-process')
       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)
+        var gTense = tf.image.rgbToGrayscale(tf.image.resizeBilinear(tf.browser.fromPixels(imageData), [modelWidth, modelHeight])).div(255.0).expandDims(0)
+        return tf.concat([gTense,gTense,gTense],3)
       })
       console.timeEnd('pre-process')