diff --git a/src/assets/detect-worker.js b/src/assets/detect-worker.js
index f220559..bc23adc 100644
--- a/src/assets/detect-worker.js
+++ b/src/assets/detect-worker.js
@@ -57,7 +57,7 @@ async function loadModel(weights, preload) {
 }
 
 async function localDetect(imageData) {
-  console.time('pre-process')
+  console.time('sw: pre-process')
   const [modelWidth, modelHeight] = model.inputs[0].shape.slice(1, 3)
   let gTense = null
   const input = tf.tidy(() => {
@@ -65,15 +65,15 @@ async function localDetect(imageData) {
     return tf.concat([gTense,gTense,gTense],3)
   })
   tf.dispose(gTense)
-  console.timeEnd('pre-process')
+  console.timeEnd('sw: pre-process')
 
-  console.time('run prediction')
+  console.time('sw: run prediction')
   const res = model.predict(input)
   const tRes = tf.transpose(res,[0,2,1])
   const rawRes = tRes.arraySync()[0]
-  console.timeEnd('run prediction')
+  console.timeEnd('sw: run prediction')
 
-  console.time('post-process')
+  console.time('sw: post-process')
   const outputSize = res.shape[1]
   let rawBoxes = []
   let rawScores = []
@@ -138,14 +138,14 @@ async function localDetect(imageData) {
   }
   tf.dispose(res)
   tf.dispose(input)
-  console.timeEnd('post-process')
+  console.timeEnd('sw: post-process')
 
   return output || { detections: [] }
 }
 
 async function videoFrame (vidData) {
   const [modelWidth, modelHeight] = model.inputs[0].shape.slice(1, 3)
-  console.time('frame-process')
+  console.time('sw: frame-process')
   let rawCoords = []
   try {
     const input = tf.tidy(() => {
@@ -171,6 +171,6 @@ async function videoFrame (vidData) {
   } catch (e) {
     console.log(e)
   }
-  console.timeEnd('frame-process')
+  console.timeEnd('sw: frame-process')
   return {cds: rawCoords, mW: modelWidth, mH: modelHeight}
 }
\ No newline at end of file
diff --git a/src/pages/camera-mixin.js b/src/pages/camera-mixin.js
index 412c1e8..8df69ec 100644
--- a/src/pages/camera-mixin.js
+++ b/src/pages/camera-mixin.js
@@ -41,7 +41,7 @@ export default {
       tempCtx.drawImage(vidViewer, 0, 0)
       this.getImage(tempCVS.toDataURL())
     },
-    async videoFrameDetect (vidData) {
+    async videoFrameDetectWorker (vidData) {
       const startDetection = () => {
         createImageBitmap(vidData).then(imVideoFrame => {
           this.vidWorker.postMessage({call: 'videoFrame', image: imVideoFrame}, [imVideoFrame])
diff --git a/src/pages/detect.vue b/src/pages/detect.vue
index 34806a9..952ba2c 100644
--- a/src/pages/detect.vue
+++ b/src/pages/detect.vue
@@ -337,22 +337,39 @@
 
         let loadSuccess = null
         let loadFailure = null
-        let modelReloading = new Promise((res, rej) => {
-          loadSuccess = res
-          loadFailure = rej
-          if (this.reloadModel) {
-            this.detectWorker.postMessage({call: 'loadModel', weights: this.modelLocation})
-          } else {
-            loadSuccess()
-          }
-        })
+        let modelReloading = null
+        if (this.isSafari && this.reloadModel) {
+          await this.loadModel(this.modelLocation)
+          this.reloadModel = false          
+        } else {
+          modelReloading = new Promise((res, rej) => {
+            loadSuccess = res
+            loadFailure = rej
+            if (this.reloadModel) {
+              this.detectWorker.postMessage({call: 'loadModel', weights: this.modelLocation})
+            } else {
+              loadSuccess()
+            }
+          })
+        }
 
         if (this.serverSettings && this.serverSettings.use) {
           this.remoteDetect()
-        } else {
+        } else if (!this.isSafari) {
           Promise.all([modelReloading,createImageBitmap(this.imageView)]).then(res => {
             this.detectWorker.postMessage({call: 'localDetect', image: res[1]}, [res[1]])
           })
+        } else {
+          this.localDetect(this.imageView).then(dets => {
+            this.detecting = false
+            this.resultData = dets
+            this.uploadDirty = true
+          }).catch((e) => {
+            console.log(e.message)
+            this.detecting = false
+            this.resultData = {}
+            f7.dialog.alert(`ALVINN structure finding error: ${e.message}`)
+          })
         }
       },
       selectAll (ev) {
@@ -368,7 +385,7 @@
           navigator.camera.getPicture(this.getImage, this.onFail, { quality: 50, destinationType: Camera.DestinationType.DATA_URL, correctOrientation: true });
           return
         }
-        if (mode == "camera") {
+        if (mode == "camera" && !this.otherSettings.disableVideo) {
           this.videoAvailable = await this.openCamera(this.$refs.image_container)
           if (this.videoAvailable) {
             this.selectedChip = -1
@@ -380,8 +397,10 @@
             var vidElement = this.$refs.vid_viewer
             vidElement.width = trackDetails.width
             vidElement.height = trackDetails.height
-            if (!this.otherSettings.disableVideo) {
+            if (this.isSafari) {
               this.videoFrameDetect(vidElement)
+            } else {
+              this.videoFrameDetectWorker(vidElement)
             }
             return
           }
diff --git a/src/pages/detection-mixin.js b/src/pages/detection-mixin.js
index d0b7197..6cb7b77 100644
--- a/src/pages/detection-mixin.js
+++ b/src/pages/detection-mixin.js
@@ -25,7 +25,7 @@ export default {
       return model
     },
     async localDetect(imageData) {
-      console.time('pre-process')
+      console.time('mx: pre-process')
       const [modelWidth, modelHeight] = model.inputs[0].shape.slice(1, 3)
       let gTense = null
       const input = tf.tidy(() => {
@@ -33,15 +33,15 @@ export default {
         return tf.concat([gTense,gTense,gTense],3)
       })
       tf.dispose(gTense)
-      console.timeEnd('pre-process')
+      console.timeEnd('mx: pre-process')
 
-      console.time('run prediction')
+      console.time('mx: run prediction')
       const res = model.predict(input)
       const tRes = tf.transpose(res,[0,2,1])
       const rawRes = tRes.arraySync()[0]
-      console.timeEnd('run prediction')
+      console.timeEnd('mx: run prediction')
 
-      console.time('post-process')
+      console.time('mx: post-process')
       const outputSize = res.shape[1]
       let rawBoxes = []
       let rawScores = []
@@ -105,7 +105,7 @@ export default {
       }
       tf.dispose(res)
       tf.dispose(input)
-      console.timeEnd('post-process')
+      console.timeEnd('mx: post-process')
 
       return output || { detections: [] }
     },
@@ -194,7 +194,7 @@ export default {
         imgHeight = imCanvas.height
       }
       while (this.videoAvailable) {
-        console.time('frame-process')
+        console.time('mx: frame-process')
         try {
           const input = tf.tidy(() => {
             return tf.image.resizeBilinear(tf.browser.fromPixels(vidData), [modelWidth, modelHeight]).div(255.0).expandDims(0)
@@ -228,7 +228,7 @@ export default {
         } catch (e) {
           console.log(e)
         }
-        console.timeEnd('frame-process')
+        console.timeEnd('mx: frame-process')
         await tf.nextFrame();
       }
     }