diff --git a/public/plugins/ufish.imjoy.html b/public/plugins/ufish.imjoy.html
index add189b..1229026 100644
--- a/public/plugins/ufish.imjoy.html
+++ b/public/plugins/ufish.imjoy.html
@@ -121,7 +121,8 @@
         )
         self.image = None
 
-    def load_image_from_bytes(self, file_name, img_bytes):
+    @staticmethod
+    def load_image_from_bytes(file_name, img_bytes):
         _file = io.BytesIO(img_bytes)
         _file.name = file_name
         if file_name.endswith(".tif") or file_name.endswith(".tiff"):
@@ -134,24 +135,18 @@
             image = image.squeeze()
         else:
             image = imageio.imread(_file)
-        self.image = image
         return image
 
-    def save_image_to_bytes(self, image):
+    @staticmethod
+    def save_image_to_bytes(image):
         _file = io.BytesIO()
         with tifffile.TiffWriter(_file) as tif:
             tif.save(image)
         return _file.getvalue()
 
-    async def predict_2d(self, image):
-        image = scale_image(image)
-        enh_img = await self.onnx_runner.infer_2d(image)
-        df = call_spots_local_maxima(enh_img)
-        coords = df.values
-        return enh_img, coords
-
     async def view_img_from_bytes(self, file_name, bytes_):
         image = self.load_image_from_bytes(file_name, bytes_)
+        self.image = image
         await self.viewer.view_image(image, name=file_name)
         return image.shape
 
diff --git a/src/main.ts b/src/main.ts
index d7b26d1..c8b5ce0 100644
--- a/src/main.ts
+++ b/src/main.ts
@@ -12,6 +12,7 @@ import * as directives from 'vuetify/directives'
 import App from './App.vue'
 import router from './router'
 import { isPluginMode } from './utils'
+import { useRunStore } from './stores/run'
 
 window.app = {}
 window.app.router = router
@@ -34,11 +35,15 @@ async function createApi() {
     console.log("U-FISH is ready.")
   }
 
+  async function run() {
+    const runStore = useRunStore()
+    await runStore.run()
+  }
+
   return {
+    "run": async () => {},
     "setup": setup,
-    "run": () => {
-      console.log("run")
-    },
+    "runPredict": run,
   }
 }
 
@@ -50,6 +55,7 @@ async function initImJoy() {
     window.app.imjoy_api = imjoy_api;
     const ufish = await createApi();
     window.app.ufish = ufish;
+    router.push("/predict")
     await imjoy_api.export(ufish)
   } else {
     // start as an standalone app
diff --git a/src/stores/run.ts b/src/stores/run.ts
index ae42cfc..4d9a29d 100644
--- a/src/stores/run.ts
+++ b/src/stores/run.ts
@@ -26,6 +26,9 @@ export const useRunStore = defineStore("run", {
       await waitRunable();
       this.queryCount += 1;
       await waitRunable();
+    },
+    setRunable(runable: boolean) {
+      this.runable = runable;
     }
   }
 }) 
\ No newline at end of file
diff --git a/src/views/PredictView.vue b/src/views/PredictView.vue
index 1f554e6..25289ed 100644
--- a/src/views/PredictView.vue
+++ b/src/views/PredictView.vue
@@ -33,7 +33,8 @@
 <script lang="ts">
 import * as ort from 'onnxruntime-web';
 import { getImjoyApi, isPluginMode, downloadBlob } from '@/utils';
-import { ref, onMounted } from 'vue';
+import { ref, onMounted, watch } from 'vue';
+import { useRunStore } from '@/stores/run';
 
 export default {
   setup() {
@@ -45,6 +46,8 @@ export default {
     const runInfoText = ref("loading...")
     const hasError = ref(false)
 
+    const runStore = useRunStore()
+
     async function loadPlugin() {
       const imjoy_api = await getImjoyApi()
       imjoy_api.log("Hello from Imjoy!")
@@ -83,6 +86,7 @@ export default {
       const plugP = loadPlugin()
       plugP.then(() => {
         runInfoText.value = "Plugin loaded"
+        runStore.setRunable(true)
       })
       plugP.catch((e) => {
         runInfoText.value = "Failed to load plugin, see console for more detail."
@@ -99,12 +103,12 @@ export default {
 
     async function run() {
       running.value = true
-      const sImg = await plugin.value.scale_image()
-      const f32data = new Float32Array(sImg._rvalue)
-      const input = new ort.Tensor(
-        sImg._rdtype, f32data, sImg._rshape);
       let output;
       try {
+        const sImg = await plugin.value.scale_image()
+        const f32data = new Float32Array(sImg._rvalue)
+        const input = new ort.Tensor(
+        sImg._rdtype, f32data, sImg._rshape);
         output = await infer_2d(input)
         const outImg = {
           _rtype: "ndarray",
@@ -128,6 +132,17 @@ export default {
       }
     }
 
+    watch(() => runStore.queryCount, async () => {
+      if (runStore.queryCount > 0) {
+        console.log('running from store')
+        await run()
+      }
+    })
+
+    watch(() => running.value, () => {
+      runStore.setRunable(!running.value)
+    })
+
     return {
       plugin,
       run,