CellPoseDemo.imjoy.html

<docs lang="markdown">
[TODO: write documentation for this plugin.]
</docs>

<config lang="json">
{
  "name": "CellPoseDemo",
  "type": "web-python",
  "version": "0.1.0",
  "description": "A demo plugin for running cell-pose segmentation",
  "tags": [],
  "ui": "",
  "cover": "",
  "inputs": null,
  "outputs": null,
  "flags": [],
  "icon": "extension",
  "api_version": "0.1.8",
  "env": "",
  "permissions": [],
  "requirements": ["pyotritonclient", "kaibu-utils"],
  "dependencies": []
}
</config>

<script lang="python">
import io
import numpy as np
from pyotritonclient import execute
from kaibu_utils import fetch_image
from imjoy import api

class ImJoyPlugin():
    async def setup(self):
        image = await fetch_image('https://static.imjoy.io/img/img02.png')
        image = image.astype('float32')
        print("example image downloaded: ", image.shape)
        self.image = image

    async def run(self, ctx):
        viewer = await api.createWindow(src="https://kaibu.org/#/app")
        
        await viewer.view_image(self.image.astype('uint8'), type="itk-vtk", name="input-image")
        
        async def form_submit_callback(fields):
            diameter = int(fields['Diameter'])
            await viewer.set_loader(True)
            try:
                # run inference
                param = {'diameter': diameter, 'model_type': 'cyto'}
                results = await execute([self.image.transpose(2, 0, 1), param],
                                              server_url='https://hypha.imjoy.io/triton',
                                              model_name='cellpose-python',
                                              decode_bytes=True)
                mask = results['mask']
                await viewer.view_image(mask, type="itk-vtk", name="output-mask", opacity=0.4)
                await api.showMessage('cellpose prediction completed!')
            except Exception as exp:
                await api.alert("Failed to run prediction: " + str(exp))
            finally:
                await viewer.set_loader(False)

        await viewer.add_widget(
            {
                "_rintf": True,
                "name": "CellPose Segmentation",
                "type": "form",
                "form_submit_callback": form_submit_callback,
                "fields": [
                    {
                        "label": "Diameter",
                        "type": "number",
                        "value": 30,
                        "rules": {
                            "min": 1,
                            "max": 400
                        }
                    }
                ],
            })


api.export(ImJoyPlugin())
</script>