CellPose-Segmentation.imjoy.html

<docs lang="markdown">
# CellPose
 
A generalist algorithm for cell and nucleus segmentation.

https://github.com/MouseLand/cellpose

</docs>

<config lang="json">
{
  "name": "CellPose-Segmentation",
  "type": "native-python",
  "version": "0.1.2",
  "description": "A generalist algorithm for cell and nucleus segmentation.",
  "tags": [],
  "ui": "",
  "cover": "",
  "inputs": null,
  "outputs": null,
  "flags": [],
  "icon": "extension",
  "api_version": "0.1.8",
  "env": [{"type": "binder", "spec": "oeway/cellpose_web/binder", "skip_requirements": true}],
  "permissions": [],
  "requirements": ["repo: https://github.com/MouseLand/cellpose_web", "cmd: pip install -r cellpose_web/requirements.txt"],
  "dependencies": []
}
</config>

<script lang="python">
import os
# for Jupyter notebooks
if os.path.exists('cellpose_web'):
    os.chdir('cellpose_web')

import re
import base64
import io
import imageio
import cv2
from imjoy import api
from main import *

def image_to_base64(image_array):
    '''This function takes a numpy image array as input
    and encode it into a base64 string
    '''
    buf = io.BytesIO()
    imageio.imwrite(buf, image_array, "PNG")
    buf.seek(0)
    img_bytes = buf.getvalue()
    base64_string = base64.b64encode(img_bytes).decode('ascii')
    return 'data:image/png;base64,' + base64_string

def base64_to_image(base64_string, format=None):
    '''This function takes a base64 string as input
    and decode it into an numpy array image
    '''
    base64_string = re.sub("^data:image/.+;base64,", "", base64_string)
    image_file = io.BytesIO(base64.b64decode(base64_string.encode('ascii')))
    return imageio.imread(image_file, format)

class ImJoyPlugin():
    def setup(self):
        api.log('initialized')

    def segment(self, config):
        input64 = config["input"]
        original_img = base64_to_image(input64, config.get('format'))
        mask, flow, img = cellpose_segment(original_img, config)
        results = {"success": True, "input_shape": original_img.shape}
        outputs = config.get("outputs", "mask").split(",")
        if "geojson" in outputs:
            geojson_features = mask_to_geojson(mask)
            results["geojson"] = geojson_features
        if "img" in outputs:
            _, buffer = cv2.imencode('.png', img)
            img64 = base64.b64encode(buffer).decode()
            results["img"] = img64
        if "flow" in outputs:
            _, buffer = cv2.imencode('.png', flow)
            flow64 = base64.b64encode(buffer).decode()
            results["flow"] = flow64
        if "mask" in outputs:
            _, buffer = cv2.imencode('.png', mask.astype('uint16'))
            mask64 = base64.b64encode(buffer).decode()
            results["mask"] = mask64
        if "outline_plot" in outputs:
            outpix = plot_outlines(mask)
            results["outline_plot"] = img_to_html(img, outpix=outpix)
        if "overlay_plot" in outputs:
            overlay = plot_overlay(img, mask)
            results["overlay_plot"] = img_to_html(overlay)
        if "flow_plot" in outputs:
            results["flow_plot"] = img_to_html(flow)
        if "img_plot" in outputs:
            results["img_plot"] = img_to_html(img)
        return results

    async def run(self, ctx):
        if ctx.data and 'input' in ctx.data:
            return self.segment(ctx.data)
        else:
            try:
                path = await api.prompt("Please input an image file path or URL", "http://www.cellpose.org/static/images/img00.png")
                api.showStatus('Loading example image...')
                image = imageio.imread(path)
                api.showStatus('Running segmentation with cellpose...')
                outputs = self.segment({'input': image_to_base64(image), "diam": 30, "net": "cyto", "chan1": 0, "chan2": 0, "outputs": "flow,mask,outline_plot,overlay_plot"})
                api.showStatus('Displaying result...')
                outline_plot = base64_to_image(outputs['outline_plot'])
                await api.createWindow(src="https://kitware.github.io/itk-vtk-viewer/app/", name="CellPose Segmentation Result", data={"image": outline_plot})
                api.showStatus('Done.')
            except Exception as e:
                api.showMessage("Failed to run cellpose: " + str(e))
                raise e

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