bioimageio-colab-annotator.imjoy.html

<config lang="json">
{
  "name": "BioImage.IO Colab Annotator",
  "type": "web-python",
  "tags": [],
  "ui": "",
  "version": "0.1.0",
  "cover": "",
  "description": "Collaborative Annotator for BioImage.IO with Automated Segmentation",
  "icon": "extension",
  "inputs": null,
  "outputs": null,
  "api_version": "0.1.8",
  "env": "",
  "permissions": [],
  "requirements": ["kaibu-utils", "imjoy-rpc", "websockets", "ssl"],
  "dependencies": []
}
</config>

<script lang="python">
from imjoy_rpc import api
from imjoy_rpc.hypha import connect_to_server

class BioImageIOCrowdSourcing():
    def __init__(self):
        
        self.image = None
        self.mask = None
        self.filename = None
        self.newname = None
        self.mask_id = None
        self.image_id = None
        self.annotation_layer = None

    async def setup(self):
        viewer = await api.createWindow(src="https://kaibu.org/#/app", fullscreen=True)
        await api.showMessage("Connecting to server....")
        server = await connect_to_server({"server_url": "https://ai.imjoy.io"})
        self.biocolab = await server.get_service("biocolab")

        ## Define image reading and displaying function
        async def get_image():
            
            if self.image is not None:
                await viewer.remove_layer({"id": self.image_id.id})
                await viewer.remove_layer({"id": self.annotation_layer.id})
            
            self.image, self.filename, self.newname = await self.biocolab.get_random_image()
            self.image_id = await viewer.view_image(
                                self.image,
                                name="image")
            # Add the little annotation functionality to the interface
            self.annotation_layer = await viewer.add_shapes(
                                    [],
                                    shape_type="polygon",
                                    draw_edge_color="magenta",
                                    name="annotation",
                                    )
            
        ## Define image annotation printing into a mask with the name "mask"
        # async def create_mask():
        #     self.features = await self.annotation_layer.get_features()
        #     if self.mask is not None:
        #         await viewer.remove_layer({"id": self.mask_id.id})
                
        #     self.mask = features_to_mask(self.features, [self.image.shape[0], self.image.shape[1]])
        #     self.mask_id = await viewer.view_image(
        #                     self.mask,
        #                     name="mask"
        #                 )
        #     await api.showMessage("Mask created")
            
        async def save_annotation():
            self.features = await self.annotation_layer.get_features()
            await self.biocolab.save_annotation(self.filename, self.newname, self.features, [self.image.shape[0], self.image.shape[1]])
            await api.showMessage("Annotation Saved to " + self.filename)
    
        async def select_option(option):
            if option == "Get Image":
                await get_image()
            elif option == "Save Annotations":
                await save_annotation()  
                

        await viewer.add_widget(
        {
            "_rintf": True,
            "name": "Control",
            "type": "control",
            "elements": [
                {
                    "type": "dropdown",
                    "label": "Options",
                    "options": ["Get Image", "Save Annotations"],
                    "callback": select_option,
                }
            ],
        })

        await api.showMessage("Redy to annotate!")

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