diff --git a/tiktorch/imjoy.py b/tiktorch/imjoy.py
new file mode 100644
index 00000000..b8da7db6
--- /dev/null
+++ b/tiktorch/imjoy.py
@@ -0,0 +1,94 @@
+import asyncio
+import base64
+import logging
+import zipfile
+from pathlib import Path
+
+import numpy
+import torch
+from imageio import imread
+
+from tiktorch.server.reader import eval_model
+
+logger = logging.getLogger(__name__)
+
+try:
+    from imjoy import api
+except ImportError:
+
+    class ImjoyApi:
+        def log(self, msg) -> None:
+            logger.info(msg)
+
+        def alert(self, msg) -> None:
+            logger.warning(msg)
+
+        async def showDialog(self, *args, **kwargs) -> None:
+            print(args, kwargs)
+
+    api = ImjoyApi()
+
+
+class ImJoyPlugin:
+    def setup(self) -> None:
+        with zipfile.ZipFile("/g/kreshuk/beuttenm/Desktop/unet2d.model.zip", "r") as model_zip:  # todo: configure path
+            self.exemplum = eval_model(
+                model_file=model_zip, devices=[f"cuda:{i}" for i in range(torch.cuda.device_count())] + ["cpu"]
+            )
+
+        self.window = None
+        api.log("initialized")
+
+    async def run(self, ctx) -> None:
+        image_path = Path("/g/kreshuk/beuttenm/data/cremi/sneak.png")  # todo: configure path
+        try:
+            await self.show_png(image_path)
+        except Exception as e:
+            logger.error(e)
+
+        assert image_path.exists()
+        img = imread(str(image_path))
+        assert img.shape[2] == 4
+        batch = img[None, :512, :512, 0]  # cyx
+
+        prediction = self.exemplum.forward(batch)
+
+        self.show_numpy(prediction)
+
+    async def show_png(self, png_path: Path):
+        with png_path.open("rb") as f:
+            data = f.read()
+            result = base64.b64encode(data).decode("ascii")
+
+        imgurl = "data:image/png;base64," + result
+        data = {"src": imgurl}
+
+        data_plot = {"name": "show png", "type": "imjoy/image", "w": 12, "h": 15, "data": data}
+
+        ## Check if window was defined
+        if self.window is None:
+            self.window = await api.createWindow(data_plot)
+            print(f"Window created")
+
+    def show_numpy(self, data: numpy.ndarray):
+        print(data)
+
+
+if __name__ == "__main__":
+    from dataclasses import dataclass, field
+
+    @dataclass
+    class Config:
+        pass
+
+    @dataclass()
+    class Ctx:
+        config: Config = field(default_factory=Config)
+
+    logging.basicConfig(level=logging.DEBUG)
+    loop = asyncio.get_event_loop()
+    ctx = Ctx()
+
+    plugin = ImJoyPlugin()
+    plugin.setup()
+    loop.run_until_complete(plugin.run(ctx))