Transfer image on run

Author: gnodar01

CP5/active_plugins/appose_demo.py

@@ -71,9 +71,8 @@
 def show(narr):
     napari.imshow(narr)
 
-narr = np.random.random([512, 384])
-show(narr)
-task.outputs["shape"] = narr.shape
+show(ndarr.ndarray())
+task.outputs["shape"] = ndarr.shape
 """
 
 READY = False
@@ -106,7 +105,7 @@ def create_settings(self):
         )
 
     def settings(self):
-        return super().settings() + [self.package_path, self.doit]
+        return super().settings() + [self.x_name, self.package_path, self.doit]
 
     def visible_settings(self):
         return self.settings()
@@ -123,6 +122,46 @@ def run(self, workspace):
 
         x_data = x.pixel_data
 
+        env = appose.base(str(self.package_path)).build()
+        with env.python() as python:
+            # Print Appose events verbosely, for debugging purposes.
+            python.debug(print)
+
+            # Start the Qt application event loop in the worker process.
+            print("Starting Qt app event loop")
+            setup = python.task(qt_setup, queue="main")
+            def check_ready(event):
+                if event.response_type == ResponseType.UPDATE:
+                    print("Got update event! Marking Qt as ready")
+                    global READY
+                    READY = True
+                    print("Ready...", READY)
+            print("attempting to start to listen", flush=True)
+            setup.listen(check_ready)
+            print("attempting start setup", flush=True)
+            setup.start()
+            print("Waiting for Qt startup...", flush=True)
+            global READY
+            while not READY:
+                print("sleeping", READY)
+                sleep(0.1)
+            print("Qt is ready!", flush=True)
+
+            print("IMAGE INFO: ", x_data.dtype, x_data.shape)
+
+            # Create a test image in shared memory.
+            ndarr = appose.NDArray(dtype=str(x_data.dtype), shape=x_data.shape)
+            # There's probably a slicker way without needing to slice/copy...
+            ndarr.ndarray()[:] = x_data[:]
+
+            # Actually do a real thing with napari: create and show an image.
+            print("Showing image with napari...", flush=True)
+            task = python.task(napari_show, inputs={"ndarr": ndarr})
+
+            task.wait_for()
+            shape = task.outputs["shape"]
+            print(f"Task complete! Got shape: {shape}", flush=True)
+
         if self.show_window:
             ...