openvino: restart if detection times out

plugins/openvino/package-lock.json

@@ -1,12 +1,12 @@
 {
    "name": "@scrypted/openvino",
-   "version": "0.1.32",
+   "version": "0.1.33",
    "lockfileVersion": 2,
    "requires": true,
    "packages": {
       "": {
          "name": "@scrypted/openvino",
-         "version": "0.1.32",
+         "version": "0.1.33",
          "devDependencies": {
             "@scrypted/sdk": "file:../../sdk"
          }

plugins/openvino/package.json

@@ -40,5 +40,5 @@
    "devDependencies": {
       "@scrypted/sdk": "file:../../sdk"
    },
-   "version": "0.1.32"
+   "version": "0.1.33"
 }

plugins/openvino/src/ov/__init__.py

@@ -109,7 +109,7 @@ class OpenVINOPlugin(PredictPlugin, scrypted_sdk.BufferConverter, scrypted_sdk.S
             self.storage.removeItem('mode')
             self.storage.removeItem('model')
             self.storage.removeItem('precision')
-            asyncio.run_coroutine_threadsafe(scrypted_sdk.deviceManager.requestRestart(), asyncio.get_event_loop())
+            self.requestRestart()
 
         labels_contents = open(labelsFile, 'r').read()
         self.labels = parse_label_contents(labels_contents)
@@ -163,7 +163,7 @@ class OpenVINOPlugin(PredictPlugin, scrypted_sdk.BufferConverter, scrypted_sdk.S
     async def putSetting(self, key: str, value: SettingValue):
         self.storage.setItem(key, value)
         await self.onDeviceEvent(scrypted_sdk.ScryptedInterface.Settings.value, None)
-        await scrypted_sdk.deviceManager.requestRestart()
+        self.requestRestart()
 
     # width, height, channels
     def get_input_details(self) -> Tuple[int, int, int]:

plugins/tensorflow-lite/src/predict/__init__.py

@@ -13,6 +13,7 @@ from scrypted_sdk.types import (ObjectDetectionResult, ObjectDetectionSession,
                                 ObjectsDetected, Setting)
 
 from detect import DetectPlugin
+import traceback
 
 from .rectangle import (Rectangle, combine_rect, from_bounding_box,
                         intersect_area, intersect_rect, to_bounding_box)
@@ -187,6 +188,18 @@ class PredictPlugin(DetectPlugin, scrypted_sdk.BufferConverter):
     async def detect_once(self, input: Image.Image, settings: Any, src_size, cvss) -> ObjectsDetected:
         pass
 
+    async def safe_detect_once(self, input: Image.Image, settings: Any, src_size, cvss) -> ObjectsDetected:
+        try:
+            f = self.detect_once(input, settings, src_size, cvss)
+            return await asyncio.wait_for(f, 60)
+        except:
+            traceback.print_exc()
+            print(
+                "encountered an error while detecting. requesting plugin restart."
+            )
+            self.requestRestart()
+            raise
+
     async def run_detection_image(self, image: scrypted_sdk.Image, detection_session: ObjectDetectionSession) -> ObjectsDetected:
         settings = detection_session and detection_session.get('settings')
         src_size = image.width, image.height
@@ -217,7 +230,7 @@ class PredictPlugin(DetectPlugin, scrypted_sdk.BufferConverter):
             })
             single = await ensureRGBData(data, (w, h), image.format)
             try:
-                ret = await self.detect_once(single, settings, src_size, cvss)
+                ret = await self.safe_detect_once(single, settings, src_size, cvss)
                 return ret
             finally:
                 single.close()
@@ -281,9 +294,9 @@ class PredictPlugin(DetectPlugin, scrypted_sdk.BufferConverter):
         def cvss2(point):
             return point[0] / sx + ow, point[1] / sy + oh
 
-        ret1 = await self.detect_once(first, settings, src_size, cvss1)
+        ret1 = await self.safe_detect_once(first, settings, src_size, cvss1)
         first.close()
-        ret2 = await self.detect_once(second, settings, src_size, cvss2)
+        ret2 = await self.safe_detect_once(second, settings, src_size, cvss2)
         second.close()
 
         two_intersect = intersect_rect(Rectangle(*first_crop), Rectangle(*second_crop))

plugins/tensorflow-lite/src/tflite/__init__.py

@@ -229,13 +229,6 @@ class TensorFlowLitePlugin(
                         interpreter, score_threshold=0.2, image_scale=(1, 1)
                     )
                 return objs
-            except:
-                traceback.print_exc()
-                print(
-                    "tensorflow-lite encountered an error while detecting. requesting plugin restart."
-                )
-                self.requestRestart()
-                raise e
             finally:
                 self.interpreters.put(interpreter)