add a debug option to the TCN node in order to see the inputs it has …

…when it decides not to create a classification

ros/angel_system_nodes/angel_system_nodes/activity_classification/activity_classifier_tcn.py

@@ -102,6 +102,10 @@
 # activity prediction for the "live" image will not occur until object
 # detections are predicted for that frame.
 PARAM_WINDOW_LEADS_WITH_OBJECTS = "window_leads_with_objects"
+# Debug file saved out to the filesystem for understanding the node's
+# inputs when it decides not to create an activity classification.
+# the format will be csv with a list of the object detections and the pose
+PARAM_DEBUG_FILE = "debug_file"
 
 
 class NoActivityClassification(Exception):
@@ -148,6 +152,7 @@ def __init__(self):
                 (PARAM_TOPIC, "medical"),
                 (PARAM_POSE_REPEAT_RATE, 0),
                 (PARAM_WINDOW_LEADS_WITH_OBJECTS, False),
+                (PARAM_DEBUG_FILE, ""),
             ],
         )
         self._img_ts_topic = param_values[PARAM_IMG_TS_TOPIC]
@@ -166,6 +171,12 @@ def __init__(self):
 
         self._window_lead_with_objects = param_values[PARAM_WINDOW_LEADS_WITH_OBJECTS]
 
+        self._debug_file = param_values[PARAM_DEBUG_FILE]
+        # clear the file if it exists (since we are appending to it)
+        if self._debug_file != "":
+            with open(self._debug_file, "w") as f:
+                f.write("")
+
         self.topic = param_values[PARAM_TOPIC]
         # Load in TCN classification model and weights
         with SimpleTimer("Loading inference module", log.info):
@@ -655,6 +666,12 @@ def rt_loop(self):
                             "not yield an activity classification for "
                             "publishing."
                         )
+                        if self._debug_file != "":
+                            # save the info for why this window was not processed
+                            repr = window.__repr__()
+                            with open(self._debug_file, "a") as f:
+                                f.write(f"timestamp: {self.get_clock().now().to_msg()}\n")
+                                f.write(f"{repr}\n")
 
                     # This window has completed processing - record its leading
                     # timestamp now.
@@ -888,5 +905,34 @@ def destroy_node(self):
 main = make_default_main(ActivityClassifierTCN, multithreaded_executor=4)
 
 
+if __name__ == "__main__":
+    main()
+        """
+        Save results if we have been initialized to do that.
+
+        This method does nothing if this node has not been initialized to
+        collect results.
+        """
+        rc = self._results_collector
+        if rc is not None:
+            self.get_logger().info(
+                f"Writing classification results to: {self._output_kwcoco_path}"
+            )
+            self._results_collector.write_file()
+
+    def destroy_node(self):
+        log = self.get_logger()
+        log.info("Stopping node runtime")
+        self.rt_stop()
+        with SimpleTimer("Shutting down runtime thread...", log.info):
+            self._rt_active.clear()  # make RT active flag "False"
+            self._rt_thread.join()
+        self._save_results()
+        super().destroy_node()
+
+
+main = make_default_main(ActivityClassifierTCN, multithreaded_executor=4)
+
+
 if __name__ == "__main__":
     main()