feat: add to_json() to Source, Interval & Feature

This lets us serialise properly

pipeline/utils.py

@@ -92,6 +92,13 @@ class Source():
         self._duration = 0.0 or float(subprocess.check_output(["ffprobe", "-v", "error", "-show_entries", "format=duration", "-of", "default=noprint_wrappers=1:nokey=1", file]))
         return self._duration
 
+    def to_json(self):
+        """Return a dict representation of the source for JSON encoding
+
+        @see video_producers.py:PipelineJSONEncoder
+        """
+        return dict(source=self.source, path=self.path, provider=self.provider)
+
 
 
 class Interval():
@@ -113,6 +120,7 @@ class Interval():
     # TODO: have default duration for intervals set by config
     # TODO: consider if we want to permit adjusting intervals (eg, start time, end time, duration) [probably yes]
     # NOTE: if we have more ways of defining, we could consider multipledispatch?
+    # TODO: consider if we want to keep a reference to the media file (source) in the interval
 
     DEFAULT_DURATION = 5 # seconds
     DEFAUT_PRECISION = 3 # decimal places
@@ -171,6 +179,13 @@ class Interval():
             return self.end < other.end
         return self.start < other.start
 
+    def to_json(self):
+        """Return a dict representation of the interval for JSON encoding
+
+        @see video_producers.py:PipelineJSONEncoder
+        """
+        return dict(start=self.start, end=self.end, duration=self.duration)
+
     # --------------------------------------------------------------
     # TODO: handle bad cases, eg negative duration, start > end, etc
     # --------------------------------------------------------------
@@ -261,3 +276,10 @@ class Feature():
                 return self.score < other.score
             return self.source < other.source
         return self.interval < other.interval
+    def to_json(self):
+        """Return a dict representation of the feature for JSON encoding
+
+        @see video_producers.py:PipelineJSONEncoder
+        """
+        return dict(interval=self.interval.to_json(), source=self.source.to_json(),
+                    feature_extractor=self.feature_extractor, score=self.score)