feat: add VisualisationProducer

Creates a plot showing where in source video(s) the pipeline features
came from

pipeline/video_producers.py

@@ -5,8 +5,9 @@ import logging
 import subprocess
 import tempfile
 
-class VideoProducer(ABC):
-    """Video producer interface."""
+# for visualisations:
+import matplotlib.pyplot as plt
+
 class Producer(ABC):
     """Generic producer interface."""
     def __init__(self, features):
@@ -87,3 +88,35 @@ class FfmpegVideoProducer(VideoProducer):
         output_filepath = f"{OUTPUT_DIR}/highlights.mp4"
         self._ffmpeg_concat_clips(clips, output_filepath)
         logging.info(f"Produced video: {output_filepath}")
+
+class VisualisationProducer(Producer):
+    """Visualisation producer -- illustrate the features we have extracted"""
+    def __init__(self, features):
+        if not features:
+            raise ValueError("No features provided")
+        self.features = features
+
+    def produce(self):
+        """Produce visualisation"""
+        # basic idea: use matplotlib to plot:
+        #  - a wide line segment representing the source video[s]
+        #  - shorter line segments representing the features extracted where:
+        #    + width represents duration
+        #    + colour represents feature type
+        #    + position represents time
+        #  - save as image
+        plotted_source_videos = []
+        fig, ax = plt.subplots()
+        for feature in self.features:
+            # plot source video line if not done already
+            if feature.source not in plotted_source_videos:
+                # use video duration as width
+                # ax.plot([0, feature.source.duration()], [0, 0], color='black', linewidth=10)
+                ax.broken_barh([(0, feature.source.duration())], (0, 5), facecolors='grey')
+                plotted_source_videos.append(feature.source)
+            # plot feature line
+            # ax.plot([feature.interval.start, feature.interval.end], [1, 1], color='red', linewidth=5)
+            ax.broken_barh([(feature.interval.start, feature.interval.duration)], (10, 5), facecolors='red')
+        # save the plot
+        plt.savefig("/tmp/visualisation.png")
+        plt.close()