From b7024717d50be8051bac92b80b1f8249ca4354b4 Mon Sep 17 00:00:00 2001
From: Rob Hallam <0504004h@student.gla.ac.uk>
Date: Mon, 5 Aug 2024 11:55:51 +0100
Subject: [PATCH] feat: add VAFE functionality

Uses ffmpeg's scdet under the hood apropos of recommendation on
ffmpeg-user ML [1]

[1]: https://ffmpeg.org/pipermail/ffmpeg-user/2024-August/058535.html
---
 pipeline/feature_extractors.py | 40 ++++++++++++++++++++++++++++++++++
 1 file changed, 40 insertions(+)

diff --git a/pipeline/feature_extractors.py b/pipeline/feature_extractors.py
index f9ab1ad..05c1f7d 100644
--- a/pipeline/feature_extractors.py
+++ b/pipeline/feature_extractors.py
@@ -258,6 +258,46 @@ class VideoActivityFeatureExtractor(FeatureExtractor):
 
     #TODO: minimum duration -- consider whether to do here, or expand duration post-consolidation
     """
+    def __init__(self, input_files=None, config=None):
+        if not input_files:
+            raise ValueError("No input files provided!")
+        self.input_files = input_files
+        self.config = config
+        self.features = []
+
+    def _scdet(self, video_file):
+        """Run scdet filter on the video file"""
+        ffmpeg_cmd = ["ffmpeg", "-i", video_file, "-vf", "scdet=threshold=0", "-f", "null", "-"]
+        # output is of the form:
+        #   [scdet @ 0x7f0798003d00] lavfi.scd.score: 0.031, lavfi.scd.time: 23.65
+        #   [scdet @ 0x7f0798003d00] lavfi.scd.score: 0.006, lavfi.scd.time: 23.70
+        # capture output, extract time & score
+        scdet_output = subprocess.run(ffmpeg_cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE).stderr.decode("utf-8")
+        # extract time & score
+        scores = []
+        for line in scdet_output.splitlines():
+            if "lavfi.scd.score" in line:
+                scores.append( (float(line.split(",")[1].split(":")[1]),
+                                float(line.split(",")[0].split(":")[1]))
+                                )
+        return scores
+
+    def setup(self):
+        pass
+
+    def run(self):
+        for file in self.input_files:
+            scores = self._scdet(file.path)
+            means = sorted(self._nonoverlap_mean(scores), key=lambda x: x[1], reverse=True)
+            for time, score in self._drop_lowest(means, 66):
+                self.features.append(Feature(interval=Interval(start=time, duration=0.500),
+                                             source=file, feature_extractor="videoactivity",
+                                             score=score))
+
+    def teardown(self):
+        pass
+
+
 
     def teardown(self):
         pass