diff --git a/pipeline/feature_extractors.py b/pipeline/feature_extractors.py index c061a8d..7502b23 100644 --- a/pipeline/feature_extractors.py +++ b/pipeline/feature_extractors.py @@ -296,12 +296,18 @@ class VideoActivityFeatureExtractor(FeatureExtractor): #TODO: minimum duration -- consider whether to do here, or expand duration post-consolidation """ - def __init__(self, input_files=None, config=None): + _CONFIG_DEFAULT_NUM_FEATURES = 5 # keep the top 5 activity moments + _CONFIG_DEFAULT_MIN_DURATION = 5.00 # seconds + def __init__(self, input_files=None, config=None, + num_features=_CONFIG_DEFAULT_NUM_FEATURES, + min_duration=_CONFIG_DEFAULT_MIN_DURATION): if not input_files: raise ValueError("No input files provided!") self.input_files = input_files self.config = config self.features = [] + self._num_features = num_features + self._min_duration = min_duration def _scdet(self, video_file): """Run scdet filter on the video file""" @@ -347,6 +353,29 @@ class VideoActivityFeatureExtractor(FeatureExtractor): scores = sorted(scores, key=lambda x: x[1], reverse=True) return scores[:int(len(scores) * (percent / 100))] + def _keep_num(self, features, num=_CONFIG_DEFAULT_NUM_FEATURES) -> list: + """Keep the top n activity features (default: 5) + + Approach: + - for range in 0-n + + expand the nth top feature to min duration + (move start back by 0.5*min_duration, end forward by 0.5*min_duration) + + drop any features that are now in that feature's range + - return the top n features + + Each feature is a Feature object, with an Interval object + """ + for i in range(num): + # expand the feature to min_duration + features[i].interval.move_start(-0.5*self._min_duration, relative=True) + features[i].interval.move_end(0.5*self._min_duration, relative=True) + # drop any features that are now in that feature's range + features = [f for f in features if + f.interval.start < features[i].interval.start or + f.interval.end > features[i].interval.end] + + return features[:num] + def setup(self): pass @@ -354,11 +383,16 @@ class VideoActivityFeatureExtractor(FeatureExtractor): for file in self.input_files: scores = self._scdet(file.path) means = sorted(self._nonoverlap_mean(scores), key=lambda x: x[1], reverse=True) + + features = [] for time, score in self._drop_lowest(means, 66): - self.features.append(Feature(interval=Interval(start=time, duration=0.500), + features.append(Feature(interval=Interval(start=time, duration=0.500), source=file, feature_extractor="videoactivity", score=score)) + # prune features list to keep self.num_features + self.features = self._keep_num(features, self._num_features) + def teardown(self): pass