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@@ -1,4 +1,4 @@
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-import os
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+import pandas as pd
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from ChildProject.projects import ChildProject
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from ChildProject.annotations import AnnotationManager
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from ChildProject.metrics import segments_to_grid, conf_matrix, segments_to_annotation
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@@ -13,42 +13,45 @@ def compare_vandam(set1: str, set2: str) :
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#get segments that intercept between two annotations
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intersection = AnnotationManager.intersection(am.annotations, [set1, set2])
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-
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- #retrieve contents
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- segments = am.get_collapsed_segments(intersection)
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- segments = segments[segments['speaker_type'].isin(speakers)]
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-
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- set1_segm = segments_to_grid(segments[segments['set'] == set1], 0, segments['segment_offset'].max(), 100, 'speaker_type', speakers)
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- set2_segm = segments_to_grid(segments[segments['set'] == set2], 0, segments['segment_offset'].max(), 100, 'speaker_type', speakers)
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-
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- print(set1_segm.shape)
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- print(set2_segm)
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-
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- ref = segments_to_annotation(segments[segments['set'] == set1], 'speaker_type')
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- hyp = segments_to_annotation(segments[segments['set'] == set2], 'speaker_type')
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-
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- if __name__ == '__main__':
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- from pyannote.metrics.detection import DetectionPrecisionRecallFMeasure
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- metric = DetectionPrecisionRecallFMeasure()
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-
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- detail = metric.compute_components(ref, hyp)
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- precision, recall, f = metric.compute_metrics(detail)
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-
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- dirName = "outputs/compare/" + set1.replace("/","") + "-" + set2.replace("/","")
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-
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- try:
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- # Create target Directory
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- Path(dirName).mkdir(parents= True)
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- print("Directory " , dirName , " Created ")
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- except FileExistsError:
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- print("Directory " , dirName , " already exists")
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-
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- file= open("{0}/{1}-{2}.txt".format(dirName, set1.replace("/",""), set2.replace("/","")),"w+")
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- # metric_output = str(f'{precision:.2f}/{recall:.2f}/{f:.2f}')
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- metric_output = "precision: {0}/recall : {1}/ f: {2}".format(precision, recall, f)
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- file.write(metric_output)
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- file.close
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- print("Metrics [precision & recall & f] saved!")
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-
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-compare_vandam('cha','eaf')
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-compare_vandam('cha', 'cha/aligned')
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+
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+ dirName = "outputs/compare/" + set1.replace("/","") + "-" + set2.replace("/","")
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+ try:
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+ # Create target Directory
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+ Path(dirName).mkdir(parents= True)
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+ print("Directory " , dirName , " Created ")
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+ except FileExistsError:
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+ print("Directory " , dirName , " already exists")
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+
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+ file= open("{0}/{1}-{2}.txt".format(dirName, set1.replace("/",""), set2.replace("/","")),"a")
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+
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+ for speaker in speakers:
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+
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+ #retrieve contents
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+ segments = am.get_collapsed_segments(intersection)
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+ segments = segments[segments['speaker_type'].isin(pd.Series(speaker))]
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+
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+ # set1_segm = segments_to_grid(segments[segments['set'] == set1], 0, segments['segment_offset'].max(), 100, 'speaker_type', speakers)
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+ # set2_segm = segments_to_grid(segments[segments['set'] == set2], 0, segments['segment_offset'].max(), 100, 'speaker_type', speakers)
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+
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+
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+ ref = segments_to_annotation(segments[segments['set'] == set1], 'speaker_type')
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+ hyp = segments_to_annotation(segments[segments['set'] == set2], 'speaker_type')
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+
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+ if __name__ == '__main__':
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+ from pyannote.metrics.detection import DetectionPrecisionRecallFMeasure
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+ metric = DetectionPrecisionRecallFMeasure()
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+
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+ detail = metric.compute_components(ref, hyp)
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+ precision, recall, f = metric.compute_metrics(detail)
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+
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+
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+ # metric_output = str(f'{precision:.2f}/{recall:.2f}/{f:.2f}')
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+ metric_output = "precision: {0} / recall : {1} / f: {2}\n".format(precision, recall, f)
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+ file.write(speaker + ": " + metric_output)
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+ print("Metrics [precision & recall & f] saved! for {0}".format(speaker))
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+ file.close
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+
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+
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+
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+compare_vandam('eaf', 'cha')
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+compare_vandam('eaf', 'cha/aligned')
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