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modify judgment in_audios type (#474)

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* Delete judgment in_audios type

* use input

---------

Co-authored-by: wantt <wantt2@qq.com>
This commit is contained in:
liangym
2023-08-18 18:22:21 +08:00
committed by GitHub
parent 4ed1111d70
commit c8826ab04b
1 changed files with 16 additions and 20 deletions
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36
modelscope/pipelines/audio/speaker_verification_light_pipeline.py
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@@ -81,28 +81,24 @@ class SpeakerVerificationPipeline(Pipeline):
inputs: torch.Tensor,
in_audios: Union[np.ndarray, list],
save_dir=None):
if isinstance(in_audios[0], str):
if save_dir is not None:
# save the embeddings
os.makedirs(save_dir, exist_ok=True)
for i, p in enumerate(in_audios):
save_path = os.path.join(
save_dir, '%s.npy' %
(os.path.basename(p).rsplit('.', 1)[0]))
np.save(save_path, inputs[i].numpy())
if isinstance(in_audios[0], str) and save_dir is not None:
# save the embeddings
os.makedirs(save_dir, exist_ok=True)
for i, p in enumerate(in_audios):
save_path = os.path.join(
save_dir, '%s.npy' %
(os.path.basename(p).rsplit('.', 1)[0]))
np.save(save_path, inputs[i].numpy())
if len(in_audios) == 2:
# compute the score
score = self.compute_cos_similarity(inputs[0], inputs[1])
score = round(score, 5)
if score >= self.thr:
ans = 'yes'
else:
ans = 'no'
output = {OutputKeys.SCORE: score, OutputKeys.TEXT: ans}
if len(inputs) == 2:
# compute the score
score = self.compute_cos_similarity(inputs[0], inputs[1])
score = round(score, 5)
if score >= self.thr:
ans = 'yes'
else:
output = {OutputKeys.TEXT: 'No similarity score output'}
ans = 'no'
output = {OutputKeys.SCORE: score, OutputKeys.TEXT: ans}
else:
output = {OutputKeys.TEXT: 'No similarity score output'}