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@ -15,7 +15,7 @@ The [default model weight](clmr_checkpoint_10000.pt) provided is pretrained on [ |
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## Code Example |
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## Code Example |
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Generate embeddings for the audio "test.wav". |
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Generate embeddings for the audio "test.wav". |
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*Write the pipeline in simplified style*: |
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*Write the pipeline in simplified style*: |
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@ -42,6 +42,7 @@ import towhee |
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.audio_decode.ffmpeg['path', 'frames']() |
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.audio_decode.ffmpeg['path', 'frames']() |
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.runas_op['frames', 'frames'](func=lambda x:[y[0] for y in x]) |
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.runas_op['frames', 'frames'](func=lambda x:[y[0] for y in x]) |
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.audio_embedding.clmr['frames', 'vecs']() |
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.audio_embedding.clmr['frames', 'vecs']() |
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.select['path', 'vecs']() |
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.show() |
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.show() |
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) |
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) |
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``` |
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``` |
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@ -91,4 +92,4 @@ The input data should represent for an audio longer than 2s. |
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*numpy.ndarray* |
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*numpy.ndarray* |
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Audio embeddings in shape (num_clips, 512). |
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Audio embeddings in shape (num_clips, 512). |
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Each embedding stands for features of an audio clip with length of 2s. |
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Each embedding stands for features of an audio clip with length of 2s. |
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