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Signed-off-by: Jael Gu <mengjia.gu@zilliz.com>
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Jael Gu 12 months ago
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  1. 46
      README.md

46
README.md

@ -18,48 +18,22 @@ As suggested, it is suitable to extract features at high level or warm up a larg
Generate embeddings for the audio "test.wav".
*Write the pipeline in simplified style*:
*Write a same pipeline with explicit inputs/outputs name specifications:*
```python
import towhee
(
towhee.glob('test.wav')
.audio_decode.ffmpeg()
.runas_op(func=lambda x:[y[0] for y in x])
.audio_embedding.vggish()
.show()
from towhee import pipe, ops
p = (
pipe.input('path')
.map('path', 'frame', ops.audio_decode.ffmpeg())
.map('frame', 'vecs', ops.audio_embedding.vggish())
.output('vecs')
)
p('test.wav').get()[0]
```
| [-0.4931737, -0.40068552, -0.032327592, ...] shape=(10, 128) |
*Write a same pipeline with explicit inputs/outputs name specifications:*
```python
import towhee
(
towhee.glob['path']('test.wav')
.audio_decode.ffmpeg['path', 'frames']()
.runas_op['frames', 'frames'](func=lambda x:[y[0] for y in x])
.audio_embedding.vggish['frames', 'vecs']()
.select['path', 'vecs']()
.show()
)
```
[array([[-0.4931737 , -0.40068552, -0.03232759, ..., -0.33428153,
0.1333081 , -0.25221825],
[-0.49023268, -0.40161428, -0.03255743, ..., -0.33395663,
0.13261834, -0.25324696],
[-0.4992406 , -0.39848825, -0.03186834, ..., -0.33684137,
0.13326398, -0.25385314],
...,
[-0.49047503, -0.40119144, -0.03144619, ..., -0.33282205,
0.13334712, -0.2520305 ],
[-0.48861542, -0.40097567, -0.03173053, ..., -0.33255234,
0.13278192, -0.25157905],
[-0.4886143 , -0.40098593, -0.03175077, ..., -0.3325425 ,
0.13271847, -0.25159872]], dtype=float32)]
<br />

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