ffmpeg/README.md

# Audio Decode Implementation With PyAV

*author: Junjie Jiang*

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### Description

**Audio** **Decode** converts the encoded audio back to uncompressed audio frames. In most cases, audio decoding is the first step of an audio processing pipeline.




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### Code Example


```Python
from towhee import pipe, ops, DataCollection

p = (
    pipe.input('audio_file')
    .flat_map('audio_file', 'frame', ops.audio_decode.ffmpeg())
    .output('frame')
)

DataCollection(p('./music.mp3')).show(limit=1)


```

![img](./img.png)

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### Factory Constructor


Create the operator via the following factory method:

***audio_decode.ffmpeg()***



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### Interface



An audio decode operator takes an audio file path as input. It decodes the audio back to audio frames.

**Args:**

**audio** (str):

Audio file path.

**Return** (generator):

An generator over audio frames with type `towhee.types.AudioFrame`.







# More Resources

- [Scalar Quantization and Product Quantization - Zilliz blog](https://zilliz.com/learn/scalar-quantization-and-product-quantization): A hands-on dive into scalar quantization (integer quantization) and product quantization with Python.
- [Vector Database Use Case: Audio Similarity Search - Zilliz](https://zilliz.com/vector-database-use-cases/audio-similarity-search): Building agile and reliable audio similarity search with Zilliz vector database (fully managed Milvus).
- [Real-Time GenAI without Hallucination Using Confluent & Zilliz Cloud](https://zilliz.com/product/integrations/confluent): nan
- [Audio Retrieval Based on Milvus - Zilliz blog](https://zilliz.com/blog/audio-retrieval-based-on-milvus): Create an audio retrieval system using Milvus, an open-source vector database. Classify and analyze sound data in real time.