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CLAP Interrogator

A simple Python class for audio tagging using the CLAP model from the LAION suite

Installation

Clone and install:

git clone https://github.com/lyramakesmusic/clap-interrogator.git clap_interrogator
cd clap_interrogator
pip install -e .

Usage

from clap_interrogator import Interrogator

interrogator = Interrogator()

# Tag audio by providing file path:
tags = interrogator.tag('/path/to/audio/file.wav')

# Tag an already loaded audio tensor:
import torchaudio
audio_tensor, sr = torchaudio.load('/path/to/audio/file.wav')
tags = interrogator.tag(audio_tensor, sr)

print(tags) # ["tag 1", "tag 2", "tag 3" . . .]

# I want more tags!
tags = interrogator.tag('/path/to/audio/file.wav', top_n=50)

# Load a different CLAP model:
interrogator = Interrogator(model_name="laion/clap-htsat-unfused")

# Use different tags to interrogate against:
interrogator = Interrogator(tags="more_tags.json")
interrogator = Interrogator(tags=["Bright", "Mellow", "Strings"])
# Efficiently tag all the files in a folder:
from concurrent.futures import ProcessPoolExecutor, as_completed
from clap_interrogator import Interrogator

interrogator = Interrogator()
tags = []
filepaths = [os.path.join(dirpath, fname) for dirpath, _, fnames in os.walk("/path/to/audio/folder") for fname in fnames]
process_file = lambda path: {"path": path, "tags": interrogator.tag(path)}

with ProcessPoolExecutor(max_workers=10) as executor:
    futures = {executor.submit(process_file, filepath): filepath for filepath in filepaths}
    for future in as_completed(futures):
        tags.append(future.result())

print(tags[0]) # {"path": "/path/to/audio/file", "tags": ["tag1", "tag2", . . . "tag10"]}

# As the worst one-liner i could manage to write:
with ProcessPoolExecutor(max_workers=10) as executor:
    tags = [result if (result := (lambda f: f.result() if not f.exception() else None)(future)) is not None else 'Error' for future in as_completed(executor.submit(lambda path: {"path": path, "tags": interrogator.tag(path)}, filepath) for filepath in [os.path.join(dirpath, fname) for dirpath, _, fnames in os.walk("/path/to/audio/folder") for fname in fnames])]

Any tags.json file you provide is expected to follow this format:

{
  "category": [
    "tag1", "tag2", "tag3"
  ],
  "category2": [
    "tag4", "tag5", "tag6", "tag7"
  ]
}

Development version (with WIP genetic algo) here: https://colab.research.google.com/drive/1GoLrpSbwm9Bersz3n42F2jVvAXr02hMB