ACRCloud provides services such as Music Recognition, Broadcast Monitoring, Custom Audio Recognition, Copyright Compliance & Data Deduplication, Live Channel Detection, and Offline Recognition etc.
This audio recognition python SDK support most of audio / video files.
Audio: mp3, wav, m4a, flac, aac, amr, ape, ogg ...
Video: mp4, mkv, wmv, flv, ts, avi ...
Follow one of the tutorials to create a project and get your host, access_key and access_secret.
python3 -m pip install pyacrcloud
You can run python -m pip install git+https://github.com/acrcloud/acrcloud_sdk_python or go to sub dir, and run"sudo python setup.py install".
If you run the SDK on Windows, you must install this library.
X86: download and install Library(windows/vcredist_x86.exe)
x64: download and install Library(windows/vcredist_x64.exe)
Introduction all API.
class ACRCloudRecognizer:
def recognize_by_file(self, file_path, start_seconds, rec_length=10):
#@param file_path : query file path
#@param start_seconds : skip (start_seconds) seconds from from the beginning of (filePath)
#@param rec_length: use rec_length seconds data to recongize
#@return result metainfos
def recognize_by_filebuffer(self, file_buffer, start_seconds, rec_length=10):
#@param file_buffer : file_path query buffer
#@param start_seconds : skip (start_seconds) seconds from from the beginning of (filePath)
#@param rec_length: use rec_length seconds data to recongize
#@return result metainfos
def recognize(self, wav_audio_buffer):
#@param wav_audio_buffer : query buffer(RIFF (little-endian) data, WAVE audio, Microsoft PCM, 16 bit, mono 8000 Hz)
#@return result metainfosdef create_fingerprint_by_file(file_name, start_time_seconds, audio_len_seconds, is_db_fingerprint, opt):
#file_name: Path of input file;
#start_time_seconds: Start time of input file, default is 0;
#audio_len_seconds: Length of audio data you need. if you create recogize frigerprint, default is 12 seconds, if you create db frigerprint, it is not usefully;
#is_db_fingerprint: If it is True, it will create db frigerprint (Fingerprint for bucket, not for recognition);
#opt opt = {
'filter_energy_min': 0,
'silence_energy_threshold': 100,
'silence_rate_threshold': 1
}
def create_humming_fingerprint_by_file(file_name, start_time_seconds, audio_len_seconds):
#file_name: Path of input file;
#start_time_seconds: Start time of input file, default is 0;
#audio_len_seconds: Length of audio data you need. if you create recogize frigerprint, default is 12 seconds, if you create db frigerprint, it is not usefully;
def create_fingerprint_by_filebuffer(data_buffer, start_time_seconds, audio_len_seconds, is_db_fingerprint, opt):
#data_buffer: data buffer of input file;
#start_time_seconds: Start time of input file, default is 0;
#audio_len_seconds: Length of audio data you need. if you create recogize frigerprint, default is 12 seconds, if you create db frigerprint, it is not usefully;
#is_db_fingerprint: If it is True, it will create db frigerprint (Fingerprint for bucket, not for recognition);
#opt = {
'filter_energy_min': 0,
'silence_energy_threshold': 100,
'silence_rate_threshold': 1
}
def create_humming_fingerprint_by_filebuffer(data_buffer, start_time_seconds, audio_len_seconds):
#data_buffer: data buffer of input file;
#start_time_seconds: Start time of input file, default is 0;
#audio_len_seconds: Length of audio data you need. if you create recogize frigerprint, default is 12 seconds, if you create db frigerprint, it is not usefully;
def create_fingerprint(data_buffer, is_db_fingerprint):
#data_buffer: audio data buffer(RIFF (little-endian) data, WAVE audio, Microsoft PCM, 16 bit, mono 8000 Hz);
#is_db_fingerprint: If it is True, it will create db frigerprint (Fingerprint for bucket, not for recognition);
def create_humming_fingerprint(data_buffer):
#data_buffer: audio data buffer(RIFF (little-endian) data, WAVE audio, Microsoft PCM, 16 bit, mono 8000 Hz);
def decode_audio_by_file(file_name, start_time_seconds, audio_len_seconds):
#It will return the audio data(RIFF (little-endian) data, WAVE audio, Microsoft PCM, 16 bit, mono 8000 Hz);
#file_name: Path of input file;
#start_time_seconds: Start time of input file, default is 0;
#audio_len_seconds: Length of audio data you need, if it is 0, will decode all the audio;
def decode_audio_by_filebuffer(data_buffer, start_time_seconds, audio_len_seconds):
#It will return the audio data(RIFF (little-endian) data, WAVE audio, Microsoft PCM, 16 bit, mono 8000 Hz);
#data_buffer: data buffer of input file;
#start_time_seconds: Start time of input file, default is 0;
#audio_len_seconds: Length of audio data you need, if it is 0, will decode all the audio;
def version()
#return the version of this modulerun Test: python test.py test.mp3
#!/usr/bin/env python
#-*- coding:utf-8 -*-
import os, sys
from acrcloud.recognizer import ACRCloudRecognizer
if __name__ == '__main__':
config = {
#Replace "xxxxxxxx" below with your project's host, access_key and access_secret.
'host':'XXXXXXXX',
'access_key':'XXXXXXXX',
'access_secret':'XXXXXXXX',
'timeout':10 # seconds
}
'''This module can recognize ACRCloud by most of audio/video file.
Audio: mp3, wav, m4a, flac, aac, amr, ape, ogg ...
Video: mp4, mkv, wmv, flv, ts, avi ...'''
re = ACRCloudRecognizer(config)
#recognize by file path, and skip 0 seconds from from the beginning of sys.argv[1].
print re.recognize_by_file(sys.argv[1], 0)
buf = open(sys.argv[1], 'rb').read()
#recognize by file_audio_buffer that read from file path, and skip 0 seconds from from the beginning of sys.argv[1].
print re.recognize_by_filebuffer(buf, 0)