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Audio Recognition -- File Scan Tool (Python Script)

Overview

ACRCloud provides Automatic Content Recognition services for Audio Fingerprinting based applications such as Audio Recognition (supports music, video, ads for both online and offline), Broadcast Monitoring, Second Screen, Copyright Protection and etc.

This tool can scan audio/video files and detect audios you want to recognize such as music, ads.

Supported Format:

Audio: mp3, wav, m4a, flac, aac, amr, ape, ogg ...
Video: mp4, mkv, wmv, flv, ts, avi ...

Requirements

  • Python
  • fuzzywuzzy
  • openpyxl
  • backports.csv
  • requests
  • Follow one of the tutorials to create a project and get your host, access_key and access_secret.

Installation

For Windows System, you must install Python and pip.

Open your terminal and change to the script directory of acrcloud_scan_files_python-master. Then run the command:

pip install -r requirements.txt

Install ACRCloud Python SDK

You can run the following command to install it.

python -m pip install git+https://github.com/acrcloud/acrcloud_sdk_python

Or you can download the sdk and install it by following command.

ACRCloud Python SDK.

sudo python setup.py install

For Windows

Install Library

Windows Runtime Library

X86: download and install Library(windows/vcredist_x86.exe)

x64: download and install Library(windows/vcredist_x64.exe)

Usage for Scan File Tool:

    _    ____ ____   ____ _                 _
   / \  / ___|  _ \ / ___| | ___  _   _  __| |
  / _ \| |   | |_) | |   | |/ _ \| | | |/ _` |
 / ___ \ |___|  _ <| |___| | (_) | |_| | (_| |
/_/   \_\____|_| \_\\____|_|\___/ \____|\____|

Before you use this script,you must have acrcloud host,access_key and access_secret. If you haven't have these ,you can register one https://console.acrcloud.com/signup

Change the content of config.json,fill in your host, access_key and access_secret

{
 "host": "xxxxx",
 "access_key": "xxxxx",
 "access_secret": "xxxxx"
}
python acrcloud_scan_files_python.py -d folder_path
python acrcloud_scan_files_python.py -f file_path
python acrcloud_scan_files_python.py -h get_usage_help

Scan Folder Example:

python acrcloud_scan_files_python.py -d ~/music

Scan File Example:

python acrcloud_scan_files_python.py -f ~/testfiles/test.mp3

Add more params

"-s" ---- scan step. (The scan interval.)

"-r" ---- scan range. (The scan range.)

"-l" ---- use how many seconds to recongize. (recongizing length)

"-c" ---- set the config file path.

"-w" ---- results with duration. (1-yes, 0-no), you must set offset config for your access key, pls contact [email protected]

"-o" ---- set the directory to save the results

If you want to change scan interval or you want to set recognize range,you can add some params
Example:
    python acrcloud_scan_files_python.py -f ~/testfiles/test.mp3 -s 30 -r 0-20
    python acrcloud_scan_files_python.py -d ~/music -s 30 -w 1

Default is scan folder where this script in.

The results are saved in the folder where this script in.

Usage for Scan File Libary

Introduction all API.

acrcloud_scan_files_libary.py

class ACRCloud_Scan_Files:
    def get_duration_by_file(self, filepath):
       #@param filepath : query file path
       #@return : total duration of the file

    def export_to_xlsx(self, result_list, export_filename, export_dir):
       #@param result_list : the list of identification results
       #@param export_filename : export to this file
       #@param export_dir : export to this directory

    def export_to_csv(self, result_list, export_filename, export_dir):
       #@param result_list : the list of recognition results
       #@param export_filename : export to this file
       #@param export_dir : export to this directory

    def parse_data(self, result):
       #@param result : one recognition result
       #@return : a tuple, as follow
       #     (title, artists, album, acrid, played_duration, label, isrc, upc,
       #       deezer, spotify, itunes, youtube, custom_files_title, audio_id)

    def apply_filter(self, results):
       #@param results : the list of recognition results
       #@return : a list results with played_duration

    def for_recognize_file(self, filepath, start_time, stop_time, step, rec_length):
       #@param filepath : query file path
       #@param start_time : the start offset to recognize (seconds)
       #@param stop_time : the end offset to recognize (seconds)
       #@param rec_length : the duration of each fragment to recognize
       #@return : iterator to return the each recognition result

    def recognize_file(self, filepath, start_time, stop_time, step, rec_length):
       #@param filepath : query file path
       #@param start_time : the start offset to recognize (seconds)
       #@param stop_time : the end offset to recognize (seconds)
       #@param rec_length : the duration of each fragment to recognize
       #@return : the list of recognition results

Example

run Text: python example.py test.mp3

#!/usr/bin/env python
#-*- coding:utf-8 -*-

import os
import sys
from acrcloud_scan_files_libary import ACRCloud_Scan_Files

if __name__ == "__main__":

   #ACRCloud Scan File Example
   is_debug = 1   #display the log info, or is_debug=0
   start_time = 0 #scan file start time(seconds)
   stop_time = 0  #scan file end time(seconds), or you can set it to the duration of file
   step = 10      #the length of each identified fragment (seconds)
   rec_length = step

   #your acrcloud project host, access_key, access_secret
   config = {
       "host": "XXX",
       "access_key":"XXX",
       "access_secret": "XXX"
   }

   filepath = sys.argv[1]

   acr_sfile = ACRCloud_Scan_Files(config, is_debug)

   stop_time = acr_sfile.get_duration_by_file(filepath)

   #get a list of recognition results
   result_list = acr_sfile.recognize_file(filepath, start_time, stop_time, step, rec_length)

   #export the result
   export_dir = "./"
   #export to csv
   export_filename_csv = "test.csv"
   acr_sfile.export_to_csv(result_list, export_filename_csv, export_dir)
   #export to xlsx
   export_filename_xlsx = "test.xlsx"
   acr_sfile.export_to_xlsx(result_list, export_filename_xlsx, export_dir)

   #iterator to get the result of each fragment
   result_list2 = []
   for item in acr_sfile.for_recognize_file(filepath, start_time, stop_time, step, rec_length):
       result_list2.append(item)
       filename = item["file"]
       timestamp = item["timestamp"]
       res = acr_sfile.parse_data(item["result"])
       title = res[0]
       print filename, timestamp, title

   #get results with played-duration
   filter_results = acr_sfile.apply_filter(result_list2)
   #export the results to xlsx
   export_filtername_xlsx = "test_with_duration.xlsx"
   acr_sfile.export_to_xlsx(filter_results, export_filtername_xlsx, export_dir)

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