Audio Recognition -- File Scan Tool (Python Script)
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 ...
Notice: This tool only support Python 2.
- Python 2.x
- fuzzywuzzy
- openpyxl
- backports.csv
- requests
- Follow one of the tutorials to create a project and get your host, access_key and access_secret.
- Install Docker
- If you are using Windows: Download Docker Desktop for Windows and install.
- If you are using MacOs: Download Docker Desktop for Mac and install.
- If you are using Linux: Open the Terminal and input
bash <(curl -s https://get.docker.com/)
- Change the config file (config.json).
- Run following command
git clone https://github.com/acrcloud/acrcloud_scan_files_python.git cd acrcloud_scan_files_python sudo docker build -t acrcloud/python_scan_tool . # Call it without arguments to display the full help sudo docker run --rm acrcloud/python_scan_tool # Basic usage sudo docker run --rm -v $(pwd):/tmp -v /Users/acrcloud/:/music/ acrcloud/python_scan_tool -f /music/test.mp4 -o /tmp You need to change /Users/acrcloud/ to the directory where your audio/video file is. And the report file will in the acrcloud_scan_files_python directory.
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
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.
sudo python setup.py install
Windows Runtime Library
X86: download and install Library(windows/vcredist_x86.exe)
x64: download and install Library(windows/vcredist_x64.exe)
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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
python acrcloud_scan_files_python.py -d ~/music
python acrcloud_scan_files_python.py -f ~/testfiles/test.mp3
"-s" ---- scan step. （The scan interval.）
"-l" ---- recongizing length. (use how many seconds to recongize. for example: -s 20 -l 10, it will get 20 seconds of audio each time and use the first 10 seconds of audio to recognize)
"-r" ---- scan range. （The scan range. for example: -r 5-20, it will recognize the file starting from the 5th second and finish at the 20th second.）
"-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
"-t" ---- set the type of file.(csv[default] or xlsx).
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.
Introduction all API.
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
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)