Video Moderation

Video moderation aims to detect malicious information in video files, and give the control suggestions for the moderation result. It supports detecting audio and video data in the file at the same time.

1. Introduction

The caller submits one or more moderation files, and specifies the detection type. The server returns the detection result through asynchronous callback.

Image supported detection types and their labels are listed below:

Voice supported detection types and their labels are listed below:

2. Restrictions

3. API

3.1 Start the Task

Request APIs

Request Parameters

The request parameter, as a json object, is stored in the request body. The specific field is described below:

Table: Request Data

Table: Extended parameters

Return the Result

3.2 Callback of Detection Results

Callback Method

Upon completion of detection, the system accesses the user provided callback address using HTTP POST, and returns the detection result to the user.
To prevent content tampering, add a checksum item to the header of HTTP request, to verify content validity.

The checksum string is generated by the following method:

The sequence + body string data contained in parameters of the starting task generate the checksum value through the SHA256 algorithm.

Callback Contents

The detection result is saved in JSON structure in body, and the specific field is described as follows:

Table: returned data

Table: result

The result structure of result->segment in different action detection is different, including the following situations:

(1)When action is v-porn or v-terrorism or v-antispam or v-sface or v-illegal or v-ad or v-ocr, the structure of result->segment as follow

Table: face

Table. porn

(2)When action is a-porn, the structure of result->segment as follow

(3)When action is a-antispam, the structure of result->segment as follow

Table. antispam-extraData

3.3 Synchronous Search of Results

Due to asynchronous processing, it is suggested to receive the processing result with the above asynchronous callback method. The results can be obtained through polling of synchronous APIs if necessary. The specific description is as below:

Request Method

Return Parameters

Data in body is JSON, and the specific field is described as follows:

4. Sample Code

The following shows the sample code of calling with python:

# -*- coding: utf-8 -*-
#! python3.5

import requests
import uuid
import base64

host = "https://ai.jocloud.com"
appid = 123456789  # Your Service id
restful_id = '********************'  # Your certificate ID
restful_secret = '********************'  # Your certificate key
traceid = str(uuid.uuid4())
dataid = str(uuid.uuid4())

# url
url = host + '/app/%s/v1/video/async/submit?traceId=%s' % (appid, traceid)

# headers
headers = {
    "content-type": "application/json"
}

auth = base64.b64encode(("%s:%s" % (restful_id, restful_secret)).encode('utf-8'))
headers['token'] = 'Base ' + auth.decode()

# The URL of the video file to be identified
file_url = 'http://newcntv.qcloudcdn.com/asp/hls/1200/0303000a/3/default/d67f1b655f0b49be87fdcc84f7f06029/7.ts'

# Context information to be used by the service to assist the subsequent treatment in the callback message, for example: 
context = {
    'myid': 123,
    'myname': 'test'
}

# Identification result and callback address of status, and the identification result and status notificafication are called back through http POST
callback_addr = 'http://mydomain.com/callback'

# content
values = {
    'actions': ['v-sface', 'v-porn'],
    'data': [
        {
            'dataId': dataid,
            'dataType': 'URL',
            'content': file_url,
            'extra': {},
            'context': context
        }
    ],
    'callback': callback_addr,
    'sequence': 'test'
}

# request
res = requests.post(url, json=values, headers=headers)
print ('url=%s\nbody=%s\ncode=%s\ndata=%s\n' % (url, values, res.status_code, res.text))

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