CN113542724B - Automatic detection method and system for video resources - Google Patents
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- 238000012360 testing method Methods 0.000 claims description 71
- 238000000034 method Methods 0.000 claims description 14
- 238000013507 mapping Methods 0.000 claims description 6
- 238000012790 confirmation Methods 0.000 claims description 5
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/439—Processing of audio elementary streams
- H04N21/4394—Processing of audio elementary streams involving operations for analysing the audio stream, e.g. detecting features or characteristics in audio streams
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/44—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
- H04N21/44008—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics in the video stream
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
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- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention provides an automatic detection method of video resources, which comprises the following steps: step S1, uploading a tested video resource, judging whether the file type of an uploaded file is in a video format, acquiring meta information of the tested video resource, and judging whether the video resource is available according to the meta information; step S2, performing Huang Jianzheng scanning on the measured resources to judge whether yellow administration is involved or not; s3, extracting an audio part of the detected video resource, playing the video resource, and starting the following two operations after starting to play the video resource; operation one: obtaining video content screenshots of different time points of the video resource to judge whether the video resource has a clamping condition or not; and (2) operation II: acquiring sound output by a system sound card, storing the acquired sound as C.wav, acquiring waveform array data of a C.wav file, and judging whether the audio of a video resource is abnormal or not according to the waveform array data; the cost of human verification is reduced, and the detection efficiency is improved.
Description
Technical Field
The invention relates to the technical field of video resource testing, in particular to an automatic detection method and system for video resources.
Background
Video resources: video generally refers to storage formats involving various motion pictures, such as flv, mp4, mov, rmvb, rm, avi, wmv, f4v, asf, mpg, mkv,3gp, m4v, vob, ts, ogv. The video can be recorded and transmitted through various physical media, and with the popularization of the computer, the universal computer equipment has the capabilities of video acquisition, storage and editing, so that the application scene of the video file is effectively improved; video resources are now ubiquitous in our lives.
Because the platform is provided with a large number of video resources and resources newly added by an uploading inlet, the number of the video resources to be checked is huge, the conventional test mode is to check the tested resources by manual random spot check, the test mode has uncertainty, and all the video resources cannot be covered; and a video file can not be completely and completely checked by people, and when the video is verified, the fast forward operation is often carried out on the played video, and some problem pictures are easily missed in the process, so that uncertainty exists to a certain extent.
The existing test mode has the defects that: 1. the video resource has a plurality of file types and the number of files in the resource library is huge. The traditional test scheme can only be a manual test, and the manual test has larger limitation, so that the files in the massive resource libraries cannot be subjected to full-scale test, and the usability of the untested files cannot be guaranteed, so that risks can exist.
2. The file uploaded by the user has larger uncertainty, and the file which cannot be normally opened or the file which does not accord with national regulations (yellow administration storm) and the like possibly cannot be uploaded, so that the abnormal situation cannot be perceived in advance.
Disclosure of Invention
In order to overcome the problems, the invention aims to provide an automatic detection method for video resources, which is used for automatic testing, can be executed in batches and reduces the cost of human verification.
The invention is realized by adopting the following scheme: an automated video asset detection method, the method comprising the steps of:
step S1, uploading a tested video resource, judging whether the file type of the uploaded file is in a video format, if not, ending the flow, if yes, acquiring meta information of the tested video resource, judging whether the video resource is available according to the meta information, if not, ending the flow, and if yes, entering step S2;
step S2, calling a content authentication Huang Jiekou, calling a content security service of a third party through an interface to perform yellow authentication operation, performing authentication Huang Jianzheng scanning on a tested resource, judging whether yellow administration is involved, if yes, performing manual check and confirmation and generating a test report, otherwise, entering step S3;
s3, extracting an audio part of the detected video resource, storing the audio part as B.wav, and acquiring the duration Tb of the B.wav; playing the video resource, acquiring the total duration Ta of the video resource, and starting the following two operations after starting to play the video resource;
operation one: acquiring video content screenshots of different time points of the video resource to judge whether the video resource has a clamping condition or not, thereby obtaining a test report;
and (2) operation II: and acquiring sound output by the sound card of the system, storing the acquired sound as C.wav, acquiring waveform array data of the C.wav file, and judging whether the audio of the video resource is abnormal according to the waveform array data, thereby obtaining a test report.
Further, the meta information is basic information of the video resource, including playing time length, resolution and frame rate.
Further, the operation one is further specifically: acquiring content screenshots of different time points of a video according to an interval time, wherein the interval time=Ta/N, ta is video resource playing time, and N is the number of video screenshots; judging whether the generated N pictures have black-and-white pictures or not through a black-and-white mapping algorithm, wherein if part of the black-and-white pictures exist in the screenshot, the pictures are abnormal in the video resource playing process; the screenshot is a black-and-white image, and then the video resource has no picture; if the screenshot is not provided with a black-and-white image, the video resource playing picture is normal, so that a test report is generated.
Further, the second operation is further specifically: acquiring duration Tb of B.wav, wherein Tb=0 indicates that the resource video has no sound, tb is not equal to 0 indicates that the resource video has sound, and when playing video resources, acquiring sound output by a sound card of a system and saving the acquired content as C.wav, acquiring waveform array data C1 of a C.wav file, and outputting a conclusion D according to the waveform array data C1, wherein D=0 indicates silence, and D is not equal to 0 and indicates sound; judging whether Tb is consistent with D, if so, the audio of the video resource is normal, and if not, the audio of the video resource is abnormal, so as to generate a test report.
The invention also provides an automatic detection system of the video resource, which comprises a video availability test module, a video content safety test module, a video content and audio test module;
the video availability test module is used for uploading the tested video resource, judging whether the file type of the uploaded file is in a video format, ending the flow if not, acquiring meta information of the tested video resource if yes, judging whether the video resource is available according to the meta information, ending the flow if not, and entering the video content security test module if yes;
the video content security test module is used for calling a content identifier Huang Jiekou, calling a content security service of a third party through an interface to perform yellow identification operation, performing identifier Huang Jianzheng scanning on a tested resource, judging whether yellow is involved, if yes, performing manual investigation and confirmation and generating a test report, and if no, entering the video content and audio test module;
the video content and audio testing module is used for extracting the audio part of the tested video resource, storing the audio part as B.wav, playing the video resource, and starting the following two operations after starting to play the video resource;
operation one: acquiring video content screenshots of different time points of the video resource to judge whether the video resource has a clamping condition or not, thereby obtaining a test report;
and (2) operation II: and acquiring sound output by the sound card of the system, storing the acquired sound as C.wav, acquiring waveform array data of the C.wav file, and judging whether the audio of the video resource is abnormal according to the waveform array data, thereby obtaining a test report.
Further, the meta information is basic information of the video resource, including playing time length, resolution and frame rate.
Further, the operation one is further specifically: acquiring content screenshots of different time points of a video according to an interval time, wherein the interval time=Ta/N, ta is video resource playing time, and N is the number of video screenshots; judging whether the generated N pictures have black-and-white pictures or not through a black-and-white mapping algorithm, wherein if part of the black-and-white pictures exist in the screenshot, the pictures are abnormal in the video resource playing process; the screenshot is a black-and-white image, and then the video resource has no picture; if the screenshot is not provided with a black-and-white image, the video resource playing picture is normal, so that a test report is generated.
Further, the second operation is further specifically: acquiring duration Tb of B.wav, wherein Tb=0 indicates that the resource video has no sound, tb is not equal to 0 indicates that the resource video has sound, and when playing video resources, acquiring sound output by a sound card of a system and saving the acquired content as C.wav, acquiring waveform array data C1 of a C.wav file, and outputting a conclusion D according to the waveform array data C1, wherein D=0 indicates silence, and D is not equal to 0 and indicates sound; judging whether Tb is consistent with D, if so, the audio of the video resource is normal, and if not, the audio of the video resource is abnormal, so as to generate a test report.
The invention has the beneficial effects that: the invention verifies the availability of video resources (the file is in legal video format, the video resources can be normally opened and played), the safety of the content of the video resources (yellow, political and violent scanning is carried out on the resources), and the content of the video resources (contents such as video pictures, video sounds and the like), and the detection can be carried out in batches, thereby reducing the cost of manual verification, automatically testing and carrying out timing task monitoring and timely sensing on-line abnormality.
Drawings
FIG. 1 is a schematic flow chart of the method of the present invention.
Fig. 2 is a schematic flow chart of a first embodiment of the present invention.
Fig. 3 is a functional block diagram of the system of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Referring to fig. 1, the method for automatically detecting video resources of the present invention includes the following steps:
step S1, usability test of video resources: uploading a detected video resource A.mp4; judging whether the file type of the uploaded file is a video format, wherein the currently supported video formats are as follows: flv, mp4, mov, rmvb, rm, avi, wmv, f4v, asf, mpg, mkv,3gp, m4v, vob, ts, ogv (there are partial files, although the file suffix is in video format, this file is not in video format in fact, so this patent adds a check on the file type); after verification, meta information of the measured resource (A.MP4) is acquired, so that whether the resource is available (a normal video file can be successfully acquired, namely, the meta information (the meta information is basic information of the file: such as duration, resolution, frame rate and the like of the video file) is judged, and the file is considered to be normally available. If the verification is passed, the content security automatic test flow of the video resource is entered.
Step S2, content security automation test of video resource (resource authentication Huang Jianzheng): firstly, a third party content security service (such as an ali content security service, an authentication Huang Jianzheng capability of providing video resources, and identification of whether the video content has sensitive content such as yellow, administrative, storm and the like) is called, and the detected resource A is scanned by the authentication Huang Jianzheng. And if the scanning is passed, continuing to perform the content automatic test flow of the video resource. The intelligent multimedia content identification service supports diversified scene detection of objects such as pictures, videos, texts, voices and the like, and effectively helps users to reduce the risk of content violations.
Step S3, content automation test of the video resource (comprising a picture content and an audio content 2 part of the video resource): extracting an audio part of a measured resource (A.MP4), independently storing the audio part as B.wav (audio format), and acquiring information such as duration of the B.wav; play resource a.mp4. Two operations are simultaneously started after playing is started:
a) Operation one: obtaining video content screenshots of different time points of the video, obtaining a screenshot at a specified interval (for example, the duration of the specified interval is 10 seconds, which means that a picture is cut every 10 seconds), and then judging whether the obtained video content screenshots have black and white pictures or not; if the screenshot file is a black-and-white image, the video A.MP4 picture is considered to be abnormal; if part of all the screen shots are black-and-white, the situation that the video is blocked in the playing process is considered to be possible; if no black-and-white image exists in all the screen shots, the video picture is considered to be normal.
b) And (2) operation II: and acquiring sound output by the sound card of the system (the time length of ending the acquisition of the A.MP4 file is equal), and storing the acquired sound as C.wav. Then the waveform array data of the c.wav file is obtained and this waveform data is processed (waveform data is a value in array format, if the values are all 0, it means that the resource a.mp4 has no sound, if the values have a content other than 0, it means that the resource a.mp4 has sound).
Integrating the conclusion of the flow and generating a test report.
The operation one is further specifically as follows: acquiring content screenshots of different time points of a video according to an interval time, wherein the interval time=Ta/N, ta is video resource playing time, and N is the number of video screenshots; judging whether the generated N pictures have black-and-white pictures or not through a black-and-white mapping algorithm, wherein if part of the black-and-white pictures exist in the screenshot, the pictures are abnormal in the video resource playing process; the screenshot is a black-and-white image, and then the video resource has no picture; if the screenshot is not provided with a black-and-white image, the video resource playing picture is normal, so that a test report is generated.
The second operation is further specifically: acquiring duration Tb of B.wav, wherein Tb=0 indicates that the resource video has no sound, tb is not equal to 0 indicates that the resource video has sound, and when playing video resources, acquiring sound output by a sound card of a system and saving the acquired content as C.wav, acquiring waveform array data C1 of a C.wav file, and outputting a conclusion D according to the waveform array data C1, wherein D=0 indicates silence, and D is not equal to 0 and indicates sound; judging whether Tb is consistent with D, if so, the audio of the video resource is normal, and if not, the audio of the video resource is abnormal, so as to generate a test report.
As shown in FIG. 2, the present invention is further described in connection with an embodiment:
1. setting an initial value; n: representing the number of generated video screenshots, for example, setting n=5, and representing that 5 video content screenshots at different time points are generated in total;
2. uploading a test resource to obtain a test video resource A;
3. whether the tested resource A is in a video format is judged (the video formats supported at present are flv, mp4, mov, rmvb, rm, avi, wmv, f4v, asf, mpg, mkv,3gp, m4v, vob, ts and ogv).
4. It is determined whether video a is available. The judgment is made by acquiring meta-information of the video a (the video meta-information includes content such as duration Ta, resolution, frame rate, etc.), if the video meta-information can be normally acquired, this indicates that the video file is available, otherwise, indicates that the resource is not available.
5. And invoking a content security service interface of the third party to authenticate Huang Jianzheng the resource A. (currently, the content security service capability of the Alice is called), and whether the resource A is yellow or not is judged through interface response.
6. Extracting an audio part of the video A, and storing the extracted audio part as B.wav (audio format file);
7. acquiring meta information such as duration Tb of the file B.wav, and judging whether the video A has sound or not by using the value of Tb (if Tb is equal to 0, the resource A has no sound, and if Tb is not equal to 0, the video A has sound);
8. playing the resource A and simultaneously entering the flow branches 9-10 (steps 9 to 10) and the flow branches 11-13 (steps 11 to 13);
9. acquiring content screenshots of different time points of a video, wherein the interval time=Ta/N (interval time: the interval time representing the action of the screenshots, such as 10 seconds interval to cut a picture);
10. and judging whether the N pictures generated in the step 9 have black and white pictures or not. Firstly, judging whether a video can be normally captured, judging whether the captured picture is normal or not through a black-and-white image algorithm, and outputting a conclusion; if the screenshot has a part of black-and-white images, the images are considered to be abnormal in the video playing process; the screenshot is a black-and-white image, and the video is considered to have no picture; if the screenshot has no black-and-white image, the video playing picture is considered to be normal.
11. The method comprises the steps of obtaining sound output by a system sound card (Ta value is the right value after the obtaining action is ended) while playing a resource A, and storing the obtained content as C.wav;
12. acquiring waveform array data C1 of a C.wav file, processing the waveform array data C1, and outputting a conclusion D (D has two conditions, D=0 indicates no sound, and D is not equal to 0 indicates sound);
13. judging the Tb value of the step 7 and the D conclusion of the step 12, if Tb=0, D=0 outputs a conclusion: video a has no sound; if Tb is not equal to 0, D is not equal to 0 to output a conclusion: video a has sound; if Tb is not equal to 0, d=0, the conclusion is output: the audio part of the video A has difference, and the information of the video A and waveform data related to the video A are recorded;
14. and integrating the test results to generate a test report. The test report generated is generally as follows in Table 1
TABLE 1
As shown in fig. 3, the present invention further provides an automated video resource detection system, where the system includes a video availability test module, a video content security test module, a video content and audio test module;
the video availability test module is used for uploading the tested video resource, judging whether the file type of the uploaded file is in a video format, ending the flow if not, acquiring meta information of the tested video resource if yes, judging whether the video resource is available according to the meta information, ending the flow if not, and entering the video content security test module if yes; the meta information is basic information of video resources and comprises playing time length, resolution and frame rate.
The video content security test module is used for calling a content identifier Huang Jiekou, calling a content security service of a third party through an interface to perform yellow identification operation, performing identifier Huang Jianzheng scanning on a tested resource, judging whether yellow is involved, if yes, performing manual investigation and confirmation and generating a test report, and if no, entering the video content and audio test module;
the video content and audio testing module is used for extracting the audio part of the tested video resource, storing the audio part as B.wav, playing the video resource, and starting the following two operations after starting to play the video resource;
operation one: acquiring video content screenshots of different time points of the video resource to judge whether the video resource has a clamping condition or not, thereby obtaining a test report;
the operation one is further specifically as follows: acquiring content screenshots of different time points of a video according to an interval time, wherein the interval time=Ta/N, ta is video resource playing time, and N is the number of video screenshots; judging whether the generated N pictures have black-and-white pictures or not through a black-and-white mapping algorithm, wherein if part of the black-and-white pictures exist in the screenshot, the pictures are abnormal in the video resource playing process; the screenshot is a black-and-white image, and then the video resource has no picture; if the screenshot is not provided with a black-and-white image, the video resource playing picture is normal, so that a test report is generated.
And (2) operation II: and acquiring sound output by the sound card of the system, storing the acquired sound as C.wav, acquiring waveform array data of the C.wav file, and judging whether the audio of the video resource is abnormal according to the waveform array data, thereby obtaining a test report.
The second operation is further specifically: acquiring duration Tb of B.wav, wherein Tb=0 indicates that the resource video has no sound, tb is not equal to 0 indicates that the resource video has sound, and when playing video resources, acquiring sound output by a sound card of a system and saving the acquired content as C.wav, acquiring waveform array data C1 of a C.wav file, and outputting a conclusion D according to the waveform array data C1, wherein D=0 indicates silence, and D is not equal to 0 and indicates sound; judging whether Tb is consistent with D, if so, the audio of the video resource is normal, and if not, the audio of the video resource is abnormal, so as to generate a test report.
The foregoing description is only of the preferred embodiments of the invention, and all changes and modifications that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Claims (4)
1. An automatic detection method for video resources is characterized in that: the method comprises the following steps:
step S1, uploading a tested video resource, judging whether the file type of the uploaded file is in a video format, if not, ending the flow, if yes, acquiring meta information of the tested video resource, judging whether the video resource is available according to the meta information, if not, ending the flow, and if yes, entering step S2;
step S2, calling a content authentication Huang Jiekou, calling a content security service of a third party through an interface to perform yellow authentication operation, performing authentication Huang Jianzheng scanning on a tested resource, judging whether yellow administration is involved, if yes, performing manual check and confirmation and generating a test report, otherwise, entering step S3;
s3, extracting an audio part of the detected video resource, storing the audio part as B.wav, playing the video resource, and starting the following two operations at the same time after starting to play the video resource;
operation one: acquiring video content screenshots of different time points of the video resource to judge whether the video resource has a clamping condition or not, thereby obtaining a test report; the operation one is further specifically as follows: acquiring content screenshots of different time points of a video according to an interval time, wherein the interval time=Ta/N, ta is video resource playing time, and N is the number of video screenshots; judging whether the generated N pictures have black-and-white pictures or not through a black-and-white mapping algorithm, wherein if part of the black-and-white pictures exist in the screenshot, the pictures are abnormal in the video resource playing process; the screenshot is a black-and-white image, and then the video resource has no picture; if the screenshot has no black-and-white image, the video resource playing picture is normal, so that a test report is generated;
and (2) operation II: acquiring sound output by a system sound card, storing the acquired sound as C.wav, acquiring waveform array data of a C.wav file, and judging whether the audio of a video resource is abnormal according to the waveform array data so as to obtain a test report; the second operation is further specifically: acquiring duration Tb of B.wav, wherein Tb=0 indicates that the resource video has no sound, tb is not equal to 0 indicates that the resource video has sound, and when playing video resources, acquiring sound output by a sound card of a system and saving the acquired content as C.wav, acquiring waveform array data C1 of a C.wav file, and outputting a conclusion D according to the waveform array data C1, wherein D=0 indicates silence, and D is not equal to 0 and indicates sound; judging whether Tb is consistent with D, if so, the audio of the video resource is normal, and if not, the audio of the video resource is abnormal, so as to generate a test report.
2. The automated video asset detection method of claim 1, wherein: the meta information is basic information of video resources and comprises playing time length, resolution and frame rate.
3. An automated video resource detection system, characterized by: the system comprises a video availability testing module, a video content security testing module, a video content and audio testing module;
the video availability test module is used for uploading the tested video resource, judging whether the file type of the uploaded file is in a video format, ending the flow if not, acquiring meta information of the tested video resource if yes, judging whether the video resource is available according to the meta information, ending the flow if not, and entering the video content security test module if yes;
the video content security test module is used for calling a content identifier Huang Jiekou, calling a content security service of a third party through an interface to perform yellow identification operation, performing identifier Huang Jianzheng scanning on a tested resource, judging whether yellow is involved, if yes, performing manual investigation and confirmation and generating a test report, and if no, entering the video content and audio test module;
the video content and audio testing module is used for extracting the audio part of the tested video resource, storing the audio part as B.wav, playing the video resource, and starting the following two operations after starting to play the video resource;
operation one: acquiring video content screenshots of different time points of the video resource to judge whether the video resource has a clamping condition or not, thereby obtaining a test report; the operation one is further specifically as follows: acquiring content screenshots of different time points of a video according to an interval time, wherein the interval time=Ta/N, ta is video resource playing time, and N is the number of video screenshots; judging whether the generated N pictures have black-and-white pictures or not through a black-and-white mapping algorithm, wherein if part of the black-and-white pictures exist in the screenshot, the pictures are abnormal in the video resource playing process; the screenshot is a black-and-white image, and then the video resource has no picture; if the screenshot has no black-and-white image, the video resource playing picture is normal, so that a test report is generated;
and (2) operation II: acquiring sound output by a system sound card, storing the acquired sound as C.wav, acquiring waveform array data of a C.wav file, and judging whether the audio of a video resource is abnormal according to the waveform array data so as to obtain a test report; the second operation is further specifically: acquiring duration Tb of B.wav, wherein Tb=0 indicates that the resource video has no sound, tb is not equal to 0 indicates that the resource video has sound, and when playing video resources, acquiring sound output by a sound card of a system and saving the acquired content as C.wav, acquiring waveform array data C1 of a C.wav file, and outputting a conclusion D according to the waveform array data C1, wherein D=0 indicates silence, and D is not equal to 0 and indicates sound; judging whether Tb is consistent with D, if so, the audio of the video resource is normal, and if not, the audio of the video resource is abnormal, so as to generate a test report.
4. An automated video asset detection system according to claim 3, wherein: the meta information is basic information of video resources and comprises playing time length, resolution and frame rate.
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| CN115002449A (en) * | 2022-05-30 | 2022-09-02 | 南京炫佳网络科技有限公司 | Method and device for testing media asset playing |
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