CN113542724A - Automatic detection method and system for video resources - Google Patents
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- H04N17/00—Diagnosis, testing or measuring for television systems or their details
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- 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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- 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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- 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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Abstract
The invention provides an automatic detection method of video resources, which comprises the following steps: step S1, uploading the tested video resource, judging whether the file type of the uploaded file is in a video format, acquiring the meta-information of the tested video resource, and judging whether the video resource is available according to the meta-information; step S2, carrying out yellow identification and administrative scan on the detected resource, and judging whether yellow-involved administration exists; step S3, extracting the audio part of the tested video resource, playing the video resource, and simultaneously starting the following two operations after the video resource is played; operation one: acquiring video content screenshots of video resources at different time points to judge whether the video resources are blocked or not; and operation II: acquiring sound output by a system sound card, storing the acquired sound as C.wav, then acquiring waveform array data of the C.wav file, and judging whether the audio frequency of the video resource is abnormal or not according to the waveform array data; the cost of artificial 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 video resource detection method and system.
Background
Video resource: 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 computers, general computer equipment has the capabilities of video acquisition, storage and editing, and the application scene of video files is effectively improved; video resources are now ubiquitous in our lives.
Because the platform is provided with a large amount of video resources and newly-added resources at an uploading entrance, the number of the video resources to be checked is huge, the tested resources are randomly spot-checked manually in the traditional testing mode, and the testing mode has uncertainty and cannot cover all the video resources; and when a video file is viewed manually, the video file cannot be played completely, and the played video is often subjected to fast forward operation when the video playing is verified, and some problem pictures are easily missed in the process, so that uncertainty exists to a certain extent.
The existing testing mode has the following defects: 1. video resource files are of many types and the number of files in the resource library is huge. The traditional test scheme can only be manual test, and the manual test has great limitation, so that the files in the massive resource libraries can not be tested in a full amount, and the untested content can not ensure the usability and possibly has risks.
2. The files uploaded by the users have high uncertainty, and the files which cannot be normally opened or files which do not conform to national regulations (concerning yellow and political storm) and the like can be uploaded, so that the abnormal conditions cannot be sensed in advance.
Disclosure of Invention
In order to overcome the above problems, an object of the present invention is to provide an automatic detection method for video resources, which can perform automatic testing, can be executed in batch, and reduce the cost of manual verification.
The invention is realized by adopting the following scheme: a method for automated detection of video assets, the method comprising the steps of:
s1, uploading the tested video resource, judging whether the file type of the uploaded file is in a video format, if not, ending the process, if yes, acquiring the meta information of the tested video resource, judging whether the video resource is available according to the meta information, if not, ending the process, and if yes, entering S2;
step S2, calling a content yellow identification interface, calling a content security service of a third party through the interface to perform yellow identification operation, performing yellow identification scanning on the measured resource, judging whether yellow identification is involved, if yes, performing manual inspection and confirmation and generating a test report, and if not, entering step S3;
step S3, extracting the audio part of the tested video resource, saving as B.wav, and obtaining the time length Tb of the B.wav; playing the video resource, acquiring the total time Ta for playing the video resource, and simultaneously starting the following two operations after the video resource is played;
operation one: acquiring video content screenshots of video resources at different time points to judge whether the video resources are blocked or not, so as to obtain a test report;
and operation II: and acquiring sound output by a system sound card, storing the acquired sound as C.wav, acquiring waveform array data of the C.wav file, and judging whether the audio frequency of the video resource is abnormal or not according to the waveform array data so as to obtain a test report.
Further, the meta information is basic information of the video resource, including a playing duration, a resolution, and a frame rate.
Further, the first operation is further specifically: acquiring content screenshots of different time points of a video according to an interval time, wherein the interval time is Ta/N, Ta is the playing time length of video resources, and N is the number of the video screenshots; judging whether the generated N pictures have black-white pictures or not through a black-white imaging algorithm, if partial black-white pictures exist in the screenshot, the picture is abnormal in the video resource playing process; if all the screenshots are black and white images, the video resources have no pictures; if no black-and-white image exists in the screenshot, the video resource playing picture is normal, and thus a test report is generated.
Further, the second operation is further specifically: acquiring the time length Tb of B.wav, wherein Tb is 0 to indicate that a resource video has no sound, Tb is not 0 to indicate that the resource video has the sound, starting to play video resources, acquiring the sound output by a system sound card, saving the acquired content as C.wav, acquiring waveform array data C1 of the C.wav file, and outputting a conclusion D according to the waveform array data C1, wherein D has two conditions, D is 0 to indicate silence, and D is not equal to 0 to indicate that the sound exists; and 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, thereby generating 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 and a video content and audio test module;
the video usability testing module is used for uploading the tested video resource, judging whether the file type of the uploaded file is in a video format, if not, ending the process, if so, acquiring the meta information of the tested video resource, judging whether the video resource is usable according to the meta information, if not, ending the process, and if so, entering the video content safety testing module;
the video content security testing module is used for calling a content yellow identification interface, calling a content security service of a third party through the interface to perform yellow identification operation, performing yellow identification scanning on the tested resource, judging whether the tested resource relates to yellow administrative, if so, performing manual inspection and confirmation and generating a testing report, and if not, entering the video content and audio testing module;
the video content and audio testing module is used for extracting an audio part of the tested video resource, storing the audio part as B.wav, playing the video resource, and simultaneously starting the following two operations after the video resource is played;
operation one: acquiring video content screenshots of video resources at different time points to judge whether the video resources are blocked or not, so as to obtain a test report;
and operation II: and acquiring sound output by a system sound card, storing the acquired sound as C.wav, acquiring waveform array data of the C.wav file, and judging whether the audio frequency of the video resource is abnormal or not according to the waveform array data so as to obtain a test report.
Further, the meta information is basic information of the video resource, including a playing duration, a resolution, and a frame rate.
Further, the first operation is further specifically: acquiring content screenshots of different time points of a video according to an interval time, wherein the interval time is Ta/N, Ta is the playing time length of video resources, and N is the number of the video screenshots; judging whether the generated N pictures have black-white pictures or not through a black-white imaging algorithm, if partial black-white pictures exist in the screenshot, the picture is abnormal in the video resource playing process; if all the screenshots are black and white images, the video resources have no pictures; if no black-and-white image exists in the screenshot, the video resource playing picture is normal, and thus a test report is generated.
Further, the second operation is further specifically: acquiring the time length Tb of B.wav, wherein Tb is 0 to indicate that a resource video has no sound, Tb is not 0 to indicate that the resource video has the sound, starting to play video resources, acquiring the sound output by a system sound card, saving the acquired content as C.wav, acquiring waveform array data C1 of the C.wav file, and outputting a conclusion D according to the waveform array data C1, wherein D has two conditions, D is 0 to indicate silence, and D is not equal to 0 to indicate that the sound exists; and 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, thereby generating a test report.
The invention has the beneficial effects that: the invention verifies the availability of video resources (files are in a legal video format, and video resources can be normally opened and played), verifies the safety of the content of the video resources (resources are scanned in yellow, administrative and storm), verifies the content of the video resources (video pictures, video sounds and other contents), can perform detection in batches, reduces the cost of artificial verification, performs automatic testing and timed task monitoring, and timely senses online abnormity.
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FIG. 1 is a schematic flow diagram of the process of the present invention.
Fig. 2 is a schematic flow chart according to 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, availability test of video resources: uploading a tested video resource A.mp4; judging whether the file type of the uploaded file is in a video format, wherein the currently supported video formats comprise: flv, mp4, mov, rmvb, rm, avi, wmv, f4v, asf, mpg, mkv,3gp, m4v, vob, ts, ogv (there is a partial file, although the file suffix is in video format, this file is not in video format in practice, so this patent adds a check on the file type); after the verification, the meta-information of the resource (a.mp4) to be tested is obtained, so as to determine whether the resource is available (if a video file is normal, the meta-information (i.e. the basic information of the file, such as the duration, resolution, frame rate, etc. of the video file) can be successfully obtained, i.e. the file is considered to be normally available). And if the verification passes, entering a content safety automatic test flow of the video resource.
Step S2, content security automation test of video resource (resource yellow authentication): firstly, calling a content security service of a third party (such as a content security service in Ali, providing the yellow-identification authentication capability of video resources, identifying whether the video contents have sensitive contents such as yellow-related, administrative-related and storm-related contents), and carrying out yellow-identification authentication scanning on the detected resource A. And if the scanning is passed, the automatic testing process of the content of the video resource is continued. The content security service in Ali is a multimedia content intelligent identification service, supports diversified scene detection on objects such as pictures, videos, texts and voices, and effectively helps people to reduce the content violation risk.
Step S3, content automation test of the video resource (including the picture content and audio content 2 part of the video resource): extracting an audio part of a measured resource (A.MP4), independently storing the audio part as a B.wav (audio format), and acquiring information such as the time length of the B.wav; play asset a.mp4. After the play is started, two operations are started simultaneously:
a) operation one: acquiring video content screenshots of different time points of a video, acquiring one screenshot at specified intervals (for example, the specified interval duration is 10 seconds, which means that one picture is acquired every 10 seconds), and then judging whether the acquired video content screenshots have black and white pictures or not; if all the screenshot files are black and white images, the video A.MP4 picture is considered to be abnormal; if part of screenshots in all screenshots are black and white images, the situation that the video is blocked possibly in the video playing process is considered; and if no black and white image exists in all the screenshots, the video picture is considered to be normal.
b) And operation II: and acquiring the sound output by the system sound card (the acquisition ending time is based on the time length of the A.MP4 file), and saving the acquired sound as C.wav. Then, waveform array data of the c.wav file is acquired, and the waveform data is processed (the waveform data is a value in an array format, if the values are all 0, it indicates that the resource a.mp4 has no sound, and if the value has a content other than 0, it indicates that the resource a.mp4 has sound).
And integrating the conclusion of the above process to generate a test report.
The first operation is further specifically: acquiring content screenshots of different time points of a video according to an interval time, wherein the interval time is Ta/N, Ta is the playing time length of video resources, and N is the number of the video screenshots; judging whether the generated N pictures have black-white pictures or not through a black-white imaging algorithm, if partial black-white pictures exist in the screenshot, the picture is abnormal in the video resource playing process; if all the screenshots are black and white images, the video resources have no pictures; if no black-and-white image exists in the screenshot, the video resource playing picture is normal, and thus a test report is generated.
The second operation is further specifically: acquiring the time length Tb of B.wav, wherein Tb is 0 to indicate that a resource video has no sound, Tb is not 0 to indicate that the resource video has the sound, starting to play video resources, acquiring the sound output by a system sound card, saving the acquired content as C.wav, acquiring waveform array data C1 of the C.wav file, and outputting a conclusion D according to the waveform array data C1, wherein D has two conditions, D is 0 to indicate silence, and D is not equal to 0 to indicate that the sound exists; and 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, thereby generating a test report.
The invention is further illustrated below with reference to a specific embodiment, as shown in fig. 2:
1. setting an initial value; n: if the number of generated video screenshots is set to be 5, generating 5 video content screenshots at different time points;
2. uploading the test resources to obtain a test video resource A;
3. and judging whether the tested resource A is in a video format (the video formats supported currently 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 carried out by acquiring the meta-information of the video A (the video meta-information comprises the content of the duration Ta, the resolution, the frame rate and the like), if the video meta-information can be normally acquired, the video file is available, otherwise, the resource is unavailable.
5. And calling a content security service interface of a third party to identify the resource A. (the content security service capability of the Ali is called currently), and whether the resource A is involved in yellow administrative is judged through an interface response.
6. Extracting an audio part of the video A, and saving the extracted audio part as a B.wav (audio format file);
7. obtaining meta information such as time length Tb of a 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, it indicates that the resource A has no sound, and if Tb is not equal to 0, it indicates that the video A has sound);
8. playing the resource A, and simultaneously entering a flow branch 9-10 (step 9 to step 10) and a flow branch 11-13 (step 11 to step 13);
9. acquiring content screenshots of different time points of a video, wherein the interval time is Ta/N (interval time: the interval time representing screenshot action, such as a screenshot at an interval of 10 seconds);
10. and (4) judging whether the N pictures generated in the step (9) have black and white pictures. Firstly, judging whether a video can be normally captured, then judging whether the captured picture is normal or not through a black-and-white picture algorithm, and outputting a conclusion; if the screenshot has a partial black-and-white picture, the picture is considered to be abnormal in the video playing process; if all the screenshots are black and white images, the video is considered to have no picture; if no black-and-white image exists in the screenshot, the video playing picture is considered to be normal.
11. When the resource A is played, acquiring the sound output by the system sound card (the Ta value is the standard after the acquisition action is finished), and storing the acquired content as C.wav;
12. acquiring waveform array data C1 of the c.wav file, and processing C1 to output a conclusion D (D has two cases, D ═ 0 indicates no sound, D ═ 0 indicates sound);
13. and judging the Tb value in the step 7 and the D conclusion in the step 12, if Tb is 0, D is 0, and outputting the conclusion: video a has no sound; if Tb is not equal to 0, D is not equal to 0 and the conclusion is output: video A has sound; if Tb is not equal to 0 and D is 0, outputting the conclusion: recording the information of the video A and waveform data related to the video A when the audio part of the video A has difference;
14. and integrating the test results to generate a test report. The generated test report is summarized in Table 1 below
TABLE 1
As shown in fig. 3, the present invention further provides an automated video resource detection system, which includes a video availability testing module, a video content security testing module, a video content and audio testing module;
the video usability testing module is used for uploading the tested video resource, judging whether the file type of the uploaded file is in a video format, if not, ending the process, if so, acquiring the meta information of the tested video resource, judging whether the video resource is usable according to the meta information, if not, ending the process, and if so, entering the video content safety testing module; the meta information is basic information of the video resource, including playing duration, resolution and frame rate.
The video content security testing module is used for calling a content yellow identification interface, calling a content security service of a third party through the interface to perform yellow identification operation, performing yellow identification scanning on the tested resource, judging whether the tested resource relates to yellow administrative, if so, performing manual inspection and confirmation and generating a testing report, and if not, entering the video content and audio testing module;
the video content and audio testing module is used for extracting an audio part of the tested video resource, storing the audio part as B.wav, playing the video resource, and simultaneously starting the following two operations after the video resource is played;
operation one: acquiring video content screenshots of video resources at different time points to judge whether the video resources are blocked or not, so as to obtain a test report;
the first operation is further specifically: acquiring content screenshots of different time points of a video according to an interval time, wherein the interval time is Ta/N, Ta is the playing time length of video resources, and N is the number of the video screenshots; judging whether the generated N pictures have black-white pictures or not through a black-white imaging algorithm, if partial black-white pictures exist in the screenshot, the picture is abnormal in the video resource playing process; if all the screenshots are black and white images, the video resources have no pictures; if no black-and-white image exists in the screenshot, the video resource playing picture is normal, and thus a test report is generated.
And operation II: and acquiring sound output by a system sound card, storing the acquired sound as C.wav, acquiring waveform array data of the C.wav file, and judging whether the audio frequency of the video resource is abnormal or not according to the waveform array data so as to obtain a test report.
The second operation is further specifically: acquiring the time length Tb of B.wav, wherein Tb is 0 to indicate that a resource video has no sound, Tb is not 0 to indicate that the resource video has the sound, starting to play video resources, acquiring the sound output by a system sound card, saving the acquired content as C.wav, acquiring waveform array data C1 of the C.wav file, and outputting a conclusion D according to the waveform array data C1, wherein D has two conditions, D is 0 to indicate silence, and D is not equal to 0 to indicate that the sound exists; and 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, thereby generating a test report.
The above description is only a preferred embodiment of the present invention, and all equivalent changes and modifications made in accordance with the claims of the present invention should be covered by the present invention.
Claims (8)
1. An automatic detection method of video resources is characterized in that: the method comprises the following steps:
s1, uploading the tested video resource, judging whether the file type of the uploaded file is in a video format, if not, ending the process, if yes, acquiring the meta information of the tested video resource, judging whether the video resource is available according to the meta information, if not, ending the process, and if yes, entering S2;
step S2, calling a content yellow identification interface, calling a content security service of a third party through the interface to perform yellow identification operation, performing yellow identification scanning on the measured resource, judging whether yellow identification is involved, if yes, performing manual inspection and confirmation and generating a test report, and if not, entering step S3;
step S3, extracting the audio part of the tested video resource, storing as B.wav, playing the video resource, and simultaneously starting the following two operations after the video resource is played;
operation one: acquiring video content screenshots of video resources at different time points to judge whether the video resources are blocked or not, so as to obtain a test report;
and operation II: and acquiring sound output by a system sound card, storing the acquired sound as C.wav, acquiring waveform array data of the C.wav file, and judging whether the audio frequency of the video resource is abnormal or not according to the waveform array data so as to obtain a test report.
2. The method of claim 1, wherein the method comprises: the meta information is basic information of the video resource, including playing duration, resolution and frame rate.
3. The method of claim 1, wherein the method comprises: the first operation 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 the playing time of video resources, and N is the number of the video screenshots; judging whether the generated N pictures have black-white pictures or not through a black-white imaging algorithm, if partial black-white pictures exist in the screenshot, the picture is abnormal in the video resource playing process; if all the screenshots are black and white images, the video resources have no pictures; if no black-and-white image exists in the screenshot, the video resource playing picture is normal, and thus a test report is generated.
4. The method of claim 1, wherein the method comprises: the second operation is further specifically: obtaining the time length Tb of B.wav, Tb =0 indicating that the resource video has no sound, Tb ≠ 0 indicating that the resource video has sound, starting to play the video resource, obtaining the sound output by the system sound card and saving the obtained content as C.wav, obtaining the waveform array data C1 of the C.wav file, and outputting conclusion D according to the waveform array data C1, wherein D has two conditions, D =0 indicating silence, and D is not equal to 0 indicating that the sound exists; and 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, thereby generating a test report.
5. An automated video asset detection system, comprising: the system comprises a video availability test module, a video content safety test module and a video content and audio test module;
the video usability testing module is used for uploading the tested video resource, judging whether the file type of the uploaded file is in a video format, if not, ending the process, if so, acquiring the meta information of the tested video resource, judging whether the video resource is usable according to the meta information, if not, ending the process, and if so, entering the video content safety testing module;
the video content security testing module is used for calling a content yellow identification interface, calling a content security service of a third party through the interface to perform yellow identification operation, performing yellow identification scanning on the tested resource, judging whether the tested resource relates to yellow administrative, if so, performing manual inspection and confirmation and generating a testing report, and if not, entering the video content and audio testing module;
the video content and audio testing module is used for extracting an audio part of the tested video resource, storing the audio part as B.wav, playing the video resource, and simultaneously starting the following two operations after the video resource is played;
operation one: acquiring video content screenshots of video resources at different time points to judge whether the video resources are blocked or not, so as to obtain a test report;
and operation II: and acquiring sound output by a system sound card, storing the acquired sound as C.wav, acquiring waveform array data of the C.wav file, and judging whether the audio frequency of the video resource is abnormal or not according to the waveform array data so as to obtain a test report.
6. The system of claim 5, wherein: the meta information is basic information of the video resource, including playing duration, resolution and frame rate.
7. The system of claim 5, wherein: the first operation 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 the playing time of video resources, and N is the number of the video screenshots; judging whether the generated N pictures have black-white pictures or not through a black-white imaging algorithm, if partial black-white pictures exist in the screenshot, the picture is abnormal in the video resource playing process; if all the screenshots are black and white images, the video resources have no pictures; if no black-and-white image exists in the screenshot, the video resource playing picture is normal, and thus a test report is generated.
8. The system of claim 5, wherein: the second operation is further specifically: obtaining the time length Tb of B.wav, Tb =0 indicating that the resource video has no sound, Tb ≠ 0 indicating that the resource video has sound, starting to play the video resource, obtaining the sound output by the system sound card and saving the obtained content as C.wav, obtaining the waveform array data C1 of the C.wav file, and outputting conclusion D according to the waveform array data C1, wherein D has two conditions, D =0 indicating silence, and D is not equal to 0 indicating that the sound exists; and 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, thereby generating a test report.
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