CN110300325B - Video processing method and device, electronic equipment and computer readable storage medium - Google Patents
Video processing method and device, electronic equipment and computer readable storage medium Download PDFInfo
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- CN110300325B CN110300325B CN201910723197.4A CN201910723197A CN110300325B CN 110300325 B CN110300325 B CN 110300325B CN 201910723197 A CN201910723197 A CN 201910723197A CN 110300325 B CN110300325 B CN 110300325B
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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, rendering scenes according to MPEG-4 scene graphs
- H04N21/44008—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream, rendering scenes according to MPEG-4 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]
- H04N21/80—Generation or processing of content or additional data by content creator independently of the distribution process; Content per se
- H04N21/83—Generation or processing of protective or descriptive data associated with content; Content structuring
- H04N21/845—Structuring of content, e.g. decomposing content into time segments
- H04N21/8456—Structuring of content, e.g. decomposing content into time segments by decomposing the content in the time domain, e.g. in time segments
Abstract
The disclosure provides a video processing method and device, electronic equipment and a computer readable storage medium, and relates to the field of video processing. The method comprises the following steps: extracting a plurality of original frame images from an original video according to a preset frame extraction mode; according to a preset distribution mode, the multiple original frame images are sent to at least two second computing devices, so that the at least two second computing devices respectively determine the similarity between the original frame images and each frame image in the video to be processed; receiving the similarity respectively sent by the at least two second computing devices; and processing the video to be processed according to the similarity. The present disclosure increases the speed of data processing; meanwhile, the related processing based on query matching aiming at the long video is subjected to distributed processing, so that the data processing efficiency is improved, and the current large-scale video calculation processing requirement is met.
Description
Technical Field
The present disclosure relates to the field of video processing technologies, and in particular, to a video processing method and apparatus, an electronic device, and a computer-readable storage medium.
Background
Short video refers to high-frequency pushed video content played on various new media platforms, suitable for viewing in mobile and short-time leisure states, varying from a few seconds to a few minutes. The contents integrate the topics of skill sharing, humorous work, fashion trend, social hotspots, street interviews, public education and the like.
Unlike micro-movies and live broadcasts, short video production does not have the specific presentation form and team configuration requirements as do micro-movies. The short video has the characteristics of simple production flow, low manufacturing threshold, strong participation and the like.
However, the short video also brings a certain copyright problem, for example, the short video uploaded by the user may be a segment of a movie stolen, in this case, the short video uploaded by the user needs to be checked, that is, the short video uploaded by the user is compared with a legal movie video, so as to determine whether the short video uploaded by the user infringes, and if so, the uploaded short video is processed correspondingly.
In the prior art, when the time of a compared video exceeds a threshold value, a computing device cannot compare a short video with a long video; further, when the time of the compared videos does not exceed the threshold and the number of the short videos is large, the computing device needs to consume a large amount of device resources and time cost, the processing speed and efficiency are low, and the large-scale short video computing processing requirements cannot be met.
Disclosure of Invention
The present disclosure provides a video processing method, a video processing apparatus, an electronic device, and a computer-readable storage medium, which can solve the problem that in the prior art, when the time of a compared video exceeds a threshold, a computing device cannot compare a short video with a long video; further, when the time of the compared videos does not exceed the threshold value and the number of the short videos is large, the computing device needs to consume a large amount of device resources and time cost, the processing speed and efficiency are low, and the large-scale short video computing processing requirement cannot be met. The technical scheme is as follows:
in a first aspect, a method for processing a video is provided, and is applied to a first computing device, and the method includes:
extracting a plurality of original frame images from an original video according to a preset frame extraction mode;
according to a preset distribution mode, the multiple original frame images are sent to at least two second computing devices, so that the at least two second computing devices respectively determine the similarity between the original frame images and each frame image in the video to be processed;
receiving the similarity respectively sent by the at least two second computing devices;
and processing the video to be processed according to the similarity.
In a second aspect, a method for processing a video is provided, which is applied to a second computing device, and includes:
receiving an original frame image sent by a first computing device, wherein the original frame image is extracted from an original video by the first computing device according to a preset frame extraction mode;
determining the similarity between the original frame image and each frame image in the video to be processed;
and sending the similarity to third computing equipment, so that the third computing equipment processes the video to be processed according to the received similarity.
In a third aspect, an apparatus for processing a video is provided, where the apparatus is applied to a first computing device, and the apparatus includes:
the extraction module is used for extracting a plurality of original frame images from an original video according to a preset frame extraction mode;
the first sending module is used for sending the plurality of original frame images to at least two second computing devices according to a preset distribution mode, so that the at least two second computing devices respectively determine the similarity between the original frame images and each frame image in the video to be processed;
the first receiving module is used for receiving the similarity respectively sent by the at least two second computing devices;
and the processing module is used for processing the video to be processed according to the similarity.
In a fourth aspect, an apparatus for processing a video is provided, where the apparatus is applied to a second computing device, and the apparatus includes:
a second receiving module, configured to receive an original frame image sent by a first computing device, where the original frame image is extracted from an original video by the first computing device according to a preset frame extraction manner;
the computing module is used for determining the similarity between the original frame image and each frame image in the video to be processed;
and the second sending module is used for sending the similarity to third computing equipment so that the third computing equipment processes the video to be processed according to the received similarity.
In a fifth aspect, an electronic device is provided, which includes:
a memory to store instructions; and
a processor coupled with the processor, the instructions, when executed by the processor, cause the electronic device to perform operations corresponding to the method of the first or second aspect of the disclosure.
In a sixth aspect, a computer-readable storage medium is provided, on which a computer program is stored, which when executed by a processor, implements the processing method of the video shown in the first or second aspect of the present disclosure.
The technical scheme provided by the disclosure has the following beneficial effects:
the method comprises the steps that a first computing device extracts a plurality of original frame images from an original video according to a preset frame extracting mode, then sends the plurality of original frame images to at least two second computing devices according to a preset distribution mode, so that the at least two second computing devices respectively determine the similarity between the original frame images and each frame image in a video to be processed, then receives the similarity sent by the at least two second computing devices respectively, and processes the video to be processed according to the similarity. Therefore, the first computing device extracts the frame images of the original video, so that a part of data amount is reduced, and then the extracted frame images are distributed to a plurality of second computing devices to be matched with the video to be processed, so that the data processing amount of a single second computing device is further reduced, and the data processing speed is improved; meanwhile, the related processing based on query matching aiming at the long video is subjected to distributed processing, so that the data processing efficiency is improved, and the current large-scale video calculation processing requirement is met.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and features are not necessarily drawn to scale.
Fig. 1 is a schematic flowchart of a video processing method according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart of a video processing method according to another embodiment of the present disclosure;
fig. 3 is a schematic block diagram of a video processing apparatus according to another embodiment of the present disclosure;
fig. 4 is a schematic block diagram of a video processing apparatus according to another embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an electronic device for processing video according to yet another embodiment of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing the devices, modules or units, and are not used for limiting the devices, modules or units to be different devices, modules or units, and also for limiting the sequence or interdependence relationship of the functions executed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
To make the objects, technical solutions and advantages of the present disclosure more apparent, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings.
The present disclosure provides a video processing method, an apparatus, an electronic device, and a computer-readable storage medium, which are intended to solve the above technical problems in the prior art.
The following describes the technical solutions of the present disclosure and how to solve the above technical problems in specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present disclosure will be described below with reference to the accompanying drawings.
In one embodiment, a method for processing a video is provided, and applied to a first computing device, as shown in fig. 1, the method includes:
step S101, extracting a plurality of original frame images from an original video according to a preset frame extraction mode;
the video to be processed is a video with a duration less than a first threshold, and the original video is a video with a duration greater than a second threshold, for example, the original video may be a legal version video file provided by a video publisher. In the embodiment of the present disclosure, the first computing device may be first adopted to perform frame extraction processing on the original video, so as to obtain a plurality of original frame images of the original video.
Step S102, according to a preset distribution manner, sending the plurality of original frame images to at least two second computing devices, so that the at least two second computing devices respectively determine the similarity between the original frame images and each frame image in the video to be processed.
Step S103, receiving the similarity respectively sent by at least two second computing devices;
and step S104, processing the video to be processed according to the similarity.
The first computing device distributes the plurality of original frame images to the plurality of second computing devices according to a preset distribution mode, each second device determines the similarity between the original frame image and each frame image in the video to be processed respectively and sends the similarity to the first computing device, and the first computing device can process the video to be processed according to the similarity.
Therefore, the first computing device extracts the frame images of the long video, so that a part of data amount is reduced, and then the extracted frame images are distributed to a plurality of second computing devices to be matched with the video to be processed, so that the data processing amount of a single second computing device is further reduced, and the data processing speed is improved; meanwhile, the related processing based on query matching aiming at the long video is subjected to distributed processing, so that the data processing efficiency is improved, and the current large-scale video calculation processing requirement is met.
In another embodiment, a detailed description of a method for processing a video as shown in fig. 1 is continued.
Step S101, extracting a plurality of original frame images from an original video according to a preset frame extraction mode;
the video to be processed is a video with a duration less than a first threshold, and the original video is a video with a duration greater than a second threshold, for example, the original video may be a legal version video file provided by a video publisher. Generally speaking, a second of video includes 36 frames of images, and assuming that the duration of an original video is 2 hours, the original video includes 259200(120 × 60 × 36) frames of images, and if a single computing device is used to process each frame of image, on one hand, even if the performance of the computing device is sufficient, it still takes a lot of time to complete the video (for example, the video cannot be completed if the computing device is down), and on the other hand, no single computing device on the market can independently process a long video. Therefore, in the embodiment of the present disclosure, the first computing device may be used to perform frame extraction on the original video to obtain a plurality of original frame images of the original video.
In a preferred embodiment of the present disclosure, extracting a plurality of original frame images from an original video according to a preset frame extraction method includes:
dividing an original video into at least two video segments according to a preset time interval;
extracting a preset number of original frame images from at least two video clips respectively.
For example, the original video may be segmented according to units of seconds, minutes, and the like to obtain a plurality of video segments, the duration of each video segment is a preset time period, and then a preset number of original frame images are extracted from each video segment, so as to obtain a plurality of original frame images extracted from the original video. For example, for a long video with a duration of 2 hours, 2 frames of images are extracted per second, resulting in extracted 14400(120 × 60 × 2) frames of images for the long video.
Step S102, according to a preset distribution manner, sending the plurality of original frame images to at least two second computing devices, so that the at least two second computing devices respectively determine the similarity between the original frame images and each frame image in the video to be processed.
The first computing device distributes the plurality of original frame images to the plurality of second computing devices according to a preset distribution mode, so that the plurality of second computing devices can simultaneously calculate the similarity, and the data processing speed is improved.
In a preferred embodiment of the present disclosure, the sending the plurality of original frame images to the at least two second computing devices according to a preset distribution manner includes one of:
sending a plurality of original frame images to at least two second computing devices in an average distribution manner;
and sending the plurality of original frame images to the at least two second computing devices in a load balancing mode according to the current load capacity of the at least two second computing devices.
Specifically, a plurality of original frame images may be transmitted to a plurality of second computing devices in an evenly distributed manner. For example, 9 original frame images are extracted from the original video, and the 9 original frame images are sequentially sent to the second computing device A, B, C, that is, the 1 st original frame image is sent to a, the 2 nd original frame image is sent to B, the 3 rd original frame image is sent to C, the 4 th original frame image is sent to a, and so on; or, the 9 original frame images are divided into three sets and then sent to A, B, C, namely, the 1 st to 3 rd original frame images are sent to A, the 4 th to 6 th original frame images are sent to B, and the 7 th to 9 th original frame images are sent to C.
Multiple original frame images can also be sent to multiple second computing devices in a load balancing manner according to the current load capacity of each second computing device, for example, a currently processes 9 frame images, B currently processes 1 frame image, and C currently processes 3 frame images, and then the original frame images are sent to B and C respectively until A, B, C processes the same number of frame images. Of course, other distribution rules may be used to distribute the plurality of original frame images, and the disclosure is not limited thereto.
In the present disclosure, each second computing device is the same, and for convenience of description, the embodiments of the present disclosure are explained in detail based on any second computing device.
In practical application, a short video database can be preset, wherein short video files uploaded by all users are stored in the database, and if the videos uploaded by the users steal segments in a certain movie, the videos uploaded by the users can cause infringement, so that the videos uploaded by the users need to be matched with the original videos.
If the video uploaded by a certain user really steals a segment of a certain movie, the matching degree of a certain frame image in the short video file uploaded by the user and the original frame image is definitely very high. If the short video files uploaded by a plurality of users steal the same segment, the matching degree of a plurality of frame images and the original frame image is very high.
It should be noted that, in practical applications, after the user uploads the video to the short video database, the first computing device may obtain any short video from the short video database for processing.
Further, the method for performing similarity calculation between at least one received original frame image and a frame image of a video to be processed by any second computing device includes:
any second computing device respectively performs feature extraction processing on the received at least one original frame image to obtain image feature vectors corresponding to the at least one original frame image;
and according to at least one original frame image, respectively corresponding to the image characteristic vectors, and carrying out similarity calculation with the preset characteristic vectors of the frame images of the video to be processed.
In practical application, a feature vector can be generated by extracting features of any frame of image. For example, extracting the face feature information for the face recognition field may include: age, sex, whether or not to wear glasses, whether or not to have mustache, etc.; for discrete variables, such as age, conversion to a vector can be directly with a specific age value; for non-discrete variables, such as gender, the probability of being male or female may be used when converting to a vector, etc.
The embodiment of the disclosure uses the characteristic to perform feature extraction on any frame of original image to generate an original feature vector, then performs similarity calculation with the feature vector of each frame of image of the video to be processed, and uses the frame image corresponding to the feature vector with the similarity greater than or equal to the similarity threshold as the matching result of the original frame image.
It should be noted that the feature vector of each frame of image of the video to be processed can be obtained by calculation before similarity calculation, and can be directly obtained when the similarity is calculated; or the similarity can be calculated when the similarity is calculated; the similarity can also be calculated at other times without affecting the similarity calculation, which is not limited by the embodiment of the disclosure.
Further, the number of the second computing devices may be adjusted according to actual needs, and the above example is only for illustration, and the disclosure does not limit the number of the second computing devices.
Step S103, receiving the similarity respectively sent by at least two second computing devices;
in a preferred embodiment of the present disclosure, processing a video to be processed according to similarity includes:
and deleting the frame images with the similarity greater than the similarity threshold in the video to be processed.
Specifically, after determining which frame images in the video to be processed are similar, similar or identical to the original frame images, the second computing device sends the determined result to the first computing device, and the first computing device performs deduplication processing, such as deletion, on the similar, similar or identical frame images in the video to be processed, so as to obtain a deduplication processed video.
And step S104, processing the video to be processed according to the similarity.
In a preferred embodiment of the present disclosure, processing a video to be processed according to similarity includes:
and determining whether the video to be processed is an illegal video or not according to the similarity.
For example, when the number of frame images with similarity greater than the similarity threshold in the video to be processed exceeds a preset threshold, or the ratio of frame images with similarity greater than the similarity threshold in the video to be processed exceeds a preset ratio threshold, it may be determined whether the video to be processed is an illegal video.
Further, each short video file in the short video database has corresponding attribute information, such as uploading a user ID, a short video type, and the like, so that a frame image of each short video also has corresponding attribute information. Moreover, because the matching is performed on a frame-by-frame basis, it may happen that multiple second computing devices all match the same short video uploaded by the same user. Therefore, when receiving a plurality of pieces of same attribute information, the third computing device may reserve one or all of the pieces of attribute information after merging, and may also perform processing in other manners, which is not limited in this disclosure.
If only one attribute information exists after the combination, the short video file corresponding to the attribute information is the target video, if a plurality of attribute information exist after the combination, the short video file corresponding to each attribute information is the target video, namely the infringement short video, and then the target video is subjected to de-duplication processing to obtain the de-duplicated video.
The first computing device and the second computing device may have the following characteristics:
(1) on a hardware architecture, a device has a central processing unit, a memory, an input unit and an output unit, that is, the device is often a microcomputer device having a communication function. In addition, various input modes such as a keyboard, a mouse, a touch screen, a microphone, a camera and the like can be provided, and input can be adjusted as required. Meanwhile, the equipment often has a plurality of output modes, such as a telephone receiver, a display screen and the like, and can be adjusted according to needs;
(2) on a software system, the device must have an operating system, such as Windows Mobile, Symbian, Palm, Android, iOS, and the like. Meanwhile, the operating systems are more and more open, and personalized application programs developed based on the open operating system platforms are infinite, such as a communication book, a schedule, a notebook, a calculator, various games and the like, so that the requirements of personalized users are met to a great extent;
(3) in terms of communication capacity, the device has flexible access mode and high-bandwidth communication performance, and can automatically adjust the selected communication mode according to the selected service and the environment, thereby being convenient for users to use. The device can support GSM (Global System for Mobile Communication), WCDMA (Wideband Code Division Multiple Access), CDMA2000(Code Division Multiple Access), TDSCDMA (Time Division-Synchronous Code Division Multiple Access), Wi-Fi (Wireless-Fidelity), WiMAX (world Interoperability for Microwave Access) and the like, thereby being suitable for various types of networks, and not only supporting voice services, but also supporting various Wireless data services;
(4) in the aspect of function use, the equipment focuses more on humanization, individuation and multi-functionalization. With the development of computer technology, devices enter a human-centered mode from a device-centered mode, and the embedded computing, control technology, artificial intelligence technology, biometric authentication technology and the like are integrated, so that the human-oriented purpose is fully embodied. Due to the development of software technology, the equipment can be adjusted and set according to individual requirements, and is more personalized. Meanwhile, the device integrates a plurality of software and hardware, and the function is more and more powerful.
In the embodiment of the disclosure, a first computing device extracts a plurality of original frame images from an original video according to a preset frame extraction mode, and then sends the plurality of original frame images to at least two second computing devices according to a preset distribution mode, so that the at least two second computing devices respectively perform similarity computing processing on the received original frame images and a video to be processed to obtain a computing result. Therefore, the first computing device extracts the frame images of the long video, so that a part of data amount is reduced, and then the extracted frame images are distributed to a plurality of second computing devices to be matched with the video to be processed, so that the data processing amount of a single second computing device is further reduced, and the data processing speed is improved; meanwhile, the related processing based on query matching aiming at the long video is subjected to distributed processing, so that the data processing efficiency is improved, and the current large-scale video calculation processing requirement is met.
In another embodiment, a method for processing a video is provided, which is applied to a second computing device, as shown in fig. 2, and includes:
step S201, receiving an original frame image sent by a first computing device, wherein the original frame image is extracted from an original video by the first computing device according to a preset frame extraction mode;
step S202, determining the similarity between the original frame image and each frame image in the video to be processed;
step S203, sending the similarity to a third computing device, so that the third computing device processes the video to be processed according to the received similarity.
Specifically, after determining which frame images in the video to be processed are similar, similar or identical to the original frame images, the second computing device sends the determined result to a third computing device, and the third computing device performs deduplication processing, such as deletion, on the similar, similar or identical frame images in the video to be processed, so as to obtain a deduplication processed video.
In a preferred embodiment of the present disclosure, the video to be processed is a video with a duration less than the first threshold, for example, the video to be processed may be a short video; the original video is a video with a duration greater than the second threshold, for example, the original video may be a video of a movie or the like.
The video processing method according to the embodiment of the present disclosure is similar to the video processing method according to the first embodiment of the present disclosure in the implementation principle, and is not described here again.
In the embodiment of the disclosure, after any second computing device receives an original frame image sent by a first computing device, the similarity between the original frame image and each frame image in a video to be processed is determined; the method comprises the steps that an original frame image is extracted from an original video by a first computing device according to a preset frame extraction mode; and then sending the similarity to third computing equipment so that the third computing equipment processes the video to be processed according to the received similarity. In this way, the first computing device extracts the frame images of the long video, so that a part of data amount is reduced, and then the extracted frame images are distributed to a plurality of second computing devices to be matched with the video to be processed, so that the data processing amount of a single second computing device is further reduced, and the data processing speed is improved; meanwhile, the related processing based on query matching aiming at the long video is subjected to distributed processing, so that the data processing efficiency is improved, and the current large-scale video calculation processing requirement is met.
Fig. 3 is a schematic structural diagram of a video processing apparatus according to another embodiment of the present disclosure, and as shown in fig. 3, the apparatus of this embodiment may include:
an extracting module 301, configured to extract a plurality of original frame images from an original video according to a preset frame extracting manner;
a first sending module 302, configured to send a plurality of original frame images to at least two second computing devices according to a preset distribution manner, so that the at least two second computing devices respectively determine similarities between the original frame images and each frame image in the video to be processed;
a first receiving module 303, configured to receive similarity degrees respectively sent by at least two second computing devices;
and the processing module 304 is configured to process the video to be processed according to the similarity.
In a preferred embodiment of the present disclosure, the extraction module includes:
the dividing submodule is used for dividing the original video into at least two video segments according to a preset time interval;
and the original frame image extraction sub-module is used for respectively extracting a preset number of original frame images from the at least two video clips.
In a preferred embodiment of the present disclosure, the first sending module is specifically configured to:
sending a plurality of original frame images to at least two second computing devices in an average distribution manner;
or the like, or, alternatively,
and sending the plurality of original frame images to the at least two second computing devices in a load balancing mode according to the current load capacity of the at least two second computing devices.
In a preferred embodiment of the present disclosure, the processing module is specifically configured to:
and deleting the frame images with the similarity greater than the similarity threshold in the video to be processed.
In a preferred embodiment of the present disclosure, the processing module is specifically configured to:
and determining whether the video to be processed is an illegal video or not according to the similarity.
In a preferred embodiment of the present disclosure, the video to be processed is a video with a duration less than a first threshold, and the original video is a video with a duration greater than a second threshold.
The video processing apparatus of this embodiment can execute the video processing method shown in the first embodiment of this disclosure, and the implementation principles thereof are similar, and are not described herein again.
In the embodiment of the disclosure, a first computing device extracts a plurality of original frame images from an original video according to a preset frame extraction mode, and then sends the plurality of original frame images to at least two second computing devices according to a preset distribution mode, so that the at least two second computing devices respectively perform similarity computing processing on the received original frame images and a video to be processed to obtain a computing result. Therefore, the first computing device extracts the frame images of the original video, so that a part of data amount is reduced, and then the extracted frame images are distributed to a plurality of second computing devices to be matched with the video to be processed, so that the data processing amount of a single second computing device is further reduced, and the data processing speed is improved; meanwhile, the related processing based on query matching aiming at the long video is subjected to distributed processing, so that the data processing efficiency is improved, and the current large-scale video calculation processing requirement is met.
Fig. 4 is a schematic structural diagram of a video processing apparatus according to still another embodiment of the present disclosure, and as shown in fig. 4, the apparatus of this embodiment may include:
a second receiving module 401, configured to receive an original frame image sent by a first computing device, where the original frame image is extracted from an original video by the first computing device according to a preset frame extraction manner;
a calculating module 402, configured to determine similarity between an original frame image and each frame image in a video to be processed;
the second sending module 403 is configured to send the similarity to the third computing device, so that the third computing device processes the video to be processed according to the received similarity.
In a preferred embodiment of the present disclosure, the video to be processed is a video with a duration less than a first threshold, and the original video is a video with a duration greater than a second threshold.
The video processing apparatus of this embodiment can execute the video processing method according to the second embodiment of the present disclosure, and the implementation principles thereof are similar, and are not described herein again.
In the embodiment of the disclosure, after receiving an original frame image sent by a first computing device, a second computing device determines the similarity between the original frame image and each frame image in a video to be processed; the method comprises the steps that an original frame image is extracted from an original video by a first computing device according to a preset frame extraction mode; and then sending the similarity to third computing equipment so that the third computing equipment processes the video to be processed according to the received similarity. In this way, the first computing device extracts the frame images of the long video, so that a part of data amount is reduced, and then the extracted frame images are distributed to a plurality of second computing devices to be matched with the video to be processed, so that the data processing amount of a single second computing device is further reduced, and the data processing speed is improved; meanwhile, the related processing based on query matching aiming at the long video is subjected to distributed processing, so that the data processing efficiency is improved, and the current large-scale video calculation processing requirement is met.
Referring now to FIG. 5, a block diagram of an electronic device 500 suitable for use in implementing embodiments of the present disclosure is shown. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., car navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
The electronic device includes: a memory and a processor, wherein the processor may be referred to as a processing device 501 described below, and the memory may include at least one of a Read Only Memory (ROM)502, a Random Access Memory (RAM)503, and a storage device 508, which are described below:
as shown in fig. 5, electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
Generally, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage devices 508 including, for example, magnetic tape, hard disk, etc.; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 5 illustrates an electronic device 500 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program performs the above-described functions defined in the methods of the embodiments of the present disclosure when executed by the processing device 501.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: extracting a plurality of original frame images from an original video according to a preset frame extraction mode; and sending the plurality of original frame images to at least two second computing devices according to a preset distribution mode, so that the at least two second computing devices respectively perform similarity computing processing on the received original frame images and the video to be processed to obtain computing results.
Computer program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including but not limited to an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules or units described in the embodiments of the present disclosure may be implemented by software or hardware. Wherein the designation of a module or unit does not in some cases constitute a limitation of the unit itself.
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
According to one or more embodiments of the present disclosure, [ example one ] there is provided a video processing method, comprising:
extracting a plurality of original frame images from an original video according to a preset frame extraction mode;
according to a preset distribution mode, the multiple original frame images are sent to at least two second computing devices, so that the at least two second computing devices respectively determine the similarity between the original frame images and each frame image in the video to be processed;
receiving the similarity respectively sent by the at least two second computing devices;
and processing the video to be processed according to the similarity.
Preferably, the extracting a plurality of original frame images from an original video according to a preset frame extraction method includes:
dividing the original video into at least two video segments according to a preset time interval;
extracting a preset number of original frame images from the at least two video segments respectively.
Preferably, the sending the plurality of original frame images to at least two second computing devices according to a preset distribution manner includes one of:
sending the plurality of original frame images to at least two second computing devices in an average distribution manner;
and sending the plurality of original frame images to the at least two second computing devices in a load balancing manner according to the current load amounts of the at least two second computing devices.
Preferably, the processing the video to be processed according to the similarity includes:
and deleting the frame images with the similarity greater than the similarity threshold value in the video to be processed.
Preferably, the processing the video to be processed according to the similarity includes:
and determining whether the video to be processed is an illegal video or not according to the similarity.
Preferably, the video to be processed is a video with a duration less than a first threshold, and the original video is a video with a duration greater than a second threshold.
According to one or more embodiments of the present disclosure, [ example two ] there is provided the apparatus of example one, further comprising:
the extraction module is used for extracting a plurality of original frame images from an original video according to a preset frame extraction mode;
the first sending module is used for sending the plurality of original frame images to at least two second computing devices according to a preset distribution mode, so that the at least two second computing devices respectively determine the similarity between the original frame images and each frame image in the video to be processed;
the first receiving module is used for receiving the similarity respectively sent by the at least two second computing devices;
and the processing module is used for processing the video to be processed according to the similarity.
Preferably, the extraction module comprises:
the dividing submodule is used for dividing the original video into at least two video segments according to a preset time interval;
and the original frame image extraction sub-module is used for respectively extracting a preset number of original frame images from the at least two video clips.
Preferably, the first sending module is specifically configured to:
sending the plurality of original frame images to at least two second computing devices in an average distribution manner;
or the like, or, alternatively,
and sending the plurality of original frame images to the at least two second computing devices in a load balancing manner according to the current load amounts of the at least two second computing devices.
Preferably, the processing module is specifically configured to:
and deleting the frame images with the similarity greater than the similarity threshold value in the video to be processed.
Preferably, the processing module is specifically configured to:
and determining whether the video to be processed is an illegal video or not according to the similarity.
Preferably, the video to be processed is a video with a duration less than a first threshold, and the original video is a video with a duration greater than a second threshold.
According to one or more embodiments of the present disclosure, [ example three ] there is provided a video processing method, comprising:
receiving an original frame image sent by a first computing device, wherein the original frame image is extracted from an original video by the first computing device according to a preset frame extraction mode;
determining the similarity between the original frame image and each frame image in the video to be processed;
and sending the similarity to third computing equipment, so that the third computing equipment processes the video to be processed according to the received similarity.
Preferably, the video to be processed is a video with a duration less than a first threshold, and the original video is a video with a duration greater than a second threshold.
According to one or more embodiments of the present disclosure, [ example four ] there is provided the apparatus of example three, further comprising:
a second receiving module, configured to receive an original frame image sent by a first computing device, where the original frame image is extracted from an original video by the first computing device according to a preset frame extraction manner;
the computing module is used for determining the similarity between the original frame image and each frame image in the video to be processed;
and the second sending module is used for sending the similarity to third computing equipment so that the third computing equipment processes the video to be processed according to the received similarity.
Preferably, the video to be processed is a video with a duration less than a first threshold, and the original video is a video with a duration greater than a second threshold.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other embodiments in which any combination of the features described above or their equivalents does not depart from the spirit of the disclosure. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.
Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
Claims (9)
1. A video processing method applied to a first computing device comprises the following steps:
extracting a plurality of original frame images from an original video according to a preset frame extraction mode;
according to a preset distribution mode, the multiple original frame images are sent to at least two second computing devices, so that the at least two second computing devices respectively perform feature extraction processing on the received original frame images to obtain image feature vectors corresponding to the original frame images, similarity calculation is performed on the image feature vectors corresponding to the original frame images and preset feature vectors of frame images of the video to be processed respectively according to the image feature vectors corresponding to the original frame images, and the similarity between the original frame images and each frame image in the video to be processed is determined;
the sending the plurality of original frame images to at least two second computing devices according to a preset distribution mode comprises one of the following steps: sending the plurality of original frame images to at least two second computing devices in an average distribution manner; according to the current load capacity of the at least two second computing devices, sending the plurality of original frame images to the at least two second computing devices in a load balancing mode;
the video to be processed is a video with the duration less than a first threshold, and the original video is a video with the duration greater than a second threshold;
receiving the similarity respectively sent by the at least two second computing devices;
and processing the video to be processed according to the similarity.
2. The method of claim 1, wherein the extracting a plurality of original frame images from an original video according to a predetermined frame extraction manner comprises:
dividing the original video into at least two video segments according to a preset time interval;
extracting a preset number of original frame images from the at least two video segments respectively.
3. The method according to claim 1, wherein the processing the video to be processed according to the similarity includes:
and deleting the frame images with the similarity greater than the similarity threshold value in the video to be processed.
4. The method according to claim 1, wherein the processing the video to be processed according to the similarity includes:
and determining whether the video to be processed is an illegal video or not according to the similarity.
5. A method for processing video, applied to a second computing device, includes:
receiving an original frame image sent by a first computing device, wherein the original frame image is extracted from an original video by the first computing device according to a preset frame extraction mode;
the original frame image is sent by the first computing device according to a preset distribution mode; the preset distribution mode comprises one of the following modes: sending a plurality of original frame images to at least two second computing devices in an average distribution manner; according to the current load capacity of at least two second computing devices, sending a plurality of original frame images to the at least two second computing devices in a load balancing mode;
performing feature extraction processing on the received original frame image to obtain image feature vectors corresponding to the original frame image respectively, and performing similarity calculation with preset feature vectors of frame images of a video to be processed respectively according to the image feature vectors corresponding to the original frame image respectively to determine the similarity between the original frame image and each frame image in the video to be processed; sending the similarity to third computing equipment, so that the third computing equipment processes the video to be processed according to the received similarity;
the video to be processed is a video with the duration less than a first threshold, and the original video is a video with the duration greater than a second threshold.
6. A video processing apparatus, applied to a first computing device, comprising:
the extraction module is used for extracting a plurality of original frame images from an original video according to a preset frame extraction mode;
the first sending module is used for sending the plurality of original frame images to at least two second computing devices according to a preset distribution mode, so that the at least two second computing devices respectively perform feature extraction processing on the received original frame images to obtain image feature vectors respectively corresponding to the original frame images, and respectively perform similarity calculation with preset feature vectors of frame images of the video to be processed according to the image feature vectors respectively corresponding to the original frame images to determine the similarity between the original frame images and each frame image in the video to be processed;
the sending the plurality of original frame images to at least two second computing devices according to a preset distribution mode comprises one of the following steps: sending the plurality of original frame images to at least two second computing devices in an average distribution manner; according to the current load capacity of the at least two second computing devices, sending the plurality of original frame images to the at least two second computing devices in a load balancing mode;
the video to be processed is a video with the duration less than a first threshold, and the original video is a video with the duration greater than a second threshold;
the first receiving module is used for receiving the similarity respectively sent by the at least two second computing devices;
and the processing module is used for processing the video to be processed according to the similarity.
7. A video processing apparatus, applied to a second computing device, comprising:
a second receiving module, configured to receive an original frame image sent by a first computing device, where the original frame image is extracted from an original video by the first computing device according to a preset frame extraction manner;
the original frame image is sent by the first computing device according to a preset distribution mode; the preset distribution mode comprises one of the following modes: sending a plurality of original frame images to at least two second computing devices in an average distribution manner; according to the current load capacity of at least two second computing devices, sending a plurality of original frame images to the at least two second computing devices in a load balancing mode;
the computing module is used for performing feature extraction processing on the received original frame images to obtain image feature vectors corresponding to the original frame images respectively, performing similarity computation with preset feature vectors of frame images of the video to be processed respectively according to the image feature vectors corresponding to the original frame images respectively, and determining the similarity between the original frame images and each frame image in the video to be processed; the second sending module is used for sending the similarity to third computing equipment so that the third computing equipment can process the video to be processed according to the received similarity;
the video to be processed is a video with the duration less than a first threshold, and the original video is a video with the duration greater than a second threshold.
8. An electronic device, comprising:
a memory to store instructions; and
a processor coupled with the memory, the instructions when executed by the processor causing the electronic device to perform the method of any of claims 1-5.
9. A computer-readable storage medium for storing computer instructions which, when executed on a computer, cause the computer to perform the method of any one of claims 1-5.
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| CN111696105B (en) * | 2020-06-24 | 2023-05-23 | 北京金山云网络技术有限公司 | Video processing method and device and electronic equipment |
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| CN109672902A (en) * | 2018-12-25 | 2019-04-23 | 百度在线网络技术（北京）有限公司 | A kind of video takes out frame method, device, electronic equipment and storage medium |
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