CN110113642B - ABS algorithm evaluation method and device - Google Patents
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- H—ELECTRICITY
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/234—Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
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- H—ELECTRICITY
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
- H04N21/266—Channel or content management, e.g. generation and management of keys and entitlement messages in a conditional access system, merging a VOD unicast channel into a multicast channel
- H04N21/2662—Controlling the complexity of the video stream, e.g. by scaling the resolution or bitrate of the video stream based on the client capabilities
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- 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
- H04N21/4402—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 reformatting operations of video signals for household redistribution, storage or real-time display
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Abstract
The embodiment of the invention provides an ABS algorithm evaluation method and device, comprising the following steps: aiming at an ABS algorithm to be evaluated, playing experience data from a plurality of clients are obtained, the playing experience data are playing experience data when the clients play videos according to target code rates, the target code rates are code rates determined by the ABS algorithm to be evaluated based on video playing parameters from the clients, the video playing parameters are video playing parameters when the clients play videos according to the code rates before the target code rates, the playing experience data represent the playing effect of the videos, and based on the acquired playing experience data from a plurality of clients, the playing experience index of the ABS algorithm to be evaluated is calculated, and comparing the playing experience index with the scale index to obtain the evaluation result of the ABS algorithm to be evaluated, the scale index is a playing experience index calculated when the video is played according to the preset code rate, and the time period of evaluation and adjustment of the ABS algorithm can be shortened.
Description
Technical Field
The invention relates to the technical field of videos, in particular to an ABS algorithm evaluation method and device.
Background
With the development of network technology, more and more users like to watch videos through the network, and with the continuous improvement of the quantity and quality of video contents in the network, the requirements of the users on the watching experience of internet videos are higher and higher. The definition and the fluency of video playing are the two most important factors influencing the viewing experience, generally speaking, the higher the code rate of a video is, the higher the definition of the video playing is, but the video with the too high code rate is often jammed and pause during playing, so that the fluency of video playing is reduced.
In order to balance the definition and the fluency during video playing, for the same playing content, a video service provider often provides a plurality of videos with fixed bit rates for a user to select when providing video services. When watching the video, the user can manually select the video with the proper code rate to watch according to the watching experience of the user. When a user watches a video, the user feels that the definition of the video cannot meet the requirement, the user can manually select the video with higher code rate, and when pause frequently occurs in the video playing process, the user can manually select to reduce the code rate to watch the video, so that the smoothness of watching the video is ensured.
Through the fact that the user manually selects the code rate for playing the video, although the definition and the fluency of the video playing can be balanced, the frequent manual selection of the code rate by the user may influence the watching experience of the user to a certain extent. Therefore, an ABS (Adaptive bit stream) technology is mostly adopted to enable the player to automatically select the code rate suitable for the current playing environment, and the implementation manner of the ABS technology is to build an ABS algorithm in the player, and the ABS algorithm determines the code rate suitable for the current playing environment according to the actual playing environment of the player, thereby avoiding the frequent manual code rate selection of the user.
In order to continuously optimize the ABS algorithm and improve the algorithm effect of the ABS algorithm, the algorithm effect of the ABS algorithm generally needs to be evaluated, when the algorithm effect of one ABS algorithm is evaluated, a player in a test area needs to be upgraded to a player including the ABS algorithm to be evaluated, video playing data of the player in the test area is collected, an evaluation result of the ABS algorithm is obtained by analyzing the playing data, and when the evaluation result of the ABS algorithm does not meet a requirement and the ABS algorithm needs to be adjusted, for example, the ABS algorithm needs to be optimized, the player needs to be upgraded to a player including the upgraded ABS algorithm again.
The inventor finds that the prior art at least has the following problems in the process of implementing the invention:
the method for building the ABS algorithm into the player needs to upgrade the player when evaluating and adjusting the ABS algorithm, and the time period is long.
Disclosure of Invention
The embodiment of the invention aims to provide an ABS algorithm evaluation method and device so as to shorten the time period for evaluating and adjusting the ABS algorithm. The specific technical scheme is as follows:
the embodiment of the invention provides an ABS algorithm evaluation method, which comprises the following steps:
the method comprises the steps that aiming at an ABS algorithm to be evaluated, playing experience data from a plurality of clients are obtained, the playing experience data are playing experience data when the clients play videos according to target code rates, the target code rates are code rates determined by the ABS algorithm to be evaluated based on video playing parameters from the clients, the video playing parameters are video playing parameters when the clients play videos according to the code rates before the target code rates, and the playing experience data represent the playing effect of the videos;
based on the acquired playing experience data from the plurality of clients, calculating a playing experience index of the ABS algorithm to be evaluated;
and comparing the playing experience index with a scale index to obtain an evaluation result of the ABS algorithm to be evaluated, wherein the scale index is the playing experience index calculated when video playing is carried out according to a preset code rate.
Further, the playing experience data includes a code rate and a pause time, and the playing experience index includes: a clarity index and a fluency index;
the calculating the playing experience index of the ABS algorithm to be evaluated based on the obtained playing experience data from the plurality of clients includes:
adding the code rates in the playing experience data from the plurality of clients to obtain a definition index of the ABS algorithm to be evaluated;
and adding the pause times in the playing experience data from the plurality of clients to obtain the fluency index of the ABS algorithm to be evaluated.
Further, the scale indicator includes: the method comprises the steps of obtaining a definition scale index and a fluency scale index, wherein the definition scale index is a definition index obtained by calculation when video playing is carried out according to a preset code rate, and the fluency scale index is a fluency index obtained by calculation when video playing is carried out according to the preset code rate;
the preset code rate comprises an original code rate, a maximum code rate and a minimum code rate of a played video;
the comparing the playing experience index with the scale index to obtain the evaluation result of the ABS algorithm to be evaluated includes:
judging whether the clarity index of the ABS algorithm to be evaluated is between the clarity scale index of the minimum code rate and the clarity scale index of the maximum code rate, and whether the fluency index of the ABS algorithm to be evaluated is between the fluency scale index of the minimum code rate and the fluency scale index of the maximum code rate;
and if so, determining that the ABS algorithm to be evaluated is a reasonable ABS algorithm.
Further, the playing experience index further includes: comprehensively evaluating indexes;
the scale index further includes: the comprehensive evaluation scale index is obtained by weighting and summing the definition scale index and the fluency scale index;
the method further comprises the following steps:
calculating the weighted sum of the definition index and the fluency index of the ABS algorithm to be evaluated according to the respective weights of the definition index and the fluency index of the ABS algorithm to be evaluated, and taking the weighted sum as the comprehensive evaluation index of the ABS algorithm to be evaluated;
when the ABS algorithm to be evaluated is a reasonable ABS algorithm, judging whether the comprehensive evaluation index of the ABS algorithm to be evaluated is larger than the comprehensive evaluation scale index of the original code rate;
and if so, determining the ABS algorithm to be evaluated as a qualified ABS algorithm.
The embodiment of the invention also provides a code rate determining method, which is applied to a client and comprises the following steps:
collecting video playing parameters when video playing is carried out according to the current code rate;
sending the video playing parameters to a server;
receiving a target code rate sent by the server, wherein the target code rate is a code rate which is determined by an ABS algorithm distributed for the client and is required to be adopted by the client based on the video playing parameter;
according to the received target code rate, video playing is carried out;
collecting playing experience data when the video is played according to the target code rate, wherein the playing experience data represents the playing effect of the video;
and sending the playing experience data to the server, wherein the playing experience data is used for evaluating the ABS algorithm.
The embodiment of the invention also provides a code rate determining method, which is applied to a server and comprises the following steps:
receiving video playing parameters sent by a client, wherein the video playing parameters are video playing parameters when the client plays videos according to the current code rate;
distributing an ABS algorithm for the client;
determining a code rate required to be adopted by the client as a target code rate by adopting the distributed ABS algorithm based on the video playing parameters;
sending the target code rate to the client;
and receiving playing experience data sent by the client, wherein the playing experience data is playing experience data when the client plays the video according to the target code rate, represents the playing effect of the video and is used for evaluating the ABS algorithm.
The embodiment of the invention also provides an ABS algorithm evaluation device, which comprises:
the data acquisition module is used for acquiring playing experience data from a plurality of clients aiming at an ABS algorithm to be evaluated, wherein the playing experience data is playing experience data when the clients play videos according to target code rates, the target code rates are code rates determined by the ABS algorithm to be evaluated based on video playing parameters from the clients, the video playing parameters are video playing parameters when the clients play videos according to the code rates before the target code rates, and the playing experience data represents the playing effect of the videos;
the index calculation module is used for calculating the playing experience indexes of the ABS algorithm to be evaluated based on the obtained playing experience data from the plurality of clients;
and the index comparison module is used for comparing the playing experience index with a scale index to obtain an evaluation result of the ABS algorithm to be evaluated, wherein the scale index is the playing experience index calculated when the video is played according to a preset code rate.
Further, the playing experience data includes a code rate and a pause time, and the playing experience index includes: a clarity index and a fluency index;
the index calculation module is specifically configured to add the code rates in the playing experience data from the multiple clients to obtain a clarity index of the ABS algorithm to be evaluated, and add the stuck times in the playing experience data from the multiple clients to obtain a fluency index of the ABS algorithm to be evaluated.
Further, the scale indicator includes: the method comprises the steps of obtaining a definition scale index and a fluency scale index, wherein the definition scale index is a definition index obtained by calculation when video playing is carried out according to a preset code rate, and the fluency scale index is a fluency index obtained by calculation when video playing is carried out according to the preset code rate; the preset code rate comprises an original code rate, a maximum code rate and a minimum code rate of a played video;
the index comparison module is specifically configured to determine whether the clarity index of the ABS algorithm to be evaluated is between the clarity scale index of the minimum code rate and the clarity scale index of the maximum code rate, and whether the fluency index of the ABS algorithm to be evaluated is between the fluency scale index of the minimum code rate and the fluency scale index of the maximum code rate, and if both are true, determine that the ABS algorithm to be evaluated is a reasonable ABS algorithm.
Further, the playing experience index further includes: comprehensively evaluating indexes; the scale index further includes: the comprehensive evaluation scale index is obtained by weighting and summing the definition scale index and the fluency scale index;
the index comparison module is specifically configured to calculate a weighted sum of the definition index and the fluency index of the ABS algorithm to be evaluated according to respective weights of the definition index and the fluency index of the ABS algorithm to be evaluated, to serve as a comprehensive evaluation index of the ABS algorithm to be evaluated, and when the ABS algorithm to be evaluated is a reasonable ABS algorithm, determine whether the comprehensive evaluation index of the ABS algorithm to be evaluated is greater than a comprehensive evaluation scale index of the original code rate, and if so, determine that the ABS algorithm to be evaluated is a qualified ABS algorithm.
The embodiment of the present invention further provides an ABS algorithm evaluation system, including: a client and a server;
the client is used for collecting video playing parameters when video playing is carried out according to the current code rate and sending the video playing parameters to the server;
the server is used for receiving the video playing parameters sent by the client, distributing an ABS algorithm to the client according to a preset distribution strategy, determining a code rate required to be adopted by the client as a target code rate by adopting the distributed ABS algorithm based on the video playing parameters, and sending the target code rate to the client;
the client is further configured to receive the target code rate sent by the server, perform video playing according to the received target code rate, collect playing experience data during video playing according to the target code rate, where the playing experience data represents a playing effect of a video, and send the playing experience data to the server;
the server is further configured to receive the playing experience data sent by the client, and evaluate the ABS algorithm according to the playing experience data.
Embodiments of the present invention also provide an electronic device, including a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor, the processor being caused by the machine-executable instructions to: and implementing the steps of any one of the ABS algorithm evaluation methods.
The invention also provides a computer-readable storage medium, in which a computer program is stored, and when the computer program is executed by a processor, the steps of any one of the above ABS algorithm evaluation methods are implemented.
Embodiments of the present invention further provide a computer program product containing instructions, which when run on a computer, cause the computer to execute any one of the above ABS algorithm evaluation methods.
In the scheme, aiming at an ABS algorithm to be evaluated, playing experience data from a plurality of clients are obtained, the playing experience data are playing experience data when the clients play videos according to target code rates, the target code rates are code rates determined by the ABS algorithm to be evaluated based on video playing parameters from the clients, the video playing parameters are video playing parameters when the clients play videos according to code rates before the target code rates are adopted, the playing experience data represent the playing effect of the videos, the playing experience indexes of the ABS algorithm to be evaluated are calculated based on the obtained playing experience data from the clients, and the playing experience indexes are compared with scale indexes to obtain the evaluation result of the ABS algorithm to be evaluated, wherein the scale indexes are playing experience indexes calculated when the videos are played according to preset code rates, the ABS algorithm is provided for the client through the server, when the ABS algorithm needs to be evaluated, the ABS algorithm to be evaluated can be distributed to the client which currently requests ABS algorithm service, so that playing experience data of the ABS algorithm to be evaluated can be obtained in real time, time for upgrading the client in the prior art is reduced, the client does not need to be upgraded according to an evaluation result when the ABS algorithm to be evaluated needs to be adjusted, the ABS algorithm to be evaluated can be adjusted in the server, and time periods for evaluating and adjusting the ABS algorithm are reduced.
Of course, not all of the advantages described above need to be achieved at the same time in the practice of any one product or method of the invention.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below.
FIG. 1 is a flow chart of an ABS algorithm evaluation method according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for determining a code rate applied to a client according to an embodiment of the present invention;
fig. 3 is a flowchart of a code rate determining method applied to a server according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an ABS algorithm evaluation apparatus according to an embodiment of the present invention;
FIG. 5 is a schematic structural diagram of an ABS algorithm evaluation system according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention;
fig. 7 is a schematic diagram of a code rate determination principle according to an embodiment of the present invention.
Detailed Description
In order to provide an implementation scheme for shortening the time period for evaluating and adjusting the ABS algorithm, the embodiment of the invention provides an ABS algorithm evaluation method and an ABS algorithm evaluation device, and the following describes the embodiment of the invention with reference to the drawings in the specification. And the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
In one embodiment of the present invention, an ABS algorithm evaluation method is provided, as shown in fig. 1, the method comprising the steps of:
s101: the method comprises the steps of acquiring playing experience data from a plurality of clients aiming at an ABS algorithm to be evaluated, wherein the playing experience data are playing experience data when the clients play videos according to target code rates, the target code rates are determined by the ABS algorithm to be evaluated based on video playing parameters from the clients, the video playing parameters are video playing parameters when the clients play videos according to code rates before the target code rates, and the playing experience data represent the playing effect of the videos.
In this step, the execution subject may be a server, in order to continuously optimize the ABS algorithm and improve the algorithm effect of the ABS algorithm, the algorithm effect of the ABS algorithm needs to be evaluated, and for the ABS algorithm to be evaluated, the playing experience data from the multiple clients may be acquired.
In an embodiment, the playing experience data may be playing experience data when each client performs video playing according to a target code rate, where the target code rate is a code rate determined by an ABS algorithm to be evaluated based on a video playing parameter from the client, the video playing parameter is a video playing parameter when the client performs video playing according to a code rate before the target code rate, and the playing experience data represents a playing effect of the video.
In one embodiment, the plurality of clients may be clients with the same preset attribute, for example, the plurality of clients are clients with the same operating system, for example, the plurality of clients are clients with an android operating system, or may be clients that provide services using the same network service provider in the same region.
S102: and calculating the playing experience indexes of the ABS algorithm to be evaluated based on the obtained playing experience data from the plurality of clients.
In this step, the playing experience index of the ABS algorithm to be evaluated may be calculated based on the obtained playing experience data from the multiple clients, and in order to evaluate the ABS algorithm to be evaluated more comprehensively, in an embodiment, the playing experience data may be obtained within a preset time, and the playing experience data may include a code rate and a stuck number, and the corresponding playing experience index may include: in an embodiment, the clarity index of the ABS algorithm to be evaluated may be obtained by adding code rates in the playing experience data from the plurality of clients, and the fluency index of the ABS algorithm to be evaluated may be obtained by adding stuck times in the playing experience data from the plurality of clients. For example, in step S101, the playing experience data of two clients, specifically, the client 1 and the client 2, is obtained, and for the client 1: the code rate is 1Mbit/s, and the calorie-on times are 1-2; for client 2: the code rate is 1-2 Mbit/s, and the number of times of clamping is 1-5. Then for the ABS algorithm to be evaluated, the sharpness indicator 1Mbit/s +2Mbit/s 3Mbit/s, in one embodiment, may be unified, so that the units may be omitted, i.e., sharpness indicator 1+2 3 and fluency indicator 2+5 7.
S103: and comparing the playing experience index with the scale index to obtain an evaluation result of the ABS algorithm to be evaluated, wherein the scale index is the playing experience index calculated when the video is played according to the preset code rate.
In this step, the playing experience index may be compared with the scale index to obtain an evaluation result of the ABS algorithm to be evaluated, and in one embodiment, the scale index may be a playing experience index calculated when the video is played according to a preset code rate. In one embodiment the scale indicator comprises: the video display device comprises a definition scale index and a fluency scale index, wherein the definition scale index is a definition index obtained by calculation when video playing is carried out according to a preset code rate, and the fluency scale index is a fluency index obtained by calculation when video playing is carried out according to the preset code rate.
In order to comprehensively and accurately evaluate the ABS algorithm to be evaluated, the preset code rate may include a plurality of code rates, and in one embodiment, the preset code rate may include an original code rate, a maximum code rate, and a minimum code rate of a video to be played. Based on this, the rationality of the ABS algorithm to be evaluated can be judged by judging whether the clarity index of the ABS algorithm to be evaluated is between the clarity scale index of the minimum code rate and the clarity scale index of the maximum code rate, and whether the fluency index of the ABS algorithm to be evaluated is between the fluency scale index of the minimum code rate and the fluency scale index of the maximum code rate, in one embodiment, when the clarity index of the ABS algorithm to be evaluated is between the clarity scale index of the minimum code rate and the clarity scale index of the maximum code rate, and the fluency index of the ABS algorithm to be evaluated is also between the fluency scale index of the minimum code rate and the fluency scale index of the maximum code rate, the ABS algorithm to be evaluated can be determined to be a rational ABS algorithm, when the clarity index of the ABS algorithm to be evaluated is not between the clarity scale index of the minimum code rate and the clarity scale index of the maximum code rate, or the fluency index of the ABS algorithm to be evaluated is not between the fluency scale index of the minimum code rate and the fluency scale index of the maximum code rate, the ABS algorithm to be evaluated can be judged to be an unreasonable ABS algorithm.
In order to further evaluate the reasonable ABS algorithm, in an embodiment, the playing experience index may further include a comprehensive evaluation index, where the comprehensive evaluation index of the ABS algorithm to be evaluated is obtained by calculating a weighted sum of the clarity index and the fluency index of the ABS algorithm to be evaluated according to respective weights, and in an embodiment, may further include weights of other parameters. The corresponding scale indexes can also comprise comprehensive evaluation scale indexes, wherein the comprehensive evaluation scale indexes are obtained by weighting and summing the definition scale indexes and the fluency scale indexes, whether the comprehensive evaluation indexes of the ABS algorithm to be evaluated are larger than the comprehensive evaluation scale indexes of the original code rate or not can be continuously judged on the basis of judging that the ABS algorithm to be evaluated is a reasonable ABS algorithm, and if yes, the ABS algorithm to be evaluated is determined to be a qualified ABS algorithm. If the comprehensive evaluation index of the ABS algorithm to be evaluated is not larger than the comprehensive evaluation scale index of the original code rate, the ABS algorithm to be evaluated can be judged to be an unqualified ABS algorithm, and further adjustment may be needed.
In an embodiment, a plurality of ABS algorithms are compared to determine an ABS algorithm with the best algorithm effect among the plurality of ABS algorithms, for example, the comprehensive evaluation index corresponding to each ABS algorithm may be compared to the comprehensive evaluation index corresponding to each ABS algorithm, and the plurality of ABS algorithms corresponding to each ABS algorithm may be ranked according to the descending of the comprehensive evaluation index, where the higher the comprehensive evaluation index is, the higher the corresponding rank is, and the best algorithm effect is represented by the corresponding ABS algorithm.
In the ABS algorithm evaluation method shown in fig. 1, provided by an embodiment of the present invention, playing experience data from a plurality of clients may be obtained for an ABS algorithm to be evaluated, where the playing experience data is playing experience data when the client plays a video according to a target bitrate, the target bitrate is a bitrate determined by using the ABS algorithm to be evaluated based on a video playing parameter from the client, the video playing parameter is a video playing parameter when the client plays a video according to a bitrate before the target bitrate is used, and the playing experience data represents a playing effect of the video, and based on the acquired playing experience data from a plurality of clients, the playing experience index of the ABS algorithm to be evaluated is calculated, and comparing the playing experience index with the scale index to obtain the evaluation result of the ABS algorithm to be evaluated, the scale index is a playing experience index calculated when the video is played according to a preset code rate. The server provides ABS algorithm service for the client, and when the ABS algorithm needs to be evaluated, playing experience data of the algorithm to be evaluated can be obtained in real time, so that the evaluation result is guaranteed to have no delay, and timeliness of the evaluation result is guaranteed.
In an embodiment of the present invention, there is also provided a bitrate determination method applied to a client, as shown in fig. 2, the method includes the following steps:
s201: and collecting video playing parameters when the video is played according to the current code rate.
In this step, video playing parameters when playing a video according to the current bitrate may be collected, in an embodiment, the current bitrate may be an original bitrate for playing the video, may also be a default bitrate set by the client, and may also be a video playing bitrate determined according to the ABS algorithm at the previous time, and in an embodiment, the video playing parameters may include the following parameters when the client plays the video: the method includes the steps of downloading speed or parameters such as the current bandwidth size of a client, the size of a video cache, the code rate of a video currently played by the client, the size of a fragment of the played video and the like.
In an embodiment, the client may periodically collect the video playing parameters according to a cycle time, or may start to collect the video playing parameters when the current bitrate is played after receiving an instruction to collect the video playing parameters, in an embodiment, an instruction to start collecting the video playing parameters may be trigger information sent by other devices, or trigger information controlled by a user, in an embodiment, when receiving a trigger operation to start ABS service, the client starts to collect the video playing parameters when the current bitrate is played, where the trigger operation may be preset various types of information, for example: the ABS service may be started by a preset double-click operation, or may be preset input information of external hardware such as a button and a mouse click, or may be preset biometric signals related to the ABS service start, such as a fingerprint signal, a facial recognition signal, and a limb movement signal.
S202: and sending the video playing parameters to a server.
In this step, the client may send the video playing parameters collected in step S201 to the server, and the sending manner may be various, and in an embodiment, the client may establish a connection with the server through the websock and send the collected video playing parameters.
In one embodiment, the video playing parameter may be a bandwidth size of the client, for example, a bandwidth of 2Mbit/s, and then the bandwidth of the server is 2Mbit/s as the video playing parameter to be sent to the server.
Correspondingly, after receiving the video playing parameter sent by the client, the server may allocate an ABS algorithm to the client, determine, based on the video playing parameter, a code rate that the client needs to adopt by the allocated ABS algorithm, and the server may reply the target code rate determined by the client, and the specific technical details will be described in detail later, and are not repeated again.
S203: and receiving a target code rate sent by the server, wherein the target code rate is a code rate which is determined by an ABS algorithm distributed for the client and is required by the client based on the video playing parameters.
In this step, a target bitrate sent by the server may be received, in an embodiment, the target bitrate may be a bitrate that needs to be adopted by the client and is determined by using an ABS algorithm allocated to the client based on the video playing parameter, and in an embodiment, when the video playing parameter is a bandwidth size of the client, for example, the bandwidth of the client is 2Mbit/s, the target bitrate that needs to be adopted by the client is determined by using the ABS algorithm allocated by the server to be 1Mbit/s, the server sends the target bitrate to the client, and the target bitrate received by the client is 1 Mbit/s. In one embodiment, the algorithm identifier of the ABS algorithm allocated by the server may be received while receiving the target bitrate sent by the server.
S204: and playing the video according to the received target code rate.
In this step, the video can be played according to the received target code rate sent by the server, and in an embodiment, when the target code rate is 1Mbit/s, the client can download the video to be played from the server providing the video service at a speed of 1Mbit/s and play the video.
S205: and collecting playing experience data when the video is played according to the target code rate, wherein the playing experience data represents the playing effect of the video.
In this step, in the process of playing the video according to the target bitrate, the client may collect playing experience data when playing the video, where the video experience data represents a playing effect of the video, and as can be understood by those skilled in the art, the playing effect of a video may be considered from two aspects of definition and fluency. In one embodiment, the playing experience data may include the number of mortises related to fluency, the target bitrate related to clarity, and in one embodiment, the playing experience data may also be other parameters such as buffer size.
S206: and sending the playing experience data to a server, wherein the playing experience data is used for evaluating an ABS algorithm.
In this step, the client may send the playing experience data collected in step S205 to the server, and the sending manner may be various, and in one embodiment, the client may establish a connection with the server through the websock and send the collected playing experience data. The playing experience data sent by the client can be used for evaluating the ABS algorithm.
In the method for determining the bit rate as shown in fig. 2, provided by the embodiment of the present invention, by collecting video playing parameters when video playing is performed according to a current bit rate, and sending the video playing parameters to a server, and receiving a target bit rate sent by the server, where the target bit rate is a bit rate that needs to be adopted by a client determined by using an ABS algorithm allocated to the client based on the video playing parameters, and performing video playing according to the received target bit rate, and collecting playing experience data when video playing is performed according to the target bit rate, where the playing experience data represents a playing effect of the video, and the playing experience data is sent to the server, and the playing experience data is used for evaluating the ABS algorithm, and since the client determines the target bit rate through the ABS algorithm in the server, when the ABS algorithm needs to be adjusted, the ABS algorithm built-in each player does not need to be adjusted, the ABS algorithm in the server only needs to be adjusted, and the time period for adjusting the ABS algorithm is shortened.
In an embodiment of the present invention, there is also provided a bitrate determination method applied to a server, as shown in fig. 3, the method including the following steps:
s301: and receiving video playing parameters sent by the client, wherein the video playing parameters are video playing parameters when the client plays the video according to the current code rate.
In this step, the server may receive the video playing parameters sent by the client in step S202, where data transmission manners between the server and the client may be various, and in an embodiment, the server may receive the video playing parameters sent by the client through the websock. In an embodiment, the video playing parameter is a video playing parameter when the client plays the video according to the current bitrate, in an embodiment, the current bitrate may be an original bitrate for playing the video, or a default bitrate set by the client, or a video playing bitrate determined according to an ABS algorithm at the previous time, and in an embodiment, the video playing parameter may include the following collected parameters when the client plays the video according to the current bitrate: the method includes the steps of downloading speed or parameters such as the current bandwidth size of a client, the size of a video cache, the code rate of a video currently played by the client, the size of a fragment of the played video and the like.
In one embodiment, the video playing parameter is a bandwidth size of the client, for example, the bandwidth is 2Mbit/s, and the video playing parameter received by the server and sent by the client is: the bandwidth is 2 Mbit/s.
S302: and allocating an ABS algorithm for the client.
In this step, multiple ABS algorithms may exist, and after the server receives the video playing data sent by the client, one ABS algorithm may be allocated to the client from among the multiple ABS algorithms.
In an embodiment, the ABS algorithm may be allocated to the client according to a current geographic location of the client, or the ABS algorithm may be allocated to the client according to a bandwidth provider of the current client, or the ABS algorithm may be allocated to the client according to a device identifier of the client, and it should be understood by those skilled in the art that when the server needs to allocate the ABS algorithm to the client according to a certain piece of information, that means that the information is included in the video playing data received by the server and sent by the client, for example, when the server needs to allocate the ABS algorithm to the client according to the current geographic location of the client, that means that the information of the current geographic location of the client is included in the video playing data received by the server and sent by the client.
In one embodiment, the ABS algorithm allocated to the client may be provided by a dedicated ABS algorithm service, in which case the ABS algorithm allocated to the client by the server is equivalent to the ABS algorithm server allocated to the client, in one embodiment, in order to better achieve matching between the client and the ABS algorithm server, hash values corresponding to multiple ABS algorithm servers may be stored in the server, it should be understood by those skilled in the art that the hash value of each ABS algorithm server and the ABS algorithm server are uniquely corresponding, when determining the hash value, the corresponding ABS algorithm server may be determined according to the hash value, in one embodiment, in order to evaluate the ABS algorithm at a later stage, fairness between the ABS algorithms is ensured to a certain extent, when the server allocates the ABS algorithm servers to the client, the ABS algorithm servers may provide the ABS algorithm service according to the number of times of each ABS algorithm server, and determining an ABS algorithm server distributed for the client.
S303: and determining the code rate required to be adopted by the client as the target code rate by adopting an allocated ABS algorithm based on the video playing parameters.
In this step, the allocated ABS algorithm may be used to determine the code rate that the client needs to use as the target code rate based on the video playing parameters, and for each ABS algorithm, the determined code rate that the client needs to use is different for different video playing parameters. In one embodiment, when the video playing parameters are: the bandwidth is 2Mbit/s, and the code rate required to be adopted by the client determined by the ABS algorithm is as follows: the target code rate is 1 Mbit/s.
S304: and sending the target code rate to the client.
In this step, the server may send the target bitrate to the client, where data transmission modes between the server and the client may be various, and in one embodiment, the server may establish a connection with the client through the websock and send the bitrate to the client through the websock. For example, a code rate with a target code rate of 1Mbit/s is sent to the client, and in one embodiment, an algorithm identifier of an allocated ABS algorithm may also be sent to the client while the target code rate is sent to the client.
S305: and receiving playing experience data sent by the client, wherein the playing experience data is playing experience data when the client plays the video according to the target code rate, represents the playing effect of the video and is used for evaluating the ABS algorithm.
In this step, when the client performs video playing according to the target bitrate, the client may collect playing experience data during video playing, where the video experience data represents a playing effect of a video, and as known to those skilled in the art, the playing effect of a video may be considered from two aspects of definition and fluency. In one embodiment, the playing experience data may include the number of mortises related to fluency, the target bitrate related to clarity, and in one embodiment, the playing experience data may also be a buffer size, etc. In one embodiment, the server may receive the play experience data sent by the client via the websock. In one embodiment, the server may evaluate the ABS algorithm according to the embodiment shown in fig. 1 by receiving the play experience data sent by the client.
In the method for determining the bit rate applied to the server and shown in fig. 3, provided by the embodiment of the invention, the video playing parameter sent by the client is received, the video playing parameter is a video playing parameter when the client plays a video according to the current bit rate, the ABS algorithm is allocated to the client, the allocated ABS algorithm is adopted based on the video playing parameter, the bit rate required to be adopted by the client is determined to be a target bit rate, the target bit rate is sent to the client, the playing experience data sent by the client is received, the playing experience data is playing experience data when the client plays a video according to the target bit rate, the playing effect of the video is represented, and the playing experience data is used for evaluating the ABS algorithm. The target code rate can be determined for the client through the ABS algorithm in the server, when the ABS algorithm needs to be adjusted, the built-in ABS algorithm of each player does not need to be adjusted, and only the ABS algorithm in the server needs to be adjusted, so that the time period for adjusting the ABS algorithm is shortened.
In an embodiment, as shown in fig. 7, fig. 7 is a schematic diagram of the code rate determining method applied to the client shown in fig. 2 and the code rate determining method applied to the server shown in fig. 3 provided in the embodiment of the present invention in practical application, where the schematic diagram includes: the method comprises a client, an algorithm distribution server and an algorithm evaluation server, wherein in one embodiment, the algorithm evaluation server and the algorithm distribution server can be the same server, and the implementation steps comprise: after the client collects video playing parameters when playing the video according to the current code rate, the client executes the step 701: sending video playing parameters; the algorithm distribution server may distribute an ABS algorithm to the client according to a preset distribution strategy after receiving the video playing parameter sent by the client, and after determining a code rate that the client needs to adopt based on the video playing parameter by using the distributed ABS algorithm as a target code rate, execute step 702, and send the target ABS algorithm distributed according to the preset distribution strategy; after receiving the target code rate sent by the algorithm distribution server, the client may play the video according to the target code rate, and at the same time, collect the play experience data when playing the video according to the target code rate, and execute step 703 to send the play experience data; after receiving the playing experience data sent by the client, the algorithm evaluation server may evaluate the ABS algorithm in combination with the playing experience data sent by the client and the playing experience data sent by the other clients, and according to the evaluation result, may execute step 704 on the algorithm allocation server to adjust the ABS algorithm. Those skilled in the art can understand that, in the embodiment of the present invention, the ABS algorithm may be adjusted according to a preset adjustment logic, or a technician may adjust each ABS algorithm in the algorithm distribution server according to an evaluation result, where the adjustment may include: deleting, improving, replacing and the like.
Based on the same inventive concept, according to the ABS algorithm evaluation method provided in the embodiments of the present invention, the embodiments of the present invention further provide an ABS algorithm evaluation device, as shown in fig. 4, the device includes:
the data obtaining module 401 is configured to obtain, for the ABS algorithm to be evaluated, play experience data from multiple clients, where the play experience data is play experience data when the clients perform video playing according to a target code rate, the target code rate is a code rate determined by the ABS algorithm to be evaluated based on a video playing parameter from the clients, the video playing parameter is a video playing parameter when the clients perform video playing according to a code rate before the target code rate, and the play experience data indicates a playing effect of a video;
the index calculation module 402 is configured to calculate a playing experience index of an ABS algorithm to be evaluated based on the obtained playing experience data from the multiple clients;
and an index comparison module 403, configured to compare the playing experience index with a scale index to obtain an evaluation result of the ABS algorithm to be evaluated, where the scale index is a playing experience index calculated when the video is played according to a preset code rate.
Further, the playing experience data includes a code rate and a pause time, and the playing experience indexes include: a clarity index and a fluency index;
the index calculation module 402 is specifically configured to add the code rates in the playing experience data from the multiple clients to obtain a clarity index of the ABS algorithm to be evaluated, and add the stuck times in the playing experience data from the multiple clients to obtain a fluency index of the ABS algorithm to be evaluated.
Further, the scale indexes include: the method comprises the steps of obtaining a definition scale index and a fluency scale index, wherein the definition scale index is a definition index obtained by calculation when video playing is carried out according to a preset code rate, and the fluency scale index is a fluency index obtained by calculation when video playing is carried out according to the preset code rate; the preset code rate comprises an original code rate, a maximum code rate and a minimum code rate of a played video;
the index comparison module 403 is specifically configured to determine whether the clarity index of the ABS algorithm to be evaluated is between the clarity scale index of the minimum code rate and the clarity scale index of the maximum code rate, and whether the fluency index of the ABS algorithm to be evaluated is between the fluency scale index of the minimum code rate and the fluency scale index of the maximum code rate, and if both are true, determine that the ABS algorithm to be evaluated is a reasonable ABS algorithm.
Further, the playing experience index further includes: comprehensively evaluating indexes; the scale indicator further comprises: comprehensively evaluating the scale indexes, wherein the comprehensive evaluating scale indexes are obtained by weighting and summing the definition scale indexes and the fluency scale indexes;
the index comparison module 403 is specifically configured to calculate a weighted sum of the definition index and the fluency index of the ABS algorithm to be evaluated according to respective weights of the definition index and the fluency index of the ABS algorithm to be evaluated, to serve as a comprehensive evaluation index of the ABS algorithm to be evaluated, and when the ABS algorithm to be evaluated is a reasonable ABS algorithm, determine whether the comprehensive evaluation index of the ABS algorithm to be evaluated is greater than a comprehensive evaluation scale index of an original code rate, and if so, determine that the ABS algorithm to be evaluated is a qualified ABS algorithm.
Based on the same inventive concept, according to the code rate determining method applied to the client shown in fig. 2 and the code rate determining method applied to the server shown in fig. 3 provided in the embodiments of the present invention, an embodiment of the present invention further provides an ABS algorithm evaluation system, as shown in fig. 5, the system includes: a client 501, a server 502;
the client 501 is configured to collect video playing parameters when video playing is performed according to a current code rate, and send the video playing parameters to the server;
the server 502 is configured to receive a video playing parameter sent by a client, allocate an ABS algorithm to the client according to a preset allocation strategy, determine, based on the video playing parameter and using the allocated ABS algorithm, a code rate that the client needs to adopt, as a target code rate, and send the target code rate to the client;
the client 501 is further configured to receive a target code rate sent by the server, perform video playing according to the received target code rate, collect playing experience data during video playing according to the target code rate, where the playing experience data represents a playing effect of the video, and send the playing experience data to the server;
the server 502 is further configured to receive the playing experience data sent by the client, and evaluate the ABS algorithm according to the playing experience data.
An electronic device is further provided in an embodiment of the present invention, as shown in fig. 6, and includes a processor 601 and a machine-readable storage medium 602, where the machine-readable storage medium 602 stores machine-executable instructions that can be executed by the processor 601.
A machine-readable storage medium 602 for storing machine-executable instructions;
a processor 601 for executing machine executable instructions stored on a machine readable storage medium 602, implementing the steps of:
the method comprises the steps that aiming at an ABS algorithm to be evaluated, playing experience data from a plurality of clients are obtained, the playing experience data are playing experience data when the clients play videos according to target code rates, the target code rates are code rates determined by the ABS algorithm to be evaluated based on video playing parameters from the clients, the video playing parameters are video playing parameters when the clients play videos according to the code rates before the target code rates, and the playing experience data represent the playing effect of the videos;
based on the acquired playing experience data from the plurality of clients, calculating a playing experience index of the ABS algorithm to be evaluated;
and comparing the playing experience index with a scale index to obtain an evaluation result of the ABS algorithm to be evaluated, wherein the scale index is the playing experience index calculated when video playing is carried out according to a preset code rate.
The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
In yet another embodiment of the present invention, a computer-readable storage medium is further provided, in which a computer program is stored, and the computer program, when executed by a processor, implements the steps of any of the ABS algorithm evaluation methods described above.
In yet another embodiment, a computer program product containing instructions is provided, which when run on a computer, causes the computer to execute any of the ABS algorithm evaluation methods of the above embodiments.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for apparatuses, systems, electronic devices, computer-readable storage media, computer program products, the description is relatively simple as they are substantially similar to the method embodiments, and reference may be made to some descriptions of the method embodiments for relevant points.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (8)
1. An ABS algorithm evaluation method, comprising:
the method comprises the steps that playing experience data from a plurality of clients are obtained aiming at an ABS algorithm to be evaluated, the ABS algorithm is a self-adaptive bit rate stream algorithm, the playing experience data are playing experience data when the clients play videos according to target code rates, the target code rates are code rates determined by the ABS algorithm to be evaluated based on video playing parameters from the clients, the video playing parameters are video playing parameters when the clients play videos according to the code rates before the target code rates, and the playing experience data represent the playing effect of the videos;
based on the acquired playing experience data from the plurality of clients, calculating a playing experience index of the ABS algorithm to be evaluated;
comparing the playing experience index with a scale index to obtain an evaluation result of the ABS algorithm to be evaluated, wherein the scale index is the playing experience index calculated when video playing is carried out according to a preset code rate;
the playing experience data comprises code rate and pause times, and the playing experience indexes comprise: a clarity index and a fluency index;
the calculating the playing experience index of the ABS algorithm to be evaluated based on the obtained playing experience data from the plurality of clients includes:
adding the code rates in the playing experience data from the plurality of clients to obtain a definition index of the ABS algorithm to be evaluated;
and adding the pause times in the playing experience data from the plurality of clients to obtain the fluency index of the ABS algorithm to be evaluated.
2. The method of claim 1, wherein the scale indicator comprises: the method comprises the steps of obtaining a definition scale index and a fluency scale index, wherein the definition scale index is a definition index obtained by calculation when video playing is carried out according to a preset code rate, and the fluency scale index is a fluency index obtained by calculation when video playing is carried out according to the preset code rate;
the preset code rate comprises an original code rate, a maximum code rate and a minimum code rate of a played video;
the comparing the playing experience index with the scale index to obtain the evaluation result of the ABS algorithm to be evaluated includes:
judging whether the clarity index of the ABS algorithm to be evaluated is between the clarity scale index of the minimum code rate and the clarity scale index of the maximum code rate, and whether the fluency index of the ABS algorithm to be evaluated is between the fluency scale index of the minimum code rate and the fluency scale index of the maximum code rate;
and if so, determining that the ABS algorithm to be evaluated is a reasonable ABS algorithm.
3. The method of claim 2, wherein the playback experience metrics further comprise: comprehensively evaluating indexes;
the scale index further includes: the comprehensive evaluation scale index is obtained by weighting and summing the definition scale index and the fluency scale index;
the method further comprises the following steps:
calculating the weighted sum of the definition index and the fluency index of the ABS algorithm to be evaluated according to the respective weights of the definition index and the fluency index of the ABS algorithm to be evaluated, and taking the weighted sum as the comprehensive evaluation index of the ABS algorithm to be evaluated;
when the ABS algorithm to be evaluated is a reasonable ABS algorithm, judging whether the comprehensive evaluation index of the ABS algorithm to be evaluated is larger than the comprehensive evaluation scale index of the original code rate;
and if so, determining the ABS algorithm to be evaluated as a qualified ABS algorithm.
4. An ABS algorithm evaluation apparatus, comprising:
the data acquisition module is used for acquiring playing experience data from a plurality of clients aiming at an ABS algorithm to be evaluated, the ABS algorithm is an adaptive bit rate stream algorithm, the playing experience data is playing experience data when the clients play videos according to target code rates, the target code rates are code rates determined by the ABS algorithm to be evaluated based on video playing parameters from the clients, the video playing parameters are video playing parameters when the clients play videos according to the code rates before the target code rates, and the playing experience data represents the playing effect of the videos;
the index calculation module is used for calculating the playing experience indexes of the ABS algorithm to be evaluated based on the obtained playing experience data from the plurality of clients;
the index comparison module is used for comparing the playing experience index with a scale index to obtain an evaluation result of the ABS algorithm to be evaluated, wherein the scale index is the playing experience index calculated when video playing is carried out according to a preset code rate;
the playing experience data comprises code rate and pause times, and the playing experience indexes comprise: a clarity index and a fluency index;
the index calculation module is specifically configured to add the code rates in the playing experience data from the multiple clients to obtain a clarity index of the ABS algorithm to be evaluated, and add the stuck times in the playing experience data from the multiple clients to obtain a fluency index of the ABS algorithm to be evaluated.
5. The apparatus of claim 4, wherein the scale indicator comprises: the method comprises the steps of obtaining a definition scale index and a fluency scale index, wherein the definition scale index is a definition index obtained by calculation when video playing is carried out according to a preset code rate, and the fluency scale index is a fluency index obtained by calculation when video playing is carried out according to the preset code rate; the preset code rate comprises an original code rate, a maximum code rate and a minimum code rate of a played video;
the index comparison module is specifically configured to determine whether the clarity index of the ABS algorithm to be evaluated is between the clarity scale index of the minimum code rate and the clarity scale index of the maximum code rate, and whether the fluency index of the ABS algorithm to be evaluated is between the fluency scale index of the minimum code rate and the fluency scale index of the maximum code rate, and if both are true, determine that the ABS algorithm to be evaluated is a reasonable ABS algorithm.
6. The apparatus of claim 5, wherein the playback experience metrics further comprise: comprehensively evaluating indexes; the scale index further includes: the comprehensive evaluation scale index is obtained by weighting and summing the definition scale index and the fluency scale index;
the index comparison module is specifically configured to calculate a weighted sum of the definition index and the fluency index of the ABS algorithm to be evaluated according to respective weights of the definition index and the fluency index of the ABS algorithm to be evaluated, to serve as a comprehensive evaluation index of the ABS algorithm to be evaluated, and when the ABS algorithm to be evaluated is a reasonable ABS algorithm, determine whether the comprehensive evaluation index of the ABS algorithm to be evaluated is greater than a comprehensive evaluation scale index of the original code rate, and if so, determine that the ABS algorithm to be evaluated is a qualified ABS algorithm.
7. An ABS algorithm evaluation system, comprising: a client and a server;
the client is used for collecting video playing parameters when video playing is carried out according to the current code rate and sending the video playing parameters to the server;
the server is used for receiving the video playing parameters sent by the client, distributing an ABS algorithm to the client according to a preset distribution strategy, determining a code rate required to be adopted by the client as a target code rate by adopting the distributed ABS algorithm based on the video playing parameters, and sending the target code rate to the client, wherein the ABS algorithm is an adaptive bit rate flow algorithm;
the client is further configured to receive the target code rate sent by the server, perform video playing according to the received target code rate, collect playing experience data during video playing according to the target code rate, where the playing experience data represents a playing effect of a video, and send the playing experience data to the server;
the server is further configured to receive the playing experience data sent by the client, and evaluate the ABS algorithm according to the playing experience data.
8. An electronic device comprising a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor, the processor being caused by the machine-executable instructions to: carrying out the method steps of any one of claims 1 to 3.
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| CN114448808A (en) * | 2020-11-02 | 2022-05-06 | 阿里巴巴集团控股有限公司 | Peak clipping method and device and electronic equipment |
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