CN107613315B - Video image quality adjusting method and device, terminal equipment and storage medium - Google Patents
Video image quality adjusting method and device, terminal equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the application discloses a video image quality adjusting method, a video image quality adjusting device, terminal equipment and a storage medium, wherein the method comprises the steps of determining whether the terminal equipment meets image quality adjusting conditions or not when a video playing event is detected; if the image quality adjustment condition is met, obtaining comment information of the played video; and determining corresponding picture adjustment parameters according to the comment information and a stored preset adjustment library, and adjusting the picture quality of the played video according to the picture adjustment parameters. According to the scheme, the flexibility of image quality adjustment of the terminal equipment during video playing is improved, the operation efficiency is improved, and the user requirements are met.
Description
Technical Field
The embodiment of the application relates to computer technologies, and in particular, to a method and an apparatus for adjusting video quality, a terminal device, and a storage medium.
Background
With the increasing popularity of terminal devices, more and more users use the terminal devices to perform various functions to meet their own needs, such as reading text, watching video, listening to music, playing games, etc. When a user watches videos by using a terminal device, the definition of the videos is significantly influenced by the image quality of the videos, the higher the image quality is, the higher the definition is, and meanwhile, the higher the flow consumed by downloading and buffering of the terminal device and the running load are.
In the prior art, when a terminal device plays a video, the adjustment mode of the video image quality has defects and needs to be improved.
Disclosure of Invention
The invention provides a video image quality adjusting method, a video image quality adjusting device, a terminal device and a storage medium.
In a first aspect, an embodiment of the present application provides a method for adjusting video quality, including:
when a video playing event is detected, determining whether the terminal equipment meets an image quality adjusting condition;
if the image quality adjustment condition is met, obtaining comment information of the played video;
and determining corresponding picture adjustment parameters according to the comment information and a stored preset adjustment library, and adjusting the picture quality of the played video according to the picture adjustment parameters.
In a second aspect, an embodiment of the present application further provides an apparatus for adjusting video quality, including:
the image quality adjustment triggering module is used for determining whether the terminal equipment meets image quality adjustment conditions or not when a video playing event is detected;
the comment information acquisition module is used for acquiring comment information of the played video if the image quality adjustment condition is met;
the picture parameter determining module is used for determining corresponding picture adjusting parameters according to the comment information and a stored preset adjusting library;
and the image quality adjusting module is used for adjusting the image quality of the played video according to the image adjusting parameters.
In a third aspect, an embodiment of the present application further provides a terminal device, including: the present invention relates to a video image quality adjustment method, and more particularly, to a video image quality adjustment method, and a storage medium.
In a fourth aspect, an embodiment of the present application further provides a storage medium containing terminal device executable instructions, where the terminal device executable instructions are executed by a terminal device processor to perform the video quality adjustment method according to the embodiment of the present application.
In the scheme, when a video playing event is detected, whether the terminal equipment meets the image quality adjusting condition is determined; if the image quality adjustment condition is met, obtaining comment information of the played video; and determining corresponding picture adjustment parameters according to the comment information and a stored preset adjustment library, adjusting the picture quality of the played video according to the picture adjustment parameters, and dynamically and reasonably adjusting the picture quality of the played video in real time, so that the resource utilization rate of the terminal equipment during playing the video is more reasonable, the flow consumption is saved, and the system operation efficiency is improved.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings:
fig. 1 is a flowchart of a video quality adjustment method according to an embodiment of the present disclosure;
fig. 2 is a flowchart of another video quality adjustment method according to an embodiment of the present disclosure;
fig. 3 is a flowchart of another video quality adjustment method according to an embodiment of the present disclosure;
fig. 4 is a flowchart of another video quality adjustment method according to an embodiment of the present disclosure;
fig. 5 is a flowchart of another video quality adjustment method according to an embodiment of the present disclosure;
fig. 6 is a block diagram illustrating a structure of an apparatus for adjusting video quality according to an embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are for purposes of illustration and not limitation. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Fig. 1 is a flowchart of a video quality adjustment method according to an embodiment of the present application, where the present embodiment is applicable to a situation where quality of a video played by a terminal device is adjusted, and the method may be executed by the terminal device according to the embodiment of the present application, and a video quality adjustment apparatus of the terminal device may be implemented in a software and/or hardware manner, as shown in fig. 1, a specific scheme provided in the present embodiment is as follows:
and step S101, when a video playing event is detected, determining whether the terminal equipment meets the image quality adjusting condition.
With the popularization of terminal devices, the situation that users watch videos by using the terminal devices is gradually increased, and the situation becomes one of main realization functions of the terminal devices. Due to the development of network and hardware performance, users mostly use terminal devices to search and watch network videos directly at present, for example, use APP provided by providers to play videos of episodes and movies.
In an embodiment, when a video playing event is detected, it is determined whether the terminal device meets an image quality adjustment condition, where the video playing event is used to represent that the terminal device performs video playing, and may be a pressing event of a playing button of a video frame, a click playing event of a video list, a video buffering event, or the like. When a video playing event is detected, whether the current terminal equipment meets the image quality adjustment condition is judged, namely whether image quality adjustment is needed. Generally, in order to adapt to various network bandwidths and user requirements, a provider provides a plurality of video resources with different image quality conditions, for example, in the same network bandwidth transmission environment, a video resource with poor image quality can be smoothly played, and a video resource with high image quality may be jammed.
Determining whether the terminal device satisfies the image quality adjustment condition includes: and determining whether at least one of the current flow use mode, the system load and the residual capacity of the terminal equipment meets an image quality adjusting condition. The current flow use mode comprises a wifi network connection mode and a mobile flow network mode, the system load comprises a CPU load and a memory occupancy rate, and the residual electric quantity is the residual electric quantity of a terminal device battery.
And step S102, if the image quality adjusting condition is met, obtaining comment information of the played video.
In one embodiment, when the network connection mode of the terminal device is determined to be the mobile traffic network mode, the terminal device may be determined to meet the image quality adjustment condition; in one embodiment, when it is determined that the system load of the terminal device is high (e.g., the CPU load is greater than 80%, and the memory occupancy is greater than 80%), it may be determined that the terminal device satisfies the image quality adjustment condition; in one embodiment, when it is determined that the remaining power is less than a preset threshold (e.g., 30%), the terminal device may be determined to satisfy the image quality adjustment condition; in an embodiment, the conditions such as the current traffic usage mode, the system load, and the remaining power of the peer device may be combined to determine whether the terminal device satisfies the image quality adjustment condition.
After determining that the terminal device meets the image quality adjustment condition, obtaining comment information of the played video, wherein the comment information may be a message, a video barrage and the like below the played video, specifically, taking an android operating system as an example, the comment information of the currently played video may be obtained through a comment list interface of video playing software, and taking a new wave video as an example: http:// api. t.sina.com.cn/settings/comments.json.
Step S103, determining corresponding picture adjustment parameters according to the comment information and a stored preset adjustment library, and adjusting the image quality of the played video according to the picture adjustment parameters.
In an embodiment, before the determining the corresponding picture adjustment parameter according to the determined comment information and the stored preset adjustment library, the method further includes: the method comprises the steps of obtaining a preset adjusting library according to video comment information and a machine learning training model, wherein different keywords and picture adjusting parameters corresponding to the keywords and the picture adjusting parameters are recorded in the preset adjusting library, and the video comment information comprises at least one of a video barrage, a message left below a video and a forwarding title. The machine learning training model can be obtained by a server through training and learning of a large number of samples, and can be obtained by supervised learning, unsupervised learning, semi-supervised learning or reinforcement learning, and the algorithm used in the learning process comprises the following steps: regression algorithms, example-based algorithms, regularization algorithms, decision tree algorithms, bayesian algorithms, kernel-based algorithms, clustering algorithms, association rule algorithms, artificial neural network algorithms, deep learning algorithms, and dimensionality reduction algorithms, among others. Specifically, the comment information is taken as a video bullet screen as an example, wherein the video bullet screen is bullet screen content which is recorded in real time when a user watches the video, the content of the bullet screen represents the video wonderful degree of the current video playing node to a certain extent, if the video bullet screen is 'classic', the video wonderful degree of the current playing node is higher, if the video barrage is boring, the video and the plot of the current playing node are correspondingly represented to be irrelevant or have poor wonderful degree, different video bullet screen contents and corresponding video wonderful degree can be associated through machine learning to form a preset adjusting library, the preset adjustment library records different keywords and corresponding picture adjustment parameters, and taking the foregoing as an example, the picture adjustment parameter corresponding to the keyword "classic" is "1020P", and the picture adjustment parameter corresponding to the keyword "boring" is "720P".
In an embodiment, the determining, according to the determined comment information and a stored preset adjustment library, a corresponding picture adjustment parameter includes: extracting keywords from the comment information to obtain one or more keywords; and determining corresponding picture adjustment parameters according to the one or more keywords and a stored preset adjustment library. And after extracting keywords from the comment information, matching the keywords in a preset adjusting library to obtain corresponding picture adjusting parameters of the currently played video. In another embodiment, the determining the corresponding picture adjustment parameter according to the determined comment information and a stored preset adjustment library includes: performing machine learning identification on the comment information to obtain one or more keywords; and determining corresponding picture adjustment parameters according to the one or more keywords and a stored preset adjustment library. And identifying the intention of the comment information by a machine identification method to obtain a keyword, matching the keyword by a preset adjusting library, and determining a corresponding picture adjusting parameter.
In one embodiment, after the picture adjustment parameter is determined, the adjustment parameter or the corresponding adjustment instruction may be sent to a video server that provides the playing video to adjust the video quality. Illustratively, the terminal device can send a video high-definition playing instruction to the server, and when the server receives the instruction, the playing video is adjusted to be high-definition. Optionally, the video high-definition playing instruction may be sent by calling a preset image quality adjustment interface in the video player.
In one embodiment, there may also be an adjustment to the amount of video buffering data. In the embodiment, the data buffering amount and the buffering duration can be adjusted while the image quality of the played video is adjusted according to the picture adjustment parameters. For example, when the terminal device satisfies the image quality adjustment condition and the image quality is adjusted to be a low image quality (e.g. 720P or lower), the amount of buffered data (e.g. the amount of buffered data is set to 1M) and the buffering duration (e.g. the buffering duration is set to 5 seconds) are correspondingly shortened, thereby avoiding unnecessary consumption of traffic and unnecessary increase of system load caused by that the amount of buffered data is too large or the buffering duration is too long and the user does not watch the end of the buffering amount. Specifically, a video playing mode that the server side supports buffering modification can adopt a mode of sending a buffering modification setting instruction to the server to set and modify the buffering data volume, and for a video playing mode that the server side does not support modification, the terminal device adopts a mode of limiting the flow time and the speed, illustratively, the flow speed is limited to 30% of the original flow speed, the time for limiting the flow to be opened when the video buffering is detected to be started is 3 seconds, and when the buffering video playing is detected to be finished, the data flow is opened again for 3 seconds to perform data buffering.
According to the content, when the terminal equipment meets the image quality adjusting condition, the video image quality is adjusted according to the comment information of the played video and the preset adjusting library, the flow consumption of the terminal equipment is reasonably saved, and the adjusting mode is more humanized and intelligent.
Fig. 2 is a flowchart of another video quality adjustment method according to an embodiment of the present application, where optionally, the determining, according to the determined comment information and the stored preset adjustment library, a corresponding picture adjustment parameter includes: extracting keywords from the comment information to obtain one or more keywords; and determining corresponding picture adjustment parameters according to the one or more keywords and a stored preset adjustment library. As shown in fig. 2, the technical solution is as follows:
step S201, detecting a video playing event.
Step S202, when a video playing event is detected, whether the terminal equipment meets the image quality adjusting condition is judged, if yes, step S203 is executed, and if not, the process is ended.
And step S203, obtaining comment information of the played video.
Step S204, extracting keywords from the comment information to obtain one or more keywords, and determining corresponding picture adjustment parameters according to the one or more keywords and a stored preset adjustment library.
In an embodiment, the comment information may be a current barrage message for playing a video, and the keyword extraction is performed on the barrage message, optionally, the barrage messages may be grouped into 20 to 50 pieces each, and the keyword extraction may be performed on all the barrage messages. Specifically, a TF-IDF, a topic-model, a textrank or a rake algorithm is adopted, wherein the TF-IDF mainly extracts keywords according to the occurrence frequency of each word in the barrage messages, wherein TF is (the number of occurrences of the word in the article)/(the total word number of the article), IDF is log (the total number of the video messages/(the number of messages containing the word +1)), and TF-IDF is TF; the topic-model algorithm extracts keywords with definite video topics, and the bullet screen words associated with the topics are marked as the keywords. After the keyword extraction is completed, determining the current image quality adjustment parameter of the played video according to a preset adjustment library, where the specific determination process is referred to in step S103, and is not described herein again.
Step S205, adjusting the quality of the played video according to the picture adjustment parameter.
In one embodiment, when it is determined that the terminal device satisfies the image quality adjustment condition and is ready to perform image quality adjustment, the determined image quality adjustment parameter may be compared with a picture parameter of the current video playing, and if the picture definition of the picture adjustment parameter is higher than the picture parameter of the current video playing, the image quality adjustment is not performed. In one embodiment, when it is detected that the terminal device satisfies the image quality adjustment condition, it is further determined whether the image quality of the currently played video is a preset image quality (e.g., super-clear image quality), and if so, the screen information of the played video is determined, and the subsequent steps are performed to perform image quality adjustment.
In another embodiment, after adjusting the image quality of the played video according to the frame adjustment parameter, the method further includes: monitoring whether the terminal equipment meets the image quality recovery condition, and if so, recovering the image quality of the played video to the image quality before adjustment. The image quality recovery condition can be that the terminal equipment is connected with a charging device or a network connection mode is converted into a wireless wifi network connection mode by a mobile data network.
Therefore, by extracting keywords from the comment information of the video and finally determining the image quality adjustment mode, the image quality adjustment flexibility of the terminal equipment during video playing is improved, the self condition of the terminal equipment can be considered during video playing, and the image quality self-adaptive adjustment can be carried out under different conditions so as to improve the efficiency of the terminal equipment and save the flow consumption.
Fig. 3 is a flowchart of another video quality adjustment method according to an embodiment of the present application, where optionally, the determining, according to the determined comment information and the stored preset adjustment library, a corresponding picture adjustment parameter includes: performing machine learning identification on the comment information to obtain one or more keywords; and determining corresponding picture adjustment parameters according to the one or more keywords and a stored preset adjustment library. As shown in fig. 3, the technical solution is as follows:
and S301, detecting a video playing event.
Step S302, when a video playing event is detected, determining whether the terminal device satisfies an image quality adjustment condition, if so, executing step S203, and if not, ending the process.
And step S303, obtaining comment information of the played video.
Step S304, machine learning identification is carried out on the comment information to obtain one or more keywords, and corresponding picture adjustment parameters are determined according to the one or more keywords and a stored preset adjustment library.
In one embodiment, the comment information may be barrage information input by other users and displayed in real time in the video playing process, or may be message information in a message board below the video, and the comment information is subjected to machine learning to obtain one or more keywords corresponding to the comment intention. Specifically, the semantic recognition may be performed based on RNN (Recurrent neural networks) or LSTM (Long Short-Term Memory) to obtain corresponding keywords. The RNN introduces directional circulation, can process the problem of front-back correlation between comment inputs, and is mainly used for processing sequence data, for example, reply information under a certain comment information, namely semantic recognition is carried out based on the RNN when the comment information which is correlated with the comment information exists; LSTM is mainly used to semantically identify a large amount of bullet-screen content that appears in a short time interval to obtain keywords. After the keyword extraction is completed, determining the current image quality adjustment parameter of the played video according to a preset adjustment library, where the specific determination process is referred to in step S103, and is not described herein again.
Step S305, adjusting the image quality of the played video according to the image adjustment parameter.
Therefore, in the video playing process of the terminal equipment, the picture quality can be adjusted in a self-adaptive mode, the adjustment mode is determined according to the comment information of the played video, the personalized requirement of the user for video watching is guaranteed, and meanwhile, the power consumption and the flow of the corresponding terminal equipment are saved.
Fig. 4 is a flowchart of another video quality adjustment method according to an embodiment of the present application, where optionally, before determining the corresponding picture adjustment parameter according to the determined comment information and the stored preset adjustment library, the method further includes: determining video information of a playing video; correspondingly, determining the corresponding picture adjustment parameters according to the determined comment information and the stored preset adjustment library comprises the following steps: and determining corresponding picture adjustment parameters according to the determined comment information, the determined video information and the stored preset adjustment library. As shown in fig. 4, the technical solution is as follows:
step S401, when a video playing event is detected, whether the terminal equipment meets the image quality adjusting condition is determined.
And step S402, if the image quality adjusting condition is met, determining video information and comment information of the played video.
In one embodiment, the video information of the playing video is further determined in the process of determining the playing video comment information, wherein the video information can be the subject content, the tag content, the video description and the like of the playing video. Specifically, when the played video is played as a webpage, taking an Android operating system as an example, the theme of the currently-opened webpage video can be determined by a getTitle method in WebView, and when a user plays videos by using various APPs such as a youku client and an love art client, the theme of the currently-played video can be determined by calling API interfaces of the clients.
And S403, determining corresponding picture adjustment parameters according to the determined comment information, the determined video information and the stored preset adjustment library.
In an embodiment, in the process of determining picture adjustment parameters according to comment information, picture quality adjustment may be performed by separately combining video information, where the video information may include video topics, tag content, and the like, optionally, keyword extraction may be performed on the video topics in the video information to obtain one or more keywords, corresponding picture adjustment parameters may be determined according to the one or more keywords and a stored preset adjustment library, or machine learning identification may be performed on the video topics in the video information to obtain one or more keywords, and corresponding picture adjustment parameters may be determined according to the one or more keywords and the stored preset adjustment library. For example, a semantic recognition algorithm may be used to perform semantic word segmentation on a text in a video topic, and determine one or more divided nouns as a keyword. And determining corresponding picture adjustment parameters according to the one or more keywords and a stored preset adjustment library. Illustratively, the image quality mode of the currently played video comprises a super-definition mode (1080P), a high-definition mode (720P) and a normal mode (480P), the determined keywords are matched with the contents in the stored preset adjusting library in a text mode, if the matching fails, the image quality adjusting parameters in the period are determined to be 720P or 480P, and if the matching succeeds, the current image quality is kept unchanged. In another embodiment, by performing machine learning on the video topic to obtain one or more keywords representing the main content of the video, semantic recognition based on RNN (Recurrent Neural Networks) or LSTM (Long Short-Term Memory) can be used to obtain corresponding keywords. In another embodiment, the preset model of the video theme and the playing content can be obtained by performing machine learning on different video themes and corresponding video playing contents, the preset model takes the video theme as input and outputs one or more predicted keywords, specifically, the preset model can be obtained by performing training learning on a large number of samples by a server, and can be obtained by supervised learning, unsupervised learning, semi-supervised learning or reinforcement learning, and an algorithm used in the learning process includes: regression algorithms, example-based algorithms, regularization algorithms, decision tree algorithms, bayesian algorithms, kernel-based algorithms, clustering algorithms, association rule algorithms, artificial neural network algorithms, deep learning algorithms, and dimensionality reduction algorithms, among others. Optionally, in this embodiment, the picture adjustment parameter is preferentially determined according to the comment information, and when the picture parameter is determined to maintain the original picture quality, the picture quality adjustment parameter is further determined according to the video information of the played video to perform picture quality adjustment.
Step S404, adjusting the image quality of the played video according to the picture adjusting parameters.
Therefore, in the process of adjusting the image quality of the video played by the terminal device, the video information of the played video is introduced as the reference quantity determined by the image quality adjustment parameter, and the image quality adjustment parameter can be determined according to the video information and the current playing content, so that the image quality adjustment mode is more flexible and the efficiency is higher.
Fig. 5 is a flowchart of another video quality adjustment method according to an embodiment of the present application, where optionally, before determining a corresponding picture adjustment parameter according to the determined comment information and a stored preset adjustment library, the method further includes: determining historical playing information of a playing video; correspondingly, determining the corresponding picture adjustment parameters according to the determined comment information and the stored preset adjustment library comprises the following steps: and determining corresponding picture adjustment parameters according to the determined comment information, the historical playing information and the stored preset adjustment library. As shown in fig. 5, the technical solution is as follows:
step S501, when a video playing event is detected, whether the terminal equipment meets the image quality adjusting condition is determined.
Step S502, if the image quality adjusting condition is met, determining historical playing information and comment information of the played video.
In one embodiment, after determining that the terminal device meets the image quality adjustment condition, further determining historical playing information of the played video, wherein the historical playing information includes a playing record of the played video watched by other users. Optionally, for the skip record, the recorded content includes a skip start node and an end node of the video, and for the fast forward and fast backward operation, the recorded content includes a start node and an end node of the fast forward and fast backward in the video. Each terminal device records and stores the playing record, uploads the recorded playing record to a server providing the playing video resource, and can also send the recorded playing record to other terminal devices loading the video.
Step S503, determining picture adjustment parameters of the played video according to the historical playing information and the video information.
In one embodiment, the adjustment of the image quality of the video can be performed according to the jump record, the drag-and-drop record and the fast forward and fast backward record in the history playing information. For example, assuming that the duration of currently playing the video is 35 minutes, wherein when the video is played by other users in the history record, the video is skipped from 10 th minute to 20 th minute, and the corresponding image quality adjustment parameter for reducing the image definition is adopted for image quality adjustment when the video is buffered and played in 10 th minute.
In an embodiment, in the process of determining the picture adjustment parameter according to the comment information, the picture quality adjustment may be performed by separately combining historical play information, and specifically, determining the picture adjustment parameter of the played video according to the historical play information includes: and determining picture adjustment parameters of the played video according to the historical playing information and a preset model, wherein the preset model is obtained by machine learning training. The preset model can be obtained by training and learning a large number of samples through a server, and can be obtained by supervised learning, unsupervised learning, semi-supervised learning or reinforcement learning, and the algorithm used in the learning process comprises the following steps: regression algorithms, example-based algorithms, regularization algorithms, decision tree algorithms, bayesian algorithms, kernel-based algorithms, clustering algorithms, association rule algorithms, artificial neural network algorithms, deep learning algorithms, and dimensionality reduction algorithms, among others. Specifically, the historical playing information is used as an input and is input into a corresponding preset model to output a uniquely determined playing record, illustratively, the historical playing information includes 10 jump records, wherein jump starting points and jump ending points recorded in each jump record may be the same or different, the preset model learns and analyzes the 10 jump records to evaluate and predict a jump starting node and a jump ending node with the maximum probability, and after the determination is finished, the reduction and adjustment are performed according to the image quality between the determined jump starting node and the determined jump ending node. Optionally, in this embodiment, the picture adjustment parameters are preferentially determined according to the comment information, and when the picture parameters are determined to maintain the original picture quality, the picture quality adjustment parameters are further determined according to historical play information of the played video to adjust the picture quality.
Step S504, the image quality of the played video is adjusted according to the picture adjusting parameters.
Therefore, in the process of adjusting the image quality of the video played by the terminal device, the historical playing information of the played video is introduced as the reference quantity determined by the image quality adjusting parameter, so that the image quality adjusting scheme is further improved, the image quality adjusting mode is more humanized, and the user requirements are met.
Fig. 6 is a block diagram illustrating a video quality adjustment apparatus according to an embodiment of the present application, where the apparatus is configured to execute the video quality adjustment method according to the embodiment, and has functional modules and beneficial effects corresponding to the execution method. As shown in fig. 6, the apparatus specifically includes: an image quality adjustment triggering module 101, a comment information obtaining module 102, a picture parameter determining module 103, and an image quality adjusting module 104, wherein,
the image quality adjustment triggering module 101 is configured to determine whether the terminal device meets an image quality adjustment condition when a video playing event is detected;
a comment information obtaining module 102, configured to obtain comment information of a played video if the image quality adjustment condition is satisfied;
the picture parameter determining module 103 is configured to determine a corresponding picture adjustment parameter according to the comment information and a stored preset adjustment library;
the image quality adjustment module 104 is configured to adjust the image quality of the played video according to the image adjustment parameter.
According to the content, when the video playing event is detected, whether the terminal equipment meets the image quality adjusting condition is determined; if the image quality adjustment condition is met, obtaining comment information of the played video; and determining corresponding picture adjustment parameters according to the comment information and a stored preset adjustment library, adjusting the picture quality of the played video according to the picture adjustment parameters, and dynamically and reasonably adjusting the picture quality of the played video in real time, so that the resource utilization rate of the terminal equipment during playing the video is more reasonable, the flow consumption is saved, and the system operation efficiency is improved.
In a possible embodiment, the adjustment library generating module 105 is configured to obtain a preset adjustment library according to the video comment information and the machine learning training model before determining the corresponding picture adjustment parameter according to the determined comment information and the stored preset adjustment library, where the preset adjustment library records different keywords and the respective corresponding picture adjustment parameter, and the video comment information includes at least one of a video bullet screen, a message left below the video, and a forwarding title.
In a possible embodiment, the picture parameter determining module 103 is specifically configured to:
extracting keywords from the comment information to obtain one or more keywords;
and determining corresponding picture adjustment parameters according to the one or more keywords and a stored preset adjustment library.
In a possible embodiment, the picture parameter determining module 103 is specifically configured to:
performing machine learning identification on the comment information to obtain one or more keywords;
and determining corresponding picture adjustment parameters according to the one or more keywords and a stored preset adjustment library.
In a possible embodiment, the image quality adjustment module 104 is specifically configured to:
and determining whether at least one of the current flow use mode, the system load and the residual capacity of the terminal equipment meets an image quality adjusting condition.
In a possible embodiment, the comment information obtaining module 102 is further configured to:
determining video information of a played video before determining corresponding picture adjustment parameters according to the determined comment information and a stored preset adjustment library;
the picture parameter determining module 103 is specifically configured to:
and determining corresponding picture adjustment parameters according to the determined comment information, the determined video information and the stored preset adjustment library.
In a possible embodiment, the comment information obtaining module 102 is further configured to:
determining historical playing information of the played video before determining corresponding picture adjusting parameters according to the determined comment information and a stored preset adjusting library;
the picture parameter determining module 103 is specifically configured to:
and determining corresponding picture adjustment parameters according to the determined comment information, the historical playing information and the stored preset adjustment library.
In this embodiment, a terminal device is provided on the basis of the foregoing embodiments, and fig. 7 is a schematic structural diagram of a terminal device provided in an embodiment of the present application, and as shown in fig. 7, the terminal device 200 includes: memory 201, processor (CPU) 202, peripheral interfaces 203, RF (Radio Frequency) circuitry 205, audio circuitry 206, speaker 211, power management chip 208, input/output (I/O) subsystem 209, touch screen 212, other input/control devices 210, and external port 204, which communicate via one or more communication buses or signal lines 207.
It should be understood that the illustrated terminal device 200 is only one example of a terminal device, and that the terminal device 200 may have more or fewer components than shown in the figures, may combine two or more components, or may have a different configuration of components. The various components shown in the figures may be implemented in hardware, software, or a combination of hardware and software, including one or more signal processing and/or application specific integrated circuits.
The following describes in detail a terminal device for rights management of multi-open applications provided in this embodiment, where the terminal device is a smart phone as an example.
A memory 201, the memory 201 being accessible by the CPU202, the peripheral interface 203, and the like, the memory 201 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic disk storage devices, flash memory devices, or other volatile solid state storage devices.
A peripheral interface 203, said peripheral interface 203 may connect input and output peripherals of the device to the CPU202 and the memory 201.
An I/O subsystem 209, the I/O subsystem 209 may connect input and output peripherals on the device, such as a touch screen 212 and other input/control devices 210, to the peripheral interface 203. The I/O subsystem 209 may include a display controller 2091 and one or more input controllers 2092 for controlling the other input/control devices 210. Where one or more input controllers 2092 receive electrical signals from or transmit electrical signals to other input/control devices 210, the other input/control devices 210 may include physical buttons (push buttons, rocker buttons, etc.), dials, slide switches, joysticks, click wheels. It is noted that the input controller 2092 may be coupled to any one of: a keyboard, an infrared port, a USB interface, and a pointing device such as a mouse.
A touch screen 212, the touch screen 212 being an input interface and an output interface between the user terminal and the user, displaying visual output to the user, which may include graphics, text, icons, video, and the like.
The display controller 2091 within the I/O subsystem 209 receives electrical signals from the touch screen 212 or transmits electrical signals to the touch screen 212. The touch screen 212 detects a contact on the touch screen, and the display controller 2091 converts the detected contact into an interaction with a user interface object displayed on the touch screen 212, i.e., implements a human-machine interaction, and the user interface object displayed on the touch screen 212 may be an icon for running a game, an icon networked to a corresponding network, or the like. It is worth mentioning that the device may also comprise a light mouse, which is a touch sensitive surface that does not show visual output, or an extension of the touch sensitive surface formed by the touch screen.
The RF circuit 205 is mainly used to establish communication between the mobile phone and the wireless network (i.e., network side), and implement data reception and transmission between the mobile phone and the wireless network. Such as sending and receiving short messages, e-mails, etc. In particular, the RF circuitry 205 receives and transmits RF signals, also referred to as electromagnetic signals, through which the RF circuitry 205 converts electrical signals to or from electromagnetic signals and communicates with communication networks and other devices. RF circuitry 205 may include known circuitry for performing these functions including, but not limited to, an antenna system, an RF transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a CODEC (CODEC) chipset, a Subscriber Identity Module (SIM), and so forth.
The audio circuit 206 is mainly used to receive audio data from the peripheral interface 203, convert the audio data into an electric signal, and transmit the electric signal to the speaker 211.
And a speaker 211 for reproducing the voice signal received by the handset from the wireless network through the RF circuit 205 into sound and playing the sound to the user.
And the power management chip 208 is used for supplying power and managing power to the hardware connected with the CPU202, the I/O subsystem and the peripheral interface.
The video quality adjustment device of the terminal device and the terminal device provided in the above embodiments may execute the video quality adjustment method of the terminal device provided in any embodiment of the present invention, and have corresponding functional modules and beneficial effects for executing the method. For details of the technique not described in detail in the above embodiments, reference may be made to the video quality adjustment method of the terminal device provided in any embodiment of the present invention.
An embodiment of the present application further provides a storage medium containing terminal device executable instructions, where the terminal device executable instructions are executed by a terminal device processor to perform a video quality adjustment method, and the method includes:
when a video playing event is detected, determining whether the terminal equipment meets an image quality adjusting condition;
if the image quality adjustment condition is met, obtaining comment information of the played video;
and determining corresponding picture adjustment parameters according to the comment information and a stored preset adjustment library, and adjusting the picture quality of the played video according to the picture adjustment parameters.
In a possible embodiment, before determining the corresponding picture adjustment parameter according to the determined comment information and the stored preset adjustment library, the method further includes:
the method comprises the steps of obtaining a preset adjusting library according to video comment information and a machine learning training model, wherein different keywords and picture adjusting parameters corresponding to the keywords and the picture adjusting parameters are recorded in the preset adjusting library, and the video comment information comprises at least one of a video barrage, a message left below a video and a forwarding title.
In a possible embodiment, the determining, according to the determined comment information and the stored preset adjustment library, the corresponding picture adjustment parameter includes:
extracting keywords from the comment information to obtain one or more keywords;
and determining corresponding picture adjustment parameters according to the one or more keywords and a stored preset adjustment library.
In a possible embodiment, the determining, according to the determined comment information and the stored preset adjustment library, the corresponding picture adjustment parameter includes:
performing machine learning identification on the comment information to obtain one or more keywords;
and determining corresponding picture adjustment parameters according to the one or more keywords and a stored preset adjustment library.
In one possible embodiment, the determining whether the terminal device satisfies the image quality adjustment condition includes:
and determining whether at least one of the current flow use mode, the system load and the residual capacity of the terminal equipment meets an image quality adjusting condition.
In a possible embodiment, before determining the corresponding picture adjustment parameter according to the determined comment information and the stored preset adjustment library, the method further includes:
determining video information of a playing video;
correspondingly, determining the corresponding picture adjustment parameters according to the determined comment information and the stored preset adjustment library comprises the following steps:
and determining corresponding picture adjustment parameters according to the determined comment information, the determined video information and the stored preset adjustment library.
In a possible embodiment, before determining the corresponding picture adjustment parameter according to the determined comment information and the stored preset adjustment library, the method further includes:
determining historical playing information of a playing video;
correspondingly, determining the corresponding picture adjustment parameters according to the determined comment information and the stored preset adjustment library comprises the following steps:
and determining corresponding picture adjustment parameters according to the determined comment information, the historical playing information and the stored preset adjustment library.
Storage medium-any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk, or tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Lanbas (Rambus) RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. The storage medium may also include other types of memory or combinations thereof. In addition, the storage medium may be located in a first computer system in which the program is executed, or may be located in a different second computer system connected to the first computer system through a network (such as the internet). The second computer system may provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations, such as in different computer systems that are connected by a network. The storage medium may store program instructions (e.g., embodied as a computer program) that are executable by one or more processors.
Of course, the storage medium containing the computer-executable instructions provided in the embodiments of the present application is not limited to the operations of the video quality adjustment method described above, and may also perform related operations in the video quality adjustment method provided in any embodiment of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (8)
1. A method for adjusting video quality, comprising:
when a video playing event is detected, determining whether the terminal equipment meets an image quality adjusting condition;
if the image quality adjustment condition is met, obtaining comment information of the played video; determining video information or historical playing information of the playing video;
determining corresponding picture adjustment parameters according to the comment information and a stored preset adjustment library, and adjusting the picture quality of the played video according to the picture adjustment parameters, specifically: determining the picture adjustment parameters according to the comment information, when the picture adjustment parameters are determined to be kept unchanged, matching according to the video theme in the video information of the played video and the content in the preset adjustment library, if the matching fails, determining that the picture adjustment parameters of the played video are 720P or 480P, if the matching succeeds, keeping the current picture adjustment parameters unchanged, and adjusting the picture quality of the played video according to the picture adjustment parameters; or determining the picture adjusting parameters according to the comment information, when the picture adjusting parameters are determined to be kept unchanged, determining the picture adjusting parameters corresponding to the operation starting node and the operation ending node of the playing operation executed at the maximum probability of the current user according to at least one of the skip record, the drag-and-drop record and the fast forward and fast backward record in the historical playing information and a preset training model, and performing reduction adjustment on the picture quality between the operation starting node and the operation ending node of the playing operation executed at the maximum probability according to the picture adjusting parameters; wherein the playing operation comprises at least one of skipping, drag-and-drop and fast forward and fast backward.
2. The method according to claim 1, wherein before determining the corresponding picture adjustment parameter according to the determined comment information and the stored preset adjustment library, the method further comprises:
the method comprises the steps of obtaining a preset adjusting library according to video comment information and a machine learning training model, wherein different keywords and picture adjusting parameters corresponding to the keywords and the picture adjusting parameters are recorded in the preset adjusting library, and the video comment information comprises at least one of a video barrage, a message left below a video and a forwarding title.
3. The method of claim 2, wherein the determining the corresponding picture adjustment parameters according to the determined comment information and a stored preset adjustment library comprises:
extracting keywords from the comment information to obtain one or more keywords;
and determining corresponding picture adjustment parameters according to the one or more keywords and a stored preset adjustment library.
4. The method of claim 2, wherein the determining the corresponding picture adjustment parameters according to the determined comment information and a stored preset adjustment library comprises:
performing machine learning identification on the comment information to obtain one or more keywords;
and determining corresponding picture adjustment parameters according to the one or more keywords and a stored preset adjustment library.
5. The method according to any one of claims 1-4, wherein the determining whether the terminal device satisfies a picture quality adjustment condition comprises:
and determining whether at least one of the current flow use mode, the system load and the residual capacity of the terminal equipment meets an image quality adjusting condition.
6. An apparatus for adjusting video quality, comprising:
the image quality adjustment triggering module is used for determining whether the terminal equipment meets image quality adjustment conditions or not when a video playing event is detected;
the comment information acquisition module is used for acquiring comment information of the played video if the image quality adjustment condition is met; determining video information or historical playing information of the playing video;
the picture parameter determining module is used for determining corresponding picture adjusting parameters according to the comment information and a stored preset adjusting library;
the picture quality adjusting module is used for adjusting the picture quality of the played video according to the picture adjusting parameters;
the picture parameter determining module and the image quality adjusting module are specifically configured to:
determining the picture adjustment parameters according to the comment information, when the picture adjustment parameters are determined to be kept unchanged, matching according to the video theme in the video information of the played video and the content in the preset adjustment library, if the matching fails, determining that the picture adjustment parameters of the played video are 720P or 480P, if the matching succeeds, keeping the current picture adjustment parameters unchanged, and adjusting the picture quality of the played video according to the picture adjustment parameters; or determining the picture adjusting parameters according to the comment information, when the picture adjusting parameters are determined to be kept unchanged, determining the picture adjusting parameters corresponding to the operation starting node and the operation ending node of the playing operation executed at the maximum probability of the current user according to at least one of the skip record, the drag-and-drop record and the fast forward and fast backward record in the historical playing information and a preset training model, and performing reduction adjustment on the picture quality between the operation starting node and the operation ending node of the playing operation executed at the maximum probability according to the picture adjusting parameters; wherein the playing operation comprises at least one of skipping, drag-and-drop and fast forward and fast backward.
7. A terminal device, comprising: processor, memory and computer program stored on the memory and executable on the processor, characterized in that the processor implements the video quality adjustment method according to any of claims 1 to 5 when executing the computer program.
8. A storage medium containing terminal device-executable instructions, which when executed by a terminal device processor, are configured to perform the video quality adjustment method of any one of claims 1-5.
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| CN108712674A (en) * | 2018-05-17 | 2018-10-26 | 深圳创维－Rgb电子有限公司 | Video playing control method, playback equipment and storage medium |
| CN109361949B (en) * | 2018-11-27 | 2020-08-25 | Oppo广东移动通信有限公司 | Video processing method, video processing device, electronic equipment and storage medium |
| CN110337008B (en) * | 2019-06-21 | 2020-10-13 | 腾讯科技（深圳）有限公司 | Video interaction adjusting method, device, equipment and storage medium |
| CN112328152B (en) * | 2020-11-26 | 2022-07-29 | 腾讯科技（深圳）有限公司 | Method and device for controlling playing of media file, electronic equipment and storage medium |
| CN113038288A (en) * | 2021-01-28 | 2021-06-25 | 维沃移动通信有限公司 | Bullet screen control method and device |
| CN114286155A (en) * | 2021-12-07 | 2022-04-05 | 咪咕音乐有限公司 | Picture element modification method, device, equipment and storage medium based on barrage |
| CN114554284B (en) * | 2022-02-22 | 2023-08-11 | 网易（杭州）网络有限公司 | Image quality information processing method, image quality information processing device, computer equipment and storage medium |
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