A multimedia production task processing method, device, electronic device and medium

Abstract

The embodiments of the present invention provide a method, device, electronic device and medium for processing multimedia production tasks, including: before processing a multimedia production task to be submitted, obtaining first parameter information and expected completion time information for processing the multimedia production task input by a user; inputting the first parameter information and the expected completion time information into a preset model to obtain first estimated completion time information for the multimedia production task; determining the production resources configured for the multimedia production task according to the first estimated completion time information, and generating corresponding resource configuration suggestions; when the multimedia production task is submitted using the resource configuration suggestions, processing the multimedia production task according to the production resources. According to the embodiments of the present invention, while ensuring that the multimedia production task is completed according to the time limit requirements, production resources can be released for more urgent multimedia production tasks.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a multimedia production task processing method, a multimedia production task processing device, an electronic device and a computer-readable storage medium. Background Art

[0002] When processing multimedia data, such as transcoding or rendering video data, after the editor submits the production task to the production system, due to the large amount of data that needs to be processed, there are problems with resource allocation and processing efficiency. The final completion time of the production task cannot be predicted, which affects the subsequent work progress and work arrangements. Summary of the invention

[0003] In view of the above problems, embodiments of the present invention are proposed to provide a multimedia production task processing method and a corresponding multimedia production task processing device, an electronic device, and a computer-readable storage medium that overcome the above problems or at least partially solve the above problems.

[0004] An embodiment of the present invention discloses a method for processing multimedia production tasks, the method comprising:

[0005] Before processing the submitted multimedia production task, obtaining first parameter information and expected completion time information for processing the multimedia production task input by the user; the first parameter information is target parameter information required for target multimedia data; the target multimedia data is generated by converting the initial multimedia data in the multimedia production task;

[0006] Inputting the first parameter information and the expected completion time information into a preset model to obtain first estimated completion time information for the multimedia production task;

[0007] Determine the production resources to be configured for the multimedia production task according to the first estimated completion time information, and generate corresponding resource configuration suggestions;

[0008] When the multimedia production task is submitted using the resource configuration suggestion, the multimedia production task is processed according to the production resources.

[0009] Optionally, the step of inputting the first parameter information and the expected completion time information into a preset model to obtain first estimated completion time information for the multimedia production task includes:

[0010] Acquire at least one preset priority parameter information; the preset priority parameter information corresponds to a preset production resource;

[0011] The at least one preset priority parameter information, the first parameter information and the expected completion time information are input into a preset model to obtain the first estimated completion time information corresponding to the at least one preset priority parameter information for the multimedia production task.

[0012] Optionally, determining the production resources to be configured for the multimedia production task according to the first estimated completion time information includes:

[0013] Determining, according to the first estimated completion time information, target priority parameter information used for processing the multimedia production task from the at least one preset priority parameter information;

[0014] The target production resource corresponding to the target priority parameter information is determined as the production resource configured for the multimedia production task.

[0015] Optionally, determining, according to the first estimated completion time information, target priority parameter information used for processing the multimedia production task from the at least one preset priority parameter information includes:

[0016] respectively calculating the time difference between the first estimated completion time information and the expected completion time information;

[0017] Determine the first estimated completion time information having the smallest time difference with the expected completion time information as the target first estimated completion time information;

[0018] The preset priority parameter information corresponding to the target first estimated completion time information is determined as the target priority parameter information used to process the multimedia production task.

[0019] Optionally, the preset model is trained in the following manner:

[0020] Acquire time-consuming training data; the time-consuming training data includes second parameter information of a multimedia production task for training and corresponding task completion time information;

[0021] The adjustment parameters in the time-consuming training data training model are used to obtain the corresponding preset model.

[0022] Optionally, the method further comprises:

[0023] Updating the time-consuming training data;

[0024] If the mean square error value of the model trained with the updated time-consuming training data meets the preset threshold condition, the model trained with the updated time-consuming training data is updated to the preset model.

[0025] Optionally, the method further comprises:

[0026] In response to a user's request to view the completion time of a current multimedia production task being processed, calling the preset model to determine second estimated completion time information for the current multimedia production task;

[0027] The second estimated completion time information is displayed to the user.

[0028] The embodiment of the present invention further discloses a multimedia production task processing device, the device comprising:

[0029] A first acquisition module is used to acquire first parameter information and expected completion time information input by a user for processing the multimedia production task before processing the submitted multimedia production task; the first parameter information is target parameter information required for target multimedia data; the target multimedia data is generated by converting the initial multimedia data in the multimedia production task;

[0030] An input module, used for inputting the first parameter information and the expected completion time information into a preset model to obtain first estimated completion time information for the multimedia production task;

[0031] a determination module, configured to determine the production resources to be configured for the multimedia production task according to the first estimated completion time information, and to generate corresponding resource configuration suggestions;

[0032] A processing module is used to process the multimedia production task according to the production resources when the multimedia production task is submitted using the resource configuration suggestion.

[0033] Optionally, the input module includes:

[0034] An acquisition submodule, used to acquire at least one preset priority parameter information; the preset priority parameter information corresponds to a preset production resource;

[0035] An input submodule is used to input the at least one preset priority parameter information, the first parameter information and the expected completion time information into a preset model to obtain the first expected completion time information corresponding to the at least one preset priority parameter information for the multimedia production task.

[0036] Optionally, the determining module includes:

[0037] A first determination submodule, configured to determine, according to the first estimated completion time information, target priority parameter information used for processing the multimedia production task from the at least one preset priority parameter information;

[0038] The second determination submodule is used to determine the target production resource corresponding to the target priority parameter information as the production resource configured for the multimedia production task.

[0039] Optionally, the first determining submodule includes:

[0040] a calculation unit, configured to respectively calculate a time difference between the first estimated completion time information and the expected completion time information;

[0041] A first determining unit, configured to determine the first estimated completion time information having the smallest time difference with the expected completion time information as the target first estimated completion time information;

[0042] The second determining unit is used to determine the preset priority parameter information corresponding to the target first estimated completion time information as the target priority parameter information used for processing the multimedia production task.

[0043] Optionally, the preset model is trained in the following manner:

[0044] A second acquisition module is used to acquire time-consuming training data; the time-consuming training data includes second parameter information of a multimedia production task for training and corresponding task completion time information;

[0045] The training module is used to adopt the adjustment parameters in the time-consuming training data training model to obtain the corresponding preset model.

[0046] Optionally, the device further comprises:

[0047] A first updating module, used for updating the time-consuming training data;

[0048] The second updating module is used to update the model trained with the updated time-consuming training data to the preset model if the mean square error value of the model trained with the updated time-consuming training data meets the preset threshold condition.

[0049] Optionally, the device further comprises:

[0050] A calling module, configured to, in response to a user's request to view the completion time of a current multimedia production task being processed, call the preset model to determine second estimated completion time information for the current multimedia production task;

[0051] A display module is used to display the second estimated completion time information to the user.

[0052] An embodiment of the present invention further discloses an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the steps of a multimedia production task processing method as described above are implemented.

[0053] An embodiment of the present invention further discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the multimedia production task processing method described above are implemented.

[0054] The embodiments of the present invention include the following advantages:

[0055] In an embodiment of the present invention, before processing a multimedia production task, the first parameter information and expected completion time information input by the user can be used to predict the expected completion time of the multimedia production task through a preset model, and a corresponding resource configuration suggestion can be generated to assist the user in submitting the task. By adopting the above method, while ensuring that the multimedia production task is completed according to the time limit requirements, production resources can be released for more urgent multimedia production tasks to avoid task timeout problems caused by shortage of production resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 is a flowchart of the steps of a multimedia production task processing method according to an embodiment of the present invention;

[0057] Figure 2 is a flowchart of another method for processing multimedia production tasks according to an embodiment of the present invention;

[0058] Figure 3 is a schematic diagram of time-consuming training data for a video transcoding task;

[0059] Figure 4 It is a schematic diagram of the training, deployment and update process of a preset model;

[0060] Figure 5 is a flow chart of a multimedia production task processing method according to an embodiment of the present invention;

[0061] Figure 6 It is a structural block diagram of a multimedia production task processing device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0062] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0063] In a multimedia data production environment, when editors submit multimedia production tasks, due to the limited production resources of the production system, they cannot know the final completion time of task processing for a large number of multimedia production tasks, which affects subsequent task processing or scheduling.

[0064] One of the core concepts of the embodiment of the present invention is that before processing a multimedia production task, the first parameter information and expected completion time information input by the user can be used to predict the expected completion time of the multimedia production task through a preset model, and a corresponding resource allocation suggestion is generated to assist the user in submitting the task. By adopting the above method, while ensuring that the multimedia production task is completed according to the time limit requirements, production resources can be released for more urgent multimedia production tasks to avoid task timeout problems caused by shortage of production resources.

[0065] Reference Figure 1 , shows a flowchart of a method for processing multimedia production tasks according to an embodiment of the present invention, which may specifically include the following steps:

[0066] Step 101 : before processing the multimedia production task to be submitted, obtaining first parameter information and expected completion time information for processing the multimedia production task input by the user.

[0067] The first parameter information is target parameter information required for the target multimedia data after the multimedia data corresponding to the multimedia production task is converted into the target multimedia data when executing the multimedia production task. In other words, the first parameter information is target parameter information required for the target multimedia data, and the target multimedia data is generated by converting the initial multimedia data in the multimedia production task.

[0068] In the embodiment of the present invention, the multimedia production task may be an audio and video production task, wherein the video production task may be a video transcoding task, a video rendering task, etc.; the audio production task may be an audio format conversion task, a subtitle generation task, etc. The multimedia production task may be various audio and video production tasks, and the embodiment of the present invention does not impose any specific limitation on this.

[0069] In an embodiment of the present invention, a multimedia production task may be executed in a production system. When a multimedia production task is submitted in the production system, the multimedia production task begins to be processed. In this embodiment, a user may input first parameter information for processing a multimedia production task in the production system. The first parameter information is parameter information for converting current multimedia data into target multimedia data. For example, there is currently a video transcoding task. The bit rate of the current video data is A1, and the bit rate of the target video data is A2. A2 is the first parameter information input by the user. The first parameter information varies according to different multimedia tasks. The first parameter information may be one or more of video attribute information such as video bit rate information, playback platform information, clarity information, video encryption information, and the like. It may also be one or more of audio attribute information such as audio format information and channel information.

[0070] The user may also input expected completion time information of processing multimedia production tasks in the production system, and the expected completion time information may be set according to the actual work needs of the user.

[0071] Step 102: input the first parameter information and the expected completion time information into a preset model to obtain first estimated completion time information for the multimedia production task.

[0072] In an embodiment of the present invention, a preset model is established, and the preset model can be used to determine the estimated completion time of the multimedia production task according to the first parameter information and the expected completion time information input by the user. The first estimated completion time information can meet the time limit requirement corresponding to the expected completion time information.

[0073] In one example, the preset model may be a regression model, and the regression model may be obtained by training a large amount of multimedia production task data. Preferably, various types of multimedia production task data may be trained separately according to categories to improve the prediction accuracy of the model.

[0074] Step 103: determine the production resources to be configured for the multimedia production task according to the first estimated completion time information, and generate corresponding resource configuration suggestions.

[0075] In an embodiment of the present invention, after a preset model is used to predict the first estimated completion time information for a multimedia production task, production resources in the production system can be allocated according to the first estimated completion time information. The allocation of production resources may include the allocation of occupied channel resources, cluster resources and other resources. For the same multimedia production task, the more production resources are allocated, the less time it takes to complete the task processing. The production resources in the production system are limited, and the present invention can determine the allocation of production resources based on the estimated completion time of the multimedia production task. In one example, for multiple multimedia production tasks to be submitted, a preset model can be used to predict the corresponding multiple first estimated completion time information, and the production resources can be allocated in chronological order.

[0076] In an embodiment of the present invention, after determining the production resources configured for the multimedia production task, a corresponding resource configuration suggestion may be generated and displayed to the user. In one example, the resource configuration suggestion may be displayed in a pop-up window.

[0077] Step 104: When the multimedia production task is submitted using the resource configuration suggestion, the multimedia production task is processed according to the production resources.

[0078] In an embodiment of the present invention, the user can determine whether to adopt the resource configuration suggestion. If it is determined to adopt, the multimedia production task is processed according to the production resources in the resource configuration suggestion. In one example, the multimedia production task can be submitted in the production system using the resource configuration suggestion. After the task is submitted, the multimedia production task can be processed according to the production resources in the suggestion.

[0079] In summary, in an embodiment of the present invention, before processing a multimedia production task, the first parameter information and expected completion time information input by the user can be used to predict the expected completion time of the multimedia production task through a preset model, and a corresponding resource configuration suggestion can be generated to assist the user in submitting the task. By adopting the above method, while ensuring that the multimedia production task is completed within the time limit, production resources can be released for more urgent multimedia production tasks to avoid task timeouts caused by a shortage of production resources.

[0080] Reference Figure 2 , shows a flowchart of another method for processing multimedia production tasks according to an embodiment of the present invention, which may specifically include the following steps:

[0081] Step 201 : before processing the submitted multimedia production task, obtaining first parameter information and expected completion time information for processing the multimedia production task input by the user.

[0082] The first parameter information is target parameter information required for the target multimedia data after the multimedia data corresponding to the multimedia production task is converted into the target multimedia data when executing the multimedia production task. In other words, the first parameter information is target parameter information required for the target multimedia data, and the target multimedia data is generated by converting the initial multimedia data in the multimedia production task.

[0083] In an embodiment of the present invention, the multimedia production task may be an audio and video production task. The multimedia production task may be executed in a production system, and a user may input first parameter information and expected completion time information for processing the multimedia production task in the production system. The first parameter information may be one or more of video attribute information or audio attribute information.

[0084] Step 202: Obtain at least one preset priority parameter information.

[0085] Among them, the preset priority parameter information corresponds to the preset production resources.

[0086] In an embodiment of the present invention, at least one preset priority parameter information is set in the production system. For example, three priorities can be set in the production system, namely high priority, medium priority and low priority. Different priorities correspond to different production resources. It can be assumed that the production resource corresponding to the high priority is A1, the production resource corresponding to the medium priority is A2, and the production resource corresponding to the low priority is A3. The higher the priority, the more production resources can be used, that is, A1 can be set to be greater than A2, and A2 can be set to be greater than A3.

[0087] In the embodiment of the present invention, all preset priority parameter information in the production system can be obtained.

[0088] Step 203: Input the at least one preset priority parameter information, the first parameter information and the expected completion time information into a preset model to obtain the first estimated completion time information corresponding to the at least one preset priority parameter information for the multimedia production task.

[0089] In the embodiment of the present invention, for different preset priority parameter information, the preset model is called respectively to predict the estimated completion time of the multimedia production task. For example, if there are three priority parameter information, the preset model is called respectively to predict the completion time of the multimedia production task, and three first estimated completion time information are obtained accordingly.

[0090] In one example, a preset model can be trained in the following way:

[0091] Acquire time-consuming training data; the time-consuming training data includes second parameter information of a multimedia production task for training and corresponding task completion time information; adopt the adjustment parameters in the training model of the time-consuming training data to obtain the corresponding preset model.

[0092] In an embodiment of the present invention, a large amount of time-consuming training data can be used for model training. The time-consuming training data may include second parameter information and task completion time information. The second parameter information is the target parameter information required for the target multimedia data after the multimedia data corresponding to the multimedia production task for training is converted into the target multimedia data for executing the multimedia production task for training. The task completion time information may be the task execution completion time of the multimedia production task for training. The second parameter information may be one or more of the characteristic parameters of the multimedia data.

[0093] Since there are many categories of feature parameters of multimedia data to be processed corresponding to multimedia production tasks, the GBDT algorithm (Gradient Boosting Decision Tree) can be adopted. Using the open source XGBoost framework, the acquired time-consuming training data is trained to adjust the parameters in the training model to obtain the required preset model.

[0094] Reference Figure 3 The figure shows a schematic diagram of time-consuming training data for a video transcoding task. The video feature parameters of the video data corresponding to the video transcoding task may include: task name, program duration, channel, bit rate, frame rate, transcoding method, program type, encoding method, color range, etc. The corresponding feature parameters can be selected for model training as needed. The task completion time in the time-consuming training data may include four stages: queuing time, transcoding time, distribution time, and confirmation time. Among them, the queuing time may be the time required to queue because there are other tasks that have not been started before the task is executed, which is limited by the use of resources. The transcoding time may be the execution time of the transcoding stage. The distribution time may be the time used to distribute the video data after the transcoding is completed. The confirmation time may be the time consumed by the user to perform quality review and other operations. Adopt Figure 3 When the model trained with the time-consuming training data shown in the figure is used for prediction, the duration of each stage can be predicted, and a total duration can also be predicted. That is, the duration of a multimedia production task can be predicted in stages.

[0095] It should be noted that the time-consuming training data mentioned above is only one type of training data, and those skilled in the art may also use other time-consuming training data for model training, and the embodiments of the present invention do not impose any specific limitation on this.

[0096] In one example, the preset model can be updated in the following ways:

[0097] The time-consuming training data is updated; if the mean square error value of the model trained with the updated time-consuming training data meets the preset threshold condition, the model trained with the updated time-consuming training data is updated to the preset model.

[0098] In an embodiment of the present invention, the preset model can be updated by updating the time-consuming training data and training the model with the updated time-consuming training data. The MSE (Mean Square Error) of the new model can be detected on the test set. When the preset threshold condition is met, the new model is used to replace the old model.

[0099] In a preferred embodiment, the preset model can be deployed in the preset service. By deploying the preset model online and using GRPC (Google Remote Procedure Call) to deploy the preset service, the user's completion time prediction request for multimedia production tasks can be responded to in real time.

[0100] Reference Figure 4 The figure shows a schematic diagram of the training, deployment and update process of a preset model. By collecting the characteristic parameters and time-consuming data of the completed multimedia production tasks, the time-consuming training data that can be used for training is sorted, and the time-consuming training data is trained to obtain a time-consuming estimation model (preset model), and the time-consuming estimation model is deployed in the GRPC prediction service. The MSE is calculated to determine whether to update the model.

[0101] Step 204: determine the production resources to be configured for the multimedia production task according to the first estimated completion time information, and generate corresponding resource configuration suggestions.

[0102] In the embodiment of the present invention, production resources in the production system may be allocated according to the first estimated completion time information, and corresponding resource allocation suggestions may be generated.

[0103] With respect to step 204, production resources are allocated to the multimedia production task, and the following steps may be specifically performed:

[0104] Sub-step S11, determining, based on the first estimated completion time information, target priority parameter information used for processing the multimedia production task from the at least one preset priority parameter information.

[0105] In the embodiment of the present invention, target priority parameter information is determined from at least one preset priority parameter information according to the acquired first estimated completion time information.

[0106] For sub-step S11, the following steps may be specifically performed:

[0107] Respectively calculate the time difference between the first estimated completion time information and the expected completion time information; determine the first estimated completion time information having the smallest time difference with the expected completion time information as the target first estimated completion time information; and determine the preset priority parameter information corresponding to the target first estimated completion time information as the target priority parameter information used to process the multimedia production task.

[0108] In the embodiment of the present invention, the time difference may be calculated, the first estimated completion time information having the smallest time difference with the expected completion time information may be used as the target first estimated completion time information, and the corresponding target priority parameter information may be determined.

[0109] Sub-step S12: determining the target production resource corresponding to the target priority parameter information as the production resource configured for the multimedia production task.

[0110] According to the corresponding relationship, the target production resources corresponding to the target priority parameter information are determined.

[0111] In the embodiment of the present invention, the resource configuration suggestion may be a priority parameter setting suggestion, and the priority parameter setting suggestion may be displayed to the user.

[0112] Step 205: When the multimedia production task is submitted using the resource configuration suggestion, the multimedia production task is processed according to the production resources.

[0113] When the user submits a multimedia production task using a priority parameter setting suggestion, the multimedia production task is processed according to the target production resources corresponding to the target priority parameter information in the priority parameter setting suggestion.

[0114] In the embodiment of the present invention, a preset model may also be used to predict the completion time of the current multimedia production task being processed. Specifically, the following steps may be performed:

[0115] In response to a user's request to view the completion time of a current multimedia production task being processed, the preset model is called to determine second estimated completion time information for the current multimedia production task; and the second estimated completion time information is displayed to the user.

[0116] In the embodiment of the present invention, for the current multimedia production task being processed, the second estimated completion time information can also be predicted by calling the preset model, that is, the remaining completion time of the submitted multimedia production task can be predicted.

[0117] In order to enable those skilled in the art to better understand step 201 to step 205 of the embodiment of the present invention, an example is given below to illustrate:

[0118] Reference Figure 5 The flowchart of a multimedia production task processing method according to an embodiment of the present invention is shown. The specific process is as follows:

[0119] 1. The preset model is deployed in the GRPC prediction service;

[0120] 2. For the multimedia production tasks being executed, the preset model in the GRPC prediction service can be called to predict the completion time of the task and display it to the user in a visual way;

[0121] 3. For multimedia production tasks to be submitted, for different priority parameters, the preset model is called to predict the completion time respectively, and multiple estimated completion times corresponding to multiple priority parameters are obtained. After comparing with the expected completion time, the corresponding priority parameter setting suggestions are generated to assist users in submitting tasks.

[0122] In summary, in an embodiment of the present invention, before processing a multimedia production task, the first parameter information and expected completion time information input by the user can be used to predict the expected completion time of the multimedia production task through a preset model, and a corresponding resource configuration suggestion can be generated to assist the user in submitting the task. By adopting the above method, while ensuring that the multimedia production task is completed according to the time limit requirements, production resources can be released for more urgent multimedia production tasks to avoid task timeouts caused by a shortage of production resources. By training time-consuming training data and using a machine learning algorithm to train a preset model, for submitted multimedia production tasks, the model can be called to predict its completion time and displayed to the user in a visual manner; for multimedia production tasks to be submitted, the model is used to automatically calculate the optional priority parameters that meet the time limit requirements based on the necessary parameters for executing the task and the expected completion time, to assist editors in submitting tasks and make full use of production resources.

[0123] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0124] Reference Figure 6 , shows a structural block diagram of a multimedia production task processing device according to an embodiment of the present invention, which may specifically include the following modules:

[0125] The first acquisition module 601 is used to acquire first parameter information and expected completion time information for processing the multimedia production task input by the user before processing the submitted multimedia production task; the first parameter information is target parameter information required for the target multimedia data; the target multimedia data is generated by converting the initial multimedia data in the multimedia production task;

[0126] An input module 602 is used to input the first parameter information and the expected completion time information into a preset model to obtain first estimated completion time information for the multimedia production task;

[0127] A determination module 603 is used to determine the production resources to be configured for the multimedia production task according to the first estimated completion time information, and generate corresponding resource configuration suggestions;

[0128] The processing module 604 is used to process the multimedia production task according to the production resources when the multimedia production task is submitted using the resource configuration suggestion.

[0129] In an embodiment of the present invention, the input module includes:

[0130] An acquisition submodule, used to acquire at least one preset priority parameter information; the preset priority parameter information corresponds to a preset production resource;

[0131] An input submodule is used to input the at least one preset priority parameter information, the first parameter information and the expected completion time information into a preset model to obtain the first expected completion time information corresponding to the at least one preset priority parameter information for the multimedia production task.

[0132] In an embodiment of the present invention, the determining module includes:

[0133] A first determination submodule, configured to determine, according to the first estimated completion time information, target priority parameter information used for processing the multimedia production task from the at least one preset priority parameter information;

[0134] The second determination submodule is used to determine the target production resource corresponding to the target priority parameter information as the production resource configured for the multimedia production task.

[0135] In this embodiment of the present invention, the first determining submodule includes:

[0136] a calculation unit, configured to respectively calculate a time difference between the first estimated completion time information and the expected completion time information;

[0137] A first determining unit, configured to determine the first estimated completion time information having the smallest time difference with the expected completion time information as the target first estimated completion time information;

[0138] The second determining unit is used to determine the preset priority parameter information corresponding to the target first estimated completion time information as the target priority parameter information used for processing the multimedia production task.

[0139] In an embodiment of the present invention, the preset model is trained in the following manner:

[0140] A second acquisition module is used to acquire time-consuming training data; the time-consuming training data includes second parameter information of a multimedia production task for training and corresponding task completion time information;

[0141] The training module is used to adopt the adjustment parameters in the time-consuming training data training model to obtain the corresponding preset model.

[0142] In an embodiment of the present invention, the device further includes:

[0143] A first updating module, used for updating the time-consuming training data;

[0144] The second updating module is used to update the model trained with the updated time-consuming training data to the preset model if the mean square error value of the model trained with the updated time-consuming training data meets the preset threshold condition.

[0145] In an embodiment of the present invention, the device further includes:

[0146] A calling module, configured to, in response to a user's request to view the completion time of a current multimedia production task being processed, call the preset model to determine second estimated completion time information for the current multimedia production task;

[0147] A display module is used to display the second estimated completion time information to the user.

[0148] In summary, in an embodiment of the present invention, before processing a multimedia production task, the first parameter information and expected completion time information input by the user can be used to predict the expected completion time of the multimedia production task through a preset model, and a corresponding resource configuration suggestion can be generated to assist the user in submitting the task. By adopting the above method, while ensuring that the multimedia production task is completed according to the time limit requirements, production resources can be released for more urgent multimedia production tasks to avoid task timeouts caused by a shortage of production resources. By training time-consuming training data and using a machine learning algorithm to train a preset model, for submitted multimedia production tasks, the model can be called to predict its completion time and displayed to the user in a visual manner; for multimedia production tasks to be submitted, the model is used to automatically calculate the optional priority parameters that meet the time limit requirements based on the necessary parameters for executing the task and the expected completion time, to assist editors in submitting tasks and make full use of production resources.

[0149] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0150] An embodiment of the present invention also provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, the various processes of the above-mentioned multimedia production task processing method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0151] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned multimedia production task processing method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0152] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0153] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0154] It will be appreciated by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0155] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0156] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0157] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable terminal device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0158] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0159] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0160] The multimedia production task processing method, a multimedia production task processing device, an electronic device and a computer-readable storage medium provided by the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A multimedia production task processing method, It is characterized in that The method comprises: Before the submitted multimedia production task is processed by the production system, first parameter information and expected completion time information for processing the multimedia production task input by the user are obtained; the first parameter information is target parameter information required for target multimedia data; the target multimedia data is generated by converting the initial multimedia data in the multimedia production task; Inputting at least one preset priority parameter information, the first parameter information and the expected completion time information into a preset model to obtain first expected completion time information for the multimedia production task, wherein the at least one preset priority parameter information is set in the production system; Determine the production resources to be configured for the multimedia production task according to the first estimated completion time information, and generate corresponding resource configuration suggestions; When the multimedia production task is submitted using the resource configuration suggestion, the multimedia production task is processed according to the production resources; The determining of the production resources configured for the multimedia production task according to the first estimated completion time information includes: Determining, according to the first estimated completion time information, target priority parameter information used for processing the multimedia production task from the at least one preset priority parameter information; The target production resource corresponding to the target priority parameter information is determined as the production resource configured for the multimedia production task.

2. The method according to claim 1, It is characterized in that The step of inputting the first parameter information and the expected completion time information into a preset model to obtain first estimated completion time information for the multimedia production task includes: Acquire at least one preset priority parameter information; the preset priority parameter information corresponds to a preset production resource; The at least one preset priority parameter information, the first parameter information and the expected completion time information are input into a preset model to obtain the first estimated completion time information corresponding to the at least one preset priority parameter information for the multimedia production task.

3. The method according to claim 1, It is characterized in that The step of determining, based on the first estimated completion time information, target priority parameter information for processing the multimedia production task from the at least one preset priority parameter information comprises: respectively calculating the time difference between the first estimated completion time information and the expected completion time information; Determine the first estimated completion time information having the smallest time difference with the expected completion time information as the target first estimated completion time information; The preset priority parameter information corresponding to the target first estimated completion time information is determined as the target priority parameter information used to process the multimedia production task.

4. The method according to claim 1, It is characterized in that The preset model is trained in the following way: Acquire time-consuming training data; the time-consuming training data includes second parameter information of a multimedia production task for training and corresponding task completion time information; The adjustment parameters in the time-consuming training data training model are used to obtain the corresponding preset model.

5. The method according to claim 4, It is characterized in that The method further comprises: Updating the time-consuming training data; If the mean square error value of the model trained with the updated time-consuming training data meets the preset threshold condition, the model trained with the updated time-consuming training data is updated to the preset model.

6. The method according to claim 1, It is characterized in that The method further comprises: In response to a user's request to view the completion time of a current multimedia production task being processed, calling the preset model to determine second estimated completion time information for the current multimedia production task; The second estimated completion time information is displayed to the user.

7. A multimedia production task processing device, It is characterized in that The device comprises: A first acquisition module is used to acquire first parameter information and expected completion time information for processing the multimedia production task input by the user before the multimedia production task to be submitted is processed by the production system; the first parameter information is target parameter information required for the target multimedia data; the target multimedia data is generated by converting the initial multimedia data in the multimedia production task; An input module, used to input at least one preset priority parameter information, the first parameter information and the expected completion time information into a preset model to obtain first expected completion time information for the multimedia production task, wherein the at least one preset priority parameter information is set in the production system; a determination module, configured to determine the production resources to be configured for the multimedia production task according to the first estimated completion time information, and to generate corresponding resource configuration suggestions; A processing module, configured to process the multimedia production task according to the production resources when the multimedia production task is submitted using the resource configuration suggestion; The determining module comprises: A first determination submodule, configured to determine, according to the first estimated completion time information, target priority parameter information used for processing the multimedia production task from the at least one preset priority parameter information; The second determination submodule is used to determine the target production resource corresponding to the target priority parameter information as the production resource configured for the multimedia production task.

8. An electronic device, It is characterized in that include: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the steps of a multimedia production task processing method as described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of a multimedia production task processing method as described in any one of claims 1 to 6 are implemented.

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