Data pre-detection method, device, equipment, medium and product

Abstract

The embodiment of the invention provides a data pre-detection method and device, equipment, a medium and a product. The method comprises the steps of obtaining special effect packet data of a target special effect in response to a trigger operation of executing release pre-detection for the target special effect in a target page; the special effect packet data is data required for presenting the target special effect; detecting the special effect packet data according to a special effect detection method corresponding to the at least one detection dimension to obtain a pre-detection result corresponding to the target special effect in the at least one detection dimension; and displaying at least one detection dimension and a pre-detection result corresponding to the detection dimension in a detection result presentation page. According to the technical scheme provided by the embodiment of the invention, the special effect can be pre-detected before being released, so that the effect of determining the efficiency and accuracy of the special effect evaluation result is improved.

Description

Technical Field

[0001] This disclosure relates to the field of computer processing technology, and in particular to a data pre-detection method, apparatus, device, medium, and product. Background Technology

[0002] Special effects artists can create effects in effects programs or effects creation platforms. These effects can be: effects packages used to generate special effects videos or effects templates used to generate special effects videos. After the effects are completed, they can be published to at least one application so that other users can use them.

[0003] Typically, after visual effects are released, they undergo performance evaluation. Currently, performance evaluation mainly relies on the experience of the visual effects artists, which introduces a subjectivity problem. Furthermore, the time required between the release of visual effects and the determination of the evaluation results is relatively long, resulting in a lag in visual effects evaluation. Summary of the Invention

[0004] This disclosure provides a data pre-detection method, apparatus, device, medium, and product, which enables pre-detection of special effects before their release, thereby improving the efficiency and accuracy of determining special effects evaluation results.

[0005] In a first aspect, embodiments of this disclosure provide a data pre-detection method, the method comprising:

[0006] In response to a trigger operation that performs a pre-release detection for a target effect on the target page, the effect package data of the target effect is obtained; wherein, the effect package data is the data required to render the target effect;

[0007] The special effects package data is detected according to the special effects detection method corresponding to at least one detection dimension to obtain the pre-detection result of the target special effects corresponding to the at least one detection dimension; and,

[0008] The detection results page displays at least one detection dimension and the corresponding pre-detection results for that detection dimension;

[0009] The at least one detection dimension includes at least one of the following: package data volume detection dimension, performance detection dimension, and special effects homogenization detection dimension.

[0010] Secondly, embodiments of this disclosure also provide a data pre-detection apparatus, the apparatus comprising:

[0011] The special effects package data acquisition module is used to respond to the trigger operation of performing a release pre-detection for the target special effects on the target page and acquire the special effects package data of the target special effects; wherein, the special effects package data is the data required to present the target special effects;

[0012] The pre-detection result determination module is used to detect the special effects package data according to the special effects detection method corresponding to at least one detection dimension, and obtain the pre-detection result of the target special effects corresponding to the at least one detection dimension; and,

[0013] The pre-detection result display module is used to display the at least one detection dimension and the pre-detection result corresponding to the detection dimension on the detection result presentation page;

[0014] The at least one detection dimension includes at least one of the following: package data volume detection dimension, performance detection dimension, and special effects homogenization detection dimension.

[0015] Thirdly, embodiments of this disclosure also provide an electronic device, the electronic device comprising:

[0016] One or more processors;

[0017] Storage device for storing one or more programs.

[0018] When the one or more programs are executed by the one or more processors, the one or more processors implement the data pre-detection method as described in any of the embodiments of this disclosure.

[0019] Fourthly, embodiments of this disclosure also provide a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the data pre-detection method as described in any of the embodiments of this disclosure.

[0020] Fifthly, embodiments of this disclosure also provide a computer program product, including a computer program that, when executed by a processor, implements the data pre-detection method as described in any of the embodiments of this disclosure.

[0021] The technical solution provided in this disclosure, by responding to a trigger operation of performing a pre-release detection for a target special effect on a target page, obtains the special effect package data of the target special effect; detects the special effect package data according to the special effect detection method corresponding to at least one detection dimension, and obtains the pre-detection result of the target special effect corresponding to the at least one detection dimension; and displays the at least one detection dimension and the pre-detection result corresponding to the detection dimension on the detection result presentation page, solves the problem of low evaluation efficiency and poor accuracy caused by relying on the experience of special effects artists to evaluate special effects in the prior art. It realizes that as long as the operation of performing a pre-release detection for the target special effect is triggered on the target page, the special effect package data of the target special effect can be detected according to the special effect detection method corresponding to different detection dimensions, and the pre-detection result of the target special effect under different detection dimensions before release can be evaluated, thereby improving the efficiency of determining the special effect evaluation result and improving the accuracy of the special effect evaluation. Furthermore, during the detection process, the detection dimensions and their corresponding pre-detection results are displayed in real time, allowing users to intuitively understand the detection status of the target effect under different detection dimensions. This enables users to make timely adjustments to the target effect before release based on the pre-detection results under different detection dimensions, thereby improving the pass rate of the target effect after release. Attached Figure Description

[0022] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0023] Figure 1 A schematic flowchart of a data pre-detection method provided in an embodiment of this disclosure;

[0024] Figure 2 This is an architecture diagram of the data pre-detection system provided in the embodiments of this disclosure;

[0025] Figure 3 This is a schematic diagram for characterizing a target page provided in an embodiment of this disclosure;

[0026] Figure 4 This is a schematic diagram of a page for presenting detection results, provided in an embodiment of this disclosure.

[0027] Figure 5 This is a schematic diagram of a page for presenting detection results, provided in an embodiment of this disclosure.

[0028] Figure 6 This is a schematic diagram of a page for presenting detection results, provided in an embodiment of this disclosure.

[0029] Figure 7 This is a schematic diagram of a page for presenting detection results, provided in an embodiment of this disclosure.

[0030] Figure 8 This is a schematic diagram illustrating an optimized text information display page provided in an embodiment of this disclosure;

[0031] Figure 9 This is a schematic diagram of a page for presenting detection results, provided in an embodiment of this disclosure.

[0032] Figure 10 A schematic flowchart of a data pre-detection method provided in an embodiment of this disclosure;

[0033] Figure 11 A schematic flowchart of a data pre-detection method provided in an embodiment of this disclosure;

[0034] Figure 12 A schematic flowchart of a data pre-detection method provided in an embodiment of this disclosure;

[0035] Figure 13 This is a schematic diagram of the structure of a data pre-detection device provided in an embodiment of the present disclosure;

[0036] Figure 14 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0037] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0038] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0039] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0040] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0041] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0042] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0043] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0044] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware, such as the electronic device, application, server, or storage medium performing the operations of this disclosed technical solution, based on the prompt message.

[0045] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0046] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0047] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.

[0048] Before introducing this technical solution, an exemplary application scenario can be provided. This technical solution can be applied in scenarios where special effects are pre-evaluated before release after production. For example, after creating video special effects or special effects templates, the finished special effects can be released online. Before release, the special effects can be pre-evaluated to quickly determine the corresponding detection results, thereby determining whether the special effects can be released. The technical solution provided in the embodiments of this disclosure can be used when pre-evaluating special effects.

[0049] Figure 1 This is a flowchart illustrating a data pre-detection method provided in an embodiment of the present disclosure. This embodiment is applicable to scenarios where special effects are pre-evaluated before release after production. The method can be executed by a data pre-detection device, which can be implemented in software and / or hardware, or optionally, by an electronic device, such as a mobile terminal, a PC, or a server.

[0050] like Figure 1 As shown, the method in this embodiment may specifically include:

[0051] S110. In response to the triggering operation of publishing pre-detection for the target effect on the target page, obtain the effect package data of the target effect.

[0052] The target effect can be any effect that needs to be pre-evaluated. For example, a target effect can be various visual effects added to a video, such as filters, animations, and transitions. Alternatively, a target effect can be a template for creating a special effects video, including the video layout, animations, and audio. The effects package data contains the data required to present the target effect. For example, the effects package data may include, but is not limited to, the tools used to create the target effect, the operating system the target effect is compatible with, the data volume, image size, audio, animation frames, playback duration, color, composition, and layout. It should be noted that the effects package data corresponding to different types of target effects may be different.

[0053] In this embodiment, a target page can be developed in advance. The target page can be the page corresponding to the completed special effects editing, or it can be the special effects editing page. The target page can contain a control for publishing special effects, which is used to trigger the execution of pre-detection of the target special effects. When a trigger operation on the control is detected, the pre-detection of the target special effects before publishing is triggered. At this time, the special effects package data of the target special effects can be obtained to perform pre-detection of the target special effects based on the special effects package data.

[0054] For example, see Figure 2When it is detected that a user clicks the "Publish" button (i.e. the control for publishing effects) on the target page, it is considered that a pre-detection operation for publishing the target effect has been triggered.

[0055] It should be noted that the technical solution provided in this disclosure can be executed by a client or the target effect can be uploaded to the cloud for execution by the cloud. If executed by the client, the data pre-detection method can be integrated into the client, and the client executes the data pre-detection method to pre-detect the target effect. If executed by the cloud, the data pre-detection method can be integrated into the cloud. Furthermore, before pre-detecting the target effect in the cloud, in response to the trigger operation of publishing pre-detection for the target effect on the target page, the effect package data of the target effect can be cached in the cloud, and the target storage identifier of the effect package data in the cloud can be determined. Based on the target storage identifier, the effect package data of the target effect can be obtained from the cloud, so that the target effect can be pre-detected in the cloud based on the effect package data. The target storage identifier can be used to characterize the uniqueness of the effect package data. For example, the target storage identifier can be a storage path, a database record ID, or any string that can uniquely identify the effect package data.

[0056] S120. Detect the special effects package data according to the special effects detection method corresponding to at least one detection dimension, and obtain the pre-detection result of the target special effects in at least one detection dimension.

[0057] Here, the detection dimension refers to the different dimensions considered when performing special effects detection. The pre-detection result refers to the result obtained after processing the special effects package data under each detection dimension. The pre-detection result can be used to characterize whether the special effects package data passes the corresponding detection dimension.

[0058] In this embodiment, the special effects package data can be detected using the special effects detection method corresponding to each detection dimension. The detection method checks whether the target special effects meet expectations under each detection dimension, obtaining pre-detection results for each detection dimension. These pre-detection results are then combined to evaluate whether the target special effects meet the expected release requirements. Optionally, at least one detection dimension includes at least one of the following: package data volume detection dimension, performance detection dimension, and special effects homogenization detection dimension. The package data volume detection dimension can refer to a dimension that evaluates the size of the special effects package data. The performance detection dimension can refer to a dimension that evaluates the running performance of the target special effects (e.g., rendering time, CPU utilization, memory usage, etc.). The special effects homogenization detection dimension can refer to a dimension that evaluates the similarity or difference between special effects and other special effects under various indicators (e.g., visual style of special effects, animation effects, etc.).

[0059] When the detection dimension includes a packet data volume detection dimension, the special effects detection method includes a data volume detection method corresponding to the packet data volume detection dimension. Based on this, the data volume detection method corresponding to the packet data volume detection dimension can be used to detect the special effects packet data, obtaining the pre-detection result of the target special effects under at least one detection dimension. This can be achieved by: obtaining the packet data volume of the special effects packet data; and when the packet data volume exceeds a preset data volume threshold, determining the pre-detection result of the packet data volume detection dimension as a pre-detection failure.

[0060] Specifically, the package size of the special effects data can be compared with a preset data size threshold. If the package size exceeds the threshold, it indicates that the package size exceeds the preset allowable data size, and the pre-detection result for the package size detection dimension is "pre-detection failed." If the package size does not exceed the threshold, it indicates that the package size does not exceed the preset allowable data size, and the pre-detection result for the package size detection dimension is "pre-detection passed." The advantage of this setting is that by performing package size detection before the target special effects are released, optimization or adjustments can be made to the target special effects in a timely manner if the package size pre-detection fails, reducing their data size to ensure that the target special effects meet the preset data size requirements before release.

[0061] S130. Display at least one detection dimension and the corresponding pre-detection result on the detection result presentation page.

[0062] The detection result presentation page can be a page that visually displays the detection status during the pre-detection process. For example, the detection result presentation page can be a certain area of ​​the target page, a mask covering the target page, or a pop-up window on the top of the target page.

[0063] In this embodiment, during the detection of special effects package data according to the special effects detection method corresponding to at least one detection dimension, each detection dimension and the corresponding pre-detection result can be dynamically displayed on the detection result presentation page. This allows users to intuitively and in real-time understand the pre-detection status of the target special effects under each detection dimension. For example, tables, charts, or other visual elements can be used to display the detection dimensions and their corresponding pre-detection results. To enable users to see the pre-detection status under each detection dimension more intuitively, different colors or icons can be used to highlight the detection dimensions and their pre-detection results based on the different detection dimensions or pre-detection results. For example, a green checkmark indicates a pre-detection result that passes, and a red cross mark indicates a pre-detection result that fails.

[0064] For example, during the pre-inspection process, the detection status corresponding to each detection dimension can be displayed on the detection results presentation page. See the illustration for an example. Figure 3 At this point, the detection status for the three detection dimensions—data volume detection, performance detection, and special effects homogenization detection—is all "detecting." After the pre-detection results corresponding to the detection dimensions are detected, the pre-detection results can be pushed to the detection result display page in real time for display. See the illustration for a similar display. Figure 4 At this point, the pre-detection result for the data volume detection dimension is "pre-detection failed", the pre-detection result for the performance detection dimension is "pre-detection passed", and the detection status for the special effects homogenization detection dimension is still "detecting".

[0065] It should be noted that S120 to S130 can be executed sequentially or in parallel. The order described above is only for explaining the technical solutions in each step, not the execution order of the steps. The advantage of parallel execution is that it allows users to know the current detection status of the target effect in each detection dimension in real time during the pre-detection of the special effects package data.

[0066] To ensure users clearly understand whether the target effect can be published after pre-detection, the target detection results displayed on the detection result page can be adjusted based on the pre-detection results corresponding to at least one detection dimension. The target detection result corresponds to whether the target effect has been published.

[0067] Specifically, the target detection result on the display page can be determined and displayed by combining the pre-detection results corresponding to different detection dimensions. For example, if the pre-detection results for all or some detection dimensions are passed, the target detection result is determined to be passed, indicating that the target effect can be published. Alternatively, if the pre-detection results for all or some detection dimensions are failed, the target detection result is determined to be failed, indicating that the target effect cannot be published, thus informing the user whether the target effect can be published.

[0068] In this embodiment, the target detection result in the detection result presentation page is adjusted according to the pre-detection result corresponding to at least one detection dimension, including: when the pre-detection result of the package data volume detection dimension and / or performance detection dimension is not passed, the target detection result is that the target effect detection is not passed.

[0069] Specifically, if the pre-detection results for the package data volume detection dimension and / or performance detection dimension are "failed," the target detection result is determined to be "target effect detection failed." If the pre-detection results for the package data volume detection dimension and performance detection dimension are "passed," the target detection result is determined to be "target effect detection passed." Furthermore, the target detection results, whether the target effect passed or failed, can be displayed on the detection results presentation page, allowing users to know whether the target effect meets the release requirements.

[0070] For example, see Figure 5 When the pre-detection result for the packet data volume detection dimension is "Pre-detection failed" and the pre-detection result for the performance detection dimension is "Pre-detection passed," the target detection result can be determined as "Detection failed," and this "Detection failed" can be displayed on the detection result presentation page. See also Figure 6 When the pre-inspection result corresponding to the data volume detection dimension is "pre-inspection passed" and the pre-inspection result corresponding to the performance detection dimension is "pre-inspection passed", the target detection result can be determined as "detection passed" and "detection passed" can be displayed on the detection result presentation page.

[0071] In this embodiment, when the target detection result indicates that the target effect has passed the detection, the target effect can also be published in response to the triggering operation of the publish control on the detection result page. After the target effect is published, it can be tested to ensure that it can be used normally after deployment to the actual environment. For example, see [link to example]. Figure 6 When the user clicks "Publish Control" on the detection results page, the target effect is published.

[0072] To help users understand how to improve special effects so that they meet the detection requirements, the system can also respond to the triggering operation of the target control on the detection result page when the target special effect fails the detection, and display optimized text information for the dimension to be detected that failed the pre-detection.

[0073] The dimension to be detected is at least one of the detection dimensions, and the optimized text information includes descriptions of reasons for failure and / or descriptions of optimization suggestions.

[0074] In this embodiment, when the target detection result indicates that the target effect detection fails, the target control can be displayed on the detection result presentation page. When the target control is triggered, optimized text information for the dimension to be detected, whose pre-detection result indicates a pre-detection failure, can be displayed according to a preset method. For example, the preset method can be various methods such as displaying it in the form of a pop-up box, displaying it in the form of a modal window, displaying it in a specific area of ​​the page, or displaying it by launching an H5 page. For examples, see below. Figure 6 When a user clicks the "View Details" button (the target control) on the detection results page, optimized text information is displayed for the failed packet data volume detection dimension and the special effect homogenization detection dimension (the dimension to be detected). See the illustration for an example. Figure 7 .

[0075] The advantage of this setting is that it can dynamically generate optimized text information based on the pre-detection results of failed pre-detection, providing users with specific optimization suggestions and reasons for failure, helping users better understand how to improve special effects so that the special effects meet the detection requirements of the dimension to be detected.

[0076] In this embodiment, if network anomalies and / or data processing anomalies are detected during the determination of pre-detection results, detection failure information can be displayed on the detection result presentation page. This detection failure information includes, but is not limited to, the anomaly type, time, possible causes of the anomaly, and the scope of its impact. For example, see [link to example]. Figure 8 When no network or poor network signal is detected, the detection result page can display a "Detection failed, network error, please try again" message. The advantage of this setting is that it clearly displays the current pre-detection anomaly, allowing users to choose whether to re-trigger the pre-detection for the target effect on the target page or directly publish the target effect.

[0077] It's worth noting that different publishing permissions can be configured for the account information of different special effects creators. Publishing permissions can include direct publishing without pre-check and publishing after pre-check. This way, in the event of network anomalies and / or data processing anomalies, if the account information of the special effects creator to whom the target special effects belongs has the direct publishing permission without pre-check, a direct publishing control can be displayed on the detection results page. This allows users to directly publish the target special effects after triggering the direct publishing control, without pre-check. The advantage of this setting is that it can increase users' enthusiasm for creating special effects while improving the efficiency of publishing high-quality special effects. See the example below. Figure 8 When the "Publish Directly" button is clicked, the target effect will be published.

[0078] Next, the technical solutions provided in the embodiments of this disclosure will be explained in terms of process. Taking the execution of the technical solutions provided in the embodiments of this disclosure in the cloud as an example, when multi-terminal interaction is involved, please refer to... Figure 9 The system architecture diagram shown illustrates this. Its specific implementation can be as follows: Users can create target effects on the client side. In response to the user's triggering of a pre-detection operation for the target effect, the client calls an API to upload the target effect to the cloud. The cloud can then call a model to evaluate the pre-detection results of the target effect under different detection dimensions, synchronously pushing the pre-detection results to the client. The client's detection result display page then shows the detection dimensions and their corresponding pre-detection results in real time. The advantage of performing target effect pre-detection in the cloud is that it can effectively improve detection efficiency.

[0079] The technical solution provided in this disclosure, by responding to a trigger operation of performing a pre-release detection for a target special effect on a target page, obtains the special effect package data of the target special effect; detects the special effect package data according to the special effect detection method corresponding to at least one detection dimension, and obtains the pre-detection result of the target special effect corresponding to the at least one detection dimension; and displays the at least one detection dimension and the pre-detection result corresponding to the detection dimension on the detection result presentation page, solves the problem of low evaluation efficiency and poor accuracy caused by relying on the experience of special effects artists to evaluate special effects in the prior art. It realizes that as long as the operation of performing a pre-release detection for the target special effect is triggered on the target page, the special effect package data of the target special effect can be detected according to the special effect detection method corresponding to different detection dimensions, and the pre-detection result of the target special effect under different detection dimensions before release can be evaluated, thereby improving the efficiency of determining the special effect evaluation result and improving the accuracy of the special effect evaluation. Furthermore, during the detection process, the detection dimensions and their corresponding pre-detection results are displayed in real time, allowing users to intuitively understand the detection status of the target effect under different detection dimensions. This enables users to make timely adjustments to the target effect before release based on the pre-detection results under different detection dimensions, thereby improving the pass rate of the target effect after release.

[0080] Figure 10 This is a flowchart illustrating a data pre-detection method provided in an embodiment of this disclosure. Based on the above embodiments, the technical solution of this embodiment includes at least one detection dimension, namely a performance detection dimension. The special effects detection method corresponding to the performance detection dimension is a performance detection method based on a target performance detection model. Next, the special effects package data can be detected based on the special effects detection method corresponding to the performance detection dimension to determine the pre-detection result of the target special effects in at least one detection dimension. For detailed implementation, please refer to the detailed description of the embodiments of this disclosure. Technical features that are the same as or similar to those in the foregoing embodiments will not be repeated here.

[0081] like Figure 10 As shown, the method in this embodiment may specifically include:

[0082] S210. When the detection dimension is the performance detection dimension, input the special effects data corresponding to the target special effects in the special effects package data into the target performance detection model so that the target performance detection model outputs the special effects running data of the target special effects.

[0083] The target performance detection model can be a pre-trained model used to detect the performance of special effects. For example, the target performance detection model could be a Galileo model. Special effects performance data can refer to performance data used to characterize the running of special effects. For example, special effects performance data includes, but is not limited to, rendering time, memory usage, animation smoothness, frames per second, CPU utilization, and GPU utilization, etc.

[0084] In this embodiment, special effects data corresponding to the target special effects can be extracted from the special effects package data. Then, the special effects data is used as the input of the target performance detection model to output the special effects operation data of the target special effects, so as to evaluate the pre-detection results of the target special effects in the detection dimension of performance detection based on the special effects operation data.

[0085] S220. Based on the special effects operation data, determine the pre-inspection results corresponding to the target special effects in the performance detection dimension.

[0086] In this embodiment, the pre-detection result of the target effect in the performance detection dimension can be evaluated by combining the effect's running data and the expected running data. For example, if the rendering time in the effect's running data is A, which is greater than the expected running data B, it can be considered that the rendering time of the target effect is too long, and therefore, the pre-detection result of the target effect in the performance detection dimension is considered to be a pre-detection failure.

[0087] In this embodiment, in the process of determining the pre-detection result of the target special effect in the performance detection dimension based on the special effect operation data, the pre-detection result of the target special effect in the performance detection dimension can be determined based on the special effect operation data and the threshold data corresponding to the special effect type of the target special effect.

[0088] The effects types include video types and template types. Video-type effects can be understood as various visual effects added to a video. Template-type effects can be understood as template effects used to create videos with special effects. Effect runtime data includes the video frame rate corresponding to the video type, or the memory increment corresponding to the template type. The video frame rate refers to the number of frames played per second in a video or animation. The memory increment refers to the amount of memory used from the start of using the effect to its end.

[0089] Specifically, if the target effect is a video effect, the video frame rate in the effect's runtime data can be compared with the threshold data corresponding to the video type. If the video frame rate is greater than the threshold data corresponding to the video type, the pre-detection result for the target effect in the performance detection dimension is determined to have failed; if the video frame rate is not greater than the threshold data corresponding to the video type, the pre-detection result for the target effect in the performance detection dimension is determined to have passed. If the target effect is a template effect, the memory increment in the effect's runtime data can be compared with the threshold data corresponding to the template type. If the memory increment is greater than the threshold data corresponding to the template type, the pre-detection result for the target effect in the performance detection dimension is determined to have failed; if the memory increment is not greater than the threshold data corresponding to the template type, the pre-detection result for the target effect in the performance detection dimension is determined to have passed.

[0090] It's important to note that the target performance detection model outputs different effect execution data for different effect types. Furthermore, the effect data corresponding to different effect types may also differ, and consequently, the effect data that the model needs to process during performance detection will also vary. Based on this, target performance detection models corresponding to different effect types can be pre-trained. Thus, when determining a target effect, the effect data corresponding to the target effect type can be input into the target performance detection model corresponding to that effect type, enabling the model to output effect execution data of the appropriate effect type and improving the model's accuracy in effect performance detection.

[0091] The technical solution provided in this disclosure involves inputting the special effects data corresponding to the target special effects from the special effects package data into the target performance detection model before the target special effects are released, thereby obtaining the special effects operation data of the target special effects. Then, the performance of the target special effects is tested based on the special effects operation data to determine the pre-detection result of the target special effects in the performance detection dimension. This ensures the accuracy of performance evaluation while allowing timely optimization or adjustment of the target special effects in the event of a pre-detection failure, ensuring that the target special effects meet the preset performance requirements before release.

[0092] Figure 11This is a flowchart illustrating a data pre-detection method provided in an embodiment of this disclosure. Based on the above embodiments, the technical solution of this embodiment includes at least one detection dimension: a special effects homogenization detection dimension. The special effects detection method corresponding to the special effects homogenization detection dimension is a homogenization detection method based on a homogenization detection model. Next, based on the special effects detection method corresponding to the special effects homogenization detection dimension, the pre-detection result corresponding to the target special effects in at least one detection dimension can be determined. For detailed implementation methods, please refer to the detailed description of the embodiments of this disclosure. Technical features that are the same as or similar to those in the foregoing embodiments will not be repeated here.

[0093] like Figure 11 As shown, the method in this embodiment may specifically include:

[0094] S310. Obtain the effect name information, effect material information, and effect thumbnail from the effect package data.

[0095] The special effects name information can be a unique identifier or title for the special effects. For example, the special effects name information includes, but is not limited to, a description of the special effects (such as their purpose, characteristics, or usage scenarios) and classification information (such as explosions, smoke, and magic effects). Special effects material information can refer to the resources used to create the animation effects. For example, special effects material information includes, but is not limited to, the textures or maps used, 3D models, animation sequences, audio data, and physical materials used (such as reflectivity, transparency, and glow properties). Special effects thumbnails can refer to thumbnail images used to preview the special effects. For example, a special effects thumbnail can be a static image representing the special effects or a dynamic image representing the special effects.

[0096] In this embodiment, the special effects name information, special effects material information, and special effects thumbnail corresponding to the target special effects can be extracted from the special effects package data, and the pre-detection results corresponding to the target special effects under the special effects homogenization detection dimension can be evaluated by combining this information.

[0097] S320. Input the special effect name information, special effect material information, and special effect thumbnail into the homogenization detection model, and output the first feature vector corresponding to the special effect name information, the second feature vector corresponding to the special effect material information, and the third feature vector corresponding to the special effect thumbnail.

[0098] Among them, the homogenization detection model can be a model used to detect the degree of similarity between special effects and other special effects.

[0099] In this embodiment, the special effects name information, special effects material information, and special effects thumbnail can be input into the homogenization detection model, so that the homogenization detection model extracts a feature vector that can represent the special effects name information as a first feature vector, extracts a feature vector that can represent the special effects material information as a second feature vector, and extracts a feature vector that can represent the special effects thumbnail as a third feature vector, so as to perform subsequent homogenization detection based on these feature vectors and evaluate the uniqueness or similarity of the special effects.

[0100] It's important to note that to improve the accuracy of feature extraction, the homogenization detection model can use different feature extraction methods based on the data types of the three data types: effect name information, effect material information, and effect thumbnail. These methods extract feature vectors from the input data under different data types. For example, if the effect name information is text, methods such as TF-IDF (a feature vector method for text mining) or Word2Vec (a method that generates word vectors by learning semantic relationships between words) can be used to convert the text into a numerical vector, extracting the first feature vector of the effect name information. If the effect thumbnail is image, machine learning or deep learning algorithms (such as Support Vector Machines, ResNet, and VGG) can be used to extract deep features from the image, extracting the second feature vector of the effect thumbnail. The effect material information includes data types such as textures, models, and animations, and machine learning or deep learning algorithms can be used to extract the third feature vector of the effect material information.

[0101] S330. Based on the first feature vector, the second feature vector, the third feature vector, and the effect vectors of the published effects stored in the homogenization comparison library, determine the pre-detection result of the target effect in the effect homogenization detection dimension.

[0102] In this embodiment, a similarity calculation method can be used to compare the first feature vector, the second feature vector, and the third feature vector with the effect vectors of published effects stored in the homogenization comparison library. This analyzes the similarity between the target effect and each published effect stored in the homogenization comparison library. If the similarity is greater than a preset similarity value, the target effect is considered to have a high degree of similarity to the published effects, and the pre-detection result for the target effect in the effect homogenization detection dimension is determined to be a pre-detection failure. If the similarity is not greater than the preset similarity value, the pre-detection result for the target effect in the effect homogenization detection dimension is determined to be a pre-detection success.

[0103] To improve the accuracy of homogenization detection, the process of determining the pre-detection result of the target effect in the homogenization detection dimension can be based on the first feature vector, the second feature vector, the third feature vector, and the effect vectors of published effects stored in the homogenization comparison library. Specifically, this involves determining the first similarity attribute between the name vector in the first feature vector and the effect vector; determining the second similarity attribute between the material vector in the second feature vector and the effect vector; and determining the third similarity attribute between the thumbnail vector in the third feature vector and the effect vector. When the first, second, and third similarity attributes meet preset conditions, the pre-detection result is determined to be passed.

[0104] The first similarity attribute can be used to characterize the similarity of the effect name information between the target effect and the published effects. The second similarity attribute can be used to characterize the similarity of the effect material information used by the target effect and the published effects. The third similarity attribute can be used to characterize the similarity of the effect thumbnails between the target effect and the published effects. The preset conditions can refer to the conditions used to evaluate whether the target effect meets the homogenization expectation.

[0105] In this embodiment, a similarity calculation method can be used to calculate the similarity between the first feature vector and the name vector in the effect vector, which is used as the first similarity attribute. A similarity calculation method can also be used to calculate the similarity between the second feature vector and the material vector in the effect vector, which is used as the second similarity attribute. A similarity calculation method can also be used to calculate the similarity between the third feature vector and the thumbnail vector in the effect vector, which is used as the third similarity attribute. Furthermore, the first, second, and third similarity attributes can be combined to determine whether a pre-defined condition is met. If the pre-defined condition is met, the pre-detection result is determined to be a pass. If the pre-defined condition is not met, the pre-detection result is determined to be a fail.

[0106] For example, the preset conditions may include conditions such as the first similarity attribute not being greater than a first similarity threshold, the second similarity attribute not being greater than a second similarity threshold, and the third similarity attribute not being greater than a third similarity threshold. Thus, if at least one of the first, second, and third similarity attributes exceeds its corresponding similarity threshold, the preset conditions are considered not met. Alternatively, the preset conditions may also be a combination of similarity thresholds corresponding to at least two of the first, second, and third similarity attributes. For example, the preset conditions may include, but are not limited to, at least one of the following conditions: the first similarity attribute is not greater than a preset second threshold and the second similarity attribute is not greater than a preset first threshold; the first similarity attribute is not greater than a preset fourth threshold and the third similarity attribute is not greater than a preset third threshold; the second similarity attribute is not greater than a preset fifth threshold and the third similarity attribute is not greater than a preset sixth threshold. Thus, if it is determined that any preset condition is not met based on the first, second, and third similarity attributes, the pre-detection result is determined to be a pre-detection failure.

[0107] The technical solution provided in this disclosure improves the comprehensiveness of effect similarity comparison by comparing feature vectors representing three different types of information characteristic of the target effect with the corresponding feature vectors of the released effect, thereby improving the accuracy of homogenization detection. Furthermore, the homogenization detection requirements can be dynamically controlled through preset conditions to support different homogenization detection needs.

[0108] It should be noted that, to improve the accuracy of similarity attribute determination, different similarity calculation methods can be used based on the data types of the three types of data: effect name information, effect material information, and effect thumbnail, to extract the similarity attributes between feature vectors under different data types. For example, if the data type of the effect name information is text, a similarity calculation method based on Euclidean distance or other distance metrics can be used to determine the first similarity attribute between the first feature vector and the name vector in the effect vector. If the data type of the effect thumbnail is image, a calculation method based on cosine similarity can be used to determine the second and third similarity attributes.

[0109] The technical solution provided in this embodiment obtains the special effects name information, special effects material information, and special effects thumbnails from the special effects package data. It then determines a first feature vector corresponding to the special effects name information, a second feature vector corresponding to the special effects material information, and a third feature vector corresponding to the special effects thumbnail. Furthermore, by combining the first, second, and third feature vectors with the effect vectors of released special effects stored in the homogenization comparison library, the similarity between special effects is determined. Using similarity to represent the degree of homogenization effectively improves the accuracy of special effects homogenization assessment. Simultaneously, it allows for timely personalized optimization or adjustment of the target special effects in cases where pre-detection fails, ensuring that the target special effects meet personalized needs and improving the quality of the target special effects.

[0110] Figure 12 This is a flowchart illustrating a data pre-detection method provided in an embodiment of this disclosure. Based on the above embodiments, the technical solution of this embodiment allows for the following steps: after pre-detecting the target effect, if the target detection result meets preset requirements (e.g., the target effect passes detection), the target effect can be published. Even after publishing the target effect, it will still be detected to ensure it meets the requirements for deployment to the client. The detection method after publishing the target effect can be found in the detailed description of the embodiments of this disclosure. Technical features that are the same as or similar to those in the foregoing embodiments will not be repeated here.

[0111] like Figure 12 As shown, the method in this embodiment may specifically include:

[0112] S410. When the target effect type is a template type, obtain the real device running data when the target effect is running, so as to obtain the first release detection result of the target effect in the performance detection dimension based on the real device running data.

[0113] Among them, real device running data can refer to the actual data of the target effect running on a real operating system, which can truly reflect the performance of the target effect on the actual device.

[0114] Specifically, after releasing the target effect, the template-type target effect can be sent to a real device for testing to obtain real device performance data. Furthermore, by analyzing the real device performance data, the first release test result for the target effect in performance testing can be determined. For example, the memory increment in the real device performance data can be compared with the threshold data corresponding to the template type. If the memory increment is less than the threshold data, the first release test result is confirmed as passed; otherwise, the first release test result is confirmed as failed.

[0115] It should be noted that when the target effect is a video type, S210 and S220 can be executed repeatedly, and the pre-detection result of the target effect in the performance detection dimension determined based on the target performance detection model can be used as the first release detection result of the target effect in the performance detection dimension.

[0116] S420. Input the special effects video corresponding to the target special effects into the homogenization detection model corresponding to the special effects homogenization detection dimension to obtain the video vector of the special effects video. Based on the video vector and the pre-detection results corresponding to the special effects homogenization detection dimension, determine the second release detection result of the special effects homogenization detection dimension.

[0117] In this embodiment, a special effects video corresponding to the target special effects can be created. Then, the special effects video is input into a homogenization detection model corresponding to the special effects homogenization detection dimension, and feature vectors characterizing the special effects video are extracted as video vectors. A similarity calculation method can be used to determine the similarity between this video vector and the special effects video vectors corresponding to the published special effects, thus determining the video similarity. Furthermore, the video similarity and the pre-detection results corresponding to the target special effects in the special effects homogenization detection dimension can be combined to comprehensively determine the second publication detection result in the special effects homogenization detection dimension. For example, if the video similarity is greater than a preset similarity threshold, and / or the pre-detection result in the special effects homogenization detection dimension is a pre-detection pass, the second publication detection result is determined to be a detection pass.

[0118] Alternatively, the second release detection result of the target effect in the effect homogenization detection dimension can be determined based on video similarity, the first similarity attribute, the second similarity attribute, and the third similarity attribute. For example, the second release detection result can be determined as failing detection when at least one of the following recall conditions is met based on video similarity, the first similarity attribute, the second similarity attribute, and the third similarity attribute. For example, the recall conditions can be: the second similarity attribute is higher than a set first threshold (e.g., 0.6) and the video similarity is higher than a set second threshold (e.g., 0.98); the second similarity attribute is higher than a set third threshold (e.g., 0.6) and the first similarity attribute is higher than a set fourth threshold (e.g., 0.33); the third similarity attribute is higher than a set fifth threshold (e.g., 0.9) and the third similarity attribute is higher than a set sixth threshold (e.g., 0.64); the video similarity is higher than a set seventh threshold (e.g., 0.98) and the first similarity attribute is higher than a set eighth threshold (e.g., 0.3); the video similarity is higher than a set ninth threshold (e.g., 0.98) and the third similarity attribute is higher than a set tenth threshold (e.g., 0.9); the video similarity is higher than a set eleventh threshold (e.g., 0.99). It should be noted that these thresholds are just example values, and the specific values ​​can be determined according to the actual detection requirements, which are not limited here.

[0119] It should be noted that when the target effect is a video effect, the steps corresponding to S420 can be repeated to obtain the second release detection result of the target effect under the effect homogenization detection dimension.

[0120] S430. Based on the first release detection result, the second release detection result, and the pre-detection result corresponding to the packet data volume detection dimension, determine the target release detection result of the target effect.

[0121] Specifically, the target release detection result of the target effect can be determined to be passed if one or more, or all, of the results of the first release detection, the second release detection, and the pre-detection results corresponding to the packet data volume detection dimension pass the detection. It should be noted that if the effect type of the target effect is video, the steps corresponding to S430 can be repeated to determine the target release detection result of the target effect.

[0122] Next, taking the detection method after the release of target special effects in the cloud as an example, we will further explain the technical solution provided in this disclosure embodiment. Please continue to refer to... Figure 9 .

[0123] The target performance detection model and homogenization detection model can be pre-trained and deployed in the cloud. After the target effect is released, a detection task can be created in the cloud. If the target effect is a template type, it is tested on a real device to obtain the first release detection result in the performance detection dimension. If the target effect is a video type, the effect data can be input into the target performance detection model for performance evaluation to obtain the first release detection result in the performance detection dimension. The corresponding effect video is then input into the homogenization detection model to determine the second release detection result in the homogenization detection dimension. Based on the first and second release detection results, as well as the pre-detection results corresponding to the packet data volume detection dimension, the target release detection result for the target effect is determined. After determining the target release detection result, if the target release detection result is passed, the target effect can be deployed to the actual environment for use by target users. If the target release detection result is "failed", the target release detection result can be fed back to the special effects production team so that the special effects production team can optimize the target special effects.

[0124] The technical solution provided in this disclosure involves obtaining real-device running data of the target special effect (template type) after its release, and then determining the first release detection result of the target special effect in the performance detection dimension based on the real-device running data. Simultaneously, the special effect video corresponding to the target special effect is input into a homogenization detection model to obtain the video vector of the special effect video. Combining the video vector with the pre-detection results corresponding to the special effect homogenization detection dimension, a second release detection result in the special effect homogenization detection dimension is determined. Finally, by combining the first release detection result, the second release detection result, and the pre-detection results corresponding to the packet data volume detection dimension, the target release detection result of the target special effect is determined. This, combined with the release detection result, determines whether the target special effect can be launched online, ensuring that the target special effect can be used normally in a real environment.

[0125] Figure 13 This is a schematic diagram of the structure of a data pre-detection device provided in an embodiment of the present disclosure, as shown below. Figure 13 As shown, the device includes: a special effects package data acquisition module 510, a pre-inspection result determination module 520, and a pre-inspection result display module 530.

[0126] The special effects package data acquisition module 510 is used to acquire the special effects package data of the target special effects in response to a trigger operation for performing a release pre-detection on the target page; wherein the special effects package data is the data required to present the target special effects; the pre-detection result determination module 520 is used to detect the special effects package data according to the special effects detection method corresponding to at least one detection dimension, and obtain the pre-detection result of the target special effects corresponding to the at least one detection dimension; the pre-detection result display module 530 is used to display the at least one detection dimension and the pre-detection result corresponding to the detection dimension on the detection result display page; wherein the at least one detection dimension includes at least one of the package data volume detection dimension, performance detection dimension, and special effects homogenization detection dimension.

[0127] Based on the above-mentioned device, optionally, the special effects detection method includes a data volume detection method corresponding to the packet data volume detection dimension, a special effects detection method corresponding to the performance detection dimension that is a performance detection method based on a target performance detection model, and / or a special effects detection method corresponding to the special effects homogenization detection dimension that is a homogenization detection method based on a homogenization detection model.

[0128] Based on the above-mentioned device, optionally, the pre-inspection result determination module 520 includes:

[0129] The special effects operation data determination unit is used to input the special effects data corresponding to the target special effects in the special effects package data into the target performance detection model when the detection dimension is the performance detection dimension, so that the target performance detection model outputs the special effects operation data of the target special effects;

[0130] The first pre-inspection result determination unit is used to determine the pre-inspection result corresponding to the target special effect in the performance detection dimension based on the special effect operation data.

[0131] Based on the above-mentioned device, optionally, the pre-detection result determination first unit is specifically used to determine the pre-detection result corresponding to the target special effect in the performance detection dimension based on the special effect operation data and the threshold data corresponding to the special effect type of the target special effect; wherein, the special effect type includes video type or template type, and the special effect operation data includes the video frame rate corresponding to the video type, or the memory increment corresponding to the template type.

[0132] Based on the above-mentioned device, optionally, the detection dimension is a special effect homogenization detection dimension, and the pre-detection result determination module 520 includes:

[0133] The information acquisition unit is used to acquire the special effects name information, special effects material information, and special effects thumbnails from the special effects package data;

[0134] The feature vector determination unit is used to input the special effect name information, the special effect material information, and the special effect thumbnail into the homogenization detection model, and output a first feature vector corresponding to the special effect name information, a second feature vector corresponding to the special effect material information, and a third feature vector corresponding to the special effect thumbnail;

[0135] The pre-detection result determination second unit is used to determine the pre-detection result of the target special effect in the special effect homogenization detection dimension based on the first feature vector, the second feature vector, the third feature vector, and the special effect vectors of published special effects stored in the homogenization comparison library.

[0136] Based on the above-mentioned device, optionally, the pre-inspection results determine the second unit, including:

[0137] The first similarity attribute determination module is used to determine the first similarity attribute between the first feature vector and the name vector in the effect vector;

[0138] The second similarity attribute determination module is used to determine the second similarity attribute between the second feature vector and the material vector in the special effect vector;

[0139] The third similarity attribute determination module is used to determine the third similarity attribute between the third feature vector and the thumbnail vector in the effect vector;

[0140] The preset condition judgment module is used to determine that the pre-inspection result is passed when the first similarity attribute, the second similarity attribute, and the third similarity attribute meet the preset conditions.

[0141] Optionally, based on the above-described apparatus, the apparatus may further include:

[0142] The target detection result adjustment module is used to adjust the target detection result in the detection result presentation page according to the pre-detection result corresponding to the at least one detection dimension; wherein, the target detection result corresponds to the result of whether the target effect has been released.

[0143] Based on the above device, optionally, a target detection result adjustment module is used to determine that the target effect detection fails when the pre-detection results of the package data volume detection dimension and / or the performance detection dimension are not passed.

[0144] Optionally, based on the above-described apparatus, the apparatus may further include:

[0145] The optimized text information display module is used to display optimized text information for the target dimension that failed the pre-detection when the target detection result is that the target effect detection fails, in response to the trigger operation of the target control on the detection result presentation page; wherein, the target dimension is the detection dimension among the at least one detection dimension, and the optimized text information includes description information of the reason for failure and / or description information of optimization suggestions.

[0146] Optionally, based on the above-described apparatus, after the target special effect is released, the apparatus further includes:

[0147] The first release detection result determination module is used to obtain real device running data when the effect type of the target effect is a template type, so as to obtain the first release detection result of the target effect in the performance detection dimension based on the real device running data;

[0148] The first release detection result determination module is used to input the special effect video corresponding to the target special effect into the homogenization detection module corresponding to the special effect homogenization detection dimension for modeling, to obtain the video vector of the special effect video, and to determine the second release detection result of the special effect homogenization detection dimension based on the video vector and the pre-detection result corresponding to the special effect homogenization detection dimension.

[0149] The target release detection result determination module is used to determine the target release detection result of the target effect based on the first release detection result, the second release detection result, and the pre-detection result corresponding to the packet data volume detection dimension.

[0150] The technical solution of this disclosure, by responding to a trigger operation of performing a pre-release detection for a target special effect on a target page, obtains the special effect package data of the target special effect; detects the special effect package data according to the special effect detection method corresponding to at least one detection dimension, and obtains the pre-detection result of the target special effect corresponding to the at least one detection dimension; and displays the at least one detection dimension and the pre-detection result corresponding to the detection dimension on a detection result presentation page, solves the problem of low evaluation efficiency and poor accuracy caused by relying on the experience of special effects artists to evaluate special effects in the prior art. It realizes that as long as the operation of performing a pre-release detection for the target special effect is triggered on the target page, the special effect package data of the target special effect can be detected according to the special effect detection method corresponding to different detection dimensions, and the pre-detection result of the target special effect under different detection dimensions before release can be evaluated, thereby achieving high efficiency in determining the special effect evaluation result and improving the accuracy of the special effect evaluation. Furthermore, during the detection process, the detection dimensions and their corresponding pre-detection results are displayed in real time, allowing users to intuitively understand the detection status of the target effect under different detection dimensions. This enables users to make timely adjustments to the target effect before release based on the pre-detection results under different detection dimensions, thereby improving the pass rate of the target effect after release.

[0151] The data pre-detection device provided in this disclosure can execute the data pre-detection method provided in any embodiment of this disclosure, and has the corresponding functional modules and beneficial effects for executing the method.

[0152] It is worth noting that the various units and modules included in the above-mentioned device are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the protection scope of the embodiments of this disclosure.

[0153] Figure 14 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Figure 14As shown, electronic device 600 may include a processing device (e.g., a central processing unit, a graphics processor, etc.) 601, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 602 or a program loaded from storage device 608 into random access memory (RAM) 603. RAM 603 also stores various programs and data required for the operation of electronic device 600. Processing device 601, ROM 602, and RAM 603 are interconnected via bus 604. Input / output (I / O) interface 605 is also connected to bus 604.

[0154] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic device 600 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 14 An electronic device 600 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0155] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a storage device 608, or installed from a ROM 602. When the computer program is executed by the processing device 601, it performs the functions defined in the methods of embodiments of this disclosure.

[0156] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0157] The electronic device provided in this disclosure and the data pre-detection method provided in the above embodiments belong to the same inventive concept. Technical details not described in detail in this disclosure can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0158] This disclosure provides a computer storage medium storing a computer program that, when executed by a processor, implements the data pre-detection method provided in the above embodiments.

[0159] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0160] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0161] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0162] The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to:

[0163] In response to a trigger operation that performs a pre-release detection for a target effect on the target page, the effect package data of the target effect is obtained; wherein, the effect package data is the data required to render the target effect;

[0164] The special effects package data is detected according to the special effects detection method corresponding to at least one detection dimension to obtain the pre-detection result of the target special effects corresponding to the at least one detection dimension; and,

[0165] The detection results page displays at least one detection dimension and the corresponding pre-detection results for that detection dimension;

[0166] The at least one detection dimension includes at least one of the following: package data volume detection dimension, performance detection dimension, and special effects homogenization detection dimension.

[0167] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0168] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0169] The units described in the embodiments of this disclosure can be implemented in software or in hardware. The name of a unit does not necessarily limit the unit itself; for example, the first acquisition unit can also be described as "a unit that acquires at least two Internet Protocol addresses".

[0170] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0171] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0172] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0173] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0174] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A data pre-detection method, characterized in that, include: In response to a trigger operation that performs a pre-release detection for a target effect on the target page, the effect package data of the target effect is obtained; wherein, the effect package data is the data required to render the target effect; The special effects package data is detected according to the special effects detection method corresponding to at least one detection dimension to obtain the pre-detection result of the target special effects corresponding to the at least one detection dimension; and, The detection results page displays at least one detection dimension and the corresponding pre-detection results for that detection dimension; The at least one detection dimension includes at least one of the following: package data volume detection dimension, performance detection dimension, and special effects homogenization detection dimension.

2. The method according to claim 1, characterized in that, The special effects detection method includes a data volume detection method corresponding to the package data volume detection dimension, a special effects detection method corresponding to the performance detection dimension that is a performance detection method based on the target performance detection model, and / or a special effects detection method corresponding to the special effects homogenization detection dimension that is a homogenization detection method based on the homogenization detection model.

3. The method according to claim 2, characterized in that, The method of detecting the special effects package data according to the special effects detection method corresponding to at least one detection dimension, and obtaining the pre-detection result of the target special effects corresponding to the at least one detection dimension, includes: When the detection dimension is the performance detection dimension, the special effects data corresponding to the target special effects in the special effects package data is input into the target performance detection model so that the target performance detection model outputs the special effects running data of the target special effects; Based on the special effects operation data, determine the pre-detection result corresponding to the target special effects in the performance detection dimension.

4. The method according to claim 3, characterized in that, The step of determining the pre-detection result of the target special effect in the performance detection dimension based on the special effect operation data includes: Based on the special effects operation data and the threshold data corresponding to the special effects type of the target special effects, the pre-detection result corresponding to the target special effects in the performance detection dimension is determined; The special effects type includes video type or template type, and the special effects running data includes the video frame rate corresponding to the video type, or the memory increment corresponding to the template type.

5. The method according to claim 2, characterized in that, The detection dimension is a special effects homogenization detection dimension. The step of detecting the special effects package data according to the special effects detection method corresponding to at least one detection dimension to obtain the pre-detection result of the target special effects corresponding to the at least one detection dimension includes: Obtain the special effects name information, special effects material information, and special effects thumbnails from the special effects package data; The special effect name information, the special effect material information, and the special effect thumbnail are input into the homogenization detection model, and the model outputs a first feature vector corresponding to the special effect name information, a second feature vector corresponding to the special effect material information, and a third feature vector corresponding to the special effect thumbnail. Based on the first feature vector, the second feature vector, the third feature vector, and the effect vectors of published effects stored in the homogenization comparison library, the pre-detection result of the target effect in the effect homogenization detection dimension is determined.

6. The method according to claim 5, characterized in that, The step of determining the pre-detection result of the target special effect in the special effect homogenization detection dimension based on the first feature vector, the second feature vector, the third feature vector, and the special effect vectors of published special effects stored in the homogenization comparison library includes: Determine the first similarity attribute between the name vectors in the first feature vector and the effect vector; Determine a second similarity attribute between the second feature vector and the material vector in the effect vector; Determine the third similarity attribute between the third feature vector and the thumbnail vector in the effect vector; When the first similarity attribute, the second similarity attribute, and the third similarity attribute meet the preset conditions, the pre-inspection result is determined to be a successful pre-inspection.

7. The method according to claim 1, characterized in that, The method further includes: Based on the pre-detection results corresponding to the at least one detection dimension, adjust the target detection results in the detection result presentation page; The target detection result corresponds to whether the target effect has been released.

8. The method according to claim 7, characterized in that, The step of adjusting the target detection result in the detection result presentation page based on the pre-detection result corresponding to the at least one detection dimension includes: If the pre-detection results for the package data volume detection dimension and / or the performance detection dimension are both unsuccessful, the target detection result is that the target effect detection fails.

9. The method according to claim 7 or 8, characterized in that, The method further includes: If the target detection result is that the target effect fails the detection, in response to the trigger operation of the target control on the detection result display page, the optimized text information of the dimension to be detected that failed the pre-detection result is displayed. Wherein, the dimension to be detected is the detection dimension among the at least one detection dimension, and the optimized text information includes description information of reasons for failure and / or description information of optimization suggestions.

10. The method according to claim 1, characterized in that, After releasing the target effect, the method further includes: When the effect type of the target effect is a template type, obtain the real device running data when the target effect is running, so as to obtain the first release detection result of the target effect in the performance detection dimension based on the real device running data; The special effects video corresponding to the target special effects is input into the homogenization detection model corresponding to the special effects homogenization detection dimension to obtain the video vector of the special effects video. Based on the video vector and the pre-detection result corresponding to the special effects homogenization detection dimension, the second release detection result of the special effects homogenization detection dimension is determined. Based on the first release detection result, the second release detection result, and the pre-detection result corresponding to the packet data volume detection dimension, the target release detection result of the target effect is determined.

11. A data pre-detection device, characterized in that, include: The special effects package data acquisition module is used to respond to the trigger operation of performing a release pre-detection for the target special effects on the target page and acquire the special effects package data of the target special effects; wherein, the special effects package data is the data required to present the target special effects; The pre-detection result determination module is used to detect the special effects package data according to the special effects detection method corresponding to at least one detection dimension, and obtain the pre-detection result of the target special effects corresponding to the at least one detection dimension; The pre-detection result display module is used to display the at least one detection dimension and the pre-detection result corresponding to the detection dimension on the detection result presentation page; The at least one detection dimension includes at least one of the following: package data volume detection dimension, performance detection dimension, and special effects homogenization detection dimension.

12. An electronic device, characterized in that, The electronic device includes: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the data pre-detection method as described in any one of claims 1-10.

13. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the data pre-detection method as described in any one of claims 1-10.

14. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the data pre-detection method as described in any one of claims 1-10.

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