Model data processing method and device and electronic equipment

Abstract

The invention provides a model data processing method and apparatus, and an electronic device. The method comprises the steps of obtaining to-be-processed data; the to-be-processed data comprises model data of the target role model and action data corresponding to at least one animation action; the target role model comprises a plurality of sub-models; determining single-frame form data based on the model data and the action data; the single-frame form data is used for indicating the form of each sub-model in each animation frame corresponding to each animation action; and based on the single-frame form data, determining a model interpenetration condition of the target role model in the process of performing each animation action. According to the mode, batch combination processing is performed on the model data and the action data, the form data of the model in each animation frame of the animation action is obtained, then the model interpenetration condition in the animation action process of the model is determined, the interpenetration detection efficiency in the game action process of the model is improved, and the labor cost is reduced.

Description

Technical Field

[0001] This disclosure relates to the field of three-dimensional modeling technology, and more specifically, to a method, apparatus, and electronic device for processing model data. Background Technology

[0002] In traditional animation or game animation, character models may exhibit overlapping or interlacing issues as they move, resulting in poor visual effects. Related technologies typically rely on manual observation to determine if this overlap occurs. For example, in long-running projects with a massive amount of animation, during the early stages of production using Digital Content Creation (DCC) software, experience is often needed to proactively verify and filter the suitability of individual actions. To check for model overlap during animation, manual testing within the game is required. This testing cycle often lasts a week or even several weeks. This method is inefficient and costly for checking overlap effects during model movement. Summary of the Invention

[0003] In view of this, the purpose of this disclosure is to provide a method, apparatus and electronic device for processing model data, so as to improve the efficiency of interlacing detection during the game action process of the model and reduce the labor cost.

[0004] In a first aspect, embodiments of this disclosure provide a method for processing model data, the method comprising: acquiring data to be processed; the data to be processed includes model data of a target character model and motion data corresponding to at least one animation action; the target character model includes multiple sub-models; determining single-frame morphological data based on the model data and motion data; the single-frame morphological data is used to indicate: the morphology of each sub-model in each animation frame corresponding to each animation action; and determining the model interleaving situation of the target character model during each animation action based on the single-frame morphological data.

[0005] Secondly, embodiments of this disclosure provide a model data processing apparatus, comprising: a data acquisition module for acquiring data to be processed; the data to be processed includes model data of a target character model and motion data corresponding to at least one animation action; the target character model includes multiple sub-models; a single-frame morphology data determination module for determining single-frame morphology data based on the model data and motion data; the single-frame morphology data is used to indicate the morphology of each sub-model in each animation frame corresponding to each animation action; and a model interleaving determination module for determining the model interleaving situation of the target character model during each animation action based on the single-frame morphology data.

[0006] Thirdly, embodiments of the present invention provide an electronic device, including a processor and a memory, wherein the memory stores machine-executable instructions that can be executed by the processor, and the processor executes the machine-executable instructions to implement the above-described method for processing model data.

[0007] Fourthly, embodiments of the present invention provide a machine-readable storage medium storing machine-executable instructions. When the machine-executable instructions are invoked and executed by a processor, the machine-executable instructions cause the processor to implement the above-described method for processing model data.

[0008] The embodiments of the present invention bring the following beneficial effects:

[0009] The aforementioned method, apparatus, and electronic device for processing model data acquire data to be processed. The data to be processed includes model data of a target character model and motion data corresponding to at least one animation action. The target character model includes multiple sub-models. Based on the model data and motion data, single-frame morphological data is determined. The single-frame morphological data indicates the morphology of each sub-model in each animation frame corresponding to each animation action. Based on the single-frame morphological data, the model interleaving situation of the target character model during each animation action is determined. This method, by batch combining and processing model data and motion data, obtains the morphological data of the model in each animation frame of the animation action, thereby determining the model interleaving situation during the animation action, improving the efficiency of interleaving detection during game actions and reducing labor costs.

[0010] Other features and advantages of this disclosure will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the disclosure. The objects and other advantages of this disclosure are realized and obtained through the structures particularly pointed out in the description, claims and drawings.

[0011] To make the above-mentioned objects, features and advantages of this disclosure more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the specific embodiments of this disclosure or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0013] Figure 1 A flowchart illustrating a method for processing model data provided in this embodiment of the disclosure;

[0014] Figure 2 A node structure diagram in a skinning caching process provided in this embodiment of the disclosure;

[0015] Figure 3 This is a schematic diagram of the shape of a target character model in a single animation frame, provided by an embodiment of the present disclosure.

[0016] Figure 4 This is a schematic diagram of the structure of a model data processing device provided in an embodiment of the present disclosure;

[0017] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0019] In related technologies, interleaving detection heavily relies on manual observation and review to determine the compatibility between actions and models. However, long-term projects involve a massive amount of actions. Besides the initial production phase in DCC software (such as Max and Maya) where experience is typically used to proactively verify and select the compatibility of individual actions, manual testing within the game is also essential. This process usually lasts a week or even several weeks, resulting in high labor costs and low efficiency.

[0020] Based on this, the present disclosure provides a method, apparatus, and electronic device for processing model data, which can be applied to model interleaving evaluation scenarios involving multiple models and multiple actions.

[0021] See Figure 1 First, a method for processing model data provided by an embodiment of the present invention will be introduced. This method includes the following steps:

[0022] Step S102: Obtain the data to be processed; the data to be processed includes the model data of the target character model and the action data corresponding to at least one animation action; the target character model includes multiple sub-models.

[0023] The target character model described above is typically a 3D model. This model has multiple sub-models, each usually connected to at least one other sub-model, allowing them to be considered as a single entity. The surface of each sub-model is typically composed of multiple connected vertices. At least one sub-model usually has a corresponding skeleton. The skeleton is typically composed of multiple connected bones. Sub-models with skeletons can perform corresponding animation actions based on motion data. Sub-models without skeletons are usually attached to other sub-models. When the attachment point moves, the attached sub-model also moves; when the attachment point rotates, the attached sub-model also rotates.

[0024] The model data mentioned above typically includes the positions of the vertices of each sub-model. When a sub-model has corresponding bones, its model data usually also includes its skinning data. The skinning data indicates which bones(s) influence the position of a vertex on the model, and the influence weight of each bone. When a sub-model does not have corresponding bones, its model data may include its attachment positions to other sub-models, indicating the relative position between the sub-model and the attached sub-models.

[0025] The target character model mentioned above can be one or more. Different target character models can include the same or different numbers of sub-models. This can be set according to requirements and is not limited here. When there are multiple target character models, it is necessary to verify the model interleaving during each animation action for each target character model.

[0026] The data to be processed mentioned above can include motion data corresponding to one or more animation actions. Each animation action typically has a corresponding duration. The motion data corresponding to each animation action usually indicates the changes in position and posture of multiple bones in a preset skeleton during the duration of that animation action. Specifically, it can be represented by interpolation. For example, if the duration is 1 second, the motion data can be the position and posture of multiple bones at times 0.1, 0.2, 0.3, ..., 1.0. The motion data can also be a function of the position and posture of each bone in multiple skeletons changing over time. This function uses time as the independent variable and the position and posture of the bones as the dependent variable, which can represent the continuous changes in the position and posture of the bones. The specific settings can be configured according to requirements and are not limited here.

[0027] Step S104: Based on the model data and motion data, determine the single-frame shape data; the single-frame shape data is used to indicate the shape of each sub-model in each animation frame corresponding to each animation action.

[0028] Animations are typically formed by playing multiple animation frames consecutively. As mentioned above, each animation action usually has a corresponding duration. The animation frame corresponding to an animation action usually refers to the animation frame played within that duration. The animation frame corresponding to an animation action is usually determined based on the frame rate of the animation playback. For example, at a frame rate of 30 frames per second, if the duration of an animation action is 2 seconds, then the animation frame corresponding to the animation action is 60 frames.

[0029] The form of each sub-model in each animation frame needs to be determined based on model data and motion data. The form of a sub-model in an animation frame is affected by the sub-model's own model data and the motion data corresponding to that animation frame. The moment corresponding to an animation frame within the duration of an animation action is fixed, and the motion data corresponding to that animation frame can be determined based on the motion data corresponding to the animation action.

[0030] When the motion data corresponding to an animation action consists of the position and pose data of multiple bones at various moments within a duration, we can check if the moment corresponding to the animation frame exists. If it exists, the position and pose data of the multiple bones at that moment can be directly determined as the motion data corresponding to that animation frame. If it is not found, interpolation calculations can be performed based on the position and pose data of multiple bones at two moments adjacent to the moment corresponding to the animation frame to obtain the position and pose data of the multiple bones corresponding to that animation frame, i.e., the motion data corresponding to that animation frame.

[0031] Single-frame morphology data needs to include the morphology data of each sub-model in each animation frame. Therefore, the model data of each sub-model and the motion data corresponding to each animation frame can be combined, and then the morphology data of the sub-model and animation frame corresponding to the current combined data can be determined based on the combined data.

[0032] In the specific implementation process, when the sub-model has a preset skeleton, the current position of each vertex in the sub-model can be determined based on the skinning data of the sub-model and the bone position and posture indicated by the motion data corresponding to the current animation frame. The position data of each vertex in the sub-model can represent the shape of the sub-model in the animation frame, that is, it can be regarded as the shape data of the sub-model in the animation frame.

[0033] When a sub-model does not have a pre-defined skeleton but is attached to other sub-models via attachment points, the current position and pose of the attachment point can be determined based on the bone position and pose indicated by the motion data corresponding to the current animation frame. Then, based on the initial position and pose of the attachment point, as well as its current position and pose, a pose transformation matrix for the attachment point is generated. This pose transformation matrix is ​​then applied to each vertex of the sub-model attached through the attachment point, causing each vertex to undergo position and pose changes through the pose transformation matrix, creating the effect that the pose change of the attachment point drives the pose change of the sub-model.

[0034] The processing logic for the combined data of model data and motion data corresponding to animation frames for each sub-model is similar. These combined data can be processed simultaneously by multiple threads, which greatly improves processing efficiency.

[0035] Step S106: Based on single-frame morphological data, determine the model interleaving situation of the target character model during each animation action.

[0036] After determining the single-frame morphological data, it is necessary to extract the single-frame morphological data for the same animation action from it, and then determine the model interleaving situation of the target character model during a certain animation action. When there are multiple target character models, it is also necessary to divide the single-frame morphological data based on both the target character models and the animation actions.

[0037] During the animation of a target character model, the relative positions of its various sub-models typically change. It's possible to determine, frame by frame, whether there is overlap between the shapes of sub-models corresponding to the same animation frame. Therefore, it's also necessary to determine the single-frame shape data for each animation frame from the single-frame shape data for the same animation action. After obtaining the single-frame shape data for a specific animation frame, the shape of each sub-model within that frame can be determined, and then it can be judged whether the display areas of the sub-models intersect. If they intersect, it indicates that model overlap has occurred between the sub-models.

[0038] Typically, Boolean operations can be performed on the display areas of each pair of sub-models to determine if their display areas intersect. In practical applications, some interweaving between sub-models is allowed, and when this interweaving occurs, it can be considered a normal phenomenon, rather than an unreasonable behavior of the target character model in response to the animation action. Besides the above-mentioned normal phenomena, if sub-models interweave within the display areas of an animation frame, that animation frame can be called an interleaved frame.

[0039] The number of interlaced frames corresponding to a specific animation action can be counted, and this can be used as the model interlacing status of the target character model during various animation actions. This model interlacing status can reflect the degree of adaptation between the animation action and the target character model. Since the number of animation frames corresponding to an animation action can be manually changed, the ratio of the number of interlaced frames to the total number of animation frames corresponding to the animation action can also be used as the model interlacing status of the target character model during various animation actions. Specific settings can be configured according to requirements and are not limited here.

[0040] The aforementioned method for processing model data involves acquiring data to be processed. This data includes model data of a target character model and motion data corresponding to at least one animation action. The target character model comprises multiple sub-models. Based on the model data and motion data, single-frame morphological data is determined. This single-frame morphological data indicates the morphology of each sub-model in each animation frame corresponding to each animation action. Based on the single-frame morphological data, the model interleaving situation of the target character model during each animation action is determined. This method improves the efficiency of interleaving detection during game actions by batch processing of model data and motion data to obtain the morphological data of the model in each animation frame of the animation action, thereby determining the model interleaving situation during the animation action. This reduces manual costs.

[0041] The following embodiments provide a specific method for determining single-frame morphological data based on model data and motion data.

[0042] Typically, during the animation of a target character model, at least one of the following—shape, position, or posture—of each sub-model will change. For each animation action, multiple first data sets can be determined based on the corresponding motion data and model data. Each first data set includes the motion data corresponding to the animation action and the model data of one of the multiple sub-models. For example, if the target character model includes a first sub-model, a second sub-model, and a third sub-model, the model data of the target character model needs to be split into the model data of the first sub-model, the model data of the second sub-model, and the model data of the third sub-model. Three first data sets are then established to store the model data of the first sub-model and the motion data corresponding to the animation action, the model data of the second sub-model and the motion data corresponding to the animation action, and the model data of the third sub-model and the motion data corresponding to the animation action, respectively. After determining multiple first data sets, single-frame shape data needs to be determined based on these sets.

[0043] In practical applications, the single-frame morphological data corresponding to a certain sub-model and a certain animation frame can be called sub-morphological data. A single-frame morphological data can then be considered as being composed of multiple sub-morphological data. Sub-morphological data indicates the shape of the sub-model corresponding to the sub-morphological data in the corresponding animation frame. The process of determining the single-frame morphological data is the process of determining each sub-morphological data.

[0044] In practical implementation, it is necessary to determine multiple animation frames corresponding to multiple first data sets of animation actions. When determining the animation frames corresponding to an animation action, it is necessary to consider the duration of the animation action and the frame rate of the animation playback. Generally speaking, the number of animation frames is equal to the product of the duration of the animation action and the frame rate of the animation playback.

[0045] After determining the multiple animation frames corresponding to the animation action, for each first data set, the following operations are performed sequentially according to the arrangement of the multiple animation frames: First, the data portion corresponding to the current animation frame in the action data of the first data set is obtained, as well as the model data in the first data set; the obtained model data is the model data of a sub-model; then, based on the obtained model data and data portion, the sub-shape data corresponding to the current animation frame and the obtained sub-model data is generated. For example, the first data set includes the model data of the first sub-model and the action data of the first animation action; the first animation action corresponds to 20 animation frames with intervals of 0.1, 0.2, ..., 2.0 seconds from the start of the animation. First, the data portion corresponding to the 0.1-second animation frame needs to be obtained to generate the sub-shape data corresponding to the first sub-model at the 0.1-second animation frame; then, the sub-shape data corresponding to the 0.2-second, 0.3-second, ..., 2.0-second animation frames are generated respectively. The process of generating sub-shape data of sub-models with and without preset skeletons has been described above and will not be repeated here.

[0046] Assume there are multiple sub-models, including a first sub-model and a second sub-model. There can be one or more first sub-models, and one or more second sub-models. The second sub-model is attached to the first sub-model through a preset attachment point. If the obtained model data is the model data of the second sub-model, the attachment parameters corresponding to the second sub-model are obtained. These attachment parameters indicate the attachment position of the second sub-model on the first sub-model. For example, if the second sub-model is a hat and the second sub-model is a human body model, a certain position of the hat model needs to be attached to a certain position of the human body model. Then, based on the obtained model data, attachment parameters, and the aforementioned data, the second sub-model data and the sub-shape data corresponding to the current animation frame are generated. The position and normal direction of the attachment point in the current animation frame can be determined based on the aforementioned data. Then, based on the relative positional relationship between the attachment point and the second sub-model, the sub-shape data of the second sub-model in the current animation frame is obtained.

[0047] The following embodiments provide a specific method for determining the model interleaving situation of a target character model during various animation actions based on single-frame morphological data.

[0048] As described above, the single-frame morphological data includes multiple sub-morphological data; each sub-morphological data has a corresponding sub-model and animation frame. In practical applications, for each animation action, it is necessary to divide the multiple sub-morphological data into multiple second data sets based on the animation frames corresponding to the multiple sub-morphological data of the animation action. That is, the sub-morphological data of multiple sub-models of the target character model corresponding to a certain animation frame are divided into a second data set.

[0049] For each second dataset, it is necessary to determine the model interleaving situation of multiple sub-models of the target character model in the animation frames corresponding to the second dataset. In practice, Boolean operations can be performed on the display forms of multiple sub-models in the animation frames corresponding to the second dataset to obtain the processing result. This result can include the intersection, union, etc., of the display forms between different sub-models. Then, based on the processing result, the model interleaving situation of multiple sub-models of the target character model in the animation frames corresponding to the second dataset is determined. When two sub-models have an intersection, and one sub-model does not completely include the other, model interleaving can be considered to have occurred between the two sub-models.

[0050] In practical applications, visibility can be set for one or more sub-models. This visibility indicates the degree to which each part of the sub-model is visible. For example, the visibility of the interior of a skirt model can be set to invisible, such as 0. Preset intersecting planes can also be set for one or more sub-models, where model overlap is normal.

[0051] After obtaining the processing results, the system determines the overlapping parts between multiple sub-models of the target character model. If the overlapping part passes through any preset overlapping plane of the multiple sub-models, or if the visibility of the overlapping part is less than a preset visibility threshold, it can be determined that the multiple sub-models of the target character model do not overlap in the animation frames corresponding to the second data set, i.e., this phenomenon is normal. If there are multiple overlapping parts, it can only be determined that the multiple sub-models of the target character model do not overlap in the animation frames corresponding to the second data set if each overlapping part passes through a preset overlapping plane or has a visibility less than a visibility threshold.

[0052] After determining the interleaving of multiple sub-models of the target character model across animation frames corresponding to multiple second data sets, it is necessary to further determine the model interleaving during the animation process of the target character model. First, the target number of animation frames generating model interleaving can be counted among the multiple animation frames corresponding to the animation actions across multiple second data sets; that is, how many animation frames generated model interleaving. Then, based on the target number and the total number of animation frames corresponding to the animation actions, the quality parameters of the target character model's animation process can be determined. For example, the ratio of the target number to the total number can be used as the quality parameter of the target character model's animation process.

[0053] Sub-models can also have preset visibility, which can reflect, to some extent, the degree of attention viewers pay to different parts of the sub-model. For example, the visibility of one part of the sub-model can be set to 1, and the visibility of another part can be set to 0.2, meaning the viewer's attention to the latter part is much less than their attention to the former. For each animation frame that produces model interleaving, the visibility of the interleaved part in the animation frame can be determined. Based on the visibility, the number of targets, and the total number of animation frames corresponding to the animation action, the quality parameters of the target character model's animation action are determined. For each animation frame that produces interleaving, the visibility of the interleaved part can be multiplied by 1 to obtain the interleaving parameter for that animation frame. Then, the sum of the interleaving parameters and the total number of wallpapers are used to determine the quality parameters of the target character model's animation action. Alternatively, the area of ​​the interleaved part can be obtained, and the product of the area and the visibility can be used as the interleaving parameter for that animation frame. Then, the sum of the interleaving parameters and the total number of wallpapers are used to determine the quality parameters of the target character model's animation action. Specific settings can be made according to requirements and are not limited here.

[0054] The following embodiments provide a detailed process for implementing the model data processing method. Figure 1 This method is implemented based on the method shown. The process relies on topnet in Houdni 18.5, enabling efficient handling of model interleaving issues.

[0055] The process is divided into two stages: the model data processing stage and the result preview stage.

[0056] In the model data processing stage, multiple sets of model data and motion data are typically used. Each set of model data usually represents a sub-model within the target character model. Each set of motion data typically corresponds to a single animation action. Each set of data is placed in a sub-process within a task, and after binding and conversion, static single-frame model vertices are generated (equivalent to the aforementioned "single-frame morphology data"). Then, single-frame models with the same animation trajectory are grouped into a set for Boolean computation. The computed data usually needs to be filtered, for example, for reasonable interlacing (usually the model's default interlacing surfaces) and low-visibility model regions. Low-visibility model regions are those that are not easily seen, such as the hem of a skirt or the back of a neck obscured by hair. These model regions have feature faces that are very close together and closed, making interlacing difficult to observe from the outside, and are therefore considered data that needs to be filtered.

[0057] The topnet includes a topnode topology. A small dot on a topnode represents a task. For example, if a node reads 60 animation tracks, it generates 60 tasks. Task allocation is typically done in a single thread, and starting a thread incurs some overhead.

[0058] The model data is in the common FBX format. It reads data from a specified folder via the Topnet network and divides the data into model data and motion data. Model data typically includes skinning data. Character models are usually decomposed, with the skinning data of each decomposed model treated as a single data set. A character model typically has a main torso for performing common actions, and also requires additional attachments such as hair, capes, weapons, etc. The main torso and attachments can be divided into different sub-models. The attachment's splicing points need to be recorded in the workflow beforehand. These splicing points serve as attachment parameters, indicating where the attachment is attached to the main torso.

[0059] After obtaining the animation and skinning, we arrive at the final stage of data assembly. We obtain the motion trajectory through one topnode, skin the character through another topnode, and then set another topnode as the merging node. This results in 60 x 3 = 180 tasks.

[0060] The trajectory frame count (equivalent to the animation frames mentioned above) is dynamically read. For example, if an animation action lasts for 1.5 seconds and has a frame rate of 30 frames per second, then the corresponding trajectory frame count is 45. For each trajectory frame, the task is further broken down. For example, 180 tasks can be broken down into 19074 tasks. Simultaneously, the role assembly within the node is configured.

[0061] The assembled data can theoretically be considered a single, flat task for TopNet, without any additional dependencies on upstream logic. Multithreading makes it easy to derive the values. With a 9-core CPU and no thread switching, 19074 divided by 9 equals 2000 tasks per thread. The actual number of tasks will vary significantly depending on the length of the operations. When not pursuing extreme computational performance, a larger value can be given, with each thread adding approximately 2 to 6 seconds to the computation time.

[0062] The node results of the skin cache are as follows Figure 2 As shown. In the animation process, the static model that stores the bone mapping weights is commonly known as skinning. Skinning cache refers to the cached static model after transforming the static model to the motion space position recorded on the bones. Figure 2 The core node is skincache, the skinning cache node. Upstream of this node (Partitionbynode) is a federated node that implements skinning and action input functionality, merging skins and actions into a single task. This merged task is combined within the cache node and cached to disk. Downstream nodes (Partitionbynode) then group the skinning cache by action number and distribute it to the interleaving test nodes.

[0063] After obtaining all the combined animation model slices (equivalent to the "single frame state data" mentioned above), they need to be grouped again for Boolean operations and health assessment. Figure 3 The image shows the recombination state of the skin cache slices. After the boolean node performs initial interleaving for each slice, it passes the information to the original model for annotation.

[0064] After processing a single trajectory set, the health of the interlacing is evaluated. Visibility-based determination of whether interlacing frames are used to calculate health is employed. Then, the number of interlacing frames within the trajectory set suitable for calculating the trajectory's quality is identified. Finally, the ratio of the determined number of interlacing frames to the trajectory frame length (equivalent to the "total number of animation frames" mentioned above) is calculated as the quality parameter for a single trajectory. The Ambient Occlusion map of the model can be used as a basic metric. The aim is to reduce the impact of low-visibility interlacing on the overall animation trajectory health.

[0065] In the process of calculating quality parameters, the area of ​​the interlaced portion in the interlaced frame can also be used for calculation. For example, the area of ​​the interlaced portion of each interlaced frame can be added together, and then the ratio of the sum to the length of the trajectory frame can be used as the quality parameter of a single trajectory.

[0066] After determining the quality parameters for each trajectory, the detection result text can be written for each trajectory individually. Simultaneously, the individual trajectory set is compressed and stored on disk. Once all action data is complete, the health set is read in and sorted to obtain the overall action data for that character.

[0067] Multi-threaded architecture is key to efficient processing. This workflow maximizes the use of the topnet structure for parallel processing of model animation splitting, calculation, splicing, and compression through reasonable process planning and allocation. Processing 70 animations and 100,000 model characters can typically be completed within 1 hour.

[0068] Once the previous set caching and health data sorting are complete, previewing and visualization can be enabled. Previewing is done directly in Houdini. By remapping the colors of the solved data, the model's interleaving can be observed intuitively. Generally, animation caches occupy a significant amount of disk space; therefore, switching between different motion trajectories is designed to be previewed after decompression to reduce disk usage. Real-time previewing primarily involves obtaining the target clicked on the interface, decompressing the corresponding result file, and loading it into Houdini for previewing.

[0069] For actions requiring repair, you can directly input the video and let the artist quickly locate the file and position. Alternatively, you can batch output all actions and let the artist make their own judgment. The video has two options: single action style and multi-selection collection style. Single and multi-selection mainly involve splicing two branches, and both have fixed styles. In the single selection style, the selected actions are rendered separately in 4 threads and then spliced ​​into a single video file. In the multi-selection style, each selected action is rendered once and then spliced ​​into a single video file.

[0070] To import the data to be processed, you can set specific locations in the `data` field of the preset interface for inputting skinning paths, animation paths, and bone paths. Clicking the `LoadData` control in the interface will load the corresponding FBX file into the `datalist`. You can also set options to configure whether to include certain elements in the test run. If the bone is entered correctly, you can select the skinning attachment points in the `skinmesh` field of the `datalist`. If there is no bone, you can manually enter it in the format `@name=xxxx`. After configuration, click the `cachemesh` control to start the test run.

[0071] After the model caching process is complete, a reslist.csv file and a compressed model cache package will be generated in the skinmesh / out directory. The first time, reslist.csv will be loaded automatically; subsequent times, simply drag and drop the csv file into the csvpath and click load.

[0072] For the above method embodiments, see Figure 4 The illustrated device is a model data processing apparatus, comprising:

[0073] The data acquisition module 402 is used to acquire data to be processed; the data to be processed includes model data of the target character model and motion data corresponding to at least one animation action; the target character model includes multiple sub-models;

[0074] The single-frame shape data determination module 404 is used to determine the single-frame shape data based on the model data and motion data; the single-frame shape data is used to indicate the shape of each sub-model in each animation frame corresponding to each animation action;

[0075] The model interleaving determination module 406 is used to determine the model interleaving of the target character model during each animation action based on single-frame morphological data.

[0076] The aforementioned model data processing device acquires data to be processed; the data to be processed includes model data of a target character model and motion data corresponding to at least one animation action; the target character model includes multiple sub-models; based on the model data and motion data, single-frame morphological data is determined; the single-frame morphological data is used to indicate the morphology of each sub-model in each animation frame corresponding to each animation action; based on the single-frame morphological data, the model interleaving situation of the target character model during each animation action is determined. This method, by batch combining and processing the model data and motion data, obtains the morphological data of the model in each animation frame of the animation action, and then determines the model interleaving situation during the animation action, improving the efficiency of interleaving detection during the model's game action and reducing labor costs.

[0077] The aforementioned single-frame morphology data determination module is also used to: for each animation action, determine multiple first data sets based on the action data and model data corresponding to the animation action; each first data set includes the action data corresponding to the animation action and the model data of one of the multiple sub-models; and determine single-frame morphology data based on the multiple first data sets.

[0078] The aforementioned single-frame morphology data includes multiple sub-morphology data; each sub-morphology data has a corresponding sub-model and animation frame; the sub-morphology data is used to indicate the form of the sub-model corresponding to the sub-morphology data in the corresponding animation frame; the aforementioned single-frame morphology data determination module is also used to: determine multiple animation frames corresponding to multiple first data sets of animation actions; for each first data set, perform the following operations sequentially according to the arrangement order of multiple animation frames: obtain the data portion of the action data in the first data set that corresponds to the current animation frame, and the model data in the first data set; based on the obtained model data and data portion, generate the sub-morphology data corresponding to the current animation frame and the obtained sub-model data.

[0079] The aforementioned multiple sub-models include a first sub-model and a second sub-model; the second sub-model is attached to the first sub-model through a preset attachment point; the aforementioned single-frame shape data determination module is also used to: if the obtained model data is the model data of the second sub-model, obtain the attachment parameters corresponding to the second sub-model; the attachment parameters are used to indicate: the attachment position of the second sub-model on the first sub-model; based on the obtained model data, attachment parameters, and data portion, generate the second sub-model data and the sub-shape data corresponding to the current animation frame.

[0080] The aforementioned single-frame morphological data includes multiple sub-morphological data; each sub-morphological data has a corresponding sub-model and animation frame; the sub-morphological data is used to indicate the morphology of the sub-model corresponding to the sub-morphological data in the corresponding animation frame; the model interleaving determination module is also used to: for each animation action, based on the animation frames corresponding to the multiple sub-morphological data corresponding to the animation action, divide the multiple sub-morphological data into multiple second data sets; for each second data set, determine the model interleaving situation of the multiple sub-models of the target character model in the animation frames corresponding to the second data set; based on the interleaving situation of the multiple sub-models of the target character model in the animation frames corresponding to the multiple second data sets, determine the model interleaving situation of the target character model during the animation action.

[0081] The aforementioned model interleaving determination module is also used to: perform Boolean operations on the display form of multiple sub-models in the animation frames corresponding to the second data set to obtain the processing result; and based on the processing result, determine the model interleaving situation of multiple sub-models of the target character model in the animation frames corresponding to the second data set.

[0082] The aforementioned model interleaving determination module is also used to: count the target number of animation frames that generate model interleaving among multiple animation frames corresponding to animation actions in multiple second data sets; and determine the quality parameters of the target character model's animation process based on the target number and the total number of animation frames corresponding to the animation actions.

[0083] The aforementioned sub-models have a preset visibility; visibility is used to indicate the visibility of each model part of the sub-model; the model interweaving determination module is also used to: determine the interweaving parts between multiple sub-models of the target character model based on the processing results; if the interweaving part passes through any preset interweaving plane of multiple sub-models, or if the visibility of the interweaving part is less than a preset visibility threshold, it is determined that the multiple sub-models of the target character model have not interweaved in the animation frame corresponding to the second data set.

[0084] The aforementioned sub-models have a preset visibility; visibility is used to indicate the visibility of each model part of the sub-model; the model interlacing determination module is also used to: for each animation frame that generates model interlacing, determine the visibility of the interlacing part in the animation frame that generates model interlacing; and determine the quality parameters of the target character model's animation process based on visibility, target quantity, and the total number of animation frames corresponding to the animation action.

[0085] This embodiment also provides an electronic device, including a processor and a memory. The memory stores machine-executable instructions that can be executed by the processor. The processor executes the machine-executable instructions to implement the above-described model data processing method, for example:

[0086] Acquire the data to be processed; the data to be processed includes the model data of the target character model and the motion data corresponding to at least one animation action; the target character model includes multiple sub-models; based on the model data and motion data, determine the single-frame morphology data; the single-frame morphology data is used to indicate: the morphology of each sub-model in each animation frame corresponding to each animation action; based on the single-frame morphology data, determine the model interleaving situation of the target character model during each animation action.

[0087] The above method obtains the morphological data of the model in each animation frame of the animation action by batch combining model data and motion data, thereby determining the model interleaving situation during the animation action, improving the efficiency of interleaving detection during the model's game action and reducing manual costs.

[0088] Optionally, the above steps for determining single-frame morphological data based on model data and motion data include: for each animation action, determining multiple first data sets based on the motion data and model data corresponding to the animation action; each first data set includes the motion data corresponding to the animation action and the model data of one of the multiple sub-models; and determining single-frame morphological data based on the multiple first data sets.

[0089] Optionally, the aforementioned single-frame morphology data includes multiple sub-morphology data; each sub-morphology data has a corresponding sub-model and animation frame; the sub-morphology data is used to indicate the form of the sub-model corresponding to the sub-morphology data in the corresponding animation frame; the step of determining single-frame morphology data based on multiple first data sets includes: determining multiple animation frames corresponding to the animation actions of the multiple first data sets; for each first data set, performing the following operations sequentially according to the arrangement order of the multiple animation frames: obtaining the data portion of the action data in the first data set corresponding to the current animation frame, and the model data in the first data set; based on the obtained model data and data portion, generating sub-morphology data corresponding to the current animation frame and the obtained sub-model data.

[0090] Optionally, the aforementioned multiple sub-models include a first sub-model and a second sub-model; the second sub-model is attached to the first sub-model through a preset attachment point; the step of generating the current animation frame and the sub-shape data corresponding to the acquired sub-model data based on the acquired model data and data portion includes: if the acquired model data is the model data of the second sub-model, obtaining the attachment parameters corresponding to the second sub-model; the attachment parameters are used to indicate: the attachment position of the second sub-model on the first sub-model; and generating the second sub-model data and the sub-shape data corresponding to the current animation frame based on the acquired model data, attachment parameters, and data portion.

[0091] Optionally, the aforementioned single-frame morphological data includes multiple sub-morphological data; each sub-morphological data has a corresponding sub-model and animation frame; the sub-morphological data is used to indicate the form of the sub-model corresponding to the sub-morphological data in the corresponding animation frame; the step of determining the model interleaving situation of the target character model during each animation action based on the single-frame morphological data includes: for each animation action, dividing the multiple sub-morphological data into multiple second data sets based on the animation frames corresponding to the multiple sub-morphological data of the animation action; for each second data set, determining the model interleaving situation of the multiple sub-models of the target character model in the animation frames corresponding to the second data set; and determining the model interleaving situation of the target character model during the animation action based on the interleaving situation of the multiple sub-models of the target character model in the animation frames corresponding to the multiple second data sets.

[0092] Optionally, the step of determining the model interleaving situation of multiple sub-models of the target character model in the animation frame corresponding to the second data set includes: performing Boolean operation processing on the display form of multiple sub-models in the animation frame corresponding to the second data set to obtain the processing result; and determining the model interleaving situation of multiple sub-models of the target character model in the animation frame corresponding to the second data set based on the processing result.

[0093] Optionally, the step of determining the model interleaving situation of the target character model during the animation process based on the interleaving situation of multiple sub-models of the target character model in the animation frames corresponding to multiple second data sets includes: counting the target number of animation frames that generate model interleaving situation in the multiple animation frames corresponding to the animation actions of the multiple second data sets; and determining the quality parameters of the target character model during the animation process based on the target number and the total number of animation frames corresponding to the animation actions.

[0094] Optionally, the aforementioned sub-models have a preset visibility; visibility is used to indicate: the visibility of each model part of the sub-model; the step of determining the model interleaving situation of multiple sub-models of the target character model in the animation frame corresponding to the second data set based on the processing result includes: determining the interleaving part between multiple sub-models of the target character model based on the processing result; if the interleaving part passes through any preset interleaving plane of the multiple sub-models, or if the visibility of the interleaving part is less than a preset visibility threshold, it is determined that the multiple sub-models of the target character model have not interleaved in the animation frame corresponding to the second data set.

[0095] Optionally, the aforementioned sub-model has a preset visibility; visibility is used to indicate: the visibility of each model part of the sub-model; the step of determining the quality parameters of the target character model performing animation actions based on the target quantity and the total number of animation frames corresponding to the animation actions includes: for each animation frame that produces model interlacing, determining the visibility of the interlacing part in the animation frame that produces model interlacing; and determining the quality parameters of the target character model performing animation actions based on the visibility, the target quantity, and the total number of animation frames corresponding to the animation actions.

[0096] See Figure 5 As shown, the electronic device includes a processor 100 and a memory 101. The memory 101 stores machine-executable instructions that can be executed by the processor 100. The processor 100 executes the machine-executable instructions to implement the above-described model data processing method.

[0097] Furthermore, Figure 5 The electronic device shown also includes a bus 102 and a communication interface 103, with the processor 100, the communication interface 103 and the memory 101 connected via the bus 102.

[0098] The memory 101 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 103 (which can be wired or wireless), such as the Internet, wide area network, local area network, or metropolitan area network. The bus 102 may be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0099] The processor 100 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of the processor 100 or by instructions in software form. The processor 100 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this disclosure. The general-purpose processor may be a microprocessor or any conventional processor. The methods disclosed in the embodiments of this disclosure can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 101, and the processor 100 reads the information in memory 101 and, in conjunction with its hardware, completes the method of the aforementioned embodiments.

[0100] This embodiment also provides a machine-readable storage medium storing machine-executable instructions. When the machine-executable instructions are called and executed by a processor, the machine-executable instructions cause the processor to implement the above-described method for processing model data.

[0101] The present disclosure provides a method, apparatus, and electronic device for processing model data, including a computer-readable storage medium storing program code. The program code includes instructions that can be used to execute the methods described in the preceding method embodiments, for example:

[0102] Acquire the data to be processed; the data to be processed includes the model data of the target character model and the motion data corresponding to at least one animation action; the target character model includes multiple sub-models; based on the model data and motion data, determine the single-frame morphology data; the single-frame morphology data is used to indicate: the morphology of each sub-model in each animation frame corresponding to each animation action; based on the single-frame morphology data, determine the model interleaving situation of the target character model during each animation action.

[0103] The above method obtains the morphological data of the model in each animation frame of the animation action by batch combining model data and motion data, thereby determining the model interleaving situation during the animation action, improving the efficiency of interleaving detection during the model's game action and reducing manual costs.

[0104] Optionally, the above steps for determining single-frame morphological data based on model data and motion data include: for each animation action, determining multiple first data sets based on the motion data and model data corresponding to the animation action; each first data set includes the motion data corresponding to the animation action and the model data of one of the multiple sub-models; and determining single-frame morphological data based on the multiple first data sets.

[0105] Optionally, the aforementioned single-frame morphology data includes multiple sub-morphology data; each sub-morphology data has a corresponding sub-model and animation frame; the sub-morphology data is used to indicate the form of the sub-model corresponding to the sub-morphology data in the corresponding animation frame; the step of determining single-frame morphology data based on multiple first data sets includes: determining multiple animation frames corresponding to the animation actions of the multiple first data sets; for each first data set, performing the following operations sequentially according to the arrangement order of the multiple animation frames: obtaining the data portion of the action data in the first data set corresponding to the current animation frame, and the model data in the first data set; based on the obtained model data and data portion, generating sub-morphology data corresponding to the current animation frame and the obtained sub-model data.

[0106] Optionally, the aforementioned multiple sub-models include a first sub-model and a second sub-model; the second sub-model is attached to the first sub-model through a preset attachment point; the step of generating the current animation frame and the sub-shape data corresponding to the acquired sub-model data based on the acquired model data and data portion includes: if the acquired model data is the model data of the second sub-model, obtaining the attachment parameters corresponding to the second sub-model; the attachment parameters are used to indicate: the attachment position of the second sub-model on the first sub-model; and generating the second sub-model data and the sub-shape data corresponding to the current animation frame based on the acquired model data, attachment parameters, and data portion.

[0107] Optionally, the aforementioned single-frame morphological data includes multiple sub-morphological data; each sub-morphological data has a corresponding sub-model and animation frame; the sub-morphological data is used to indicate the form of the sub-model corresponding to the sub-morphological data in the corresponding animation frame; the step of determining the model interleaving situation of the target character model during each animation action based on the single-frame morphological data includes: for each animation action, dividing the multiple sub-morphological data into multiple second data sets based on the animation frames corresponding to the multiple sub-morphological data of the animation action; for each second data set, determining the model interleaving situation of the multiple sub-models of the target character model in the animation frames corresponding to the second data set; and determining the model interleaving situation of the target character model during the animation action based on the interleaving situation of the multiple sub-models of the target character model in the animation frames corresponding to the multiple second data sets.

[0108] Optionally, the step of determining the model interleaving situation of multiple sub-models of the target character model in the animation frame corresponding to the second data set includes: performing Boolean operation processing on the display form of multiple sub-models in the animation frame corresponding to the second data set to obtain the processing result; and determining the model interleaving situation of multiple sub-models of the target character model in the animation frame corresponding to the second data set based on the processing result.

[0109] Optionally, the step of determining the model interleaving situation of the target character model during the animation process based on the interleaving situation of multiple sub-models of the target character model in the animation frames corresponding to multiple second data sets includes: counting the target number of animation frames that generate model interleaving situation in the multiple animation frames corresponding to the animation actions of the multiple second data sets; and determining the quality parameters of the target character model during the animation process based on the target number and the total number of animation frames corresponding to the animation actions.

[0110] Optionally, the aforementioned sub-models have a preset visibility; visibility is used to indicate: the visibility of each model part of the sub-model; the step of determining the model interleaving situation of multiple sub-models of the target character model in the animation frame corresponding to the second data set based on the processing result includes: determining the interleaving part between multiple sub-models of the target character model based on the processing result; if the interleaving part passes through any preset interleaving plane of the multiple sub-models, or if the visibility of the interleaving part is less than a preset visibility threshold, it is determined that the multiple sub-models of the target character model have not interleaved in the animation frame corresponding to the second data set.

[0111] Optionally, the aforementioned sub-model has a preset visibility; visibility is used to indicate: the visibility of each model part of the sub-model; the step of determining the quality parameters of the target character model performing animation actions based on the target quantity and the total number of animation frames corresponding to the animation actions includes: for each animation frame that produces model interlacing, determining the visibility of the interlacing part in the animation frame that produces model interlacing; and determining the quality parameters of the target character model performing animation actions based on the visibility, the target quantity, and the total number of animation frames corresponding to the animation actions.

[0112] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and apparatus described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0113] Furthermore, in the description of the embodiments of this disclosure, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this disclosure based on the specific circumstances.

[0114] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of this disclosure, in essence, or the parts that contribute to the prior art, or parts of the technical solutions, can be embodied in the form of software products. These computer software products are stored in a storage medium and include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0115] In the description of this disclosure, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this disclosure and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this disclosure. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0116] Finally, it should be noted that the above embodiments are merely specific implementations of this disclosure, used to illustrate the technical solutions of this disclosure, and not to limit it. The protection scope of this disclosure is not limited thereto. Although this disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this disclosure. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure, and should all be covered within the protection scope of this disclosure. Therefore, the protection scope of this disclosure should be determined by the protection scope of the claims.

Claims

1. A method for processing model data, characterized in that, The method includes: Acquire the data to be processed; the data to be processed includes model data of the target character model and motion data corresponding to at least one animation action; the target character model includes multiple sub-models; Based on the model data and the motion data, single-frame shape data is determined; the single-frame shape data is used to indicate the shape of each sub-model in each animation frame corresponding to each animation action; Based on the single-frame morphological data, the model interleaving situation of the target character model during each of the animation actions is determined.

2. The method according to claim 1, characterized in that, The steps for determining single-frame morphological data based on the model data and the motion data include: For each animation action, multiple first data sets are determined based on the action data corresponding to the animation action and the model data; each first data set includes the action data corresponding to the animation action and the model data of one of the multiple sub-models; Based on the multiple first data sets, the single-frame morphological data is determined.

3. The method according to claim 2, characterized in that, The single-frame morphology data includes multiple sub-morphology data; each sub-morphology data has a corresponding sub-model and animation frame; the sub-morphology data is used to indicate the morphology of the sub-model corresponding to the sub-morphology data in the corresponding animation frame; The step of determining single-frame morphological data based on the multiple first data sets includes: Determine multiple animation frames corresponding to the animation actions corresponding to the multiple first data sets; For each of the first data sets, the following operations are performed sequentially according to the arrangement order of the plurality of animation frames: Obtain the data portion corresponding to the current animation frame from the motion data in the first data set, and the model data from the first data set; Based on the acquired model data and the data portion, sub-morphological data corresponding to the current animation frame and the acquired sub-model data are generated.

4. The method according to claim 3, characterized in that, The plurality of sub-models includes a first sub-model and a second sub-model; the second sub-model is attached to the first sub-model through a preset attachment point; The step of generating sub-morphological data corresponding to the current animation frame and the acquired sub-model data based on the acquired model data and the data portion includes: If the obtained model data is the model data of the second sub-model, obtain the attachment parameters corresponding to the second sub-model; The attachment parameters are used to indicate the attachment position of the second sub-model on the first sub-model; Based on the acquired model data, the attachment parameters, and the data portion, the second sub-model data and the sub-morphology data corresponding to the current animation frame are generated.

5. The method according to claim 1, characterized in that, The single-frame morphology data includes multiple sub-morphology data; each sub-morphology data has a corresponding sub-model and animation frame; the sub-morphology data is used to indicate the morphology of the sub-model corresponding to the sub-morphology data in the corresponding animation frame; Based on the single-frame morphological data, the step of determining the model interleaving situation of the target character model during each of the animation actions includes: For each animation action, based on the animation frames corresponding to the multiple sub-shape data corresponding to the animation action, the multiple sub-shape data are divided into multiple second data sets; For each of the second data sets, determine the model interleaving situation of multiple sub-models of the target character model in the animation frames corresponding to the second data set; Based on the interleaving of multiple sub-models of the target character model in the animation frames corresponding to the multiple second data sets, the model interleaving situation of the target character model during the animation action is determined.

6. The method according to claim 5, characterized in that, The step of determining the model interleaving situation of multiple sub-models of the target character model in the animation frames corresponding to the second data set includes: Boolean operations are performed on the display form of the multiple sub-models in the animation frames corresponding to the second data set to obtain the processing result; Based on the processing results, the model interleaving situation of multiple sub-models of the target character model in the animation frames corresponding to the second data set is determined.

7. The method according to claim 5, characterized in that, The step of determining the model interleaving situation of the target character model during the animation process based on the interleaving situation of multiple sub-models of the target character model in the animation frames corresponding to the multiple second data sets includes: Based on the interleaving of multiple sub-models of the target character model in the animation frames corresponding to the multiple second data sets, the target number of animation frames that generate model interleaving in the multiple animation frames corresponding to the animation actions of the multiple second data sets is counted. Based on the target quantity and the total number of animation frames corresponding to the animation action, the quality parameters of the target character model performing the animation action are determined.

8. The method according to claim 6, characterized in that, The sub-model has a preset visibility; the visibility is used to indicate the degree of visibility of each model part of the sub-model. Based on the processing results, the step of determining the model interleaving situation of multiple sub-models of the target character model in the animation frames corresponding to the second data set includes: Based on the processing results, the overlapping parts between multiple sub-models of the target character model are determined; If the interlacing portion passes through any preset interlacing plane of the plurality of sub-models, or if the visibility of the interlacing portion is less than a preset visibility threshold, it is determined that the plurality of sub-models of the target character model do not interlac in the animation frame corresponding to the second data set.

9. The method according to claim 7, characterized in that, The sub-model has a preset visibility; the visibility is used to indicate the degree of visibility of each model part of the sub-model. The step of determining the quality parameters of the target character model performing the animation action based on the target quantity and the total number of animation frames corresponding to the animation action includes: For each animation frame that generates model interleaving, determine the visibility of the interleaved portion in the animation frame that generates model interleaving; Based on the visibility, the number of targets, and the total number of animation frames corresponding to the animation action, the quality parameters of the target character model performing the animation action are determined.

10. A device for processing model data, characterized in that, The device includes: The data acquisition module is used to acquire data to be processed; the data to be processed includes model data of the target character model and motion data corresponding to at least one animation action; the target character model includes multiple sub-models; A single-frame shape data determination module is used to determine single-frame shape data based on the model data and the action data; the single-frame shape data is used to indicate the shape of each sub-model in each animation frame corresponding to each animation action; The model interleaving determination module is used to determine the model interleaving situation of the target character model during each of the animation actions based on the single-frame morphology data.

11. An electronic device, characterized in that, It includes a processor and a memory, the memory storing machine-executable instructions that can be executed by the processor, the processor executing the machine-executable instructions to implement the model data processing method according to any one of claims 1-9.

12. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores machine-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the model data processing method according to any one of claims 1-9.

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