CN115359211A - Model loading method and device, storage medium and electronic equipment - Google Patents
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Abstract
The model loading method comprises the steps that a loading instruction for a target webpage is received, if the target webpage comprises a specified three-dimensional grid model to be loaded, the contraction cost value of each edge in the specified three-dimensional grid model is obtained, and an initial cost value set is obtained; the current three-dimensional grid model is subjected to iterative optimization according to the initial cost value set and at least one newly added cost value set, so that the model simplification efficiency can be effectively improved, the loading of the specified three-dimensional grid model data in the target webpage is realized by loading the optimized target three-dimensional grid model, the loading time of the target webpage can be effectively shortened, and the user experience can be effectively improved.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a model loading method and apparatus, a storage medium, and an electronic device.
Background
With the continuous development of computer software and hardware technologies, the continuous popularization of augmented reality, virtual reality and mixed reality, the demand of three-dimensional modeling is increasing exponentially, the structure of a three-dimensional grid model is also becoming more complex, which leads to a large data volume of a three-dimensional grid model file, and when data loading is performed on a webpage containing the three-dimensional grid model, the data loading of the webpage can be completed only by long waiting time due to the fact that the loading of the three-dimensional grid model file consumes more time, which is not favorable for improving user experience.
Disclosure of Invention
The purpose of the disclosure is to provide a model loading method and device, a storage medium and an electronic device.
In order to achieve the above object, a first aspect of the present disclosure provides a model loading method, including:
in response to receiving a loading instruction for a target webpage, if the target webpage is determined to include a specified three-dimensional grid model to be loaded, acquiring a contraction cost value of each edge in the specified three-dimensional grid model to obtain an initial cost value set, wherein the contraction cost value is used for representing a geometric error generated by contraction;
determining an edge to be optimized in the appointed three-dimensional grid model according to the initial cost value set;
collapsing the to-be-optimized edge to obtain an updated current three-dimensional grid model;
determining the contraction cost value of the newly added edges in the current three-dimensional grid model to obtain at least one newly added cost value set;
and performing iterative optimization on the current three-dimensional grid model according to the initial cost value set and the at least one newly added cost value set to obtain an optimized target three-dimensional grid model, and loading the target three-dimensional grid model as loading data of the target webpage.
Optionally, the determining a contraction cost value of a newly added edge in the current three-dimensional mesh model to obtain at least one newly added cost value set includes:
acquiring the target number of the newly added edges;
under the condition that the target number is larger than a preset number threshold, dividing contraction cost values corresponding to the newly added edges of the target number into a plurality of groups, wherein each group corresponds to one newly added cost value set so as to obtain a plurality of newly added cost value sets; or,
and generating the newly added cost value set under the condition that the target number is less than or equal to the preset number threshold, wherein the contraction cost values corresponding to the newly added edges of the target number are all elements in the newly added cost value set.
Optionally, the performing iterative optimization on the current three-dimensional mesh model according to the initial cost value set and the at least one newly added cost value set to obtain an optimized target three-dimensional mesh model includes:
determining a designated edge adjacent to the edge to be optimized in the designated three-dimensional grid model;
deleting the contraction cost value of the appointed edge from the initial cost value set to obtain an updated initial cost value set;
and performing iterative optimization on the current three-dimensional grid model according to the at least one newly added cost value set and the updated initial cost value set to obtain the target three-dimensional grid model.
Optionally, the performing iterative optimization on the current three-dimensional mesh model according to the at least one newly added cost value set and the updated initial cost value set to obtain the target three-dimensional mesh model includes:
determining the minimum contraction cost value in each newly added cost value set to obtain at least one first contraction cost value, and determining the minimum contraction cost value in the updated initial cost value set to obtain a second contraction cost value;
determining a target systolic edge based on the at least one first systolic cost value and the second systolic cost value;
collapse processing is carried out on the current three-dimensional grid model according to the target contraction edge so as to obtain an updated current three-dimensional grid model;
determining the ratio of the number of planes contained in the updated current three-dimensional grid model to the number of planes contained in the specified three-dimensional grid model;
determining whether the ratio is greater than a preset ratio threshold;
under the condition that the ratio is determined to be larger than the preset ratio threshold, updating the current initial cost value set according to the target contraction edge, determining the contraction cost value of a newly increased edge in the updated current three-dimensional grid model to update the current at least one newly increased cost value set, and executing the step of determining the minimum contraction cost value in each newly increased cost value set again to obtain at least one first contraction cost value until the step of determining whether the ratio is larger than the preset ratio threshold or not;
and taking the current three-dimensional grid model as the target three-dimensional grid model under the condition that the ratio is determined to be less than or equal to the preset ratio threshold.
Optionally, said determining a target systolic edge from said at least one first systolic cost value and said second systolic cost value comprises:
determining a target systolic cost value that is the smallest of the at least one first systolic cost value and the second systolic cost value;
determining a first target distance between the midpoint position of each edge corresponding to the first contraction cost value and the midpoint position of the edge corresponding to the target contraction cost value, and a second target distance between the midpoint position of the edge corresponding to the second contraction cost value and the midpoint position of the edge corresponding to the target contraction cost value;
and taking the side of which the first target distance is greater than or equal to a preset side length threshold as the target contraction side, and taking the corresponding side of the second contraction cost value as the target contraction side under the condition that the second target distance is greater than or equal to the preset side length threshold, so as to obtain one or more target contraction sides.
Optionally, said determining a target systolic edge from said at least one first systolic cost value and said second systolic cost value comprises:
and taking the edge corresponding to the minimum specified number of the first contraction cost values and the second contraction cost values as the target contraction edge.
Optionally, the determining a contraction cost value of the newly added edge in the updated current three-dimensional mesh model to update the current at least one newly added cost value set includes:
executing the following updating strategy aiming at the contraction cost value of each newly added edge in the updated current three-dimensional grid model so as to update the current at least one newly added cost value set;
the update policy includes:
acquiring the number of elements in each newly added cost value set;
under the condition that the appointed newly added cost value set with the element quantity smaller than or equal to the preset quantity threshold value exists, adding the contraction cost value of the current newly added edge to the appointed newly added cost value set;
and under the condition that the appointed newly added cost value set does not exist, generating a target newly added cost value set, and adding the contraction cost value of the current newly added edge to the target newly added cost value set.
Optionally, collapsing the to-be-optimized edge to obtain an updated current three-dimensional mesh model, including:
determining a target point corresponding to the edge to be optimized, wherein the target point is a point with the minimum sum of squares of distances between the edge to be optimized and an adjacent surface of the edge to be optimized;
deleting the edge to be optimized and the edge connected with the edge to be optimized;
and connecting the target point with the adjacent point of the end point of the edge to be optimized to obtain the current three-dimensional grid model.
A second aspect of the present disclosure provides a model loading apparatus, the apparatus comprising:
the first determining module is configured to respond to a received loading instruction of a target webpage, and if the target webpage is determined to include a specified three-dimensional grid model to be loaded, obtain a contraction cost value of each edge in the specified three-dimensional grid model to obtain an initial cost value set, wherein the contraction cost value is used for representing a geometric error generated by contraction;
a second determining module configured to determine an edge to be optimized in the specified three-dimensional mesh model according to the initial cost value set;
a third determining module configured to perform collapse processing on the edge to be optimized to obtain an updated current three-dimensional grid model;
a fourth determining module, configured to determine a shrinkage cost value of a newly added edge in the current three-dimensional mesh model to obtain at least one newly added cost value set;
and the fifth determining module is configured to perform iterative optimization on the current three-dimensional grid model according to the initial cost value set and the at least one newly added cost value set to obtain an optimized target three-dimensional grid model, and load the target three-dimensional grid model as loading data of the target webpage.
Optionally, the fourth determining module is configured to:
acquiring the target number of the newly added edges;
under the condition that the target number is larger than a preset number threshold, dividing contraction cost values corresponding to the newly added edges of the target number into a plurality of groups, wherein each group corresponds to one newly added cost value set so as to obtain a plurality of newly added cost value sets; or,
and generating the newly added cost value set under the condition that the target number is less than or equal to the preset number threshold, wherein the contraction cost values corresponding to the newly added edges of the target number are all elements in the newly added cost value set.
Optionally, the fifth determining module is configured to:
determining a designated edge adjacent to the edge to be optimized in the designated three-dimensional grid model;
deleting the contraction cost value of the appointed edge from the initial cost value set to obtain an updated initial cost value set;
and performing iterative optimization on the current three-dimensional grid model according to the at least one newly added cost value set and the updated initial cost value set to obtain the target three-dimensional grid model.
Optionally, the fifth determining module is configured to:
determining the minimum contraction cost value in each newly added cost value set to obtain at least one first contraction cost value, and determining the minimum contraction cost value in the updated initial cost value set to obtain a second contraction cost value;
determining a target systolic edge based on the at least one first systolic cost value and the second systolic cost value;
performing collapse processing on the current three-dimensional grid model according to the target contraction edge to obtain an updated current three-dimensional grid model;
determining the ratio of the number of planes contained in the updated current three-dimensional grid model to the number of planes contained in the specified three-dimensional grid model;
determining whether the ratio is greater than a preset ratio threshold;
under the condition that the ratio is determined to be larger than the preset ratio threshold, updating the current initial cost value set according to the target contraction edge, determining the contraction cost value of a newly increased edge in the updated current three-dimensional grid model so as to update the current at least one newly increased cost value set, and executing the step of determining the minimum contraction cost value in each newly increased cost value set again so as to obtain at least one first contraction cost value until the step of determining whether the ratio is larger than the preset ratio threshold or not;
and taking the current three-dimensional grid model as the target three-dimensional grid model under the condition that the ratio is determined to be less than or equal to the preset ratio threshold.
Optionally, the fifth determining module is configured to:
determining a target systolic cost value that is the smallest of the at least one first systolic cost value and the second systolic cost value;
determining a first target distance between the midpoint position of each edge corresponding to the first contraction cost value and the midpoint position of the edge corresponding to the target contraction cost value, and a second target distance between the midpoint position of the edge corresponding to the second contraction cost value and the midpoint position of the edge corresponding to the target contraction cost value;
and taking the side of which the first target distance is greater than or equal to a preset side length threshold as the target contraction side, and taking the corresponding side of the second contraction cost value as the target contraction side under the condition that the second target distance is greater than or equal to the preset side length threshold, so as to obtain one or more target contraction sides.
Optionally, the fifth determining module is configured to:
and taking the edge corresponding to the minimum specified number of the first contraction cost values and the second contraction cost values as the target contraction edge.
Optionally, the fifth determining module is configured to:
aiming at the contraction cost value of each newly added edge in the updated current three-dimensional grid model, executing the following updating strategy to update the current at least one newly added cost value set;
the update policy includes:
acquiring the number of elements in each newly added cost value set;
adding the contraction cost value of the current newly added edge to the specified newly added cost value set under the condition that the specified newly added cost value set with the element number smaller than or equal to the preset number threshold value exists;
and under the condition that the appointed newly added cost value set does not exist, generating a target newly added cost value set, and adding the contraction cost value of the current newly added edge to the target newly added cost value set.
Optionally, the third determining module is configured to:
determining a target point corresponding to the edge to be optimized, wherein the target point is a point with the minimum sum of squares of distances between the edge to be optimized and an adjacent surface of the edge to be optimized;
deleting the edge to be optimized and the edge connected with the edge to be optimized;
and connecting the target point with the adjacent point of the end point of the edge to be optimized to obtain the current three-dimensional grid model.
A third aspect of the disclosure provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of the first aspect described above.
A fourth aspect of the present disclosure provides an electronic device, comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to carry out the steps of the method of the first aspect above.
According to the technical scheme, by responding to a received loading instruction of a target webpage, if the target webpage is determined to comprise a specified three-dimensional grid model to be loaded, the contraction cost value of each edge in the specified three-dimensional grid model is obtained to obtain an initial cost value set; determining an edge to be optimized in the appointed three-dimensional grid model according to the initial cost value set; collapsing the edges to be optimized to obtain an updated current three-dimensional grid model; determining the contraction cost value of the newly added edges in the current three-dimensional grid model to obtain at least one newly added cost value set; and performing iterative optimization on the current three-dimensional grid model according to the initial cost value set and the at least one newly added cost value set to obtain an optimized target three-dimensional grid model, and loading the target three-dimensional grid model as loading data of the target webpage. Therefore, iterative optimization is carried out on the current three-dimensional grid model according to the initial cost value set and the at least one newly added cost value set, model simplification efficiency can be effectively improved, loading of the specified three-dimensional grid model data in the target webpage is achieved through loading the optimized target three-dimensional grid model, loading duration of the target webpage can be effectively shortened, and therefore user experience can be effectively improved.
Additional features and advantages of the present disclosure will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure, but do not constitute a limitation of the disclosure. In the drawings:
FIG. 1 is a flow chart diagram illustrating a method of model loading in accordance with an exemplary embodiment of the present disclosure;
FIG. 2 is a flow chart diagram illustrating a method of model loading according to the embodiment shown in FIG. 1 of the present disclosure;
FIG. 3 is a flow diagram of another method of loading a model according to the embodiment of the present disclosure shown in FIG. 1;
FIG. 4 is a flow chart illustrating yet another method of model loading according to the embodiment shown in FIG. 1 of the present disclosure;
FIG. 5 is a block diagram of a model loading apparatus shown in an exemplary embodiment of the present disclosure;
FIG. 6 is a block diagram of an electronic device shown in accordance with an exemplary embodiment;
FIG. 7 is a block diagram illustrating another electronic device in accordance with an example embodiment.
Detailed Description
The following detailed description of specific embodiments of the present disclosure is provided in connection with the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
Before the detailed description of the specific embodiments of the present disclosure, the following description is first made on an application scenario of the present disclosure, and the present disclosure may be applied to a scenario in which a three-dimensional mesh model in a webpage is simplified to reduce the data amount of the three-dimensional mesh model to be loaded and increase the model loading speed. The simplification of the three-dimensional mesh model in the related art generally includes: the model subtracts face, exhibition UV, cures etc. and the inventor finds the model optimization method in the correlation technique, and after the model face number reached a certain magnitude, optimization efficiency can't satisfy the actual work needs, and the optimization process still need spend longer time, is unfavorable for shortening the model loading time to be unfavorable for promoting user experience.
In order to solve the above technical problems, the present disclosure provides a model loading method, apparatus, storage medium, and electronic device, where the model loading method obtains a contraction cost value of each edge in a specified three-dimensional mesh model to obtain an initial cost value set by responding to a received loading instruction for a target web page and if it is determined that the target web page includes the specified three-dimensional mesh model to be loaded; the current three-dimensional grid model is subjected to iterative optimization according to the initial cost value set and at least one newly added cost value set, so that the model simplification efficiency can be effectively improved, the loading of the specified three-dimensional grid model data in the target webpage is realized by loading the optimized target three-dimensional grid model, the loading time of the target webpage can be effectively shortened, and the user experience can be effectively improved.
FIG. 1 is a flow chart diagram illustrating a method of model loading in accordance with an exemplary embodiment of the present disclosure; as shown in fig. 1, the method may include:
Wherein the shrinkage cost value is used to characterize geometric errors that would result from shrinkage. In this step, each element (i.e., the contraction cost value of each edge) in the initial cost value set may be stored in the storage space corresponding to the variable C.
It should be noted that the computation process of the contraction cost value of the edge is as follows: if two end points of one edge are V1 and V2, the secondary measurement error value generated by contracting the V1 is QEM (V1), and the secondary measurement error value generated by contracting the V2 is QEM (V2), the contraction cost value of the edge is QEM (V1) + QEM (V2), and the QEM (V1) can be obtained by calculating the sum of squares of distances from the end point V1 to all triangular surfaces (also called associated planes, and planes containing the end points) in the neighborhood of the end point; the QEM (V2) may be obtained by calculating the sum of the squares of the distances from the endpoint V2 to all the triangular faces in its neighborhood.
And 102, determining an edge to be optimized in the specified three-dimensional grid model according to the initial cost value set.
In this step, the elements (data in the variable C) in the initial cost value set may be arranged in a sequence from large to small (or from small to large) to obtain an ordered variable C0, and an edge corresponding to a minimum preset number of cost shrinkage values in the ordered variable C0 is used as the edge to be optimized.
For example, if the preset number is 1, the edge corresponding to the minimum shrinkage cost value in the initial cost value set is used as the edge to be optimized in the specified three-dimensional grid model, and if the preset number is 2, the edge corresponding to the minimum shrinkage cost value and the edge corresponding to the next minimum shrinkage value in the initial cost value set are used as the edge to be optimized in the specified three-dimensional grid model.
And 103, collapsing the edge to be optimized to obtain an updated current three-dimensional grid model.
In this step, a target point corresponding to the edge to be optimized may be determined, where the target point is a point on the edge to be optimized, and a sum of squares of distances between the target point and an adjacent surface of the edge to be optimized is minimum; deleting the edge to be optimized and the edge connected with the edge to be optimized; and connecting the target point with the adjacent point of the end point of the edge to be optimized to obtain the current three-dimensional grid model. The adjacent surface is an associated plane of an endpoint of the edge to be optimized, and the associated plane is a plane containing the endpoint. The adjacent point is a vertex having a common edge or edge with the original vertex (i.e., the end point of the edge to be optimized), for example, a square, whose vertex is ABCD in turn, and AB and AD are adjacent vertices.
And 104, determining the contraction cost value of the newly added edge in the current three-dimensional grid model to obtain at least one newly added cost value set.
And the newly added edge is an edge added by the current three-dimensional grid model compared with the three-dimensional grid model before the collapse treatment is carried out on the edge to be optimized, and is a connecting line between the target point and the adjacent point.
In this step, the target number of the newly added edges can be obtained; under the condition that the number of the targets is larger than a preset number threshold, dividing contraction cost values corresponding to the newly added edges of the number of the targets into a plurality of groups, wherein each group corresponds to one newly added cost value set so as to obtain a plurality of newly added cost value sets; or, generating the newly added cost value set when the target number is less than or equal to the preset number threshold, wherein the contraction cost values corresponding to the newly added edges of the target number are all elements in the newly added cost value set.
For example, if the number of newly added edges in the current three-dimensional mesh model is N, when the shrinkage cost values of the newly added edges in the current three-dimensional mesh model are stored into a plurality of newly added cost value sets, the shrinkage cost values corresponding to the 1 st to nth edges may be sequentially stored into the variable C1 as a newly added cost value set, the shrinkage cost values corresponding to the N +1 st to 2 nth edges may be stored into the variable C2 as a newly added cost value set, and the process is repeated until the shrinkage cost value corresponding to the N th newly added edge is stored into the corresponding newly added cost value set. When N is less than or equal to N, a plurality of newly added cost value sets are generated, and when N is greater than N, a newly added cost value set is generated.
It should be noted that the preset number threshold may be b s The product is
Wherein t is e The number of sets of the at least one new added cost value set is less than or equal to b for specifying the total number of edges of the three-dimensional mesh model n ，
And 105, performing iterative optimization on the current three-dimensional grid model according to the initial cost value set and the at least one newly added cost value set to obtain an optimized target three-dimensional grid model, and loading the target three-dimensional grid model as loading data of the target webpage.
According to the technical scheme, iterative optimization is carried out on the current three-dimensional grid model according to the initial cost value set and the at least one newly added cost value set, model simplification efficiency can be effectively improved, loading of the specified three-dimensional grid model data in the target webpage is achieved through loading the optimized target three-dimensional grid model, loading duration of the target webpage can be effectively shortened, and therefore user experience can be effectively improved.
FIG. 2 is a flow chart diagram of a method of model loading according to the embodiment of the present disclosure shown in FIG. 1; as shown in fig. 2, the iteratively optimizing the current three-dimensional mesh model according to the initial cost value set and the at least one newly added cost value set in step 105 in fig. 1 to obtain an optimized target three-dimensional mesh model may include:
It should be noted that, in the specified three-dimensional mesh model, the specified edge adjacent to the edge to be optimized is an edge whose end point is an a point or a B point, when two end points of the edge to be optimized are an a point and a B point, respectively.
The specified edge is deleted during the collapse process, that is, the specified edge is not included in the current three-dimensional mesh model, so that the contraction cost value of the specified edge needs to be deleted to obtain the initial cost value set corresponding to the current three-dimensional mesh model (that is, the updated initial cost value set is obtained).
And 1053, performing iterative optimization on the current three-dimensional grid model according to the at least one newly added cost value set and the updated initial cost value set to obtain the target three-dimensional grid model.
This step may be implemented by the steps shown in S1 to S7 in fig. 3, and fig. 3 is a flowchart of another model loading method shown in the embodiment shown in fig. 1 according to the present disclosure; as shown in fig. 3, the above step 1053 may include:
s1, determining the minimum shrinkage cost value in each newly added cost value set to obtain at least one first shrinkage cost value, and determining the minimum shrinkage cost value in the updated initial cost value set to obtain a second shrinkage cost value.
Illustratively, each newly added cost value set is stored in a storage space corresponding to one variable, for example, the first newly added cost value set is stored in the variable C1, the second newly added cost value set is stored in the variable C2, and the mth newly added cost value set is stored in the variable Cm, so that the minimum contraction cost values in the variables C1 to Cm are respectively obtained to obtain m first contraction cost values. And determining the minimum shrinkage cost value from the updated initial cost value set (i.e. the set of shrinkage cost values corresponding to each edge in the current three-dimensional mesh model) to obtain the second shrinkage cost value.
And S2, determining a target contraction edge according to the at least one first contraction cost value and the second contraction cost value.
In this step, one possible implementation manner is: and taking the edge corresponding to the minimum specified number of the first contraction cost values and the second contraction cost values as the target contraction edge.
Illustratively, the m first contraction cost values and the second contraction cost values are sorted in order from small to large (or from large to small), and if the specified number is 5, the edge corresponding to the smallest 5 contraction cost values is taken as the target contraction edge.
Another possible implementation manner is shown in fig. 4, where fig. 4 is a flowchart of another model loading method shown in the embodiment shown in fig. 1 according to the present disclosure, and the S2 may include:
s21, determining the minimum target contraction cost value in the at least one first contraction cost value and the second contraction cost value.
S22, determining a first target distance between the midpoint position of the edge corresponding to each first contraction cost value and the midpoint position of the edge corresponding to the target contraction cost value, and a second target distance between the midpoint position of the edge corresponding to the second contraction cost value and the midpoint position of the edge corresponding to the target contraction cost value.
Illustratively, the minimum of the m first and second systolic values is taken as the target systolic value if the corresponding edge of the target systolic value is e min The corresponding edge application e of the first contraction cost value i Corresponding edge e representing i ∈ (1, m), the second shrinkage cost value z The first target distance may be expressed as distance (e) i ，e min ) As shown, the second target distance may be expressed as distance (e) z ，e min )。
And S23, taking the side of which the first target distance is greater than or equal to a preset side length threshold as the target contracted side, and taking the corresponding side of the second contracted cost value as the target contracted side under the condition that the second target distance is greater than or equal to the preset side length threshold so as to obtain one or more target contracted sides.
The preset side length threshold may be 2 times of the minimum side length, where the minimum side is a corresponding side of the target contraction cost value.
Illustratively, if the target contraction margin is used e set Indicate, then e set The conditions are satisfied:
{e set |distance(e x ，e min )≥2le min ,e x ∈e}
wherein e is (e) 1 ，e 2 ，…e i …e m ,e z ) I.e., the e is the current set of minimum cost edges.
Through the steps shown in the steps S21 to S23, at least one target shrinkage edge which is larger than or equal to the preset side length threshold can be obtained through setting the preset side length threshold, the optimization of the appointed three-dimensional grid model is realized through the collapse of the target shrinkage edge, and the phenomenon that the model structure is lost due to the fact that the multiple edges collapse over-concentration can be effectively avoided, so that the model simplification efficiency can be effectively improved, and more model structures can be reserved.
And S3, performing collapse processing on the current three-dimensional grid model according to the target contraction edge to obtain an updated current three-dimensional grid model.
In this step, for each target contraction side, a substitution point corresponding to the target contraction side may be determined, where the sum of squares of distances between the substitution point and an adjacent surface of the target contraction side is the minimum; deleting the target contraction edge and the edge connected with the target contraction edge; and connecting the substitute point with the adjacent point of the target contraction edge end point to obtain the updated current three-dimensional grid model.
And S4, determining the ratio of the number of planes contained in the updated current three-dimensional grid model to the number of planes contained in the specified three-dimensional grid model.
And S5, determining whether the ratio is greater than the preset ratio threshold value.
In this step, step S6 is executed if it is determined that the ratio is greater than the preset ratio threshold, and step S7 is executed if it is determined that the ratio is less than or equal to the preset ratio threshold.
Illustratively, if the number of planes included in the current three-dimensional mesh model is t 1 Designating the number of planes contained in the three-dimensional mesh model as t e And the ratio obtained in S4 is
The preset ratio threshold is greater than 0 and less than 1, the larger the preset ratio threshold is, the smaller the total number of edges needing to be optimized is, and the lower the simplification degree of the obtained target three-dimensional grid model is.
And S6, updating the current initial cost value set according to the target contraction edge, and determining the contraction cost value of the newly added edge in the updated current three-dimensional grid model so as to update the current at least one newly added cost value set.
In this step, the following update strategy may be executed for the contraction cost value of each newly added edge in the updated current three-dimensional grid model, so as to update the current at least one newly added cost value set;
wherein the update policy comprises:
acquiring the number of elements in each newly added cost value set;
under the condition that the appointed newly added cost value set with the element quantity less than or equal to the preset quantity threshold value exists, adding the contraction cost value of the current newly added edge to the appointed newly added cost value set;
and under the condition that the appointed newly added cost value set does not exist, generating a target newly added cost value set, and adding the contraction cost value of the current newly added edge to the target newly added cost value set. The set of target added cost values is a new added set.
It should be noted that the preset number threshold may be b s The product is
Wherein t is e The number of sets of the at least one newly added cost value set is less than or equal to b for specifying the total number of edges of the three-dimensional mesh model n ，
And S7, taking the current three-dimensional grid model as the target three-dimensional grid model.
Through the steps shown in S1 to S7, the simplification efficiency of the specified three-dimensional grid model can be greatly improved, the loading of the data of the specified three-dimensional grid model in the target webpage is realized through loading the optimized target three-dimensional grid model, the loading time of the target webpage can be effectively shortened, and therefore the user experience can be effectively improved.
FIG. 5 is a block diagram of a model loading apparatus shown in an exemplary embodiment of the present disclosure; as shown in fig. 5, the apparatus may include:
a first determining module 501, configured to, in response to receiving a load instruction for a target web page, if it is determined that the target web page includes a specified three-dimensional mesh model to be loaded, obtain a contraction cost value of each edge in the specified three-dimensional mesh model to obtain an initial cost value set, where the contraction cost value is used to represent a geometric error that may be generated by contraction;
a second determining module 502 configured to determine an edge to be optimized in the specified three-dimensional mesh model according to the initial cost value set;
a third determining module 503, configured to collapse the edge to be optimized to obtain an updated current three-dimensional mesh model;
a fourth determining module 504, configured to determine a contraction cost value of the newly added edge in the current three-dimensional mesh model to obtain at least one newly added cost value set;
a fifth determining module 505, configured to perform iterative optimization on the current three-dimensional mesh model according to the initial cost value set and the at least one newly added cost value set to obtain an optimized target three-dimensional mesh model, and load the target three-dimensional mesh model as load data of the target web page.
According to the technical scheme, the iterative optimization is carried out on the current three-dimensional grid model according to the initial cost value set and the at least one newly added cost value set, the model simplification efficiency can be effectively improved, the loading of the specified three-dimensional grid model data in the target webpage is realized by loading the optimized target three-dimensional grid model, the loading time of the target webpage can be effectively shortened, and therefore the user experience can be effectively improved.
Optionally, the fourth determining module 504 is configured to:
acquiring the target number of the newly added edges;
under the condition that the number of the targets is larger than a preset number threshold, dividing contraction cost values corresponding to the newly added edges of the number of the targets into a plurality of groups, wherein each group corresponds to one newly added cost value set so as to obtain a plurality of newly added cost value sets; or,
and generating the newly added cost value set under the condition that the target number is less than or equal to the preset number threshold, wherein the contraction cost values corresponding to the newly added edges of the target number are all elements in the newly added cost value set.
Optionally, the fifth determining module 505 is configured to:
determining a designated edge adjacent to the edge to be optimized in the designated three-dimensional grid model;
deleting the contraction cost value of the appointed edge from the initial cost value set to obtain an updated initial cost value set;
and performing iterative optimization on the current three-dimensional grid model according to the at least one newly added cost value set and the updated initial cost value set to obtain the target three-dimensional grid model.
Optionally, the fifth determining module 505 is configured to:
determining the minimum shrinkage cost value in each newly added cost value set to obtain at least one first shrinkage cost value, and determining the minimum shrinkage cost value in the updated initial cost value set to obtain a second shrinkage cost value;
determining a target shrinkage edge according to the at least one first shrinkage cost value and the second shrinkage cost value;
collapsing the current three-dimensional grid model according to the target shrinkage edge to obtain an updated current three-dimensional grid model;
determining the ratio of the number of planes contained in the updated current three-dimensional grid model to the number of planes contained in the specified three-dimensional grid model;
determining whether the ratio is greater than the preset ratio threshold;
under the condition that the ratio is determined to be larger than the preset ratio threshold, updating the current initial cost value set according to the target contracted edge, determining the contracted cost value of a newly-added edge in the updated current three-dimensional grid model so as to update the current at least one newly-added cost value set, and executing the step of determining the minimum contracted cost value in each newly-added cost value set again so as to obtain at least one first contracted cost value until the step of determining whether the ratio is larger than the preset ratio threshold or not is carried out;
and taking the current three-dimensional mesh model as the target three-dimensional mesh model under the condition that the ratio is determined to be less than or equal to the preset ratio threshold.
Optionally, the fifth determining module 505 is configured to:
determining a minimum specified number of the at least one first and second systolic cost values;
determining a first target distance between the midpoint position of the edge corresponding to each first contraction cost value and the midpoint position of the edge corresponding to the target contraction cost value, and a second target distance between the midpoint position of the edge corresponding to the second contraction cost value and the midpoint position of the edge corresponding to the target contraction cost value;
and taking the side with the first target distance greater than or equal to a preset side length threshold as the target contracted side, and taking the corresponding side of the second contracted cost value as the target contracted side under the condition that the second target distance is greater than or equal to the preset side length threshold so as to obtain one or more target contracted sides.
Optionally, the fifth determining module 505 is configured to:
and taking the edge corresponding to the minimum target shrinkage cost value in the at least one first shrinkage cost value and the second shrinkage cost value as the target shrinkage edge.
Optionally, the fifth determining module 505 is configured to:
executing the following updating strategy aiming at the contraction cost value of each newly added edge in the updated current three-dimensional grid model so as to update the current at least one newly added cost value set;
the update policy includes:
acquiring the number of elements in each newly added cost value set;
under the condition that the appointed newly added cost value set with the element quantity less than or equal to the preset quantity threshold value exists, adding the contraction cost value of the current newly added edge to the appointed newly added cost value set;
and under the condition that the appointed newly added cost value set does not exist, generating a target newly added cost value set, and adding the contraction cost value of the current newly added edge to the target newly added cost value set.
Optionally, the third determining module 503 is configured to:
determining a target point corresponding to the edge to be optimized, wherein the target point is a point with the minimum sum of squares of distances between the edge to be optimized and an adjacent surface of the edge to be optimized;
deleting the edge to be optimized and the edge connected with the edge to be optimized;
and connecting the target point with the adjacent point of the end point of the edge to be optimized to obtain the current three-dimensional mesh model.
According to the technical scheme, the iterative optimization is carried out on the current three-dimensional grid model according to the initial cost value set and the at least one newly added cost value set, the model simplification efficiency can be effectively improved, the loading of the specified three-dimensional grid model data in the target webpage is realized by loading the optimized target three-dimensional grid model, the loading time of the target webpage can be effectively shortened, and therefore the user experience can be effectively improved.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
FIG. 6 is a block diagram illustrating an electronic device in accordance with an example embodiment. As shown in fig. 6, the electronic device 700 may include: a processor 701 and a memory 702. The electronic device 700 may also include one or more of a multimedia component 703, an input/output (I/O) interface 704, and a communication component 705.
The processor 701 is configured to control the overall operation of the electronic device 700, so as to complete all or part of the steps in the above-described model loading method. The memory 702 is used to store various types of data to support operation at the electronic device 700, such as instructions for any application or method operating on the electronic device 700 and application-related data, such as contact data, transmitted and received messages, pictures, audio, video, and the like. The Memory 702 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically Erasable Programmable Read-Only Memory (EEPROM), erasable Programmable Read-Only Memory (EPROM), programmable Read-Only Memory (PROM), read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk. The multimedia components 703 may include screen and audio components. Wherein the screen may be, for example, a touch screen and the audio component is used for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may further be stored in the memory 702 or transmitted through the communication component 705. The audio assembly further comprises at least one speaker for outputting audio signals. The I/O interface 704 provides an interface between the processor 701 and other interface modules, such as a keyboard, mouse, buttons, and the like. These buttons may be virtual buttons or physical buttons. The communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless Communication, such as Wi-Fi, bluetooth, near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, or combinations thereof, which is not limited herein. The corresponding communication component 705 may thus include: wi-Fi modules, bluetooth modules, NFC modules, and the like.
In an exemplary embodiment, the electronic Device 700 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the above-described model loading method.
In another exemplary embodiment, a computer readable storage medium comprising program instructions which, when executed by a processor, implement the steps of the model loading method described above is also provided. For example, the computer readable storage medium may be the memory 702 described above comprising program instructions that are executable by the processor 701 of the electronic device 700 to perform the model loading method described above.
FIG. 7 is a block diagram illustrating another electronic device in accordance with an exemplary embodiment. For example, the electronic device 1900 may be provided as a server. Referring to fig. 7, an electronic device 1900 includes a processor 1922, which may be one or more in number, and a memory 1932 to store computer programs executable by the processor 1922. The computer program stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processor 1922 may be configured to execute the computer program to perform the model loading method described above.
Additionally, electronic device 1900 may also include a power component 1926 and a communication component 1950, the power component 1926 may be configured to perform power management of the electronic device 1900, and the communication component 1950 may be configured to enable communication, e.g., wired or wireless communication, of the electronic device 1900. In addition, the electronic device 1900 may also include input/output (I/O) interfaces 1958. The electronic device 1900 may operate based on an operating system, such as Windows Server, stored in memory 1932 TM ，Mac OS X TM ，Unix TM ，Linux TM And so on.
In another exemplary embodiment, a computer readable storage medium comprising program instructions which, when executed by a processor, implement the steps of the model loading method described above is also provided. For example, the non-transitory computer readable storage medium may be the memory 1932 described above that includes program instructions that are executable by the processor 1922 of the electronic device 1900 to perform the model loading method described above.
In another exemplary embodiment, a computer program product is also provided, which comprises a computer program executable by a programmable apparatus, the computer program having code portions for performing the above-described model loading method when executed by the programmable apparatus.
The preferred embodiments of the present disclosure are described in detail with reference to the accompanying drawings, however, the present disclosure is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present disclosure within the technical idea of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.
It should be noted that, in the foregoing embodiments, various features described in the above embodiments may be combined in any suitable manner, and in order to avoid unnecessary repetition, various combinations that are possible in the present disclosure are not described again.
In addition, any combination of various embodiments of the present disclosure may be made, and the same should be considered as the disclosure of the present disclosure, as long as it does not depart from the spirit of the present disclosure.
Claims (11)
1. A method of model loading, the method comprising:
in response to receiving a loading instruction for a target webpage, if the target webpage is determined to include a specified three-dimensional grid model to be loaded, acquiring a contraction cost value of each edge in the specified three-dimensional grid model to obtain an initial cost value set, wherein the contraction cost value is used for representing a geometric error generated by contraction;
determining an edge to be optimized in the appointed three-dimensional grid model according to the initial cost value set;
collapsing the to-be-optimized edge to obtain an updated current three-dimensional grid model;
determining the contraction cost value of the newly added edge in the current three-dimensional grid model to obtain at least one newly added cost value set;
and performing iterative optimization on the current three-dimensional grid model according to the initial cost value set and the at least one newly added cost value set to obtain an optimized target three-dimensional grid model, and loading the target three-dimensional grid model as loading data of the target webpage.
2. The method of claim 1, wherein determining the contraction cost value of the new edge in the current three-dimensional mesh model to obtain at least one new set of cost values comprises:
acquiring the target number of the newly added edges;
under the condition that the target number is larger than a preset number threshold, dividing contraction cost values corresponding to the newly added edges of the target number into a plurality of groups, wherein each group corresponds to one newly added cost value set so as to obtain a plurality of newly added cost value sets; or,
and generating one newly added cost value set under the condition that the target number is less than or equal to the preset number threshold, wherein the contraction cost values corresponding to the newly added edges of the target number are all elements in the newly added cost value set.
3. The method of claim 1, wherein said iteratively optimizing said current three-dimensional mesh model based on said initial set of cost values and said at least one newly added set of cost values to obtain an optimized target three-dimensional mesh model, comprises:
determining a designated edge adjacent to the edge to be optimized in the designated three-dimensional grid model;
deleting the contraction cost value of the appointed edge from the initial cost value set to obtain an updated initial cost value set;
and performing iterative optimization on the current three-dimensional grid model according to the at least one newly added cost value set and the updated initial cost value set to obtain the target three-dimensional grid model.
4. The method of claim 3, wherein iteratively optimizing the current three-dimensional mesh model according to the at least one newly added set of cost values and the updated initial set of cost values to obtain the target three-dimensional mesh model comprises:
determining the minimum contraction cost value in each newly added cost value set to obtain at least one first contraction cost value, and determining the minimum contraction cost value in the updated initial cost value set to obtain a second contraction cost value;
determining a target systolic edge based on the at least one first systolic cost value and the second systolic cost value;
performing collapse processing on the current three-dimensional grid model according to the target contraction edge to obtain an updated current three-dimensional grid model;
determining a ratio of the number of planes contained in the updated current three-dimensional mesh model to the number of planes contained in the specified three-dimensional mesh model;
determining whether the ratio is greater than a preset ratio threshold;
under the condition that the ratio is determined to be larger than the preset ratio threshold, updating the current initial cost value set according to the target contraction edge, determining the contraction cost value of a newly increased edge in the updated current three-dimensional grid model to update the current at least one newly increased cost value set, and executing the step of determining the minimum contraction cost value in each newly increased cost value set again to obtain at least one first contraction cost value until the step of determining whether the ratio is larger than the preset ratio threshold or not;
and taking the current three-dimensional mesh model as the target three-dimensional mesh model under the condition that the ratio is determined to be smaller than or equal to the preset ratio threshold.
5. The method of claim 4, wherein determining a target systolic edge based on the at least one first systolic cost value and the second systolic cost value comprises:
determining a target systolic cost value that is the smallest of the at least one first systolic cost value and the second systolic cost value;
determining a first target distance between the midpoint position of each edge corresponding to the first contraction cost value and the midpoint position of the edge corresponding to the target contraction cost value, and a second target distance between the midpoint position of the edge corresponding to the second contraction cost value and the midpoint position of the edge corresponding to the target contraction cost value;
and taking the side of which the first target distance is greater than or equal to a preset side length threshold as the target contraction side, and taking the corresponding side of the second contraction cost value as the target contraction side under the condition that the second target distance is greater than or equal to the preset side length threshold, so as to obtain one or more target contraction sides.
6. The method of claim 4, wherein determining a target systolic edge as a function of the at least one first systolic cost value and the second systolic cost value comprises:
and taking the edge corresponding to the minimum specified number of the first contraction cost values and the second contraction cost values as the target contraction edge.
7. The method of claim 4, wherein determining a contraction cost value of the new edge in the updated current three-dimensional mesh model to update the current at least one new set of cost values comprises:
aiming at the contraction cost value of each newly added edge in the updated current three-dimensional grid model, executing the following updating strategy to update the current at least one newly added cost value set;
the update policy includes:
acquiring the number of elements in each newly added cost value set;
adding the contraction cost value of the current newly added edge to the specified newly added cost value set under the condition that the specified newly added cost value set with the element number smaller than or equal to the preset number threshold value exists;
and under the condition that the appointed newly added cost value set does not exist, generating a target newly added cost value set, and adding the contraction cost value of the current newly added edge to the target newly added cost value set.
8. The method according to any one of claims 1 to 7, wherein collapsing the edge to be optimized to obtain the updated current three-dimensional mesh model comprises:
determining a target point corresponding to the edge to be optimized, wherein the target point is a point with the minimum sum of squares of distances between the edge to be optimized and an adjacent surface of the edge to be optimized;
deleting the edge to be optimized and the edge connected with the edge to be optimized;
and connecting the target point with the adjacent point of the end point of the edge to be optimized to obtain the current three-dimensional grid model.
9. A model loading apparatus, the apparatus comprising:
the first determining module is configured to respond to a received loading instruction of a target webpage, and if the target webpage is determined to include a specified three-dimensional grid model to be loaded, obtain a contraction cost value of each edge in the specified three-dimensional grid model to obtain an initial cost value set, wherein the contraction cost value is used for representing a geometric error generated by contraction;
a second determining module configured to determine an edge to be optimized in the specified three-dimensional mesh model according to the initial cost value set;
a third determining module, configured to perform collapse processing on the edge to be optimized to obtain an updated current three-dimensional grid model;
a fourth determining module configured to determine a contraction cost value of a newly added edge in the current three-dimensional mesh model to obtain at least one newly added cost value set;
and the fifth determining module is configured to perform iterative optimization on the current three-dimensional grid model according to the initial cost value set and the at least one newly added cost value set to obtain an optimized target three-dimensional grid model, and load the target three-dimensional grid model as loading data of the target webpage.
10. A non-transitory computer readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 8.
11. An electronic device, comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to carry out the steps of the method of any one of claims 1 to 8.
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| CN117473655B (en) * | 2023-12-27 | 2024-03-15 | 中国人民解放军国防科技大学 | Aircraft simulation driving design method and device based on edge collapse grid optimization |
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