CN109272567B - Three-dimensional model optimization method and device - Google Patents
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Abstract
The embodiment of the invention provides a three-dimensional model optimization method and a three-dimensional model optimization device, wherein the three-dimensional model optimization method comprises the steps of obtaining the level information of each sub-model in a model to be processed; classifying each submodel in the model to be processed according to whether the hierarchical information is the same or not to form a plurality of file packages to be processed, wherein the hierarchical information of each submodel contained in each file package to be processed is the same; for each file packet to be processed, combining all sub models in the file packet to be processed based on the mesh grid attribute to obtain an initial model file; judging whether the mesh grid parameters in the initial model file meet first preset requirements or not, if not, calling an optimization strategy corresponding to the mesh grid parameters to carry out mesh grid optimization on the initial model file to obtain a first target file. The method can realize batch optimization processing of the model and improve the optimization efficiency of the model.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a three-dimensional model optimization method and device.
Background
When building three-dimensional models such as buildings, terrain, trees, rivers, etc., three-dimensional visualization has gradually become the main trend of visualization. The model optimization method adopted at present is mainly realized by reducing the number of top points and faces of the model or changing rendering parameters of a rendering engine and the like when the model is created, but most of the model optimization methods realize optimization adjustment of the model based on a manual mode or realize model optimization by adopting targeted optimization codes and the like, so that the model optimization efficiency is low, integral optimization standards and processes are not formed, and batch and automatic processing cannot be realized or realized.
Disclosure of Invention
In view of this, an object of the embodiments of the present invention is to provide a method and an apparatus for optimizing a three-dimensional model, so as to improve the above problem.
In one aspect, a preferred embodiment of the present invention provides a three-dimensional model optimization method, where the three-dimensional model optimization method includes:
acquiring the level information of each sub-model in the model to be processed;
classifying each submodel in the model to be processed according to whether the hierarchical information is the same or not to form a plurality of file packages to be processed, wherein the hierarchical information of each submodel contained in each file package to be processed is the same;
for each file packet to be processed, combining all sub models in the file packet to be processed based on the mesh grid attribute to obtain an initial model file;
judging whether the mesh grid parameters in the initial model file meet first preset requirements or not, and if not, calling an optimization strategy corresponding to the mesh grid parameters to carry out mesh grid optimization on the initial model file to obtain a first target file.
Further, the step of judging whether the mesh grid parameter in the initial model file meets a first preset requirement or not, if not, calling an optimization strategy corresponding to the mesh grid parameter to perform mesh grid optimization on the initial model file to obtain a first target file includes:
and judging whether the number of the top points or the number of the faces of the initial model file is greater than a first preset value, if so, calling a face reduction strategy to carry out face reduction processing on the initial model file until the number of the top points or the number of the faces is not greater than the first preset value, and taking the initial model file subjected to the face reduction processing as a first target file.
Further, the three-dimensional model optimization method further comprises the following steps:
merging a plurality of material ball files corresponding to the first target file to obtain a material ball file to be processed;
merging a plurality of mapping files corresponding to all the material ball files based on the material ball files to be processed to obtain mapping files to be processed;
and judging whether the map parameters of the map file to be processed meet second preset requirements, if not, calling an optimization strategy corresponding to the map parameters to optimize the map file to be processed to obtain a second target file.
Further, the step of determining whether the map parameter of the to-be-processed map file meets a second preset requirement, if not, calling an optimization strategy corresponding to the map parameter to optimize the to-be-processed map file to obtain a second target file includes:
and judging whether the image resolution is greater than a second preset value, if so, optimally adjusting the image resolution of the to-be-processed mapping file so that the image resolution of the to-be-processed mapping file is not greater than the second preset value, and taking the first target file with resolution adjustment completed as a second target file.
Further, the method further comprises:
and naming the first target file or the second target file according to a preset naming rule.
Further, the hierarchical information of each sub-model includes a service type.
In another aspect, a preferred embodiment of the present invention provides a model optimization apparatus, including:
the hierarchical information acquisition module is used for acquiring hierarchical information of each submodel in the model to be processed;
the hierarchical classification module is used for classifying each sub-model in the to-be-processed model according to whether hierarchical information is the same or not so as to form a plurality of to-be-processed file packages, and the hierarchical information of each sub-model contained in each to-be-processed file package is the same;
the first merging module is used for merging each submodel in each file packet to be processed based on the mesh grid attribute so as to obtain an initial model file;
and the first judgment module is used for judging whether the mesh grid parameter in the initial model file meets a first preset requirement or not, and if not, calling an optimization strategy corresponding to the mesh grid parameter to carry out mesh grid optimization on the initial model file so as to obtain a first target file.
Further, the mesh grid parameters include a vertex number and a face number, and the first judgment module is further configured to
And judging whether the number of the top points or the number of the faces of the initial model file is greater than a first preset value, if so, calling a face reduction strategy to perform face reduction processing on the initial model file until the number of the top points or the number of the faces is not greater than the first preset value, and taking the initial model file subjected to the face reduction processing as a first target file.
Further, the model optimization device further comprises:
the second merging module is used for merging the plurality of material ball files corresponding to the first target file to obtain a material ball file to be processed;
the third merging module is used for merging a plurality of mapping files corresponding to all the material ball files based on the material ball files to be processed to obtain mapping files to be processed;
and the second judgment module is used for judging whether the map parameters of the map file to be processed meet second preset requirements or not, and if not, calling an optimization strategy corresponding to the map parameters to optimize the map file to be processed to obtain a second target file.
Further, the map parameter includes an image resolution, the second determining module is further configured to determine whether the image resolution is greater than a second preset value, and if the image resolution is greater than the second preset value, optimally adjust the image resolution of the map file to be processed so that the image resolution of the map file to be processed is not greater than the second preset value, and use the first target file with resolution adjustment completed as a second target file.
Compared with the prior art, the embodiment of the invention provides a three-dimensional model optimization method and a three-dimensional model optimization device, wherein the method realizes batch and automatic optimization processing of the model based on unified and rationalized model optimization standards, can effectively remove manual participation in the model optimization process, improves the model optimization performance, reduces the model optimization difficulty, and reduces the error rate in the model optimization process.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic block structure diagram of an electronic terminal to which the three-dimensional model optimization method and apparatus provided by the embodiment of the present invention are applied.
Fig. 2 is a schematic flowchart of a three-dimensional model optimization method according to an embodiment of the present invention.
Fig. 3 is another schematic flow chart of the three-dimensional model optimization method according to the embodiment of the present invention.
Fig. 4 is a schematic block structure diagram of a model optimization apparatus according to an embodiment of the present invention.
An icon: 10-an electronic terminal; 100-model optimization means; 110-a hierarchy information acquisition module; 120-level classification module; 130-a first merge module; 140-a first determination module; 150-a second merge module; 160-a third merging module; 170-a second judgment module; 300-a memory; 400-a memory controller; 500-a processor.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
As shown in fig. 1, a block diagram of an electronic terminal 10 to which the method and apparatus for optimizing a three-dimensional model according to the embodiments of the present invention are applied is shown, where the electronic terminal 10 includes a model optimizing apparatus 100, a memory 300, a storage controller 400, and a processor 500. The memory 300, the memory controller 400, and the processor 500 are electrically connected to each other directly or indirectly, so as to implement data transmission or interaction. For example, the components are electrically connected to each other through one or more communication buses or signal lines. The model optimization device 100 includes at least one software function module that may be stored in the memory 300 in the form of software or firmware or be solidified in an operating system in the electronic terminal 10. The processor 500 accesses the memory 300 under the control of the memory controller 400 for executing executable modules stored in the memory 300, such as software functional modules and computer programs included in the model optimization device 100.
It will be appreciated that the configuration shown in FIG. 1 is merely illustrative and that the electronic terminal 10 may include more or fewer components than shown in FIG. 1 or may have a different configuration than shown in FIG. 1. In addition, the electronic terminal 10 may be, but is not limited to, a smart phone, a Personal Computer (PC), a tablet PC, a Personal Digital Assistant (PDA), a Mobile Internet Device (MID), a cloud server, a small computer, and the like.
Further, as shown in fig. 2, a schematic flow chart of a three-dimensional model optimization method provided in an embodiment of the present invention is applied to the above-mentioned electronic terminal 10, and specific steps and a flow of the three-dimensional model optimization method will be described in detail below with reference to fig. 2. It should be understood that the three-dimensional model optimization method given in the present embodiment is not limited by the order of the steps and flow described below.
S11, acquiring the level information of each sub-model in the model to be processed;
step S12, classifying each sub-model in the model to be processed according to whether the hierarchical information is the same or not to form a plurality of file packages to be processed, wherein the hierarchical information of each sub-model contained in each file package to be processed is the same;
s13, aiming at each file packet to be processed, merging each sub-model in the file packet to be processed based on the mesh grid attribute to obtain an initial model file;
step S14, judging whether the mesh grid parameters in the initial model file meet a first preset requirement, if not, executing step S15, otherwise, judging that the mesh grid attributes in the initial model file do not need to be optimized;
and S15, calling an optimization strategy corresponding to the mesh grid parameters to carry out mesh grid optimization on the initial model file to obtain a first target file.
In the three-dimensional model optimization method provided in the above steps S11 to S15, each submodel in the model to be processed is classified based on the hierarchical information, and mesh merging is performed on submodels belonging to the same class based on the mesh attributes, so as to determine whether mesh parameters in the merged model need to be optimized, and mesh optimization is performed when the merged model does not meet the requirements, thereby realizing automatic, batch and standardized model optimization on a plurality of submodels, improving the model optimization efficiency, and reducing the error probability during model optimization.
In detail, in step S11 and step S12, the model to be processed may be a three-dimensional model such as a building model, a terrain model, a tree model, and the like. In addition, the model to be processed may be composed of one or more building models or one or more terrain models, and this embodiment is not limited herein. The hierarchical information may include, but is not limited to, a service type, service requirement information, and the like, for example, when the hierarchical information is a service type, if the to-be-processed model is assumed to be a building model, the building model includes a plurality of sub-models such as a wall sub-model, a floor sub-model, a furniture sub-model, a garden sub-model, a pipe sub-model, and the like, when the hierarchical information according to the service type is classified, the plurality of wall sub-models may be divided into one to-be-processed document package, the floor sub-model may be divided into one to-be-processed document package, \\ 8230, and the λ 8230, so as to form a plurality of to-be-processed document packages corresponding to different service types.
In actual implementation, besides the automatic classification of the sub-models in the to-be-processed model, the classification of multiple sub-models can be realized by responding to a classification operation instruction of a user based on a preset classification standard, which is not described herein in detail in this embodiment.
Further, in step S13, considering that the mesh grid parameters of the model directly affect the performance of the model in terms of model performance optimization, in this embodiment, each sub-model in the to-be-processed file package may be merged based on the mesh grid attributes to obtain an initial model file.
Further, in step S14 and step S15, the mesh grid parameters may include, but are not limited to, a vertex number and a face number, and the first preset requirement may be flexibly set according to different mesh grid parameters. For example, in this embodiment, when the mesh grid parameters include the number of vertices and the number of faces, the actual implementation process of step S14 may include: and judging whether the number of the top points or the number of the faces of the initial model file is greater than a first preset value, if so, calling a face reduction strategy to perform face reduction processing on the initial model file until the number of the top points or the number of the faces is not greater than the first preset value, and taking the initial model file subjected to the face reduction processing as a first target file. The first preset value may be flexibly designed according to actual requirements, and the embodiment is not limited herein. It should be noted that, according to the corresponding relationship between the number of vertices and the number of facets, the first preset value is different, and if one facet corresponds to four vertices, the first preset value when the mesh grid parameter is the number of vertices is four times that when the mesh grid parameter is the number of facets, and the like, and this embodiment is not limited in particular here.
Further, in order to further reduce the human involvement in the process of model optimization and improve the intelligence of model optimization, as shown in fig. 3, in this embodiment, the three-dimensional model optimization method may further include the following steps S16 to S19, which are specifically as follows.
Step S16, merging a plurality of material ball files corresponding to the first target file to obtain a material ball file to be processed;
step S17, merging a plurality of mapping files corresponding to the material ball files based on the material ball files to be processed to obtain mapping files to be processed;
step S18, judging whether the mapping parameters of the mapping file to be processed meet second preset requirements, if not, executing step S19, otherwise, judging that the first target file does not need to be optimized;
and S19, calling an optimization strategy corresponding to the mapping parameters to optimize the mapping file to be processed to obtain a second target file.
And S16-S19, merging material balls and optimizing mapping based on the first target file after mesh grid merging and optimization are completed, wherein each submodel in each file packet to be processed corresponds to a material ball file, and each material ball carries a mapping file, so that the mapping files can be merged while merging the material ball files to obtain the mapping files to be processed, and further the model is further optimized according to the merged mapping files to be processed.
In detail, in steps S18 to S19, the mapping parameters may include, but are not limited to, a size of the mapping, a resolution of the mapping, and the like, and the second preset requirement may be flexibly designed according to actual conditions of the mapping parameters. In this embodiment, assuming that the mapping parameter is an image resolution, the specific implementation process of step S17 may include: and judging whether the image resolution is greater than a second preset value, if so, optimally adjusting the image resolution of the to-be-processed mapping file so that the image resolution of the to-be-processed mapping file is not greater than the second preset value, and taking the first target file with resolution adjustment completed as a second target file. For another example, when the mapping parameter is the size of the mapping, the specific implementation process of step S17 may include: and calculating the size of the combined map file, judging whether the size of the map exceeds a preset value, and if so, adjusting and optimizing the size of the combined map until the size of the map does not exceed the preset value.
It can be understood that, for the sub-models in other to-be-processed file packages, the above steps S13 to S17 may be repeatedly performed, so as to complete the batch optimization operation of the to-be-processed models, which is not described herein again. Further, since each sub-model is a file having a tree structure including node information, the optimized file can be output in the form of a model file, for example, a plurality of sub-models having the same hierarchical information can be output as one model file (for example, a first object file and a second object file), or a plurality of sub-models corresponding to a plurality of different hierarchical information can be output as one model file.
Further, according to actual requirements, before the model is output, in order to enable a model user to conveniently use the optimized model, a uniform control interface may be provided for the optimized model, that is, in this embodiment, the first target file or the second target file may be further named according to a preset naming rule. Specifically, names of nodes in each hierarchical structure, such as material ball files and map files, may be named according to a preset naming rule (e.g., an industry standard), which is not limited herein.
Based on the description of the three-dimensional model optimization method, as shown in fig. 4, an embodiment of the present invention further provides a model optimization apparatus 100, where the model optimization apparatus 100 is applied to the electronic terminal 10, and the model optimization apparatus 100 includes a hierarchy information obtaining module 110, a hierarchy classifying module 120, a first merging module 130, a first determining module 140, a second merging module 150, a third merging module 160, and a second determining module 170.
The hierarchical information obtaining module 110 is configured to obtain hierarchical information of each sub-model in the model to be processed; in this embodiment, the description of the hierarchy information acquiring module 110 may specifically refer to the detailed description of the step S11, that is, the step S11 may be executed by the hierarchy information acquiring module 110, and therefore, no further description is provided herein.
The hierarchical classification module 120 is configured to classify each sub-model in the to-be-processed model according to whether hierarchical information is the same or not to form a plurality of to-be-processed file packages, where hierarchical information of each sub-model included in each to-be-processed file package is the same; in this embodiment, the description of the hierarchical classification module 120 may specifically refer to the detailed description of the step S12, that is, the step S12 may be executed by the hierarchical classification module 120, and thus will not be further described herein.
The first merging module 130 is configured to merge, for each to-be-processed file package, each sub-model in the to-be-processed file package based on the mesh grid attribute to obtain an initial model file; in this embodiment, the description of the first combining module 130 may specifically refer to the detailed description of the step S13, that is, the step S13 may be executed by the first combining module 130, and therefore, no further description is provided herein.
The first determining module 140 is configured to determine whether a mesh grid parameter in the initial model file meets a first preset requirement, and if not, invoke an optimization strategy corresponding to the mesh grid parameter to perform mesh grid optimization on the initial model file to obtain a first target file. In addition, in the present embodiment, the description of the first determining module 140 may specifically refer to the detailed description of the steps S14 to S15, that is, the steps S14 to S15 may be executed by the first determining module 140, and therefore, no further description is provided herein.
The second merging module 150 is configured to merge multiple material ball files corresponding to the first target file to obtain a material ball file to be processed; in this embodiment, the detailed description of the step S16 may be referred to for the description of the second merging module 150, that is, the step S16 may be executed by the second merging module 150, and therefore, no further description is provided herein.
The third merging module 160 merges a plurality of mapping files corresponding to the material ball files based on the material ball file to be processed to obtain a mapping file to be processed; in this embodiment, the detailed description of the step S17 may be referred to for the description of the third merging module 160, that is, the step S17 may be executed by the third merging module 160, and thus, no further description is provided herein.
The second determining module 170 is configured to determine whether a map parameter of the to-be-processed map file meets a second preset requirement, and if not, invoke an optimization policy corresponding to the map parameter to optimize the to-be-processed map file to obtain a second target file. In this embodiment, the detailed description of the step S18 to the step S19 may be referred to for the description of the second determining module 170, that is, the step S18 to the step S19 may be executed by the second determining module 170, and therefore, no further description is provided herein.
In summary, embodiments of the present invention provide a method and an apparatus for optimizing a three-dimensional model, wherein the method and the apparatus implement batch and automatic optimization processing on models based on unified and rationalized model optimization criteria, and can effectively remove manual participation in the model optimization process, improve model optimization performance, reduce model optimization difficulty, and reduce error rate in the model optimization process.
In the embodiments provided in the embodiments of the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. The apparatus and method embodiments described above are illustrative only, as the flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions may be stored in a computer-readable storage medium if they are implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solution of the present invention or a part thereof which substantially contributes to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, an electronic device, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.
The above description is only an alternative embodiment of the present invention and is not intended to limit the present invention, and various modifications and variations of the present invention may occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A three-dimensional model optimization method, characterized in that the three-dimensional model optimization method comprises:
acquiring the level information of each sub-model in the model to be processed;
classifying each submodel in the model to be processed according to whether the hierarchical information is the same or not to form a plurality of file packages to be processed, wherein the hierarchical information of each submodel contained in each file package to be processed is the same;
aiming at each file packet to be processed, merging each sub-model in the file packet to be processed based on mesh grid attributes to obtain an initial model file;
judging whether the mesh grid parameters in the initial model file meet first preset requirements or not, if not, calling an optimization strategy corresponding to the mesh grid parameters to carry out mesh grid optimization on the initial model file to obtain a first target file;
the mesh grid parameters comprise a vertex number and a face number, whether the mesh grid parameters in the initial model file meet a first preset requirement is judged, if not, an optimization strategy corresponding to the mesh grid parameters is called to carry out mesh grid optimization on the initial model file so as to obtain a first target file, and the method comprises the following steps:
and judging whether the number of the top points or the number of the faces of the initial model file is greater than a first preset value, if so, calling a face reduction strategy to carry out face reduction processing on the initial model file until the number of the top points or the number of the faces is not greater than the first preset value, and taking the initial model file subjected to the face reduction processing as a first target file.
2. The three-dimensional model optimization method of claim 1, further comprising:
merging a plurality of material ball files corresponding to the first target file to obtain a material ball file to be processed;
merging a plurality of mapping files corresponding to the material ball files based on the material ball files to be processed to obtain mapping files to be processed;
and judging whether the map parameters of the map file to be processed meet second preset requirements, if not, calling an optimization strategy corresponding to the map parameters to optimize the map file to be processed to obtain a second target file.
3. The three-dimensional model optimization method according to claim 2, wherein the mapping parameter includes an image resolution, and the step of determining whether the mapping parameter of the mapping file to be processed satisfies a second preset requirement, and if not, invoking an optimization policy corresponding to the mapping parameter to perform optimization processing on the mapping file to be processed to obtain a second target file includes:
and judging whether the image resolution is greater than a second preset value, if so, optimally adjusting the image resolution of the to-be-processed mapping file so that the image resolution of the to-be-processed mapping file is not greater than the second preset value, and taking the first target file with the resolution adjustment completed as a second target file.
4. The three-dimensional model optimization method of claim 2, further comprising:
and naming the first target file or the second target file according to a preset naming rule.
5. The three-dimensional model optimization method of claim 1, wherein the hierarchical information of each sub-model includes a traffic type.
6. A three-dimensional model optimization apparatus, characterized in that the three-dimensional model optimization apparatus comprises:
the hierarchical information acquisition module is used for acquiring hierarchical information of each submodel in the model to be processed;
the hierarchical classification module is used for classifying each sub-model in the to-be-processed model according to whether hierarchical information is the same or not so as to form a plurality of to-be-processed file packages, and the hierarchical information of each sub-model contained in each to-be-processed file package is the same;
the first merging module is used for merging each submodel in each file packet to be processed based on the mesh grid attribute so as to obtain an initial model file;
the first judgment module is used for judging whether the mesh grid parameter in the initial model file meets a first preset requirement or not, and if not, calling an optimization strategy corresponding to the mesh grid parameter to carry out mesh grid optimization on the initial model file so as to obtain a first target file;
the mesh grid parameters comprise the number of the top points and the number of the faces, the first judging module is further used for judging whether the number of the top points or the number of the faces of the initial model file is larger than a first preset value or not, if so, a face reduction strategy is called to carry out face reduction processing on the initial model file, and the initial model file subjected to face reduction processing is used as a first target file until the number of the top points or the number of the faces is not larger than the first preset value.
7. The three-dimensional model optimization device of claim 6, further comprising:
the second merging module is used for merging the plurality of material ball files corresponding to the first target file to obtain a material ball file to be processed;
the third merging module is used for merging a plurality of mapping files corresponding to all the material ball files based on the material ball files to be processed to obtain mapping files to be processed;
and the second judging module is used for judging whether the map parameters of the map file to be processed meet second preset requirements or not, and if not, calling an optimization strategy corresponding to the map parameters to optimize the map file to be processed to obtain a second target file.
8. The apparatus of claim 7, wherein the map parameter comprises an image resolution, and the second determining module is further configured to determine whether the image resolution is greater than a second predetermined value, and if so, perform an optimization adjustment on the image resolution of the to-be-processed map file to make the image resolution of the to-be-processed map file not greater than the second predetermined value, and use the first target file with the resolution adjusted as the second target file.
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