CN113779674A - Method, device, equipment and storage medium for designing customized household three-dimensional model scheme - Google Patents
Method, device, equipment and storage medium for designing customized household three-dimensional model scheme Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a storage medium for designing a customized household three-dimensional model scheme, wherein the method comprises the following steps: establishing a house type characteristic database, a house type design characteristic database and a furniture arrangement relation database; acquiring a plan view of a space to be designed and a design requirement label, extracting house type characteristics, and splitting a design requirement list; comparing the house type characteristics with a house type characteristic database, comparing the matched first design scheme with a house type design characteristic database, and selecting a plurality of second design schemes meeting all requirements of a requirement list; acquiring a third design scheme selected by a user from the plurality of second design schemes; constructing a three-dimensional space; and extracting core design elements of the third design scheme, and intelligently arranging the core design elements in a three-dimensional space to obtain a three-dimensional design scene. The invention can ensure the design quality of new design to a great extent, and simultaneously can greatly improve the design efficiency and shorten the design period aiming at a large number of design spaces with commonality.
Description
Technical Field
The invention relates to a method, a device, equipment and a storage medium for designing a customized home three-dimensional model scheme, and belongs to the field of customized home design.
Background
Under the background of consumer upgrading, along with the improvement of the life taste of people, more and more consumers put higher requirements on the overall effect and style matching of the home space; with the development of the customized home furnishing industry, in order to meet the demand, the customized home furnishing is not a single-finger customized furniture, but the customized home furnishing jumps out of the limitations of customized cabinet products such as wardrobes, cabinets and bookcases, and then the full-house customized home furnishing design of a whole set of house is developed to meet the increasing expectations of people on home furnishing level.
The core competitiveness of customized home furnishing lies in design, a consumer expects that the design is to be selected by matching a house type with actual size of the house with various customized decoration schemes of different styles, the design of the whole house customization needs to design each room (space) of a whole house type, each space needs to establish a three-dimensional model corresponding to the decoration style to manufacture VR display scenes or effect diagrams of various angles, the design work is heavy, great labor cost needs to be invested in scheme modification of the customized home furnishing enterprise in early negotiation and middle period with the consumer, and when a large amount of designer manpower is invested, newly-enrolled young designers have low design efficiency and design quality often cannot satisfy the consumer due to reasons of insufficient experience, product familiarity, unskilled design tools and the like in the design process of the early period and the middle period. Resulting in long design cycle and even loss of orders.
Generally, home design is common, the home design comprises a living room, a dining room, a kitchen, a toilet, a master bed, a child room, a study room and the like according to functional space division, a customized home enterprise accumulates massive excellent designs for the functional spaces, core design elements of the excellent designs are separated from scenes to manufacture a gallery (a called three-dimensional module) and put the gallery into a professional home design tool, however, due to the large number of the galleries, a designer cannot conveniently find a matching relational gallery in a calling process, and three-dimensional models in the gallery are different in size and structure to form a new space and are not comprehensively adaptive, so that higher requirements are provided for the designer.
Disclosure of Invention
In view of the above, the present invention provides a method, an apparatus, a device and a storage medium for designing a customized home three-dimensional model scheme, which can copy a set of core design elements of an excellent design into a new design scene through machine learning of the excellent design scheme of a senior designer, so as to ensure the design quality of the new design to a great extent, and meanwhile, for a large amount of design spaces with commonality, the artificial intelligence design can greatly improve the design efficiency and shorten the design period.
The invention aims to provide a design method for a customized household three-dimensional model scheme.
The second purpose of the invention is to provide a design device for a customized household three-dimensional model scheme.
It is a third object of the invention to provide a computer apparatus.
It is a fourth object of the present invention to provide a storage medium.
The first purpose of the invention can be achieved by adopting the following technical scheme:
a method for designing a customized household three-dimensional model scheme comprises the following steps:
according to the existing three-dimensional design scheme, a house type feature database, a house type design feature library and a furniture arrangement relation library are established in a machine learning mode;
acquiring a plan view of a space to be designed and a design requirement label;
according to the plan, extracting house type features, and splitting a design requirement list according to a design requirement label;
comparing the house type characteristics with a house type characteristic database to match a first design scheme;
comparing the matched first design scheme with a house type design feature library, and selecting a plurality of second design schemes meeting all requirements of a requirement list;
acquiring a third design scheme selected by a user from the plurality of second design schemes;
constructing a three-dimensional space according to the three-dimensional data of the plan;
extracting core design elements of the third design scheme;
and intelligently arranging the core design elements into a three-dimensional space according to the furniture arrangement relation library to obtain a three-dimensional design scene.
Further, the building of a house type feature database, a house type design feature database and a furniture arrangement relation database according to the existing three-dimensional design scheme in a machine learning manner specifically includes:
analyzing and machine learning the existing three-dimensional design scheme, and establishing a house type characteristic database, a house type design characteristic database and a furniture arrangement relation database.
Further, the three-dimensional design scheme comprises an effect graph, a panoramic graph and a three-dimensional model;
the method comprises the following steps of analyzing the existing three-dimensional design scheme and learning by a machine, and establishing a house type characteristic database, a house type design characteristic library and a furniture arrangement relation library, and specifically comprises the following steps:
analyzing the three-dimensional model to obtain a house type feature code of a design scheme, performing machine learning, and establishing a house type feature library;
analyzing the materials of the ceiling, the wall and the ground of the three-dimensional model and the color tones of the effect diagram to obtain the decoration style of the three-dimensional model, extracting the design style characteristics, performing machine learning, and establishing a house type design database;
analyzing the furniture in the three-dimensional model to obtain the model of each furniture, the dependency relationship and the relative placing position relationship of each furniture, and performing machine learning to establish a furniture arrangement relation library.
Further, the analyzing the three-dimensional model to obtain the house type feature code of the design scheme specifically includes:
and aiming at the three-dimensional model, encoding the house type outer contour into sixteen-dimensional characteristic vectors, and carrying out structural encoding on doors and windows according to the types, positions and sizes of the doors and windows.
Further, comparing the house type characteristics with the house type characteristic database to match a first design scheme specifically includes:
comparing the house type outer contour of the house type characteristic with the house type outer contour of the house type characteristic database to obtain a first matching value;
comparing the door and window of the house type characteristic with the door and window of the house type characteristic database to obtain a second matching value;
and taking the design scheme that the first matching value is greater than or equal to the first scalar value and the second matching value is greater than or equal to the second scalar value as the first design scheme.
Further, the extracting of the core design element of the third design scheme specifically includes:
and extracting the customized furniture product, the soft decoration, the space material and the space light of the third design scheme, and taking the customized furniture product, the soft decoration, the space material and the space light as core design elements.
Further, the intelligently arranging the core design elements into a three-dimensional space according to the furniture arrangement relation library to obtain a three-dimensional design scene specifically includes:
taking the space where the core design elements are located as a source space and taking the three-dimensional space as a target space;
establishing a transformation matrix by taking a wall, a door, a window and male and female corners as characteristic objects according to the relative coordinate relation of the source space and the target space;
and transferring the core design elements from the source space to the target space by combining the mutual placement relationship characteristics of the core design elements and the actual space size of the target space to obtain the three-dimensional design scene.
The second purpose of the invention can be achieved by adopting the following technical scheme:
a device for designing a customized household three-dimensional model scheme, comprising:
the building module is used for building a house type characteristic database, a house type design characteristic database and a furniture arrangement relation database according to the existing three-dimensional design scheme in a machine learning mode;
the first acquisition module is used for acquiring a plan view of a space to be designed and a design requirement label;
the first extraction module is used for extracting house type characteristics according to the plan and splitting a design requirement list according to the design requirement label;
the first comparison module is used for comparing the house type characteristics with the house type characteristic database to match a first design scheme;
the second comparison module is used for comparing the matched first design scheme with the house type design feature library and selecting a plurality of second design schemes meeting all requirements of the requirement list;
the second obtaining module is used for obtaining a third design scheme selected by a user from the plurality of second design schemes;
the construction module is used for constructing a three-dimensional space according to the three-dimensional data of the plan;
the second extraction module extracts core design elements of the third design scheme;
and the intelligent arrangement module is used for intelligently arranging the core design elements into a three-dimensional space according to the furniture arrangement relation library to obtain a three-dimensional design scene.
The third purpose of the invention can be achieved by adopting the following technical scheme:
the computer equipment comprises a processor and a memory for storing an executable program of the processor, wherein when the processor executes the program stored in the memory, the customized household three-dimensional model scheme design method is realized.
The fourth purpose of the invention can be achieved by adopting the following technical scheme:
a storage medium stores a program, and when the program is executed by a processor, the method for designing the customized home three-dimensional model scheme is realized.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, a large number of existing excellent three-dimensional design schemes are deeply learned through an artificial intelligence technology, and a scheme feature library is established; the space function classification with the space of waiting to design now, room type structure, room type size, multidimension degree characteristic such as user's demand is compared with scheme feature library, select optimum matching from massive existing outstanding design, and with the core design element complete set's intelligence arrange to waiting to design the space in having outstanding design, establish three-dimensional model scheme, the design quality of assurance new design that can to a great extent, simultaneously to a large amount of design spaces that have the commonality, artificial intelligence design can be very big improvement design efficiency, shorten design cycle.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
Fig. 1 is a flowchart of a customized home three-dimensional model scheme design method according to embodiment 1 of the present invention.
Fig. 2 is a flowchart of establishing a house type feature database, a house type design feature database, and a furniture arrangement relationship database according to embodiment 1 of the present invention.
Fig. 3 is a flowchart of comparing house type characteristics with a house type characteristic database according to embodiment 1 of the present invention.
Fig. 4 is a flowchart of intelligently arranging core design elements into a three-dimensional space according to embodiment 1 of the present invention.
Fig. 5 is a block diagram of a device for designing a customized home three-dimensional model scheme according to embodiment 2 of the present invention.
Fig. 6 is a block diagram of a computer device according to embodiment 3 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer and more complete, the technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments of the present invention, but not all embodiments, and all other embodiments obtained by a person of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the protection scope of the present invention.
Example 1:
at present, the idea, the originality, the life experience, the emotion control of an owner and the like of a senior designer cannot be replaced by artificial intelligence design, but through machine learning of an excellent design scheme of the senior designer, core design elements of the excellent design scheme can be copied into a new design scene in a set.
As shown in fig. 1, the embodiment provides a method for designing a customized home three-dimensional model scheme, which includes the following steps:
s101, establishing a house type characteristic database, a house type design characteristic database and a furniture arrangement relation database in a machine learning mode according to the existing three-dimensional design scheme.
Analyzing and machine learning the existing three-dimensional design scheme, and establishing a house type characteristic database, a house type design characteristic database and a furniture arrangement relation database; the existing three-dimensional design scheme is an excellent three-dimensional design scheme designed by a large number of senior designers, and comprises an effect picture, a panoramic picture and a three-dimensional model.
Further, as shown in fig. 2, the step S101 specifically includes:
and S1011, analyzing the three-dimensional model to obtain the house type feature code of the design scheme, and performing machine learning to establish a house type feature library.
Specifically, aiming at the three-dimensional model, the house type outer contour is coded into sixteen-dimensional characteristic vectors, and doors and windows are structurally coded according to the door and window type, the position and the size.
S1012, analyzing the materials of the ceiling, the wall and the ground of the three-dimensional model and the tone of the effect diagram to obtain the decoration style of the three-dimensional model, extracting the design style characteristics, performing machine learning, and establishing a house type design database.
S1013, analyzing the furniture in the three-dimensional model to obtain the model of each furniture, the dependency relationship and the relative placing position relationship of each furniture, performing machine learning, and establishing a furniture arrangement relation library;
s102, obtaining a plan view of a space to be designed and a design requirement label.
The plan view comprises three-dimensional data such as wall size, door and window size, position and type, building column and house beam position size, and the design requirement label can be manually input by a user.
S103, according to the plan, extracting house type features, and splitting a design requirement list according to the design requirement labels.
And S104, comparing the house type characteristics with the house type characteristic database to match a first design scheme.
Further, as shown in fig. 3, the step S104 specifically includes:
s1041, comparing the house type outer contour of the house type feature with the house type outer contour of the house type feature database to obtain a first matching value.
Specifically, sixteen-dimensional feature vectors of the house-type outer contour of the house-type feature are extracted, and the similarity comparison is performed between the sixteen-dimensional feature vectors of the house-type outer contour and the Euclidean distance of the sixteen-dimensional feature vectors of the house-type outer contour of the house-type feature database to obtain a first matching value.
S1042, comparing the doors and windows of the house type characteristic with the doors and windows of the house type characteristic database to obtain a second matching value.
Specifically, the door and window structured code of the house type characteristic and the door and window structured code of the house type characteristic database are compared in similarity, and a second matching value is obtained.
And S1043, taking the design scheme that the first matching value is greater than or equal to the first scalar value and the second matching value is greater than or equal to the second scalar value as a first design scheme (a plurality of design schemes).
And S105, comparing the matched first design scheme with the house type design feature library, and selecting a plurality of second design schemes meeting all requirements of the requirement list.
And S106, acquiring a third design scheme selected by the user from the plurality of second design schemes.
And the user manually selects the returned second design scheme to obtain a design scheme needing to establish the three-dimensional scene as a third design scheme (a plurality of design schemes).
And S107, constructing a three-dimensional space according to the three-dimensional data of the plan.
The plane graph is made by using the design of the user (civil drawing software which can be used online based on a browser), the plane graph comprises wall data, three-dimensional data of door and window types and positions, the data of the plane graph is read, and a three-dimensional space is directly constructed in three-dimensional virtual reality software (professional three-dimensional design software) according to the data read by the plane graph, namely a process picture of converting the plane graph into a three-dimensional model, wherein the three-dimensional space comprises a wall, a door and window, a building cylinder and the like.
And S108, extracting core design elements of the third design scheme.
Specifically, the customized furniture product, the soft decoration, the space material and the space light of the third design scheme are extracted, and the customized furniture product, the soft decoration, the space material and the space light are used as core design elements.
S109, intelligently arranging the core design elements into a three-dimensional space according to the furniture arrangement relation library to obtain a three-dimensional design scene.
Further, as shown in fig. 4, the step S109 specifically includes:
s1091, taking the space where the core design elements are located as a source space, and taking the three-dimensional space as a target space.
S1092, establishing a transformation matrix by taking the wall, the door and window and the male and female corners as characteristic objects according to the relative coordinate relation of the source space and the target space.
S1093, transferring the core design elements from the source space to the target space by combining the mutual placement relationship (dependency relationship and relative position relationship) characteristics of the core design elements and the actual size of the target space, and obtaining a three-dimensional design scene.
It should be noted that although the method operations of the above-described embodiments are depicted in the drawings in a particular order, this does not require or imply that these operations must be performed in this particular order, or that all of the illustrated operations must be performed, to achieve desirable results. Rather, the depicted steps may change the order of execution. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.
Example 2:
as shown in fig. 5, this embodiment provides a device for designing a customized home three-dimensional model scheme, where the device includes a building module 501, a first obtaining module 502, a first extracting module 503, a first comparing module 504, a second comparing module 505, a second obtaining module 506, a building module 507, a second extracting module 508, and an intelligent arrangement module 509, and specific functions of each module are as follows:
the establishing module 501 is configured to establish a house type feature database, a house type design feature database, and a furniture arrangement relationship database according to an existing three-dimensional design scheme in a machine learning manner.
The first obtaining module 502 is configured to obtain a plan view of a space to be designed and a design requirement label.
The first extracting module 503 is configured to extract house type features according to the plan view, and split the design requirement list according to the design requirement labels.
The first comparison module 504 is configured to compare the house type characteristics with the house type characteristic database to match a first design solution.
And a second comparison module 505, configured to compare the matched first design solution with the house type design feature library, and select a plurality of second design solutions meeting all requirements of the requirement list.
A second obtaining module 506, configured to obtain a third design solution selected by the user from the plurality of second design solutions.
And a constructing module 507, configured to construct a three-dimensional space according to the three-dimensional data of the plan.
The second extraction module 508 extracts core design elements of the third design solution.
And an intelligent arrangement module 509, configured to arrange the core design elements into a three-dimensional space intelligently according to the furniture arrangement relationship library, so as to obtain a three-dimensional design scene.
The specific implementation of each module in this embodiment may refer to embodiment 1, which is not described herein any more; it should be noted that the system provided in this embodiment is only illustrated by the division of the functional modules, and in practical applications, the functions may be distributed by different functional modules according to needs, that is, the internal structure is divided into different functional modules to complete all or part of the functions described above.
It will be understood that the terms "first," "second," and the like as used in the above-described apparatus may be used to describe various modules, but these modules are not limited by these terms. These terms are only used to distinguish one module from another. For example, a first acquisition module may be referred to as a second acquisition module, and similarly, a second acquisition module may be referred to as a first acquisition module, both the first and second acquisition modules being acquisition modules, but not the same acquisition module, without departing from the scope of the present invention.
Example 3:
as shown in fig. 6, the present embodiment provides a computer device, which includes a processor 602, a memory, an input device 603, a display device 604 and a network interface 605 connected by a system bus 601, where the processor is configured to provide computing and control capabilities, the memory includes a nonvolatile storage medium 606 and an internal memory 607, the nonvolatile storage medium 606 stores an operating system, a computer program and a database, the internal memory 607 provides an environment for the operating system and the computer program in the nonvolatile storage medium to run, and when the processor 602 executes the computer program stored in the memory, the customized home three-dimensional model scheme design method of embodiment 1 is implemented as follows:
according to the existing three-dimensional design scheme, a house type feature database, a house type design feature library and a furniture arrangement relation library are established in a machine learning mode;
acquiring a plan view of a space to be designed and a design requirement label;
according to the plan, extracting house type features, and splitting a design requirement list according to a design requirement label;
comparing the house type characteristics with a house type characteristic database to match a first design scheme;
comparing the matched first design scheme with a house type design feature library, and selecting a plurality of second design schemes meeting all requirements of a requirement list;
acquiring a third design scheme selected by a user from the plurality of second design schemes;
constructing a three-dimensional space according to the three-dimensional data of the plan;
extracting core design elements of the third design scheme;
and intelligently arranging the core design elements into a three-dimensional space according to the furniture arrangement relation library to obtain a three-dimensional design scene.
Further, the building of a house type feature database, a house type design feature database and a furniture arrangement relation database according to the existing three-dimensional design scheme in a machine learning manner specifically includes:
analyzing and machine learning the existing three-dimensional design scheme, and establishing a house type characteristic database, a house type design characteristic database and a furniture arrangement relation database.
Further, the three-dimensional design scheme comprises an effect graph, a panoramic graph and a three-dimensional model;
the method comprises the following steps of analyzing the existing three-dimensional design scheme and learning by a machine, and establishing a house type characteristic database, a house type design characteristic library and a furniture arrangement relation library, and specifically comprises the following steps:
analyzing the three-dimensional model to obtain a house type feature code of a design scheme, performing machine learning, and establishing a house type feature library;
analyzing the materials of the ceiling, the wall and the ground of the three-dimensional model and the color tones of the effect diagram to obtain the decoration style of the three-dimensional model, extracting the design style characteristics, performing machine learning, and establishing a house type design database;
analyzing the furniture in the three-dimensional model to obtain the model of each furniture, the dependency relationship and the relative placing position relationship of each furniture, and performing machine learning to establish a furniture arrangement relation library.
Further, the analyzing the three-dimensional model to obtain the house type feature code of the design scheme specifically includes:
and aiming at the three-dimensional model, encoding the house type outer contour into sixteen-dimensional characteristic vectors, and carrying out structural encoding on doors and windows according to the types, positions and sizes of the doors and windows.
Example 4:
the present embodiment provides a storage medium, which is a computer-readable storage medium, and stores a computer program, and when the computer program is executed by a processor, the method for designing a customized home three-dimensional model scheme according to embodiment 1 is implemented as follows:
according to the existing three-dimensional design scheme, a house type feature database, a house type design feature library and a furniture arrangement relation library are established in a machine learning mode;
acquiring a plan view of a space to be designed and a design requirement label;
according to the plan, extracting house type features, and splitting a design requirement list according to a design requirement label;
comparing the house type characteristics with a house type characteristic database to match a first design scheme;
comparing the matched first design scheme with a house type design feature library, and selecting a plurality of second design schemes meeting all requirements of a requirement list;
acquiring a third design scheme selected by a user from the plurality of second design schemes;
constructing a three-dimensional space according to the three-dimensional data of the plan;
extracting core design elements of the third design scheme;
and intelligently arranging the core design elements into a three-dimensional space according to the furniture arrangement relation library to obtain a three-dimensional design scene.
Further, the building of a house type feature database, a house type design feature database and a furniture arrangement relation database according to the existing three-dimensional design scheme in a machine learning manner specifically includes:
analyzing and machine learning the existing three-dimensional design scheme, and establishing a house type characteristic database, a house type design characteristic database and a furniture arrangement relation database.
Further, the three-dimensional design scheme comprises an effect graph, a panoramic graph and a three-dimensional model;
the method comprises the following steps of analyzing the existing three-dimensional design scheme and learning by a machine, and establishing a house type characteristic database, a house type design characteristic library and a furniture arrangement relation library, and specifically comprises the following steps:
analyzing the three-dimensional model to obtain a house type feature code of a design scheme, performing machine learning, and establishing a house type feature library;
analyzing the materials of the ceiling, the wall and the ground of the three-dimensional model and the color tones of the effect diagram to obtain the decoration style of the three-dimensional model, extracting the design style characteristics, performing machine learning, and establishing a house type design database;
analyzing the furniture in the three-dimensional model to obtain the model of each furniture, the dependency relationship and the relative placing position relationship of each furniture, and performing machine learning to establish a furniture arrangement relation library.
Further, the analyzing the three-dimensional model to obtain the house type feature code of the design scheme specifically includes:
and aiming at the three-dimensional model, encoding the house type outer contour into sixteen-dimensional characteristic vectors, and carrying out structural encoding on doors and windows according to the types, positions and sizes of the doors and windows.
It should be noted that the computer readable storage medium of the present embodiment may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
In the present embodiment, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this embodiment, however, a computer readable signal medium may include a propagated data signal with a computer readable program embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable storage medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program embodied on the computer readable storage medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer-readable storage medium may be written with a computer program for performing the present embodiments in one or more programming languages, including an object oriented programming language such as Java, Python, C + +, and conventional procedural programming languages, such as C, or similar programming languages, or combinations thereof. The program may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
In conclusion, the method carries out deep learning on mass existing excellent three-dimensional design schemes through an artificial intelligence technology and establishes a scheme feature library; the space function classification with the space of waiting to design now, room type structure, room type size, multidimension degree characteristic such as user's demand is compared with scheme feature library, select optimum matching from massive existing outstanding design, and with the core design element complete set's intelligence arrange to waiting to design the space in having outstanding design, establish three-dimensional model scheme, the design quality of assurance new design that can to a great extent, simultaneously to a large amount of design spaces that have the commonality, artificial intelligence design can be very big improvement design efficiency, shorten design cycle.
The above description is only for the preferred embodiments of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art can substitute or change the technical solution and the inventive concept of the present invention within the scope of the present invention.
Claims (10)
1. A method for designing a customized household three-dimensional model scheme is characterized by comprising the following steps:
according to the existing three-dimensional design scheme, a house type feature database, a house type design feature library and a furniture arrangement relation library are established in a machine learning mode;
acquiring a plan view of a space to be designed and a design requirement label;
according to the plan, extracting house type features, and splitting a design requirement list according to a design requirement label;
comparing the house type characteristics with a house type characteristic database to match a first design scheme;
comparing the matched first design scheme with a house type design feature library, and selecting a plurality of second design schemes meeting all requirements of a requirement list;
acquiring a third design scheme selected by a user from the plurality of second design schemes;
constructing a three-dimensional space according to the three-dimensional data of the plan;
extracting core design elements of the third design scheme;
and intelligently arranging the core design elements into a three-dimensional space according to the furniture arrangement relation library to obtain a three-dimensional design scene.
2. The method for designing the customized home three-dimensional model scheme according to claim 1, wherein the building of a house type feature database, a house type design feature library and a furniture arrangement relation library according to the existing three-dimensional design scheme in a machine learning manner specifically comprises:
analyzing and machine learning the existing three-dimensional design scheme, and establishing a house type characteristic database, a house type design characteristic database and a furniture arrangement relation database.
3. The method for designing the customized household three-dimensional model scheme according to claim 2, wherein the three-dimensional design scheme comprises an effect graph, a panoramic graph and a three-dimensional model;
the method comprises the following steps of analyzing the existing three-dimensional design scheme and learning by a machine, and establishing a house type characteristic database, a house type design characteristic library and a furniture arrangement relation library, and specifically comprises the following steps:
analyzing the three-dimensional model to obtain a house type feature code of a design scheme, performing machine learning, and establishing a house type feature library;
analyzing the materials of the ceiling, the wall and the ground of the three-dimensional model and the color tones of the effect diagram to obtain the decoration style of the three-dimensional model, extracting the design style characteristics, performing machine learning, and establishing a house type design database;
analyzing the furniture in the three-dimensional model to obtain the model of each furniture, the dependency relationship and the relative placing position relationship of each furniture, and performing machine learning to establish a furniture arrangement relation library.
4. The method for designing the customized household three-dimensional model scheme according to claim 3, wherein the analyzing the three-dimensional model to obtain the house type feature code of the design scheme specifically comprises:
and aiming at the three-dimensional model, encoding the house type outer contour into sixteen-dimensional characteristic vectors, and carrying out structural encoding on doors and windows according to the types, positions and sizes of the doors and windows.
5. The method for designing the customized home three-dimensional model scheme according to any one of claims 1 to 4, wherein the comparing the house type characteristics with the house type characteristic database to match the first design scheme specifically comprises:
comparing the house type outer contour of the house type characteristic with the house type outer contour of the house type characteristic database to obtain a first matching value;
comparing the door and window of the house type characteristic with the door and window of the house type characteristic database to obtain a second matching value;
and taking the design scheme that the first matching value is greater than or equal to the first scalar value and the second matching value is greater than or equal to the second scalar value as the first design scheme.
6. The method for designing the customized home three-dimensional model scheme according to any one of claims 1 to 4, wherein the extracting of the core design elements of the third design scheme specifically comprises:
and extracting the customized furniture product, the soft decoration, the space material and the space light of the third design scheme, and taking the customized furniture product, the soft decoration, the space material and the space light as core design elements.
7. The method for designing the customized home three-dimensional model scheme according to any one of claims 1 to 4, wherein the core design elements are intelligently arranged in a three-dimensional space according to a furniture arrangement relation library to obtain a three-dimensional design scene, and the method specifically comprises the following steps:
taking the space where the core design elements are located as a source space and taking the three-dimensional space as a target space;
establishing a transformation matrix by taking a wall, a door, a window and male and female corners as characteristic objects according to the relative coordinate relation of the source space and the target space;
and transferring the core design elements from the source space to the target space by combining the mutual placement relationship characteristics of the core design elements and the actual space size of the target space to obtain the three-dimensional design scene.
8. A device for designing a customized household three-dimensional model scheme is characterized by comprising:
the building module is used for building a house type characteristic database, a house type design characteristic database and a furniture arrangement relation database according to the existing three-dimensional design scheme in a machine learning mode;
the first acquisition module is used for acquiring a plan view of a space to be designed and a design requirement label;
the first extraction module is used for extracting house type characteristics according to the plan and splitting a design requirement list according to the design requirement label;
the first comparison module is used for comparing the house type characteristics with the house type characteristic database to match a first design scheme;
the second comparison module is used for comparing the matched first design scheme with the house type design feature library and selecting a plurality of second design schemes meeting all requirements of the requirement list;
the second obtaining module is used for obtaining a third design scheme selected by a user from the plurality of second design schemes;
the construction module is used for constructing a three-dimensional space according to the three-dimensional data of the plan;
the second extraction module extracts core design elements of the third design scheme;
and the intelligent arrangement module is used for intelligently arranging the core design elements into a three-dimensional space according to the furniture arrangement relation library to obtain a three-dimensional design scene.
9. A computer device comprising a processor and a memory for storing a program executable by the processor, wherein the processor implements the method for designing a customized home three-dimensional model according to any one of claims 1-7 when executing the program stored in the memory.
10. A storage medium storing a program, wherein the program, when executed by a processor, implements the customized home three-dimensional model scenario designing method of any one of claims 1-7.
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