Construction method of package design three-dimensional model

Abstract

The invention relates to the technical field of package design data three-dimensional processing, in particular to a construction method of a package design three-dimensional model. The method comprises the following steps: acquiring a package design data set; performing data preprocessing on the package design data set to obtain a package design standard data set; contour feature extraction is carried out on the package design standard data set to obtain package contour features; performing design component identification on the package contour features to generate design component data; performing size parameter quantization on the design component data to obtain component size parameters; and carrying out packaging surface structure feature mapping on the packaging contour features based on the component size parameters to obtain packaging surface structure features. A data processing technology, a mode recognition technology and a machine learning technology are adopted; geometric constraint analysis is carried out on the geometric structure of the package design, and the topological relation of the package structure is determined according to the geometric constraint, so that the package design three-dimensional model presents a complete visual effect.

Description

Technical Field

[0001] The present invention relates to the technical field of three-dimensional processing of packaging design data, and in particular to a method for constructing a three-dimensional model of packaging design. Background Art

[0002] Three-dimensional construction technology is a technology that converts virtual three-dimensional models into real objects or scenes based on the mathematical principles and algorithms of computer graphics. It specifically includes three elements: model, texture and lighting. Model refers to the basic shape and surface structure of an object, texture refers to the color and pattern on the surface of an object, and lighting refers to the reflection, refraction and scattering of an object in different scenes. With the development of computer graphics and image processing technology and virtual three-dimensional model technology, packaging design has changed from pure manual drawing to computer-aided design. Three-dimensional visualization technology allows designers to perform three-dimensional design in a virtual three-dimensional space, so that the visual communication, morphological structure, overall effect and engineering design of packaging are supported by computer-aided design software. However, the existing method of constructing three-dimensional models of packaging design makes it difficult to perform geometric constraint analysis on the geometric structure of packaging design, and fails to determine the topological relationship of the packaging structure based on the packaging geometric constraints, which makes it difficult for the constructed three-dimensional model to accurately present the visual effect of packaging design. Summary of the invention

[0003] Based on this, it is necessary to provide a method for constructing a three-dimensional model of packaging design to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for constructing a three-dimensional model of packaging design is provided, the method comprising the following steps:

[0005] Step S1: obtaining a packaging design data set; performing data preprocessing on the packaging design data set to obtain a packaging design standard data set; performing contour feature extraction on the packaging design standard data set to obtain packaging contour features;

[0006] Step S2: performing design component recognition on the package contour features to generate design component data; performing size parameter quantification on the design component data to obtain component size parameters; performing package surface structure feature mapping on the package contour features based on the component size parameters to obtain package surface structure features;

[0007] Step S3: Perform structural geometric constraint detection on the packaging surface structural features to obtain structural geometric constraints; determine the structural topological relationship of the packaging surface structural features according to the structural geometric constraints to generate a structural topological relationship; perform polygonal surface modeling based on the packaging surface structural features, structural geometric constraints and structural topological relationship to obtain a preliminary packaging surface model;

[0008] Step S4: Perform three-dimensional visual enhancement on the preliminary packaging surface model to obtain a packaging design three-dimensional model; perform three-dimensional packaging appearance evaluation based on the packaging design three-dimensional model to obtain a packaging appearance evaluation report.

[0009] The present invention can obtain a standardized packaging design data set by acquiring a packaging design data set and performing data preprocessing, which provides a high-quality data basis for subsequent feature extraction; extracting contour features from the packaging design standard data set is the key to subsequent design component identification and dimensional parameter quantification, ensuring that the data basis of the packaging design three-dimensional model construction method has high accuracy and reliability. Design component identification of packaging contour features provides a basis for subsequent dimensional parameter quantification; dimensional parameter quantification of design component data enables packaging design to have accurate dimensional information, ensuring accurate mapping of packaging surface structural features; mapping packaging surface structural features of packaging contour features based on component dimensional parameters provides detailed structural information for subsequent structural geometric constraint detection and structural topological relationship determination. Structural geometric constraint detection of packaging surface structural features provides necessary geometric restrictions for packaging design and ensures the feasibility of the design; structural topological relationships of packaging surface structural features are determined based on structural geometric constraints, providing a logical framework for polygonal surface modeling; polygonal surface modeling based on packaging surface structural features, structural geometric constraints and structural topological relationships provides an accurate geometric basis for subsequent three-dimensional visual enhancement and appearance evaluation. The preliminary packaging surface model is subjected to three-dimensional visual enhancement, and the obtained three-dimensional model of the packaging design has a more realistic visual effect, which can more intuitively show the final appearance of the packaging design; the three-dimensional appearance of the packaging is evaluated based on the three-dimensional model of the packaging design, and the obtained packaging appearance evaluation report shows the three-dimensional appearance of the packaging design; and provides a scientific basis for the subsequent optimization of the packaging design. Therefore, the present invention uses data processing technology, pattern recognition technology and machine learning technology to realize geometric constraint analysis of the geometric structure of the packaging design, and determines the topological relationship of the packaging structure according to the geometric constraints, so that the three-dimensional model of the packaging design presents a complete visual effect.

[0010] Preferably, step S1 comprises the following steps:

[0011] Step S11: Acquire a packaging design data set;

[0012] Step S12: screening the packaging design data set for outliers to obtain packaging design outliers; performing data cleaning on the packaging design data set according to the packaging design outliers to generate a design cleaning data set;

[0013] Step S13: unifying the format of the design cleansing data set to obtain a unified format data set; standardizing the design parameters of the unified format data set to obtain a packaging design standard data set;

[0014] Step S14: marking the packaging edge attributes of the packaging design standard data set to obtain edge attribute marking values; performing marking value statistics on the edge attribute marking values ​​to generate edge attribute statistical data;

[0015] Step S15: performing edge contour attribute matching on the edge attribute statistical data to obtain edge contour attribute data; performing contour feature extraction on the packaging design standard data set according to the edge contour attribute data to obtain packaging contour features.

[0016] The present invention obtains a packaging design data set to ensure that the data source for subsequent processing is comprehensive and original, and provides a basis for subsequent outlier screening and data cleaning; performs outlier screening on the packaging design data set and obtains packaging design outliers, effectively identifying and marking abnormal data points in the data set; performs data cleaning on the packaging design data set based on these outliers, timely removes inaccurate data, and improves the quality and reliability of the data set; unifies the format of the design cleaned data set to ensure data consistency and compatibility; standardizes design parameters on the format-unified data set to provide a standardized data environment for subsequent feature extraction and attribute labeling, thereby improving the accuracy of feature extraction and the consistency of attribute labeling; The edge attributes of the packaging are marked on the standard data set to provide a data basis for subsequent statistical analysis; the edge attribute marking values ​​are counted to provide necessary statistical information for edge contour attribute matching; through detailed analysis of edge attributes, the edge attribute data is clarified and the accuracy of contour feature extraction is improved; the edge attribute statistical data is matched with edge contour attributes to provide detailed attribute guidance for contour feature extraction of the packaging design standard data set; contour features of the packaging design standard data set are extracted based on the edge contour attribute data, which provides key geometric information for constructing a three-dimensional model of packaging design, ensuring that the geometric features of the three-dimensional model closely correspond to the edge attributes of the actual packaging design, thereby improving the authenticity and practicality of the model.

[0017] Preferably, step S2 comprises the following steps:

[0018] Step S21: performing contour detail enhancement on the package contour feature to obtain contour feature enhancement data; performing contour morphology recognition on the contour feature enhancement data to generate contour morphology data;

[0019] Step S22: classifying the contour morphology data into morphology types to obtain contour morphology types; identifying design components of the packaging contour features according to the contour morphology types to generate design component data;

[0020] Step S23: measuring the geometric dimensions of the design component data to obtain geometric dimension values; calculating the component rectangularity using the geometric dimension values ​​to generate the component rectangularity value;

[0021] Step S24: quantifying component parameters of the design component data based on the component rectangularity value to obtain component size parameters;

[0022] Step S25: mapping the package contour features to package surface structure features based on the component size parameters to obtain package surface structure features.

[0023] The present invention performs contour detail enhancement on the contour feature of the package, so that the subtle features of the contour are more obvious and clear, and the recognition accuracy of the contour feature is improved; contour morphology recognition is performed on the contour feature enhancement data, and accurate morphological feature information is provided for subsequent morphological type classification and design component recognition; morphological type classification is performed on the contour morphological data, and a clear basis is provided for the classification of the design component; design component recognition is performed on the package contour feature according to the contour morphological type, and the classification accuracy of the design component data is ensured; geometric dimension measurement is performed on the design component data, and necessary dimension information is provided for the accurate modeling of the component; component rectangularity calculation is performed on the geometric dimension value, and the shape feature of the component is quantified, and the actual shape and size of the component are accurately reconstructed in the three-dimensional model; component parameter quantification is performed on the design component data based on the component rectangularity value, and it is ensured that in the process of building the three-dimensional model, the size of each component can accurately correspond to the actual design; packaging surface structure feature mapping is performed on the package contour feature based on the component size parameter, and detailed structure information is provided for the surface details of the three-dimensional model; so that the three-dimensional model can accurately reflect the surface structure features of the packaging design, including texture, pattern and shape.

[0024] Preferably, step S25 comprises the following steps:

[0025] Step S251: sorting the parameter values ​​of the component size parameters to obtain parameter value sorting data; determining the size parameter range of the parameter value sorting data to generate size parameter range data; classifying the design component data into component types according to the size parameter range data to obtain the design component type;

[0026] Step S252: locating component contour points of the package contour features by design component type to generate design component contour points; identifying component contour line segments of the package contour features based on the design component contour points to obtain design component contour line segments;

[0027] Step S253: determining the packaging geometric structure according to the design component contour points and the design component contour line segments to obtain the packaging design geometric structure; assigning geometric structure parameters to the packaging design geometric structure according to the component size parameters to generate geometric structure assignment data;

[0028] Step S254: matching the geometric structure assignment data with the design surface features to obtain the design surface matching features; mapping the design surface matching features to the packaging surface structure features to obtain the packaging surface structure features.

[0029] The present invention sorts the parameter values ​​of component size parameters so that the size parameters are arranged in a certain order for easy identification and comparison; determines the size parameter range of the parameter value sorting data, providing a clear boundary for the classification of design component data; classifies the design component data into component types according to the size parameter range data, ensuring the systematic management of components and accurate type identification; locates the component contour points of the package contour features by the design component type, providing accurate positioning information for subsequent contour line segment identification; identifies the component contour line segments of the package contour features based on the design component contour points, ensuring accurate identification of the contour points and line segments of the components in the three-dimensional model of the package design; and locates the component contour points and the design component according to the design component contour points and the design component type. The packaging geometry is determined by the contour segments of the components, providing an accurate geometric framework for the 3D model; the geometric structure parameters of the packaging design geometry are assigned by the component size parameters, providing specific size information for the geometric structure, ensuring that the geometric structure in the 3D model of the packaging design meets the design requirements and has accurate size parameters; the geometric structure assignment data is matched with the design surface features, providing the necessary surface feature information for the packaging surface structure feature mapping; the packaging surface structure feature mapping is performed on the design surface matching features, ensuring that the surface features of the 3D model of the packaging design completely correspond to the actual design, achieving a high degree of restoration and accurate presentation of the original design, thereby improving the authenticity and reliability of the model.

[0030] Preferably, step S3 comprises the following steps:

[0031] Step S31: performing spatial structural analysis on the packaging surface structural features to obtain packaging spatial structural data; performing structural geometric constraint detection on the packaging spatial structural data to obtain structural geometric constraints;

[0032] Step S32: determining the structural topological relationship of the packaging surface structural features according to the structural geometric constraints to generate the structural topological relationship;

[0033] Step S33: construct a polygonal geometric framework based on the packaging surface structural features and structural geometric constraints to obtain a polygonal geometric framework; perform surface modeling on the polygonal geometric framework based on the structural topological relationship to obtain a preliminary packaging surface model.

[0034] The present invention performs spatial structural analysis on the surface structural features of packaging to ensure that the construction of the three-dimensional model of packaging design is based on accurate spatial information; performs structural geometric constraint detection on the spatial structural data of packaging to ensure that in the subsequent modeling process, all geometric structures comply with actual manufacturing and physical limitations, thereby ensuring the practicality and feasibility of the three-dimensional model of packaging design; determines the structural topological relationship of the surface structural features of packaging according to the structural geometric constraints, and provides a logical connection and hierarchical relationship for the three-dimensional model of packaging design, so that the three-dimensional model of packaging design is not only geometrically accurate, but also structurally logical and coherent; constructs a polygonal geometric framework based on the surface structural features of packaging and the structural geometric constraints, ensuring that the geometric structure of the model closely corresponds to the design features; performs surface modeling on the polygonal geometric framework based on the structural topological relationship, accurately reflects the surface features and structural relationships of the packaging design, and then completes the transformation from two-dimensional features to three-dimensional models, ensuring that the construction method of the three-dimensional model of packaging design can produce high-quality results.

[0035] Preferably, step S31 includes the following steps:

[0036] Step S311: Perform geometric structural feature fractal on the packaging surface structural features to obtain packaging structural fractal features; perform spatial structural layout recognition on the packaging structural fractal features to generate a spatial structural layout; perform spatial structural attribute detection on the spatial structural layout to obtain packaging spatial structural data;

[0037] Step S312: determining the symmetry of the packaging space structure data to obtain a structural symmetry constraint; performing a curvature continuity test on the packaging surface structure features according to the structural symmetry constraint to obtain a curvature continuity constraint;

[0038] Step S313: performing edge curvature comparison on the package space structure data based on the curvature continuity constraint to obtain the structure edge curvature value; performing surface structure flatness detection on the package surface structure features according to the structure edge curvature value to obtain the structure flatness constraint;

[0039] Step S314: Integrate the structural symmetry constraint, the curvature continuity constraint and the structural flatness constraint to generate the structural geometric constraint.

[0040] The present invention performs geometric structural feature fractal on the structural features of the packaging surface, so as to identify the spatial structural layout of the fractal features of the packaging structure, providing a clear framework for understanding the spatial configuration of the packaging design; performs spatial structural attribute detection on the spatial structural layout, providing basic data for subsequent symmetry determination, curvature continuity test and flatness test; performs symmetry determination on the packaging spatial structural data, providing clear guidance for the symmetry properties of the packaging design; performs curvature continuity test on the packaging surface structural features according to the structural symmetry constraint, ensuring that the curved surface of the packaging design is geometrically smooth and continuous; performs curvature continuity test on the packaging spatial structural data based on the curvature continuity constraint, Edge curvature comparison provides accurate data for evaluating the curvature change of the edge of the packaging design; the surface structural flatness detection is performed on the packaging surface structural features according to the structural edge curvature value to ensure that there are no obvious bumps on the packaging design surface, providing a standard and improving the practicality of the packaging design; the integration of structural symmetry constraints, curvature continuity constraints and structural flatness constraints provides comprehensive geometric restrictions for the construction of the three-dimensional model of the packaging design, ensuring that during the modeling process, all geometric structures meet the design symmetry, curvature continuity and flatness requirements, so that the generated three-dimensional model is geometrically accurate and reasonable, ensuring that the geometric structure of the model closely corresponds to the actual design.

[0041] Preferably, step S32 includes the following steps:

[0042] Step S321: determining the position of the symmetry axis of the packaging surface structural feature according to the structural symmetry constraint to obtain the symmetry axis position information; judging the symmetry constraint degree of the structural symmetry constraint based on the symmetry axis position information to generate the symmetry constraint degree;

[0043] Step S322: performing curvature gradient division on the packaging surface structural features according to the curvature continuity constraint to obtain a structural curvature gradient value; performing structural position curvature gradient mapping on the packaging surface structural features based on the structural curvature gradient value to generate a structural position curvature gradient;

[0044] Step S323: performing surface structural defect feature recognition on the packaging surface structural features according to the structural flatness constraint to obtain the surface structural defect features; performing trapping degree evaluation on the surface structural defect features to generate the surface structural trapping degree;

[0045] Step S324: performing symmetry topological determination on the degree of symmetry constraint to obtain a symmetry topological relationship; performing curvature continuity topological determination based on the curvature gradient of the structural position to obtain a curvature continuity topological relationship; performing defect tension topological determination based on the degree of surface structure trapping to obtain a defect tension topological relationship;

[0046] Step S325: merging the symmetry topological relationship, the curvature continuity topological relationship and the defect tension topological relationship into a structural topological relationship to generate a structural topological relationship.

[0047] The present invention determines the position of the symmetry axis of the packaging surface structural features according to the structural symmetry constraints, providing an accurate reference point for the symmetry analysis of the packaging design; judges the degree of symmetry constraints based on the symmetry axis position information of the structural symmetry constraints, ensuring the accuracy and consistency of the symmetry of the three-dimensional model of the packaging design, thereby improving the geometric structural stability of the model; divides the packaging surface structural features into curvature gradients according to the curvature continuity constraints, providing detailed curvature information for the surface changes of the packaging design; maps the structural position curvature gradient of the packaging surface structural features based on the structural curvature gradient value, ensuring that the surface of the three-dimensional model of the packaging design is geometrically continuous and smooth, thereby improving the visual coherence and structural integrity of the model; identifies the surface structural defect features of the packaging surface structural features according to the structural flatness constraints, and evaluates the degree of trapping of the surface structural defect features, providing a basis for evaluating the surface quality of the packaging design. It provides quantitative data to ensure the accuracy and reliability of the surface flatness of the three-dimensional model of packaging design; the degree of symmetry constraint is determined by symmetry topology, and the curvature continuity is determined by topology according to the curvature gradient of the structural position, providing a topological description for the surface continuity of the packaging design; the defect tension is determined by topology based on the degree of surface structural defects, providing a topological description for the surface defects of the packaging design; these topological relationships provide a structural logical framework for the construction of the three-dimensional model of packaging design, ensuring the accuracy and completeness of the model in topological structure; the symmetry topological relationship, curvature continuity topological relationship and defect tension topological relationship are merged into structural topological relationships to ensure the consistency and completeness of the three-dimensional model of packaging design in structural topology; through this comprehensive topological relationship, the three-dimensional model of packaging design can accurately reflect all key geometric and topological features of the design, improving the accuracy and practicality of the model.

[0048] Preferably, step S33 includes the following steps:

[0049] Step S331: performing structural parameterization on the packaging surface structural features to obtain parameterized structural representation data; applying geometric constraints to the parameterized structural representation data according to structural geometric constraints to generate constraint structural information;

[0050] Step S332: Packing the constraint structure information into polygonal meshes to obtain polygonal mesh data; aligning the edges of the polygonal mesh data based on the structural geometric constraints to generate polygonal edge forms; constructing a polygonal geometric framework for the polygonal edge forms to obtain a polygonal geometric framework;

[0051] Step S333: performing topological relationship mapping on the polygonal geometric framework based on the structural topological relationship to obtain framework topological structure data; performing surface fitting on the framework topological structure data to obtain a polygonal surface fitting form;

[0052] Step S334: Optimize the surface smoothing features of the polygonal surface fitting form to generate a surface feature optimized form; perform surface modeling on the surface feature optimized form to obtain a preliminary packaging surface model.

[0053] The present invention performs structural parameterized representation of the surface structural features of the packaging, and applies geometric constraints to the parameterized structural representation data according to the structural geometric constraints, ensuring that the geometric structure of the packaging design conforms to the actual physical and design limitations, thereby providing precise geometric parameters for subsequent meshing and geometric framework construction, and ensuring the geometric accuracy and reliability of the three-dimensional model of the packaging design; performing packaging polygonal meshing of the constrained structural information, providing a basic mesh structure for subsequent geometric modeling; and aligning the edges of the polygonal mesh data based on the structural geometric constraints, ensuring the precise correspondence between the mesh edges and the design features. The polygonal edge morphology is used to construct a polygonal geometric framework, which provides an accurate geometric foundation for the three-dimensional model of packaging design and ensures the consistency between the geometric structure of the model and the design intent; the topological relationship of the polygonal geometric framework is mapped based on the structural topological relationship, which provides a detailed description of the topological structure of the packaging design; the framework topological structure data is fitted with a surface to provide a preliminary shape for the surface construction of the three-dimensional model of packaging design, ensuring the correspondence between the topological structure of the model and the design features, and providing a basis for subsequent surface smoothing and optimization; the surface smoothing feature optimization of the polygonal surface fitting morphology improves the surface quality of the three-dimensional model of packaging design and eliminates the errors and discontinuities generated in the fitting process; the surface feature optimization morphology is used for surface modeling to accurately reflect all the geometric and topological features of the packaging design; and the transformation from polygonal mesh to smooth surface is completed, providing a high-quality basic model for subsequent model refinement and evaluation.

[0054] Preferably, step S4 comprises the following steps:

[0055] Step S41: performing color high-contrast rendering on the preliminary packaging surface model to generate model high-contrast rendering data; performing rendering level refinement on the model high-contrast rendering data to obtain model rendering level data;

[0056] Step S42: performing hierarchical stereoscopic shadow rendering on the preliminary packaging surface model according to the model rendering hierarchical data to obtain model stereoscopic shadow rendering data; performing model perspective correction on the model stereoscopic shadow rendering data to generate model perspective correction data;

[0057] Step S43: performing model texture mapping on the preliminary packaging surface model based on the model perspective correction data to obtain model texture mapping data; performing three-dimensional visualization view enhancement on the preliminary packaging surface model according to the model texture mapping data to obtain a packaging design three-dimensional model;

[0058] Step S44: outputting three-dimensional appearance information based on the packaging design three-dimensional model to obtain packaging three-dimensional appearance data; and performing packaging three-dimensional appearance evaluation on the packaging three-dimensional appearance data to obtain a packaging appearance evaluation report.

[0059] The present invention performs color high-contrast rendering on the preliminary packaging surface model, thereby enhancing the visual recognition and detail expression of the model; performs rendering level refinement on the model high-contrast rendering data, thereby providing the model with a richer visual level, making the packaging design three-dimensional model closer to the actual product in terms of color and level, and improving the realism and visual effect of the model; performs hierarchical stereoscopic shadow rendering on the preliminary packaging surface model according to the model rendering level data, thereby increasing the stereoscopic sense and depth, and making the light and shadow effect of the model more realistic; performs model perspective correction on the model stereoscopic shadow rendering data, thereby ensuring that the perspective relationship of the model remains correct when the model is observed from different viewing angles, thereby improving the visual accuracy of the model, and ensuring the consistency and authenticity when the model is observed from various angles; performs model texture mapping on the preliminary packaging surface model based on the model perspective correction data, thereby enhancing the texture and visual effect of the model; performs three-dimensional visualization view enhancement on the preliminary packaging surface model according to the model texture mapping data, thereby making the display effect of the model closer to the texture and appearance of the actual product; outputs three-dimensional appearance information based on the packaging design three-dimensional model, and performs packaging three-dimensional appearance evaluation on the packaging three-dimensional appearance data, thereby being able to comprehensively display the appearance effect of the design.

[0060] Preferably, step S44 includes the following steps:

[0061] Step S441: outputting three-dimensional appearance information based on the packaging design three-dimensional model to obtain packaging three-dimensional appearance data;

[0062] Step S442: performing surface concave detection on the three-dimensional appearance data of the package to obtain concave features on the package surface; performing surface convex detection on the three-dimensional appearance data of the package to obtain convex features on the package surface;

[0063] Step S443: quantifying the packaging surface defect attributes based on the packaging surface concave features and the packaging surface convex features to obtain the packaging surface defect attributes; performing packaging appearance integrity recognition on the packaging surface defect attributes to generate packaging appearance integrity data;

[0064] Step S444: classifying the packaging appearance integrity data according to the degree of packaging design appearance defects to obtain a packaging appearance classification; and evaluating the three-dimensional appearance integrity of the packaging on the packaging appearance classification to obtain a packaging appearance evaluation report.

[0065] The present invention outputs three-dimensional appearance information based on the three-dimensional model of the packaging design, providing detailed visual information for the surface features of the packaging design; ensuring that the appearance data extracted from the three-dimensional model can fully reflect the actual appearance of the packaging design, providing an accurate data basis for subsequent surface defect detection and integrity evaluation; performing surface depression detection on the three-dimensional appearance data of the packaging, providing a clear standard for identifying the depressed areas in the packaging design; performing surface convexity detection on the three-dimensional appearance data of the packaging, providing a clear standard for identifying the convex areas in the packaging design; performing detailed detection of the surface features of the packaging design, providing necessary feature data for subsequent defect attribute quantification and integrity identification; based on the concave features and convex features of the packaging surface The packaging surface defect attributes are quantified based on the characteristics, providing quantitative data for evaluating the surface quality of the packaging design; the packaging appearance integrity is identified based on the packaging surface defect attributes, providing a basis for judging the integrity of the packaging design and ensuring that surface defects in the packaging design can be accurately identified and quantified; the packaging appearance integrity data is divided into the degree of packaging design appearance defects, providing a clear classification for the degree of defects in the packaging design; the three-dimensional appearance integrity of the packaging is evaluated based on the packaging appearance classification, providing a detailed report for the final quality evaluation of the packaging design, ensuring that the packaging design can be classified according to the degree of defects, and providing a comprehensive evaluation of the appearance quality of the packaging design, thereby providing an important reference for design improvement and quality control. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 A schematic diagram of the steps of a method for constructing a three-dimensional model of a packaging design;

[0067] Figure 2 for Figure 1 Detailed implementation steps of step S4 in FIG.

[0068] Figure 3 for Figure 2 Detailed implementation steps of step S44 are shown in the flowchart;

[0069] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0070] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0071] In addition, the drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the drawings are functional entities, which do not necessarily correspond to physically or logically independent entities; the functional entities are implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different network and / or processor methods and / or microcontroller methods.

[0072] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0073] To achieve this, please refer to Figures 1 to 3 A method for constructing a three-dimensional model of packaging design, the method comprising the following steps:

[0074] Step S1: obtaining a packaging design data set; performing data preprocessing on the packaging design data set to obtain a packaging design standard data set; performing contour feature extraction on the packaging design standard data set to obtain packaging contour features;

[0075] Step S2: performing design component recognition on the package contour features to generate design component data; performing size parameter quantification on the design component data to obtain component size parameters; performing package surface structure feature mapping on the package contour features based on the component size parameters to obtain package surface structure features;

[0076] Step S3: Perform structural geometric constraint detection on the packaging surface structural features to obtain structural geometric constraints; determine the structural topological relationship of the packaging surface structural features according to the structural geometric constraints to generate a structural topological relationship; perform polygonal surface modeling based on the packaging surface structural features, structural geometric constraints and structural topological relationship to obtain a preliminary packaging surface model;

[0077] Step S4: Perform three-dimensional visual enhancement on the preliminary packaging surface model to obtain a packaging design three-dimensional model; perform three-dimensional packaging appearance evaluation based on the packaging design three-dimensional model to obtain a packaging appearance evaluation report.

[0078] The present invention can obtain a standardized packaging design data set by acquiring a packaging design data set and performing data preprocessing, which provides a high-quality data basis for subsequent feature extraction; extracting contour features from the packaging design standard data set is the key to subsequent design component identification and dimensional parameter quantification, ensuring that the data basis of the packaging design three-dimensional model construction method has high accuracy and reliability. Design component identification of packaging contour features provides a basis for subsequent dimensional parameter quantification; dimensional parameter quantification of design component data enables packaging design to have accurate dimensional information, ensuring accurate mapping of packaging surface structural features; mapping packaging surface structural features of packaging contour features based on component dimensional parameters provides detailed structural information for subsequent structural geometric constraint detection and structural topological relationship determination. Structural geometric constraint detection of packaging surface structural features provides necessary geometric restrictions for packaging design and ensures the feasibility of the design; structural topological relationships of packaging surface structural features are determined based on structural geometric constraints, providing a logical framework for polygonal surface modeling; polygonal surface modeling based on packaging surface structural features, structural geometric constraints and structural topological relationships provides an accurate geometric basis for subsequent three-dimensional visual enhancement and appearance evaluation. The preliminary packaging surface model is subjected to three-dimensional visual enhancement, and the obtained three-dimensional model of the packaging design has a more realistic visual effect, which can more intuitively show the final appearance of the packaging design; the three-dimensional appearance of the packaging is evaluated based on the three-dimensional model of the packaging design, and the obtained packaging appearance evaluation report shows the three-dimensional appearance of the packaging design; and provides a scientific basis for the subsequent optimization of the packaging design. Therefore, the present invention uses data processing technology, pattern recognition technology and machine learning technology to realize geometric constraint analysis of the geometric structure of the packaging design, and determines the topological relationship of the packaging structure according to the geometric constraints, so that the three-dimensional model of the packaging design presents a complete visual effect.

[0079] In the embodiment of the present invention, reference Figure 1 FIG. 1 is a schematic diagram of a method for constructing a three-dimensional model of a packaging design according to the present invention. In this example, the method for constructing a three-dimensional model of a packaging design includes the following steps:

[0080] Step S1: obtaining a packaging design data set; performing data preprocessing on the packaging design data set to obtain a packaging design standard data set; performing contour feature extraction on the packaging design standard data set to obtain packaging contour features;

[0081] In the embodiment of the present invention, image data related to packaging design is collected from multiple sources, including images downloaded from the Internet or obtained by actual shooting, using Python language to write scripts to automate the download process, or using API to extract data from a database to obtain a packaging design dataset. The collected packaging design dataset is preprocessed to obtain a standardized dataset. This step involves techniques such as image reading, resizing, and normalization. Specifically, use Python language, combined with OpenCV library (cv2) and NumPy library to read and process images. Define function load_data, which traverses the data directory, reads each image file, and uses cv2.imread function to read the image into memory, and then uses cv2.resize function to uniformly resize the image to the specified size (such as 128x128 pixels). Normalize the image data, using MinMaxScaler in scikit-learn library to scale the data to a specific range or convert it to a standard normal distribution to reduce the scale difference between different features. Convert the image to grayscale, using cv2.cvtColor function in OpenCV with parameter set to cv2.COLOR_BGR2GRAY. Apply thresholding operation to convert the image to grayscale. Convert to a black and white image and use the cv2.threshold function in OpenCV. The parameters include the source image, threshold and maximum value, and the threshold type cv2.THRESH_BINARY. Use the Canny edge detection algorithm to identify the edges in the image. Call the cv2.Canny function and pass in the grayscale image, minimum threshold and maximum threshold. Use OpenCV's cv2.findContours function to extract the contours in the image. This function can find the coordinates of all contours in the image and return a list of contours. Perform attribute analysis on the extracted contours, such as calculating the area and perimeter of the contours, using the cv2.contourArea and cv2.arcLength functions. Perform polygonal approximation on the contours using the cv2.approxPolyDP function, passing in the contour, approximation accuracy parameter and curve approximation method cv2.ARC_LENGTH, and finally obtain the package contour feature.

[0082] Step S2: performing design component recognition on the package contour features to generate design component data; performing size parameter quantification on the design component data to obtain component size parameters; performing package surface structure feature mapping on the package contour features based on the component size parameters to obtain package surface structure features;

[0083] In an embodiment of the present invention, a convolutional neural network (CNN) model is constructed using a deep learning framework such as TensorFlow or PyTorch, and the model can identify different design components in an image; for example, a CNN comprising multiple convolutional layers and pooling layers is constructed, followed by a fully connected layer for classification. For each image, the findContours function in the OpenCV library is used to extract contour features, and then the Hough transform is applied to identify geometric shapes such as straight lines and circles, which is used as a preliminary identification of the design components; for each identified design component, the minAreaRect function of OpenCV is used to calculate the minimum enclosing rectangle to obtain the width and height parameters of the component; the Pandas library is used to organize and store the size data of the component, such as creating a DataFrame, wherein Contains the ID and corresponding size parameters of each component, saved in a CSV file; based on the component size parameters, use OpenCV's getPerspectiveTransform and warpPerspective functions to perform perspective transformation on the package contour features, and map the two-dimensional contour to the three-dimensional surface structure; uses block mapping technology to divide the three-dimensional surface structure into multiple small blocks, and uses a Python script to perform parameterized mapping on each block to ensure that the angle remains unchanged during the mapping process and achieve angle-preserving mapping; calculates the ratio of the area of ​​the mapped triangle to its corresponding area in the three-dimensional model, determines the area with large area distortion, and evaluates the mapping quality; this is achieved by writing a Python function that calculates the area of ​​each triangle and compares the area difference before and after mapping.

[0084] Step S3: Perform structural geometric constraint detection on the packaging surface structural features to obtain structural geometric constraints; determine the structural topological relationship of the packaging surface structural features according to the structural geometric constraints to generate a structural topological relationship; perform polygonal surface modeling based on the packaging surface structural features, structural geometric constraints and structural topological relationship to obtain a preliminary packaging surface model;

[0085] In an embodiment of the present invention, computer-aided design (CAD) software or an open source library such as Open CASCADE Technology is used to perform structural geometric constraint detection; the detection process includes identifying geometric elements such as straight lines, curves, angles, etc. on the packaging surface, and verifying whether preset geometric constraints are met; using NumPy and SciPy libraries for geometric calculations, specifically calculating whether the angle between two line segments is within the allowable error range, and checking whether the curvature of the curve meets the design specifications; applying graph theory algorithms to determine the topological relationship of the packaging surface structure, by constructing a graph in which nodes represent geometric elements in the structure and edges represent the relationship between the elements; using the NetworkX library to represent and analyze the graph; determining which nodes (geometric elements) are interconnected and the order of connection between them, thereby generating a structural topological relationship; based on the packaging surface structural features, structural geometric constraints, and structural topological relationships, using 3D modeling software such as Rhinoceros 3D or open source libraries such as Blender are used for polygonal surface modeling. In Python, Matplotlib and Plotly are used for preliminary 3D graphics drawing, and PyMesh is used for 3D mesh processing and editing. The getPerspectiveTransform and warpPerspective functions in the OpenCV library are used to perform perspective transformation on the image to correct the angle and size in the image. The four_point_transform function is used to perform perspective transformation on the four corner points in the image to correct the image to a plane view. Next, the order_points function is used to sort the corner points and calculate the size of the maximum enclosing rectangle. Finally, the resize function is used to adjust the image size for subsequent polygonal surface modeling.

[0086] Step S4: Perform three-dimensional visual enhancement on the preliminary packaging surface model to obtain a packaging design three-dimensional model; perform three-dimensional packaging appearance evaluation based on the packaging design three-dimensional model to obtain a packaging appearance evaluation report.

[0087] In the embodiment of the present invention, the 3D modeling software Blender is used to perform 3D visual enhancement on the preliminary packaging surface model. In Blender, the visual effect of the model is enhanced by adjusting the material, lighting and camera angle; the Python library three.js is used to render the 3D model, by loading the model file in .glb or .gltf format, and coloring, texture mapping and lighting processing are performed on the model to improve the visual realism of the model; specifically, in Blender, the "cycles" rendering engine is applied to the model, appropriate exposure and white balance parameters are set, HDRI environment texture is used to increase reflection and refraction effects, and different perspectives of the model are exported through Python scripts; based on the 3D model of the packaging design, computer vision technology is used to evaluate the appearance; this includes using OpenCV for image processing , extract the texture features and geometric features of the model; use machine learning algorithms, such as convolutional neural networks (CNN), to score the three-dimensional appearance of the model, and train the CNN model to identify and evaluate design elements; specifically use Python and OpenCV libraries to extract features from different perspectives of the model, including color histograms, shape descriptors, and texture features; input these features into the pre-trained CNN model to obtain the score for each perspective and generate a packaging appearance evaluation report; use the Pandas library to organize the evaluation results and create a DataFrame to store the score and related features for each perspective; use Matplotlib or Plotly libraries to generate visualization charts of the evaluation results, such as bar charts and heat maps, to intuitively display the appearance quality of the model; specifically, integrate the scoring results and feature data into a Pandas DataFrame, use Matplotlib to generate a graph containing multiple subgraphs, each subgraph showing the score and key features from different perspectives, and finally save the graph as a PNG format image file as part of the packaging appearance evaluation report.

[0088] Preferably, step S1 comprises the following steps:

[0089] Step S11: Acquire a packaging design data set;

[0090] Step S12: screening the packaging design data set for outliers to obtain packaging design outliers; performing data cleaning on the packaging design data set according to the packaging design outliers to generate a design cleaning data set;

[0091] Step S13: unifying the format of the design cleansing data set to obtain a unified format data set; standardizing the design parameters of the unified format data set to obtain a packaging design standard data set;

[0092] Step S14: marking the packaging edge attributes of the packaging design standard data set to obtain edge attribute marking values; performing marking value statistics on the edge attribute marking values ​​to generate edge attribute statistical data;

[0093] Step S15: performing edge contour attribute matching on the edge attribute statistical data to obtain edge contour attribute data; performing contour feature extraction on the packaging design standard data set according to the edge contour attribute data to obtain packaging contour features.

[0094] In an embodiment of the present invention, a data set containing packaging design information is extracted from a storage medium or online resource through a data import technology; including image files and related parameter data in the formats of JPEG, PNG and CSV; a data reading tool, such as the OpenCV library commonly used in computer vision projects, is used to read the image file, and finally a packaging design data set is obtained; a statistical analysis method is used to screen outliers for the packaging design data set, such as by calculating the mean and standard deviation of the data to identify outliers that are far away from other data points; in actual operation, a threshold is set, such as the mean ± 3 times the standard deviation, to determine the range of outliers; according to the results of outlier screening, the data set is cleaned; data cleaning includes deleting or correcting outliers to ensure the accuracy and consistency of the data set; for example, for image data, it is necessary to remove noise or repair damaged pixels; for parameter data, it is necessary to replace or delete unreasonable values; the cleaned data set is formatted in a unified manner, and the data follows the same format standard; for example, for image data, images of different sizes need to be adjusted to a unified resolution; for parameter data, data of different units need to be converted to a unified unit; the formatted data set is processed Standardization of design parameters, such as using the minimum-maximum standardization method to scale the data to between 0 and 1, and using the Z-score standardization method to convert the data into a distribution with zero mean and unit variance; using image processing techniques, such as Canny operator edge detection, to attribute the packaging edges in the image; the Canny operator identifies the edges in the image through Gaussian filtering, gradient calculation, non-maximum suppression and double threshold detection; statistical analysis of edge attribute tag values ​​to identify the most common edge attributes and their distribution, and calculate the frequency of occurrence of each edge attribute to generate an edge attribute statistical data set; matching edge attribute statistical data with edge contours in the packaging design standard data set to identify edge contours with similar attributes; such as using the matchShapes function in OpenCV to compare the similarity of edge contours, and evaluating their similarity by calculating the distance between two contours; based on the edge contour attribute data, contour feature extraction is performed on the packaging design standard data set; such as using the findContours function in OpenCV to extract contours in the image, and analyzing these contours to extract features such as area, perimeter, and bounding rectangle.

[0095] Preferably, step S2 comprises the following steps:

[0096] Step S21: performing contour detail enhancement on the package contour feature to obtain contour feature enhancement data; performing contour morphology recognition on the contour feature enhancement data to generate contour morphology data;

[0097] Step S22: classifying the contour morphology data into morphology types to obtain contour morphology types; identifying design components of the packaging contour features according to the contour morphology types to generate design component data;

[0098] Step S23: measuring the geometric dimensions of the design component data to obtain geometric dimension values; calculating the component rectangularity using the geometric dimension values ​​to generate the component rectangularity value;

[0099] Step S24: quantifying component parameters of the design component data based on the component rectangularity value to obtain component size parameters;

[0100] Step S25: mapping the package contour features to package surface structure features based on the component size parameters to obtain package surface structure features.

[0101] In an embodiment of the present invention, the contour details of the package contour feature are enhanced to highlight the key information in the contour. This usually involves image processing technology, such as using Gaussian filtering to remove noise, and using edge enhancement algorithms to improve the contrast of the contour; contour morphology recognition is performed on the contour feature enhancement data, and image analysis technology is used to identify the basic shape of the contour, such as a circle, rectangle or irregular shape; this includes contour feature extraction and shape matching algorithms, such as using the findContours function in OpenCV to extract the contour, and using the matchShapes function to perform shape matching; the contour morphology data is divided into morphological types, specifically classified into different morphological types according to the geometric features of the contour, such as a circle, ellipse, rectangle, etc.; the packaging contour features are identified according to the contour morphological type, and the design components are classified and identified using morphological features and machine learning algorithms, such as using a support vector machine (SVM) for classification; The geometric dimensions of the design component data are measured, and the dimensions of the design components, such as length, width and height, are measured using image analysis technology. Representative technologies include using the minAreaRect function in OpenCV to calculate the minimum enclosing rectangle. The geometric dimension values ​​are used to calculate the component rectangularity, and specifically the rectangularity of the component, that is, the similarity between the component and the ideal rectangle, is calculated using the area and perimeter ratio method. The design component data are quantified based on the component rectangularity value, and the component parameters are converted into numerical representations using a quantization algorithm based on the geometric dimensions and rectangularity of the component. The packaging contour features are mapped to the packaging surface structure features based on the component dimension parameters, and the two-dimensional contour features are converted into three-dimensional surface structure features using three-dimensional modeling and mapping technology, such as using a three-dimensional reconstruction algorithm to map the contour features into three-dimensional space.

[0102] Preferably, step S25 comprises the following steps:

[0103] Step S251: sorting the parameter values ​​of the component size parameters to obtain parameter value sorting data; determining the size parameter range of the parameter value sorting data to generate size parameter range data; classifying the design component data into component types according to the size parameter range data to obtain the design component type;

[0104] Step S252: locating component contour points of the package contour features by design component type to generate design component contour points; identifying component contour line segments of the package contour features based on the design component contour points to obtain design component contour line segments;

[0105] Step S253: determining the packaging geometric structure according to the design component contour points and the design component contour line segments to obtain the packaging design geometric structure; assigning geometric structure parameters to the packaging design geometric structure according to the component size parameters to generate geometric structure assignment data;

[0106] Step S254: matching the geometric structure assignment data with the design surface features to obtain the design surface matching features; mapping the design surface matching features to the packaging surface structure features to obtain the packaging surface structure features.

[0107] In an embodiment of the present invention, the parameter values ​​of component size parameters are sorted, and the size parameters are sorted according to the numerical values, and a sorting algorithm in statistical analysis technology is used, such as quick sort and merge sort; the size parameter range is determined for the parameter value sorting data, and the maximum value and minimum value of the size parameter, as well as the interval range are specifically determined; the component type of the design component data is classified according to the size parameter range data to obtain the design component type; the components are divided into different types according to the size parameter range, such as small, medium and large components; the component contour points of the package contour features are located by the design component type, and the contour positioning method in image processing technology is specifically used, such as using edge detection and contour extraction algorithms in OpenCV to locate the contour points of the component; the component contour line segments of the package contour features are recognized based on the design component contour points, and the contour line segments of the package contour features are recognized by using the image processing technology. The line segment detection method, such as Hough transform, is used to identify the straight line segments in the contour; the packaging geometry is determined according to the design component contour points and the design component contour segments, and the three-dimensional modeling technology is used specifically to build the packaging geometry model in combination with the contour point and line segment information; the geometric structure parameters of the packaging design geometry are assigned through the component size parameters, and the size parameters are applied to the geometric structure model to assign specific size values ​​to each part of the model; the geometric structure assignment data is used for design surface feature matching, and image processing and pattern recognition technologies, such as feature point matching and template matching, are used to identify and match the features of the design surface; the design surface matching features are mapped to the packaging surface structure features to obtain the packaging surface structure features, and the mapping technology is used to convert the two-dimensional feature matching results into three-dimensional surface structure features to provide detailed surface feature information for packaging design.

[0108] Preferably, step S3 comprises the following steps:

[0109] Step S31: performing spatial structural analysis on the packaging surface structural features to obtain packaging spatial structural data; performing structural geometric constraint detection on the packaging spatial structural data to obtain structural geometric constraints;

[0110] Step S32: determining the structural topological relationship of the packaging surface structural features according to the structural geometric constraints to generate the structural topological relationship;

[0111] Step S33: construct a polygonal geometric framework based on the packaging surface structural features and structural geometric constraints to obtain a polygonal geometric framework; perform surface modeling on the polygonal geometric framework based on the structural topological relationship to obtain a preliminary packaging surface model.

[0112] In the embodiment of the present invention, a spatial structural analysis is performed on the surface structural features of the packaging, and specifically, a geometric analysis is performed on the three-dimensional model of the packaging to determine its spatial layout and structural characteristics; representative technologies include three-dimensional modeling and analysis tools in computer-aided design (CAD) software, such as NURBS modeling technology, which accurately expresses the contour and shape of the three-dimensional model of complex objects; structural geometric constraint detection is performed on the spatial structural data of the packaging, and a method of geometric prior constraints is used to detect the geometric rationality of the structure, such as a method for detecting building damage, which is applied to the geometric constraint detection of the packaging structure, and the geometric characteristics of the structure meet the design specifications; structural topology is performed on the surface structural features of the packaging according to the structural geometric constraints. Relationship determination, specifically using GIS spatial analysis tools, such as the topology analysis function in ArcGIS, to identify and define the spatial relationships between packaging structure elements, such as adjacency, connection, and containment relationships; constructing a polygonal geometric framework based on the packaging surface structure characteristics and structural geometric constraints, and using 3D modeling technology, such as the surface modeling tool in Solidworks, to construct a polygonal framework of the packaging structure, and create and edit complex surfaces; performing surface modeling on the polygonal geometric framework based on the structural topological relationship, using surface modeling technology, such as the surface optimization and modeling tools in CATIA, to perform surface fitting and optimization on the polygonal framework, and generate a preliminary 3D surface model for the packaging design.

[0113] Preferably, step S31 includes the following steps:

[0114] Step S311: Perform geometric structural feature fractal on the packaging surface structural features to obtain packaging structural fractal features; perform spatial structural layout recognition on the packaging structural fractal features to generate a spatial structural layout; perform spatial structural attribute detection on the spatial structural layout to obtain packaging spatial structural data;

[0115] Step S312: determining the symmetry of the packaging space structure data to obtain a structural symmetry constraint; performing a curvature continuity test on the packaging surface structure features according to the structural symmetry constraint to obtain a curvature continuity constraint;

[0116] Step S313: performing edge curvature comparison on the package space structure data based on the curvature continuity constraint to obtain the structure edge curvature value; performing surface structure flatness detection on the package surface structure features according to the structure edge curvature value to obtain the structure flatness constraint;

[0117] Step S314: Integrate the structural symmetry constraint, the curvature continuity constraint and the structural flatness constraint to generate the structural geometric constraint.

[0118] In the embodiment of the present invention, the geometric structure feature fractal is performed on the structural features of the packaging surface to obtain the fractal features of the packaging structure. This process involves decomposing a complex geometric structure into self-similar, smaller geometric units. This technology is called fractal geometry in geometry; the spatial structure layout of the fractal features of the packaging structure is identified to generate a spatial structure layout. Specifically, GIS spatial analysis tools, such as ArcGIS, are used to identify and define the spatial relationship and layout between the packaging structure elements; the spatial structure attribute detection is performed on the spatial structure layout, and the spatial structure data is obtained by analyzing the spatial attributes of the packaging structure, such as volume, surface area and shape complexity; the symmetry of the packaging spatial structure data is determined, and the symmetry axis and symmetry plane in the packaging structure are identified based on the symmetry principle in structural mechanics; the packaging surface structure features are symmetric according to the structural symmetry constraints. Perform curvature continuity test, use the multi-order curvature continuity technology in SolidWorks to ensure the curvature continuity of curves or surfaces in the design; compare the edge curvature of the packaging space structure data based on the curvature continuity constraint, identify the curvature change by comparing the curvature values ​​of different edges, and ensure the continuity and smoothness of the design; perform surface structure flatness test on the packaging surface structure features according to the structure edge curvature value, and ensure the uniformity and quality of the packaging design by testing the flatness of the surface structure; integrate structural symmetry constraints, curvature continuity constraints and structural flatness constraints to generate structural geometric constraints; take all the above geometric constraints into consideration to form a complete set of geometric constraints to guide the optimization and verification process of packaging design.

[0119] Preferably, step S32 includes the following steps:

[0120] Step S321: determining the position of the symmetry axis of the packaging surface structural feature according to the structural symmetry constraint to obtain the symmetry axis position information; judging the symmetry constraint degree of the structural symmetry constraint based on the symmetry axis position information to generate the symmetry constraint degree;

[0121] Step S322: performing curvature gradient division on the packaging surface structural features according to the curvature continuity constraint to obtain a structural curvature gradient value; performing structural position curvature gradient mapping on the packaging surface structural features based on the structural curvature gradient value to generate a structural position curvature gradient;

[0122] Step S323: performing surface structural defect feature recognition on the packaging surface structural features according to the structural flatness constraint to obtain the surface structural defect features; performing trapping degree evaluation on the surface structural defect features to generate the surface structural trapping degree;

[0123] Step S324: performing symmetry topological determination on the degree of symmetry constraint to obtain a symmetry topological relationship; performing curvature continuity topological determination based on the curvature gradient of the structural position to obtain a curvature continuity topological relationship; performing defect tension topological determination based on the degree of surface structure trapping to obtain a defect tension topological relationship;

[0124] Step S325: merging the symmetry topological relationship, the curvature continuity topological relationship and the defect tension topological relationship into a structural topological relationship to generate a structural topological relationship.

[0125] In an embodiment of the present invention, the position of the symmetry axis of the packaging surface structural features is determined, and the position information of the symmetry axis is determined by analyzing the geometric shape and physical characteristics of the packaging structure and using the symmetry principle in structural mechanics; a three-dimensional model is constructed and analyzed using computer-aided design (CAD) software to determine the specific position of the symmetry axis; the degree of symmetry constraint of the structural symmetry constraint is judged based on the position information of the symmetry axis, and the degree of structural symmetry is evaluated by comparing the deviation between the actual structure and the ideal symmetrical structure to determine whether the structure meets the symmetry requirements of the design; the curvature gradient of the packaging surface structural features is divided according to the curvature continuity constraint, and the curvature gradient of the structure is divided using geometric analysis technology, such as a parameterized free-form surface construction method based on partial differential equations; the structural position curvature gradient mapping of the packaging surface structural features is performed based on the structural curvature gradient value, and the curvature gradient value is mapped to the specific position of the structure to form a structural position curvature gradient map, which is achieved through the spatial analysis function of GIS software. According to the structural flatness constraint, the surface structural defect characteristics of the packaging surface are identified, and the surface defect detection methods of industrial products, such as machine vision and deep learning technology, are used to identify the defect characteristics of the surface structure; the degree of trapping of the surface structural defect characteristics is evaluated, and the characteristics and degree of the defects are evaluated to determine the impact of the defects on the structural performance, which is achieved through an automated visual inspection system; the degree of symmetry constraint is determined by symmetry topology, and based on the structural symmetry constraint, the symmetry topological relationship of the structure is determined; the curvature continuity topology is determined according to the curvature gradient of the structural position to obtain the curvature continuity topological relationship; based on the curvature gradient value, the curvature continuity topological relationship of the structure is determined to ensure the curvature continuity of the structure; based on the degree of trapping of the surface structure, the defect tension topological relationship of the structure is determined to evaluate the impact of the defect on the structural tension; the symmetry topological relationship, curvature continuity topological relationship and defect tension topological relationship are combined into a structural topological relationship to form a complete structural topological relationship model, which provides a basis for structural optimization and analysis of packaging design.

[0126] Preferably, step S33 includes the following steps:

[0127] Step S331: performing structural parameterization on the packaging surface structural features to obtain parameterized structural representation data; applying geometric constraints to the parameterized structural representation data according to structural geometric constraints to generate constraint structural information;

[0128] Step S332: Packing the constraint structure information into polygonal meshes to obtain polygonal mesh data; aligning the edges of the polygonal mesh data based on the structural geometric constraints to generate polygonal edge forms; constructing a polygonal geometric framework for the polygonal edge forms to obtain a polygonal geometric framework;

[0129] Step S333: performing topological relationship mapping on the polygonal geometric framework based on the structural topological relationship to obtain framework topological structure data; performing surface fitting on the framework topological structure data to obtain a polygonal surface fitting form;

[0130] Step S334: Optimize the surface smoothing features of the polygonal surface fitting form to generate a surface feature optimized form; perform surface modeling on the surface feature optimized form to obtain a preliminary packaging surface model.

[0131] In the embodiment of the present invention, the structural features of the packaging surface are represented by structural parameterization, and the structural re-parameterization technology is used to decompose the complex structure into a simpler parameterized form to facilitate subsequent processing and analysis; geometric constraints are applied to the parameterized structure representation data according to the structural geometric constraints, and geometric constraints such as symmetry and curvature continuity are applied to adjust the parameterized structure to ensure that it meets the design requirements; the constrained structure information is packaged with polygonal meshes, and the meshing technology, such as Delaunay triangulation and Voronoi diagram, is used to divide the structure into polygonal meshes; the edges of the polygonal mesh data are aligned based on the structural geometric constraints to generate polygonal edge shapes, Ensure that the edges of the polygonal mesh are aligned with the geometric features of the structure; map the topological relationships of the polygonal geometric framework based on the structural topological relationships, and use topological mapping techniques, such as D-TIN multi-core parallel construction, to determine the topological relationships of the polygonal framework; perform surface fitting on the framework topological structure data, and use surface fitting techniques, such as 3D surface fitting technology in MATLAB, to fit the surface of the polygonal framework; optimize the surface smoothing features of the polygonal surface fitting form, and use surface smoothing techniques, such as Fourier transform and manifold harmonics, to smooth the fitted surface, remove high-frequency noise, and retain low-frequency features; perform surface modeling on the surface feature optimization form, and use Geomagic Studio surface modeling tools to model according to the optimized surface features to obtain a preliminary packaging surface model.

[0132] As an example of the present invention, refer to Figure 2 As shown, in this example, step S4 includes:

[0133] Step S41: performing color high-contrast rendering on the preliminary packaging surface model to generate model high-contrast rendering data; performing rendering level refinement on the model high-contrast rendering data to obtain model rendering level data;

[0134] Step S42: performing hierarchical stereoscopic shadow rendering on the preliminary packaging surface model according to the model rendering hierarchical data to obtain model stereoscopic shadow rendering data; performing model perspective correction on the model stereoscopic shadow rendering data to generate model perspective correction data;

[0135] Step S43: performing model texture mapping on the preliminary packaging surface model based on the model perspective correction data to obtain model texture mapping data; performing three-dimensional visualization view enhancement on the preliminary packaging surface model according to the model texture mapping data to obtain a packaging design three-dimensional model;

[0136] Step S44: outputting three-dimensional appearance information based on the packaging design three-dimensional model to obtain packaging three-dimensional appearance data; and performing packaging three-dimensional appearance evaluation on the packaging three-dimensional appearance data to obtain a packaging appearance evaluation report.

[0137] In the embodiment of the present invention, the preliminary packaging surface model is rendered in high-contrast color to generate high-contrast rendering data of the model; the HDR high dynamic range lighting rendering technology is used to enhance the visual impact of the model by adjusting the contrast of lighting and color; the rendering level of the model high-contrast rendering data is refined, and the rendering effect is refined by adjusting rendering parameters, such as the softness and hardness of the shadow, the intensity and direction of the lighting, so as to achieve richer visual effects; hierarchical stereoscopic shadow rendering is performed on the preliminary packaging surface model according to the model rendering level data to obtain model stereoscopic shadow rendering data; the screen space shadow technology is used to calculate the shadow in the image space to enhance the three-dimensional sense; the model perspective correction is performed on the model stereoscopic shadow rendering data, and specifically the perspective transformation algorithm of opencv is used to perform perspective correction on the rendered image. , to ensure the geometric accuracy of the image; perform model texture mapping on the preliminary packaging surface model based on the model perspective correction data, and use texture mapping technology to map the texture image to the three-dimensional model surface to enhance the realism of the model; enhance the three-dimensional visualization view of the preliminary packaging surface model according to the model texture mapping data, and optimize the visual effect of the three-dimensional view by adjusting the parameters and viewing angle of the texture mapping to make the model more realistic; output the three-dimensional appearance information based on the packaging design three-dimensional model, and use reverse engineering software such as Geomagic Studio to output the detailed appearance information of the three-dimensional model; evaluate the three-dimensional appearance of the packaging on the three-dimensional appearance data to obtain a packaging appearance evaluation report, evaluate the appearance quality of the packaging by comparing the actual appearance of the model with the design standard, and generate a detailed evaluation report.

[0138] As an example of the present invention, refer to Figure 3 As shown, in this example, step S44 includes:

[0139] Step S441: outputting three-dimensional appearance information based on the packaging design three-dimensional model to obtain packaging three-dimensional appearance data;

[0140] Step S442: performing surface concave detection on the three-dimensional appearance data of the package to obtain concave features on the package surface; performing surface convex detection on the three-dimensional appearance data of the package to obtain convex features on the package surface;

[0141] Step S443: quantifying the packaging surface defect attributes based on the packaging surface concave features and the packaging surface convex features to obtain the packaging surface defect attributes; performing packaging appearance integrity recognition on the packaging surface defect attributes to generate packaging appearance integrity data;

[0142] Step S444: classifying the packaging appearance integrity data according to the degree of packaging design appearance defects to obtain a packaging appearance classification; and evaluating the three-dimensional appearance integrity of the packaging on the packaging appearance classification to obtain a packaging appearance evaluation report.

[0143] In the embodiment of the present invention, three-dimensional appearance information is output based on the three-dimensional model of the packaging design. Specifically, three-dimensional visualization software, such as 3D Studio Max, is used to design and model the packaging structure, and each block of graphic files after the plane design is segmented is made into 3D mapping materials, and then the three-dimensional appearance information is output; surface depression detection is performed on the three-dimensional appearance data of the packaging to obtain the depression characteristics of the packaging surface; specifically, 3D visual detection technology, such as structured light projection or laser scanning, is used to obtain the elevation information of the packaging surface, and image processing technology is used to identify the depression area; surface convexity detection is performed on the three-dimensional appearance data of the packaging, and the 3D visual detection technology is also used to identify the convexity area by comparing the deviation between the standard model and the actual model; based on the depression characteristics and the convex characteristics of the packaging surface, the packaging surface defect attributes are quantified, specifically by measuring the concave surface and the convex surface. The system can quantify the severity of defects by using parameters such as the area and depth of sunken and raised areas; identify the integrity of packaging appearance based on the properties of packaging surface defects to generate packaging appearance integrity data; determine whether the packaging appearance is complete and identify areas with defects by comparing with the preset defect threshold; classify the packaging appearance integrity data according to the degree of packaging design appearance defects, and classify the defects into different categories such as minor defects and serious defects according to the type and severity of the defects; evaluate the integrity of the three-dimensional appearance of the packaging based on the packaging appearance classification to obtain a packaging appearance evaluation report; and comprehensively consider the type, quantity and location of the defects to evaluate the overall appearance quality of the packaging and generate a detailed evaluation report.

[0144] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0145] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for constructing a three-dimensional model of packaging design, characterized in that: The following steps are involved: Step S1: Obtain packaging design dataset; Perform data preprocessing on the packaging design data set to obtain a packaging design standard data set; Extract contour features from the packaging design standard data set to obtain packaging contour features; Step S2: performing design component recognition on the packaging contour features to generate design component data; Quantify the size parameters of the design component data to obtain the component size parameters; Mapping the packaging surface structure features to the packaging contour features based on the component size parameters to obtain the packaging surface structure features; Step S3: Perform structural geometric constraint detection on the packaging surface structural features to obtain structural geometric constraints; Determine the structural topological relationship of the packaging surface structural features according to the structural geometric constraints and generate the structural topological relationship; Based on the packaging surface structural features, structural geometric constraints and structural topological relationships, polygonal surface modeling is performed to obtain a preliminary packaging surface model; Step S4: Perform three-dimensional visual enhancement on the preliminary packaging surface model to obtain a three-dimensional model of the packaging design; The three-dimensional appearance of the packaging is evaluated based on the three-dimensional model of the packaging design to obtain a packaging appearance evaluation report.

2. The method for constructing a three-dimensional model of packaging design according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: Acquire a packaging design data set; Step S12: screening the packaging design data set for outliers to obtain packaging design outliers; performing data cleaning on the packaging design data set according to the packaging design outliers to generate a design cleaning data set; Step S13: unifying the format of the design cleansing data set to obtain a unified format data set; standardizing the design parameters of the unified format data set to obtain a packaging design standard data set; Step S14: marking the packaging edge attributes of the packaging design standard data set to obtain edge attribute marking values; performing marking value statistics on the edge attribute marking values ​​to generate edge attribute statistical data; Step S15: performing edge contour attribute matching on the edge attribute statistical data to obtain edge contour attribute data; performing contour feature extraction on the packaging design standard data set according to the edge contour attribute data to obtain packaging contour features.

3. The method for constructing a three-dimensional model of packaging design according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: performing contour detail enhancement on the package contour feature to obtain contour feature enhancement data; performing contour morphology recognition on the contour feature enhancement data to generate contour morphology data; Step S22: classifying the contour morphology data into morphology types to obtain contour morphology types; identifying design components of the packaging contour features according to the contour morphology types to generate design component data; Step S23: measuring the geometric dimensions of the design component data to obtain geometric dimension values; calculating the component rectangularity using the geometric dimension values ​​to generate the component rectangularity value; Step S24: quantifying component parameters of the design component data based on the component rectangularity value to obtain component size parameters; Step S25: mapping the package contour features to package surface structure features based on the component size parameters to obtain package surface structure features.

4. The method for constructing a three-dimensional model of packaging design according to claim 3, characterized in that: Step S25 includes the following steps: Step S251: sorting the parameter values ​​of the component size parameters to obtain parameter value sorting data; determining the size parameter range of the parameter value sorting data to generate size parameter range data; classifying the design component data into component types according to the size parameter range data to obtain the design component type; Step S252: locating component contour points of the package contour features by design component type to generate design component contour points; identifying component contour line segments of the package contour features based on the design component contour points to obtain design component contour line segments; Step S253: determining the packaging geometric structure according to the design component contour points and the design component contour line segments to obtain the packaging design geometric structure; assigning geometric structure parameters to the packaging design geometric structure according to the component size parameters to generate geometric structure assignment data; Step S254: matching the geometric structure assignment data with the design surface features to obtain the design surface matching features; mapping the design surface matching features to the packaging surface structure features to obtain the packaging surface structure features.

5. The method for constructing a three-dimensional model of packaging design according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: performing spatial structural analysis on the packaging surface structural features to obtain packaging spatial structural data; performing structural geometric constraint detection on the packaging spatial structural data to obtain structural geometric constraints; Step S32: determining the structural topological relationship of the packaging surface structural features according to the structural geometric constraints to generate the structural topological relationship; Step S33: construct a polygonal geometric framework based on the packaging surface structural features and structural geometric constraints to obtain a polygonal geometric framework; perform surface modeling on the polygonal geometric framework based on the structural topological relationship to obtain a preliminary packaging surface model.

6. The method for constructing a three-dimensional model of packaging design according to claim 5, characterized in that: Step S31 includes the following steps: Step S311: Perform geometric structural feature fractal on the packaging surface structural features to obtain packaging structural fractal features; perform spatial structural layout recognition on the packaging structural fractal features to generate a spatial structural layout; perform spatial structural attribute detection on the spatial structural layout to obtain packaging spatial structural data; Step S312: determining the symmetry of the packaging space structure data to obtain a structural symmetry constraint; performing a curvature continuity test on the packaging surface structure features according to the structural symmetry constraint to obtain a curvature continuity constraint; Step S313: performing edge curvature comparison on the package space structure data based on the curvature continuity constraint to obtain the structure edge curvature value; performing surface structure flatness detection on the package surface structure features according to the structure edge curvature value to obtain the structure flatness constraint; Step S314: Integrate the structural symmetry constraint, the curvature continuity constraint and the structural flatness constraint to generate the structural geometric constraint.

7. The method for constructing a three-dimensional model of packaging design according to claim 6, characterized in that: Step S32 includes the following steps: Step S321: determining the position of the symmetry axis of the packaging surface structural feature according to the structural symmetry constraint to obtain the symmetry axis position information; judging the symmetry constraint degree of the structural symmetry constraint based on the symmetry axis position information to generate the symmetry constraint degree; Step S322: performing curvature gradient division on the packaging surface structural features according to the curvature continuity constraint to obtain a structural curvature gradient value; performing structural position curvature gradient mapping on the packaging surface structural features based on the structural curvature gradient value to generate a structural position curvature gradient; Step S323: performing surface structural defect feature recognition on the packaging surface structural features according to the structural flatness constraint to obtain the surface structural defect features; performing trapping degree evaluation on the surface structural defect features to generate the surface structural trapping degree; Step S324: performing symmetry topological determination on the degree of symmetry constraint to obtain a symmetry topological relationship; performing curvature continuity topological determination based on the curvature gradient of the structural position to obtain a curvature continuity topological relationship; performing defect tension topological determination based on the degree of surface structure trapping to obtain a defect tension topological relationship; Step S325: merging the symmetry topological relationship, the curvature continuity topological relationship and the defect tension topological relationship into a structural topological relationship to generate a structural topological relationship.

8. The method for constructing a three-dimensional model of packaging design according to claim 5, characterized in that: Step S33 includes the following steps: Step S331: performing structural parameterization on the packaging surface structural features to obtain parameterized structural representation data; applying geometric constraints to the parameterized structural representation data according to structural geometric constraints to generate constraint structural information; Step S332: Packing the constraint structure information into polygonal meshes to obtain polygonal mesh data; aligning the edges of the polygonal mesh data based on the structural geometric constraints to generate polygonal edge forms; constructing a polygonal geometric framework for the polygonal edge forms to obtain a polygonal geometric framework; Step S333: performing topological relationship mapping on the polygonal geometric framework based on the structural topological relationship to obtain framework topological structure data; performing surface fitting on the framework topological structure data to obtain a polygonal surface fitting form; Step S334: Optimize the surface smoothing features of the polygonal surface fitting form to generate a surface feature optimized form; perform surface modeling on the surface feature optimized form to obtain a preliminary packaging surface model.

9. The method for constructing a three-dimensional model of packaging design according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: performing color high-contrast rendering on the preliminary packaging surface model to generate model high-contrast rendering data; performing rendering level refinement on the model high-contrast rendering data to obtain model rendering level data; Step S42: performing hierarchical stereoscopic shadow rendering on the preliminary packaging surface model according to the model rendering hierarchical data to obtain model stereoscopic shadow rendering data; performing model perspective correction on the model stereoscopic shadow rendering data to generate model perspective correction data; Step S43: performing model texture mapping on the preliminary packaging surface model based on the model perspective correction data to obtain model texture mapping data; performing three-dimensional visualization view enhancement on the preliminary packaging surface model according to the model texture mapping data to obtain a packaging design three-dimensional model; Step S44: outputting three-dimensional appearance information based on the packaging design three-dimensional model to obtain packaging three-dimensional appearance data; and performing packaging three-dimensional appearance evaluation on the packaging three-dimensional appearance data to obtain a packaging appearance evaluation report.

10. The method for constructing a three-dimensional model of packaging design according to claim 9, characterized in that: Step S44 includes the following steps: Step S441: outputting three-dimensional appearance information based on the packaging design three-dimensional model to obtain packaging three-dimensional appearance data; Step S442: performing surface concave detection on the three-dimensional appearance data of the package to obtain concave features on the package surface; performing surface convex detection on the three-dimensional appearance data of the package to obtain convex features on the package surface; Step S443: quantifying the packaging surface defect attributes based on the packaging surface concave features and the packaging surface convex features to obtain the packaging surface defect attributes; performing packaging appearance integrity recognition on the packaging surface defect attributes to generate packaging appearance integrity data; Step S444: classifying the packaging appearance integrity data according to the degree of packaging design appearance defects to obtain a packaging appearance classification; and evaluating the three-dimensional appearance integrity of the packaging on the packaging appearance classification to obtain a packaging appearance evaluation report.

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