Model shaping method and electronic equipment

Abstract

The invention discloses a model shaping method and electronic equipment. The method comprises the following steps: acquiring a model to be shaped; receiving a first control instruction, and determining a plurality of selection points on the surface of the to-be-shaped model according to the first control instruction; determining coordinates of a plurality of sampling points based on the coordinates of the plurality of selection points and a first preset distance; determining a neighborhood point set corresponding to each sampling point based on the coordinate of each sampling point, the coordinate of the vertex of the surface of the to-be-shaped model and a first preset distance; and shaping the to-be-shaped model based on the coordinate of each sampling point and the coordinates of all neighborhood points in the corresponding neighborhood point set to obtain a shaped model. According to the invention, the coordinates of the plurality of sampling points are determined based on the coordinates of the plurality of selection points and the first preset distance, so that the distance between two adjacent sampling points in the plurality of sampling points can be equal, and the problem that the shaping form is not coherent due to the unequal distance between two adjacent selection points in the plurality of selection points is avoided. Therefore, the shaping effect is improved.

Description

Technical Field

[0001] The present invention relates to the field of oral medical technology, and in particular to a model shaping method and electronic equipment. Background Art

[0002] In the field of oral medical technology, it is often necessary to add wax or reduce wax to shape dental restorations (such as dentures, bridges, and crown restorations) so that the dental restorations match the patient's oral physiological morphology.

[0003] With the advancement of technology, the traditional manual wax shaping method has been gradually replaced by the digital wax shaping method. The digital wax shaping method is to obtain a three-dimensional model of the dental restoration through digital scanning and modeling, and then the user adds wax or reduces wax to shape the dental restoration model to produce a dental restoration that better conforms to the patient's oral physiological morphology. Specifically, the user determines the shaping area on the dental restoration model by dragging the mouse, and then the computer performs real-time shaping.

[0004] However, in the existing digital wax shaping method, the speed at which the user drags the mouse is uncertain, which often leads to the morphology of the shaping area being broken, thus causing the problem of discontinuous shaping. Summary of the invention

[0005] In response to the shortcomings of the prior art, the present application provides a model shaping method and an electronic device, which determines the coordinates of multiple sampling points based on the coordinates of multiple selection points and a first preset distance, and then further shapes the model to be shaped based on the coordinates of the multiple sampling points to obtain a shaping model. The shaping model can make the distance between two adjacent sampling points in the multiple sampling points equal, avoiding the problem of incoherent shaping morphology caused by unequal distances between two adjacent selection points in the multiple selection points, thereby improving the shaping effect.

[0006] To solve the above problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present application provides a model shaping method, comprising: obtaining a model to be shaped, wherein the model to be shaped is a dental restoration model; receiving a first control instruction, and determining a plurality of selection points on the surface of the model to be shaped according to the first control instruction; determining the coordinates of a plurality of sampling points based on the coordinates of the plurality of selection points and a first preset distance; determining a neighborhood point set corresponding to each sampling point based on the coordinates of each sampling point, the coordinates of the vertices on the surface of the model to be shaped, and the first preset distance; shaping the model to be shaped based on the coordinates of each sampling point and the coordinates of all neighborhood points in the corresponding neighborhood point set to obtain a shaped model.

[0008] In some embodiments, determining the coordinates of multiple sampling points based on the coordinates of the multiple selection points and the first preset distance includes: screening the multiple selection points based on the coordinates of the multiple selection points and the first preset distance to obtain multiple screening points; determining the coordinates of multiple sampling points on the surface of the model to be shaped based on the coordinates of the multiple screening points and the first preset distance.

[0009] In some embodiments, the multiple selection points are screened based on the coordinates of the multiple selection points and the first preset distance to obtain multiple screening points, including: when the distance between the Nth selection point and the N+1th selection point in the viewing direction is greater than a first preset value multiplied by the first preset distance, the N+1th selection point is determined as the screening point, wherein N is a positive integer and the initial value is 1; let N=N+1, and return to execute the step of determining the N+1th selection point as the screening point when the distance between the Nth selection point and the N+1th selection point in the viewing direction is greater than the first preset value multiplied by the first preset distance.

[0010] In some embodiments, the coordinates of multiple sampling points on the surface of the model to be shaped based on the coordinates of the multiple screening points and the first preset distance include: when the total number of the multiple screening points is 2, determining the connecting line segment of the two screening points based on the coordinates of the two screening points; performing interpolation sampling on the connecting line segment according to a sampling interval of a second preset value multiplied by the first preset distance to obtain the coordinates of the sampling points on the surface of the model to be shaped, and also determining the first screening point as the sampling point to obtain the multiple sampling points; when the total number of the multiple screening points is greater than 2, fitting a curve based on the coordinates of the multiple screening points, and performing interpolation sampling on the curve according to a sampling interval of the second preset value multiplied by the first preset distance to obtain the multiple sampling points.

[0011] In some embodiments, the coordinates of the screening points are the coordinates of the screening points when the model to be shaped has not been shaped, and when the total number of the multiple screening points is greater than 2, a curve is fitted based on the coordinates of the multiple screening points, and interpolation sampling is performed on the curve according to the sampling interval of the second preset value multiplied by the first preset distance to obtain the multiple sampling points, including: when the total number of the multiple screening points is greater than 2, a first queue including the Xth screening point, the X+1th screening point to the X+Yth screening point is constructed, wherein X is a positive integer and its initial value is 1, Y is a positive integer greater than 1 and is a preset value, and the The number of screening points included in the first queue is Y+1; ​​a curve is fitted based on the coordinates of all the screening points in the first queue, and interpolation sampling is performed on the curve according to the sampling interval of the second preset value multiplied by the first preset distance, to obtain a plurality of sampling points including the Xth screening point in the first queue; the coordinates of the X+Yth screening point are updated to the coordinates of a sampling point that is closest to the X+Yth screening point; let X=X+1, and return to execute the construction of the first queue including the Xth screening point, the X+1th screening point, the X+2th screening point, and up to the X+Yth screening point.

[0012] In some embodiments, fitting a curve based on the coordinates of all the screening points in the first queue, and performing interpolation sampling on the curve at a sampling interval of the second preset value multiplied by the first preset distance to obtain a plurality of sampling points including the Xth screening point in the first queue, includes: calculating the average coordinate points of the X+Y-1th screening point and the X+Yth screening point in the first queue and using them as interpolation points; fitting the curve based on the coordinates of all the screening points in the first queue and the coordinates of the interpolation points; performing interpolation sampling on the curve based on the length of the curve and a sampling interval of the second preset value multiplied by the first preset distance to obtain a plurality of sampling points including the Xth screening point in the first queue.

[0013] In some embodiments, the model to be shaped is a mesh model composed of multiple polygonal patches, each of which has multiple vertices. The method of shaping the model to be shaped based on the coordinates of each sampling point and the coordinates of all neighboring points in the corresponding neighborhood point set to obtain the shaped model includes: determining a neighborhood patch set corresponding to each sampling point based on the coordinates of all neighboring points in the neighborhood point set corresponding to each sampling point; calculating a shaping direction vector corresponding to all neighboring points in the neighborhood point set corresponding to the sampling point based on the normal vector of each neighborhood patch in the neighborhood patch set corresponding to each sampling point; selecting a corresponding target calculation method according to a preset shaping type; determining a shaping height of each neighborhood point based on the distance between the sampling point and each neighborhood point in the neighborhood point set corresponding to each sampling point using the target calculation method; and moving the neighborhood point based on the shaping direction vector and shaping height corresponding to each neighborhood point in all the neighborhood point sets to shape the model to be shaped to obtain the shaped model.

[0014] In some embodiments, the calculating of the shaping direction vector corresponding to all the neighborhood points in the neighborhood point set corresponding to the sampling point based on the normal vector of each neighborhood patch in the neighborhood patch set corresponding to each sampling point includes: performing weighted calculation on the normal vectors of all the neighborhood patches according to the area of ​​each neighborhood patch in the neighborhood patch set corresponding to each sampling point to obtain the weighted normal vector corresponding to the sampling point; and determining the shaping direction vectors of all the neighborhood points in the neighborhood point set corresponding to the sampling point based on the weighted normal vector corresponding to each sampling point and the preset shaping type.

[0015] In some embodiments, the method of using the target calculation method to determine the shaping height of each neighborhood point based on the distance between the sampling point and each neighborhood point in the neighborhood point set corresponding to each sampling point includes: for each neighborhood point in the neighborhood point set corresponding to each sampling point, when the neighborhood point has not moved, calculating the first distance between the neighborhood point and the sampling point based on the current coordinates of the neighborhood point and the coordinates of the sampling point; using the target calculation method to determine the shaping height of the neighborhood point according to the first distance; when the neighborhood point has moved, calculating the second distance between the neighborhood point and the sampling point based on the current coordinates of the neighborhood point and the coordinates of the sampling point; and using the target calculation method to update the shaping height of the neighborhood point according to the second distance.

[0016] In a second aspect, an embodiment of the present application provides an electronic device, the electronic device comprising:

[0017] at least one processor; and,

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the model shaping method as described in the first aspect.

[0020] The present application provides a model shaping method and an electronic device. The present application determines the coordinates of multiple sampling points based on the coordinates of multiple selection points and a first preset distance, and then further shapes the model to be shaped based on the coordinates of the multiple sampling points to obtain a shaping model. The shaping model can make the distance between two adjacent sampling points in the multiple sampling points equal, avoiding the problem of discontinuity in shaping caused by unequal distances between two adjacent selection points in the multiple selection points, thereby improving the shaping effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a flow chart of the model shaping method provided in the embodiment of the present application.

[0022] Figure 2A It is a schematic diagram of the result of shaping the model to be shaped using the existing method provided in an embodiment of the present application.

[0023] Figure 2B It is a schematic diagram of the result of shaping the model to be shaped using the model shaping method provided in an embodiment of the present application.

[0024] Figure 3 yes Figure 1 Detailed flowchart of step S300.

[0025] Figure 4 yes Figure 3 Detailed flowchart of step S310 in FIG.

[0026] Figure 5 yes Figure 3 Detailed flowchart of step S320 in FIG.

[0027] Figure 6 yes Figure 5 Detailed flowchart of step S323 in FIG.

[0028] Figure 7 yes Figure 1 Detailed flowchart of step S500.

[0029] Figure 8 yes Figure 7 Schematic diagram of the principles of steps S510 to S550.

[0030] Fig. 9It is a schematic diagram of a morphology curve obtained by using the first target calculation method provided in an embodiment of the present application.

[0031] Fig.10 It is a schematic diagram of a morphology curve obtained by using the second target calculation method provided in an embodiment of the present application.

[0032] Fig.11A It is a first schematic diagram of a first shaping model obtained by performing one shaping using a first target calculation method provided in an embodiment of the present application.

[0033] Fig. 11B It is a schematic diagram of the first transverse cross-sectional profile of the first shaping model provided in an embodiment of the present application.

[0034] Fig. 11C It is a second schematic diagram of the first shaping model obtained by performing one shaping using the first target calculation method provided in an embodiment of the present application.

[0035] Fig.11D It is a schematic diagram of the first longitudinal cross-sectional profile of the first shaping model provided in an embodiment of the present application.

[0036] Fig.11E It is a first schematic diagram of a second shaping model obtained by performing one shaping using a second target calculation method provided in an embodiment of the present application.

[0037] Fig.11F It is a schematic diagram of the second transverse cross-sectional profile of the second shaping model provided in an embodiment of the present application.

[0038] Fig.11G It is a second schematic diagram of a second shaping model obtained by performing one shaping using a second target calculation method provided in an embodiment of the present application.

[0039] Fig.11H It is a schematic diagram of the second longitudinal cross-sectional profile of the second shaping model provided in an embodiment of the present application.

[0040] Fig. 12A It is a first schematic diagram of a third shaping model obtained by performing two shaping operations using a second target calculation method provided in an embodiment of the present application.

[0041] Fig. 12B It is a schematic diagram of the superposition of the transverse cross-sectional profiles of the second shaping of the third shaping model provided in an embodiment of the present application.

[0042] Fig. 12C It is a second schematic diagram of a third shaping model obtained by performing two shaping operations using a second target calculation method provided in an embodiment of the present application.

[0043] Fig.12DIt is a schematic diagram of the superposition of the longitudinal cross-sectional profiles of the second shaping of the third shaping model provided in an embodiment of the present application.

[0044] Fig.13 It is a schematic diagram of a fourth shaping model obtained by performing multiple shaping operations using the model shaping method provided in an embodiment of the present application.

[0045] Fig.14 It is a schematic diagram of the fifth shaping model obtained by performing multiple shaping operations using the model shaping method provided in an embodiment of the present application.

[0046] Fig.15 It is a structural schematic diagram of the model shaping device provided in an embodiment of the present application.

[0047] Fig.16 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0048] Fig.17 It is a structural block diagram of a computer-readable storage medium provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0050] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0051] The present application provides a model shaping method and an electronic device, which determines the coordinates of multiple sampling points based on the coordinates of multiple selection points and a first preset distance, and then further shapes the model to be shaped based on the coordinates of the multiple sampling points to obtain a shaping model. The shaping model can make the distance between two adjacent sampling points in the multiple sampling points equal, avoiding the problem of discontinuity in shaping caused by unequal distances between two adjacent selection points in the multiple selection points, thereby improving the shaping effect.

[0052] The model shaping method provided by the present application will be described in detail below with reference to the accompanying drawings.

[0053] See also Figure 1 , Figure 1Schematic diagram of the model shaping method provided in the embodiment of the present application. Figure 1 As shown, the model shaping method includes: step S100 to step S500.

[0054] Step S100: Obtain the model to be shaped.

[0055] The model to be shaped is a tooth restoration model. For example, the model to be shaped is a denture model, a molar pad model, a bridge model, a base model or a crown restoration model. The model shaping method can be used to shape the pit and fissure area on the denture model or the base model with wax addition or wax reduction.

[0056] Step S200: receiving a first control instruction, and determining a plurality of selection points on the surface of the model to be shaped according to the first control instruction.

[0057] In some embodiments, a mouse drag event is determined according to a first control instruction, and a selection point selected by the mouse on the model to be shaped is determined once every mouse refresh time, thereby obtaining multiple selection points on the surface of the model to be shaped.

[0058] Optionally, multiple selection points are sorted according to the process of mouse dragging to obtain the order of each selection point, wherein the order of the selection point that the mouse passes first is in the front.

[0059] In some embodiments, the model shaping method is performed in real time, that is, the shaping model is calculated and generated in real time during the mouse dragging process.

[0060] See also Figure 2A , Figure 2A Schematic diagram of the result of shaping the model to be shaped using the existing method provided in the embodiment of the present application. Figure 2A As shown, in some embodiments, the dragging track of the mouse on the model to be shaped 1 is a curve L1, and the area A1 shows the result of wax shaping of the model to be shaped according to the mouse dragging event corresponding to the curve L1. It can be seen that the shape of the shaping area is broken, and the concave and convex feeling is strong, and the concave and convex are uneven along the curve L1. This is because the speed of the mouse dragging is relatively fast at this time, and a good shaping effect cannot be achieved according to the existing method. The shape of the shaping area shown in area A2 is more seriously broken, because the speed of the mouse dragging is faster at this time.

[0061] See also Figure 2B , Figure 2B Schematic diagram of the result of shaping the model to be shaped using the model shaping method provided in the embodiment of the present application. Figure 2BAs shown, in some embodiments, the dragging track of the mouse on the model to be shaped 1 is a curve L2. It can be seen that the shape of the shaping area is coherent and the concave and convex along the curve L2 are uniform. This shows that the model shaping method can achieve a good shaping effect.

[0062] Step S300: determining the coordinates of a plurality of sampling points based on the coordinates of a plurality of selected points and a first preset distance.

[0063] See also Figure 3 , Figure 3 yes Figure 1 Detailed flow chart of step S300 in FIG. Figure 3 As shown, in some implementations, step S300 includes steps S310 to S320.

[0064] Step S310: Filtering the plurality of selection points based on the coordinates of the plurality of selection points and the first preset distance to obtain a plurality of filter points.

[0065] When the mouse is dragged at a slow speed, the distance between two selection points is short and the number of selection points is large. By screening multiple selection points to obtain multiple screening points, it is possible to avoid the situation where the selection points are too dense.

[0066] See also Figure 4 , Figure 4 yes Figure 3 Detailed flow chart of step S310 in FIG. Figure 4 As shown, in some embodiments, step S310 includes steps S311 to S312.

[0067] Step S311: when the distance between the Nth selection point and the N+1th selection point in the viewing angle direction is greater than the first preset value multiplied by the first preset distance, the N+1th selection point is determined as a screening point.

[0068] Wherein, N is a positive integer and its initial value is 1.

[0069] As described above, optionally, multiple selection points are sorted according to the process of mouse dragging to obtain the order of each selection point. Among them, the order of the selection point that the mouse passes first is in the front. Therefore, the order of the Nth selection point is before the order of the N+1th selection point.

[0070] When the distance between the Nth selection point and the N+1th selection point in the viewing direction is greater than the first preset value multiplied by the first preset distance, it is considered that the user has the motivation to continue dragging the mouse backwards, so the N+1th selection point is also determined as a screening point.

[0071] The distance between the Nth selected point and the N+1th selected point in the viewing direction refers to the distance between the projection point of the Nth selected point on the ideal plane and the projection point of the N+1th selected point on the ideal plane in the viewing direction of the user observing the model to be shaped. The ideal plane is a plane perpendicular to the viewing direction vector.

[0072] Optionally, the first preset distance ranges from 0.2 mm (millimeter) to 5 mm, such as 0.2 mm, 1 mm, 3 mm or 5 mm.

[0073] Optionally, the first preset value ranges from 0.1 to 0.5, for example, the first preset value is 0.1, 0.2, 0.25 or 0.5.

[0074] Step S312: Set N=N+1, and return to execute step S311.

[0075] Optionally, the model shaping method is executed in real time, and the subsequent steps are executed immediately after the screening point is recorded, and the model to be shaped is shaped in real time. In step S312, when a mouse drag event ends, the execution of step S311 is stopped, and the shaping of the model to be shaped is stopped.

[0076] Step S320: determining the coordinates of a plurality of sampling points on the surface of the model to be shaped based on the coordinates of the plurality of screening points and the first preset distance.

[0077] When the mouse is dragged at a faster speed, the distance between the two selection points is longer, and the distance between the corresponding screening points is also longer. By further determining the coordinates of the multiple sampling points based on the coordinates of the multiple screening points and the first preset distance, the situation where the screening points are too sparse can be avoided.

[0078] See also Figure 5 , Figure 5 yes Figure 3 Detailed flow chart of step S320 in FIG. Figure 5 As shown, in some embodiments, step S320 includes steps S321 to S323.

[0079] Step S321: when the total number of the plurality of filtering points is 2, determining a connecting line segment of the two filtering points based on the coordinates of the two filtering points.

[0080] Step S322: interpolate and sample on the connecting line segment at a sampling interval of the second preset value multiplied by the first preset distance to obtain the coordinates of the sampling points on the surface of the model to be shaped, and also determine the first screening point as a sampling point to obtain multiple sampling points.

[0081] Among them, all sampling points except the first screening point are obtained through interpolation sampling.

[0082] In some embodiments, the connecting line segment may not strictly fit the surface of the model to be shaped. In this case, interpolation sampling is performed on the connecting line segment according to the sampling interval of the second preset value multiplied by the first preset distance to obtain an initial sampling point, and then the nearest neighbor search method is used to find the final sampling point on the surface of the model to be shaped that corresponds to the initial sampling point, and the coordinates of the final sampling point on the surface of the model to be shaped are obtained. The coordinates of the sampling points used for calculation later refer to the coordinates of the final sampling point on the surface of the model to be shaped.

[0083] Optionally, the second preset value ranges from 0.1 to 0.5, for example, the second preset value is 0.1, 0.2, 0.25 or 0.5.

[0084] Step S323: when the total number of the plurality of screening points is greater than 2, a curve is fitted based on the coordinates of the plurality of screening points, and interpolation sampling is performed on the curve at a sampling interval of the second preset value multiplied by the first preset distance to obtain a plurality of sampling points.

[0085] In some embodiments, the coordinates of the screening points are the coordinates of the screening points when the model to be shaped has not been shaped. In this way, when the shaping process is repeated, the sampling points calculated based on the screening points will be close to the surface of the model to be shaped, so that the shaping morphological effects can be naturally superimposed.

[0086] See also Figure 6 , Figure 6 yes Figure 5 Detailed flow chart of step S323 in FIG. Figure 6 As shown, in some embodiments, step S323 includes steps S3231 to S3234.

[0087] Step S3231: When the total number of the plurality of screening points is greater than 2, a first queue including the Xth screening point, the X+1th screening point to the X+Yth screening point is constructed.

[0088] Where X is a positive integer with an initial value of 1, Y is a positive integer greater than 1 and a preset value, and the number of screening points included in the first queue is Y+1. In this way, only one section of the curve is fitted according to Y+1 screening points each time, so that the fitted curve can be basically consistent with the trajectory of the user dragging the mouse in real time, thereby improving the accuracy of shaping.

[0089] Optionally, the value range of Y is 2 to 10, for example, the value of Y is 2, 3, 4, 5, or 10.

[0090] Preferably, the value of Y is 3.

[0091] Step S3232: Fit a curve based on the coordinates of all the screening points in the first queue, and perform interpolation sampling on the curve according to a sampling interval of the second preset value multiplied by the first preset distance to obtain multiple sampling points including the Xth screening point in the first queue.

[0092] Among them, all sampling points except the Xth screening point are obtained through interpolation sampling.

[0093] In some embodiments, step S3232 includes steps (3232.1) to (3232.3).

[0094] (3232.1) Calculate the average coordinate point of the X+Y-1th screening point and the X+Yth screening point in the first queue and use it as the interpolation point.

[0095] The X+Yth screening point in the first queue is the last screening point in the first queue, and the X+Y-1th screening point is a screening point before the last screening point.

[0096] (3232.2) Fit a curve based on the coordinates of all the filtered points in the first queue and the coordinates of the interpolation points.

[0097] Optionally, the curve fitting algorithm includes a cubic B-spline algorithm, a polynomial interpolation algorithm, a K-spline interpolation algorithm, and the like.

[0098] (3232.3) Perform interpolation sampling on the curve based on the length of the curve and a sampling interval of the second preset value multiplied by the first preset distance to obtain multiple sampling points including the Xth screening point in the first queue.

[0099] Optionally, the length of the curve is calculated, and interpolation sampling is performed on the curve at a sampling interval of a second preset value multiplied by a first preset distance to obtain a plurality of sampling points including the Xth screening point in the first queue.

[0100] Step S3233: Update the coordinates of the X+Yth screening point to the coordinates of a sampling point that is closest to the X+Yth screening point.

[0101] like Figure 2B As shown, for example, when a first queue including the first screening point, the second screening point, the third screening point and the fourth screening point is constructed, sampling points A, B, C and D are calculated based on the coordinates of all the screening points in the first queue, and then the coordinates of the fourth screening point are updated to the coordinates of the sampling point D. It can be understood that there are other multiple sampling points on the curve L2. Figure 2B Not shown.

[0102] Step S3234: Let X=X+1, and return to execute step S3231.

[0103] Optionally, the model shaping method is executed in real time, and the subsequent steps are executed immediately after the first queue is constructed, and the model to be shaped is shaped in real time. In step S3234, when a mouse drag event ends, the execution of step S3231 is stopped, and the shaping of the model to be shaped is stopped.

[0104] In some embodiments, the curve on the model to be shaped is the final curve obtained by fitting according to the above method based on multiple screening points, and the curve is piecewise fitted. In this way, the curve can be made substantially consistent with the trajectory formed by the user dragging the mouse on the model to be shaped in real time, thereby improving the accuracy of shaping.

[0105] like Figure 2B As shown, exemplarily, after the coordinates of the 4th screening point are updated to the coordinates of the sampling point D, the distance between the sampling point E and the sampling point D calculated based on the 5th screening point, the 6th screening point, the 7th screening point, and the 8th screening point on the curve L2 is also the sampling interval of the second preset value multiplied by the first preset distance. Among the sampling points A, B, C, D, and E, the distance between any two sampling points on the curve L2 is the sampling interval of the second preset value multiplied by the first preset distance. In this way, the distance between any two sampling points on the curve can be made the same, avoiding the problem of discontinuity of the shaping form caused by the unequal distance between two adjacent selection points in the multiple selection points, thereby improving the shaping effect.

[0106] In some embodiments, the curve may not strictly fit the surface of the model to be shaped. In this case, the initial sampling point is obtained by interpolation sampling on the curve according to the sampling interval of the second preset value multiplied by the first preset distance, and then the final sampling point corresponding to the initial sampling point on the surface of the model to be shaped is found by the nearest neighbor search method to obtain the coordinates of the final sampling point on the surface of the model to be shaped. The coordinates of the sampling points used for calculation later refer to the coordinates of the final sampling point on the surface of the model to be shaped. The difference between the coordinates of the initial sampling point and the final sampling point is generally small.

[0107] Step S400: determining a neighborhood point set corresponding to each sampling point based on the coordinates of each sampling point, the coordinates of the vertices of the surface of the model to be shaped, and a first preset distance.

[0108] In some embodiments, the model to be shaped is a mesh model composed of a plurality of polygonal patches, each of which has a plurality of vertices.

[0109] In some implementations, for each sampling point, when a distance between a vertex in the neighborhood of the sampling point and the sampling point is less than or equal to a first preset distance, the vertex is determined as a neighborhood point in the neighborhood point set corresponding to the sampling point.

[0110] Optionally, starting from a sampling point, vertices in the neighborhood of the sampling point are traversed one by one according to a preset number of traversed vertices, and it is determined whether the distance between the vertex and the sampling point is less than or equal to a first preset distance.

[0111] Optionally, the number of traversed vertices may be dynamically adjusted in real time according to the size of the patch and the first preset distance to improve the execution efficiency of the algorithm.

[0112] An isolated point is a vertex in a mesh model that is not included in any facet and is not connected to other vertices. In some embodiments, vertices included in a neighborhood point set may be isolated points, which may affect subsequent calculations. Therefore, an isolated point detection is performed on each neighborhood point set to remove the isolated points.

[0113] Optionally, traverse each vertex in the neighborhood point set to determine whether the vertex has a neighboring vertex. If not, the vertex is an isolated point and the vertex is deleted from the neighborhood point set. If so, the vertex is not an isolated point and no operation is performed on the vertex.

[0114] Step S500: shaping the model to be shaped based on the coordinates of each sampling point and the coordinates of all neighborhood points in the corresponding neighborhood point set to obtain a shaped model.

[0115] See also Figure 7 , Figure 7 yes Figure 1 Detailed flow chart of step S500 in FIG. Figure 7 As shown, in some implementations, step S500 includes steps S510 to S550.

[0116] Step S510: determining a neighborhood patch set corresponding to each sampling point based on the coordinates of all neighborhood points in the neighborhood point set corresponding to each sampling point.

[0117] In some implementations, when all vertices of a patch are neighborhood points in a neighborhood point set corresponding to a sampling point, the patch is determined as a neighborhood patch in a neighborhood patch set corresponding to the sampling point.

[0118] See also Figure 8 , Figure 8 yes Figure 7 The schematic diagram of the principle of step S510 to step S550 in FIG. Figure 8 As shown, illustratively, sampling point A corresponds to neighborhood point set R1, sampling point B corresponds to neighborhood point set R2, sampling point C corresponds to neighborhood point set R3, sampling point D corresponds to neighborhood point set R4, and sampling point E corresponds to neighborhood point set R5. Figure 8The neighborhood points and neighborhood patches contained in each neighborhood point set are not shown in the figure, but it can be understood that the neighborhood points and neighborhood patches contained in each neighborhood point set are all located within the closed contour line range of the neighborhood point set.

[0119] In some implementations, before step S520, the method further includes: performing mesh optimization processing on the model to be shaped.

[0120] Optionally, when the number of neighborhood facets included in the neighborhood point set is greater than a first quantity threshold, it is determined that the amount of calculation is large, and at this time, the mesh edge length of the model to be shaped is increased.

[0121] Optionally, when the number of neighborhood facets included in the neighborhood point set is less than a second quantity threshold, it is determined that there are not enough neighborhood points and neighborhood facets for subsequent calculations. At this time, the shaping model is subjected to geometric processing such as long edge interruption and short edge folding of the mesh so that the relevant topology quality within the neighborhood point set is good and does not affect other areas that do not require shaping.

[0122] Optionally, the first quantity threshold and the second quantity threshold are calculated based on an average side length of neighborhood patches included in the neighborhood point set and a first preset distance.

[0123] Step S520: Calculate the shaping direction vectors corresponding to all the neighborhood points in the neighborhood point set corresponding to the sampling point based on the normal vector of each neighborhood patch in the neighborhood patch set corresponding to each sampling point.

[0124] In some implementations, step S520 includes steps S521 to S522.

[0125] Step S521: performing weighted calculation on the normal vectors of all neighboring facets according to the area of ​​each neighboring facet in the set of neighboring facets corresponding to each sampling point, so as to obtain a weighted normal vector corresponding to the sampling point.

[0126] In a mesh model, each face has a corresponding normal vector.

[0127] In some embodiments, for the neighborhood patch set corresponding to each sampling point, the normal vector of each neighborhood patch in the neighborhood patch set is multiplied by the numerical value of the area of ​​the neighborhood patch to obtain a weighted normal vector of the neighborhood patch, and then the weighted normal vectors of all neighborhood patches in the neighborhood patch set are added to obtain a weighted result normal vector, and the weighted result normal vector is normalized. The normalized weighted result normal vector is the weighted normal vector corresponding to the sampling point.

[0128] In other implementations, the average vector of the normal vectors of all neighboring facets in the set of neighboring facets corresponding to the sampling point is used as the normal vector corresponding to the sampling point.

[0129] Step S522: determining the shaping direction vectors of all neighborhood points in the neighborhood point set corresponding to the sampling point based on the weighted normal vector corresponding to each sampling point and the preset shaping type.

[0130] In some embodiments, the preset shaping types include wax-added shaping types and wax-reduced shaping types. According to the shaping degree, the wax-added shaping type further includes wax-added shaping types of different degrees such as smooth wax-added shaping types and sharp wax-added shaping types, and the wax-reduced shaping type further includes wax-reduced shaping types of different degrees such as smooth wax-reduced shaping types and sharp wax-reduced shaping types.

[0131] In some embodiments, when the preset shaping type belongs to the wax-added shaping type, the weighted normal vector corresponding to the sampling point is determined as the shaping direction vector of all the neighborhood points in the neighborhood point set corresponding to the sampling point. When the preset shaping type belongs to the wax-reduced shaping type, the inverse vector of the weighted normal vector corresponding to the sampling point is determined as the shaping direction vector of all the neighborhood points in the neighborhood point set corresponding to the sampling point.

[0132] In other embodiments, when the preset shaping type belongs to the wax-added shaping type, the normal vector corresponding to the sampling point is determined as the shaping direction vector of all the neighboring points in the neighborhood point set corresponding to the sampling point. When the preset shaping type belongs to the wax-reduced shaping type, the inverse vector of the normal vector corresponding to the sampling point is determined as the shaping direction vector of all the neighboring points in the neighborhood point set corresponding to the sampling point.

[0133] Step S530: Select a corresponding target calculation method according to the preset shaping type.

[0134] In some embodiments, when the preset shaping type is a smooth shaping type, a first target calculation method is selected. When the preset shaping type is a sharp shaping type, a second target calculation method is selected. In the first target calculation method and the second target calculation method, the calculation formula of the shaping height of each neighborhood point is different.

[0135] Step S540: Determine the shaping height of each neighborhood point based on the distance between the sampling point in the neighborhood point set corresponding to each sampling point and each neighborhood point by adopting a target calculation method.

[0136] In some implementations, step S540 includes steps S541 to S544.

[0137] Step S541: for each neighborhood point in the neighborhood point set corresponding to each sampling point, when the neighborhood point has not moved, a first distance between the neighborhood point and the sampling point is calculated based on the current coordinates of the neighborhood point and the coordinates of the sampling point.

[0138] Among them, the first distance between the neighborhood point and the sampling point is the Euclidean distance.

[0139] Step S542: Determine the shaping height of the neighborhood point according to the first distance using a target calculation method.

[0140] In some embodiments, in the first target calculation method, the calculation formula for the shaping height is:

[0141]

[0142] Among them, x represents the first distance between the neighborhood point and the sampling point, f(x) represents the shaping height calculated using the first target calculation method, a represents the first shaping strength coefficient, b represents the second shaping strength coefficient, and R represents the first preset distance.

[0143] Optionally, according to the number of times the neighborhood point moves, a recursive calculation formula is subsequently used to calculate the shaping height corresponding to the neighborhood point.

[0144] In some implementations, in the first target calculation method, when the neighborhood point has not moved, the calculation formula for the shaping height is:

[0145]

[0146] Among them, x1 represents the first distance between the neighborhood point and the sampling point when the neighborhood point has not moved, f(x1) represents the shaping height obtained by the first calculation using the first target calculation method, a represents the first shaping strength coefficient, b represents the second shaping strength coefficient, and R represents the first preset distance.

[0147] In some embodiments, in the second target calculation method, the calculation formula for the shaping height is:

[0148]

[0149] Wherein, H(x) represents the shaping height calculated using the second target calculation method.

[0150] Optionally, according to the number of times the neighborhood point moves, a recursive calculation formula is subsequently used to calculate the shaping height corresponding to the neighborhood point.

[0151] In some implementations, in the second target calculation method, when the neighborhood point has not moved, the calculation formula for the shaping height is:

[0152]

[0153] Wherein, H(x1) represents the shaping height obtained by the first calculation using the second target calculation method.

[0154] Step S543: When the neighborhood point has moved, a second distance between the neighborhood point and the sampling point is calculated based on the current coordinates of the neighborhood point and the coordinates of the sampling point.

[0155] In some implementations, in the first target calculation method and the second target calculation method, when the neighborhood point has moved, a recursive method is used to calculate the second distance between the neighborhood point and the sampling point.

[0156] In some implementations, in the first target calculation method, when the neighborhood point has moved once, the calculation formula for the second distance is:

[0157]

[0158] Wherein, x2 represents the second distance between the neighborhood point and the sampling point when the neighborhood point has moved once, c represents the second preset value, and n represents the number of times the neighborhood point has moved, and n is 1 at this time.

[0159] In some implementations, in the first target calculation method, when the neighborhood point has moved twice, the calculation formula for the second distance is:

[0160]

[0161] Wherein, x3 represents the second distance between the neighborhood point and the sampling point when the neighborhood point has moved twice, and n is 2 at this time.

[0162] In some implementations, in the first target calculation method, when the neighborhood point has moved three times, the calculation formula for the second distance is:

[0163]

[0164] Wherein, x4 represents the second distance between the neighborhood point and the sampling point when the neighborhood point has moved three times, and n is 3 at this time.

[0165] Thereafter, the formula for calculating the second distance after each movement of the neighboring point is similar.

[0166] The calculation formula of the second distance in the second target calculation method refers to the calculation formula of the second distance in the first target calculation method.

[0167] Step S544: using a target calculation method to update the shaping height of the neighborhood point according to the second distance.

[0168] In some implementations, the shaping heights of neighborhood points are updated recursively based on a target calculation method.

[0169] In some implementations, in the first target calculation method, when the neighborhood point has moved once, the calculation formula for the shaping height is:

[0170]

[0171] Among them, f(x2) represents the shaping height obtained by the second calculation using the first target calculation method (that is, the shaping height after the first update).

[0172] In some implementations, in the first target calculation method, when the neighborhood point has moved twice, the calculation formula for the shaping height is:

[0173]

[0174] Among them, f(x3) represents the shaping height obtained by the third calculation using the first target calculation method (that is, the shaping height after the second update).

[0175] In some implementations, in the first target calculation method, when the neighborhood point has moved three times, the calculation formula for the shaping height is:

[0176]

[0177] Among them, f(x4) represents the shaping height obtained by the fourth calculation using the first target calculation method (that is, the shaping height after the third update). Thereafter, the calculation formula for updating the shaping height using the first target calculation method is similar.

[0178] See also Fig. 9 , Fig. 9 is a schematic diagram of a morphological curve obtained by using the first target calculation method provided in an embodiment of the present application. At this time, the first preset distance is 0.5 mm, and the value of the first plastic strength coefficient is 0.3. Fig. 9 As shown, for example, curve f1 is the morphological curve obtained by the first target calculation method for the first time, curve f2 is the morphological curve obtained by the second target calculation method for the first target, curve f3 is the morphological curve obtained by the third target calculation method for the first target, curve f4 is the morphological curve obtained by the fourth target calculation method for the first target, and curve f5 is the morphological curve obtained by the fifth target calculation method for the first target. It can be seen that when the number of calculations increases, the top fluctuations of the morphological curve tend to be smooth. The morphological deviation of curve f1 and curve f5 is the source of the convex and concave feeling of the side.

[0179] When the shaping strength coefficient remains unchanged, the larger the first preset distance, the smaller the fluctuation of the top of the shape curve, and the smoother it tends to be. When the first preset distance remains unchanged, the smaller the shaping strength coefficient, the smaller the fluctuation of the top of the shape curve, and the smoother it tends to be.

[0180] like Figure 8As shown, exemplarily, sampling point A corresponds to neighborhood point set R1, sampling point B corresponds to neighborhood point set R2, sampling point C corresponds to neighborhood point set R3, sampling point D corresponds to neighborhood point set R4, and sampling point E corresponds to neighborhood point set R5. For each neighborhood point in neighborhood point set R1, the target calculation method is used to perform the first calculation to obtain the shaping height. For each neighborhood point in neighborhood point set R1 that also belongs to neighborhood point set R2, the target calculation method is used to perform the second calculation to obtain the shaping height after updating once. For each neighborhood point in neighborhood point set R1 that also belongs to neighborhood point set R2 and neighborhood point set R3, the target calculation method is used to perform the third calculation to obtain the shaping height after updating twice. For each neighborhood point in neighborhood point set R1 that also belongs to neighborhood point set R2, neighborhood point set R3, and neighborhood point set R4, the target calculation method is used to perform the fourth calculation to obtain the shaping height after updating three times. For each neighborhood point in the neighborhood point set R1 that also belongs to the neighborhood point set R2, the neighborhood point set R3, the neighborhood point set R4, and the neighborhood point set R5, the target calculation method is used to perform the fifth calculation to obtain the shaping height after updating 4 times, and so on, until the final shaping height of each neighborhood point is obtained. For example, for a neighborhood point that only belongs to the neighborhood point set R1, the corresponding shaping height satisfies Fig. 9 For the neighborhood points in the neighborhood point set R1 that also belong to the neighborhood point set R2, the corresponding shaping height satisfies Fig. 9 For the neighborhood points in the neighborhood point set R1 that belong to both the neighborhood point set R2 and the neighborhood point set R3, the corresponding shaping height satisfies Fig. 9 For the neighborhood points in the neighborhood point set R1 that belong to the neighborhood point set R2, the neighborhood point set R3, and the neighborhood point set R4 at the same time, the corresponding shaping height satisfies Fig. 9 For the neighborhood points in the neighborhood point set R1 that belong to the neighborhood point set R2, the neighborhood point set R3, the neighborhood point set R4, and the neighborhood point set R5, the corresponding shaping height satisfies Fig. 9 Curve f5 in .

[0181] It is understandable that in some embodiments, because the model shaping method is executed in real time, that is, the shaping model is calculated and generated in real time during the mouse dragging process, each time a sampling point is determined, the neighborhood point set corresponding to the sampling point is determined, and then the shaping height of the neighborhood point is calculated in real time and the shaping model is generated, rather than generating the shaping model only after the final shaping height of the neighborhood point is determined. Each time the shaping height of the neighborhood point is calculated, it is determined whether the neighborhood point has moved and how many times it has moved based on the calculation record, and then the corresponding calculation formula is used to calculate the shaping height.

[0182] In some embodiments, when an area in a shaping model that has been shaped is reshaped, the coordinates of the screening point are the coordinates of the screening point when the model to be shaped has not been shaped, and the coordinates of the neighborhood point are the coordinates of the neighborhood point when the model to be shaped has been shaped.

[0183] In some implementations, in the second target calculation method, when the neighborhood point has moved once, the calculation formula for the shaping height is:

[0184]

[0185] Among them, H(x2) represents the shaping height obtained by the second calculation using the second target calculation method (that is, the shaping height after the first update).

[0186] In some implementations, in the second target calculation method, when the neighborhood point has moved twice, the calculation formula for the shaping height is:

[0187]

[0188] Among them, H(x3) represents the shaping height obtained by the third calculation using the second target calculation method (that is, the shaping height after the second update).

[0189] In some implementations, in the second target calculation method, when the neighborhood point has moved three times, the calculation formula for the shaping height is:

[0190]

[0191] Among them, H(x4) represents the shaping height obtained by the fourth calculation using the second target calculation method (that is, the shaping height after the third update). Thereafter, the calculation formula for updating the shaping height using the second target calculation method is similar.

[0192] In the second target calculation method, x1, x2, x3, x4, etc. are calculated by referring to the calculation formula of the second distance in the first target calculation method and using the calculation formula of the shaping height in the second target calculation method.

[0193] See also Fig.10 , Fig.10 is a schematic diagram of a morphological curve obtained by using the second target calculation method provided in an embodiment of the present application. At this time, the first preset distance is 0.5 mm, and the value of the first plastic strength coefficient is 0.3. Fig.10As shown, for example, curve f6 is the morphological curve obtained by the first calculation using the second target calculation method, curve f7 is the morphological curve obtained by the second calculation using the second target calculation method, curve f8 is the morphological curve obtained by the third calculation using the second target calculation method, curve f9 is the morphological curve obtained by the fourth calculation using the second target calculation method, and curve f10 is the morphological curve obtained by the fifth calculation using the second target calculation method. It can be seen that when the number of calculations increases, the top fluctuations of the morphological curve tend to be smooth. The morphological deviation of curve f6 and curve f10 is the source of the convex and concave feeling of the side.

[0194] When the shaping strength coefficient remains unchanged, the larger the first preset distance, the smaller the fluctuation of the top of the shape curve, and the smoother it tends to be. When the first preset distance remains unchanged, the smaller the shaping strength coefficient, the smaller the fluctuation of the top of the shape curve, and the smoother it tends to be.

[0195] The method of recursively updating the shaping height using the second target calculation method refers to the above description.

[0196] By using the first target calculation method or the second target calculation method to calculate the shaping height, the shaping shape can be accurately controlled so that the shaping shape after multiple shaping processes are superimposed still meets the user's shape requirements.

[0197] Step S550: Move the neighborhood point based on the shaping direction vector and shaping height corresponding to each neighborhood point in all neighborhood point sets to shape the model to be shaped, thereby obtaining a shaped model.

[0198] Optionally, each neighborhood point is moved along the corresponding shaping direction vector and shaping height to achieve shaping of the model to be shaped, thereby obtaining the shaped model. This process is calculated in real time.

[0199] In some implementations, after step S500, the method further includes: performing smoothing processing on the shaping model to obtain a final shaping model.

[0200] In some embodiments, the mesh of the shaping model is Laplace smoothed according to a preset smoothness and weight factor. In this way, it is possible to ensure that the shaped shape is not affected too much by the smoothing process, retain more original shape features, and ensure that the shaped shape of the neighborhood point set of each sampling point and the shaped shape of the neighborhood point set of the remaining sampling points are evenly superimposed and transitioned.

[0201] See also Fig.11A and Fig. 11B , Fig.11A is a first schematic diagram of a first shaping model obtained by performing one shaping process using a first target calculation method according to an embodiment of the present application, Fig. 11B: is a schematic diagram of the first transverse cross-sectional profile of the first shaping model provided in the embodiment of the present application. At this time, the first preset distance is 0.5 mm, and the value of the first shaping strength coefficient is 0.3. Fig.11A As shown, the smooth wax-added shaping form and the smooth wax-reduced shaping form in the first shaping model 2 are both continuous without breaks, and there are no abrupt concave-convex feelings on both sides and the top. Fig. 11B As shown, in the cross-sectional contour L3 of the first shaping model 2 at the cross section 21, the partial cross-sectional contour in area A3 represents the shaping effect of smooth wax reduction shaping, and the partial cross-sectional contour in area A4 represents the shaping effect of smooth wax addition shaping, which further illustrates that the shaping shape has no abrupt concave-convex feeling.

[0202] See also Fig. 11C and Fig.11D , Fig. 11C is a second schematic diagram of a first shaping model obtained by performing one shaping process using a first target calculation method according to an embodiment of the present application, Fig.11D : is a schematic diagram of the first longitudinal cross-sectional profile of the first shaping model provided in the embodiment of the present application. At this time, the first preset distance is 0.5 mm, and the value of the first shaping strength coefficient is 0.3. Fig. 11C As shown, the smooth wax-added shaping shape in the first shaping model 2 is continuous without any breaks, and there is no abrupt concave-convex feeling on both sides and the top. Fig.11D As shown, in the cross-sectional contour L4 of the first shaping model 2 at the cross section 22, the partial cross-sectional contour within the area A5 represents the shaping effect of smooth wax shaping, which further illustrates that the smooth wax shaping shape is continuous without breaks, and the shaping shape has no abrupt concave-convex feeling.

[0203] See also Fig.11E and Fig.11F , Fig.11E is a first schematic diagram of a second shaping model obtained by performing one shaping using a second target calculation method provided in an embodiment of the present application, Fig.11F is a schematic diagram of the second transverse cross-sectional profile of the second shaping model provided in an embodiment of the present application. The first preset distance is 0.5 mm, and the value of the first shaping strength coefficient is 0.3. Fig.11E As shown, the sharp wax-added shaping and sharp wax-reduced shaping in the second shaping model 3 are both continuous without breaks, and there is no abrupt concave-convex feeling on both sides and the top. Fig.11F As shown, in the cross-sectional contour L5 of the second shaping model 3 at the cross section 31, the partial cross-sectional contour in area A6 represents the shaping effect of sharp wax reduction shaping, and the partial cross-sectional contour in area A7 represents the shaping effect of sharp wax addition shaping, which further illustrates that the shaping form has no abrupt concave-convex feeling.

[0204] See also Fig.11G and Fig.11H , Fig.11G is a second schematic diagram of a second shaping model obtained by performing one shaping process using a second target calculation method according to an embodiment of the present application, Fig.11H : is a schematic diagram of the second longitudinal cross-sectional profile of the second shaping model provided in the embodiment of the present application. At this time, the first preset distance is 0.5 mm, and the value of the first shaping strength coefficient is 0.3. Fig.11G As shown, the sharp wax-added shaping in the second shaping model 3 is continuous without any breaks, and there is no abrupt concave-convex feeling on both sides and the top. Fig.11H As shown, in the cross-sectional contour L6 of the second shaping model 3 at the cross section 32, the partial cross-sectional contour within the area A8 represents the shaping effect of sharp wax shaping, which further illustrates that the sharp wax shaping shape is continuous without breaks, and the shaping shape has no abrupt convexity or concavity.

[0205] Also, see FIG. 11A to FIG. 11H It can be seen that the shaping height of sharp shaping is higher than that of smooth shaping, and the shaping effect is more obvious.

[0206] In some implementations, multiple superimposed shaping processes may be performed on a shaping area of ​​the model to be shaped.

[0207] See also Fig. 12A and Fig. 12B , Fig. 12A is a first schematic diagram of a third shaping model obtained by performing shaping twice using a second target calculation method provided in an embodiment of the present application, Fig. 12B : is a schematic diagram of the superposition of the transverse cross-sectional profile of the second shaping of the third shaping model provided in the embodiment of the present application. At this time, the first preset distance is 0.5 mm, and the value of the first shaping strength coefficient is 0.3. Fig. 12A As shown, the sharp wax-added sculpting shapes obtained by the second sculpting in the third sculpting model 4 are all continuous without breaks, and there are no abrupt concave-convex feelings on both sides and the top. Fig. 12B As shown, in the cross-sectional contour L7 of the third shaping model 4 at the cross-sectional area 41, the partial cross-sectional contour within the area A9 represents the shaping effect of two sharp wax shaping. This means that by using the second target calculation method to calculate the shaping height, the shaping shape can be accurately controlled so that the shaping shape after multiple shaping processes are superimposed still has no abrupt convexity and concavity, which meets the user's shape requirements.

[0208] See also Fig. 12C and Fig.12D , Fig. 12C It is a second schematic diagram of a third shaping model obtained by performing two shaping operations using a second target calculation method provided in an embodiment of the present application. Fig.12D: is a schematic diagram of the superposition of the longitudinal cross-sectional profile of the second shaping of the third shaping model provided in the embodiment of the present application. At this time, the first preset distance is 0.5 mm, and the value of the first shaping strength coefficient is 0.3. Fig. 12C As shown, the sharp wax-added sculpting shapes obtained by the second sculpting in the third sculpting model 4 are all continuous without breaks, and there are no abrupt concave-convex feelings on both sides and the top. Fig.12D As shown, in the cross-sectional contour L8 of the third shaping model 4 at the cross-sectional area 42, the partial cross-sectional contour within the area A10 represents the shaping effect of two sharp wax shaping. This means that by using the second target calculation method to calculate the shaping height, the shaping shape can be accurately controlled, so that the shaping shape after multiple shaping processes are superimposed is still coherent and without breaks, and has no abrupt convexity or concavity, which meets the user's shape requirements.

[0209] The effect diagram of multiple shaping processes performed using the first target calculation method is not shown, but by using the first target calculation method to calculate the shaping height, the shaping shape can also be accurately controlled so that the shaping shape after multiple shaping processes are superimposed still has no abrupt convexity or concavity, meeting the user's shape requirements.

[0210] See also Fig.13 and Fig.14 , Fig.13 is a schematic diagram of a fourth shaping model obtained by performing shaping multiple times using the model shaping method provided in an embodiment of the present application, Fig.14 Schematic diagram of a fifth shaping model obtained by performing multiple shaping operations using the model shaping method provided in the embodiment of the present application. Fig.13 As shown, the fourth shaping model 5 is a mesh model, which is continuous without breaks in the multiple wax addition shaping area and the multiple wax reduction shaping area, has no abrupt concave-convex feeling on both sides and the top, and has a uniform mesh without spikes, and has good mesh quality. Fig.14 As shown, the multiple wax-adding shaping areas and the multiple wax-reducing shaping areas of the fifth shaping model 6 are both continuous without breaks, and there are no abrupt bumps on the sides and the top, indicating that the model shaping method provided in the present application has a very good shaping effect.

[0211] In summary, the model shaping method provided in the embodiment of the present application has the following advantages:

[0212] 1. By determining the coordinates of multiple sampling points based on the coordinates of multiple selection points and a first preset distance, and then further shaping the model to be shaped based on the coordinates of the multiple sampling points, a shaping model is obtained, which can make the distance between two adjacent sampling points in the multiple sampling points equal, avoiding the problem of incoherent shaping caused by the unequal distance between two adjacent selection points in the multiple selection points, thereby improving the shaping effect.

[0213] 2. By using the first target calculation method or the second target calculation method to calculate the shaping height, the shaping shape can be accurately controlled so that the shaping shape after multiple shaping processes are superimposed still meets the user's shape requirements.

[0214] 3. By screening multiple selection points to obtain multiple screening points, it is possible to avoid the situation where the selection points are too dense.

[0215] 4. By further determining the coordinates of the plurality of sampling points based on the coordinates of the plurality of screening points and the first preset distance, it is possible to avoid the situation where the screening points are too sparse.

[0216] 5. By using the coordinates of the screening points as the coordinates of the screening points when the model to be shaped has not been shaped, when the shaping process is repeated, the sampling points calculated based on the screening points will be close to the surface of the model to be shaped, so that the shaping effect can be naturally superimposed.

[0217] 6. By fitting a curve based on Y+1 screening points each time, the fitted curve can be basically consistent with the trajectory of the user dragging the mouse in real time, thereby improving the accuracy of shaping.

[0218] 7. By using the first target calculation method or the second target calculation method to calculate the shaping height, the shaping shape can be accurately controlled so that the shaping shape after multiple shaping processes are superimposed still meets the user's shape requirements.

[0219] See also Fig.15 , Fig.15 Schematic diagram of the structure of the model shaping device provided in the embodiment of the present application. Fig.15 As shown, the model shaping device 300 includes an acquisition module 310 and a processing module 320 .

[0220] In some embodiments, the acquisition module 310 is used to acquire the model to be shaped, and the model to be shaped is a dental restoration model.

[0221] In some embodiments, the processing module 320 is used to receive a first control instruction, determine a plurality of selection points on the surface of the model to be shaped according to the first control instruction; determine the coordinates of a plurality of sampling points based on the coordinates of the plurality of selection points and a first preset distance; determine a neighborhood point set corresponding to each sampling point based on the coordinates of each sampling point, the coordinates of the vertices of the surface of the model to be shaped, and the first preset distance; and shape the model to be shaped based on the coordinates of each sampling point and the coordinates of all neighborhood points in the corresponding neighborhood point set to obtain a shaped model.

[0222] See also Fig.16 , Fig.16 Schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Fig.16As shown, the electronic device 400 includes: one or more processors 410 and a memory 420, Fig.16 A processor 410 is taken as an example.

[0223] In some implementations, the processor 410 and the memory 420 may be connected via a bus or other means. Fig.16 The example of connecting through bus is taken in the following.

[0224] In some embodiments, the processor 410 is used to obtain a model to be shaped, which is a dental restoration model; receive a first control instruction, and determine a plurality of selected points on the surface of the model to be shaped according to the first control instruction; determine the coordinates of a plurality of sampling points based on the coordinates of the plurality of selected points and a first preset distance; determine a neighborhood point set corresponding to each sampling point based on the coordinates of each sampling point, the coordinates of the vertices on the surface of the model to be shaped, and the first preset distance; and shape the model to be shaped based on the coordinates of each sampling point and the coordinates of all neighborhood points in the corresponding neighborhood point set to obtain a shaped model.

[0225] In some embodiments, the memory 420, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as program instructions / modules of the model shaping method in the embodiment of the present application. The processor 410 executes various functional applications and data processing of the electronic device 400 by running the non-volatile software programs, instructions and modules stored in the memory 420, that is, the model shaping method of the above method embodiment is implemented.

[0226] In some embodiments, the memory 420 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the electronic device 400, etc. In addition, the memory 420 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 420 may optionally include a memory remotely arranged relative to the processor 410, and these remote memories may be connected to the controller via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0227] In some embodiments, one or more modules are stored in the memory 420, and when executed by one or more processors 410, the model shaping method in any of the above method embodiments is executed, for example, the above described Figure 1 The method comprises steps S100 to S500.

[0228] In some embodiments, the electronic device may be a chip, such as a data processor (DPU) chip used in a data center, or the electronic device may be a network interface card including a chip and multiple interfaces (such as a PCI / PCIE interface, a UART interface, a USB interface, etc.), or the electronic device may be a traditional server, or a server including a network interface card or a chip, wherein the server includes a host and a data processor, wherein the data processor is used to dispatch messages to the host or the data processor itself for processing, and the host is used to process messages dispatched by the data processor.

[0229] Please refer to Fig.17 , Fig.17 5 is a structural block diagram of a computer-readable storage medium provided in an embodiment of the present application. The computer-readable storage medium 500 stores a program code 510, which can be called by a processor to execute the model shaping method described in the above method embodiment.

[0230] The computer-readable storage medium 500 may be an electronic memory such as a flash memory, an EEPROM (Electrically Erasable Programmable Read-Only Memory), an EPROM, a hard disk or a ROM. Optionally, the computer-readable storage medium includes a non-transitory computer-readable storage medium. The computer-readable storage medium 500 has a storage space for program codes for executing any method steps in the above-mentioned model shaping method. These program codes may be read from or written to one or more computer program products. The program code may be compressed, for example, in an appropriate form.

[0231] In some implementations, the embodiments of the present application also provide a computer program product, including a computer program, which implements the above-mentioned model shaping method when executed by a processor.

[0232] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium 500. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited thereto.

[0233] In summary, the present application provides a model shaping method and electronic device, the model shaping method comprising: obtaining a model to be shaped, the model to be shaped being a dental restoration model; receiving a first control instruction, and determining a plurality of selection points on the surface of the model to be shaped according to the first control instruction; determining the coordinates of a plurality of sampling points based on the coordinates of the plurality of selection points and a first preset distance; determining a neighborhood point set corresponding to each sampling point based on the coordinates of each sampling point, the coordinates of the vertices on the surface of the model to be shaped, and the first preset distance; shaping the model to be shaped based on the coordinates of each sampling point and the coordinates of all the neighborhood points in the corresponding neighborhood point set to obtain a shaping model. The present application determines the coordinates of a plurality of sampling points based on the coordinates of a plurality of selection points and a first preset distance, and then further shapes the model to be shaped based on the coordinates of the plurality of sampling points to obtain a shaping model, so that the distance between two adjacent sampling points among the plurality of sampling points is equal, and avoids the problem of discontinuity in shaping morphology caused by unequal distances between two adjacent selection points among the plurality of selection points, thereby improving the shaping effect.

[0234] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A model shaping method, characterized in that: include: Acquire a model to be shaped, wherein the model to be shaped is a tooth restoration model; receiving a first control instruction, and determining a plurality of selected points on the surface of the model to be shaped according to the first control instruction; determining coordinates of a plurality of sampling points based on the coordinates of the plurality of selected points and a first preset distance; Determine a neighborhood point set corresponding to each sampling point based on the coordinates of each sampling point, the coordinates of the vertices of the surface of the model to be shaped, and the first preset distance; The model to be shaped is shaped based on the coordinates of each sampling point and the coordinates of all neighborhood points in the corresponding neighborhood point set to obtain a shaped model.

2. The model shaping method according to claim 1, characterized in that: The determining the coordinates of the plurality of sampling points based on the coordinates of the plurality of selected points and the first preset distance comprises: Filtering the plurality of selection points based on the coordinates of the plurality of selection points and the first preset distance to obtain a plurality of filter points; The coordinates of a plurality of sampling points on the surface of the model to be shaped are determined based on the coordinates of the plurality of screening points and the first preset distance.

3. The model shaping method according to claim 2, characterized in that: The step of screening the plurality of selected points based on the coordinates of the plurality of selected points and the first preset distance to obtain a plurality of screening points includes: When the distance between the Nth selection point and the N+1th selection point in the viewing angle direction is greater than a first preset value multiplied by the first preset distance, the N+1th selection point is determined as the screening point, where N is a positive integer and the initial value is 1; Let N=N+1, and return to execute the step of determining the N+1th selection point as the screening point when the distance between the Nth selection point and the N+1th selection point in the viewing direction is greater than a first preset value multiplied by the first preset distance.

4. The model shaping method according to claim 2, characterized in that: The step of determining the coordinates of a plurality of sampling points on the surface of the model to be shaped based on the coordinates of the plurality of screening points and the first preset distance comprises: When the total number of the plurality of screening points is 2, determining a connecting line segment of the two screening points based on the coordinates of the two screening points; Performing interpolation sampling on the connecting line segment according to a sampling interval of a second preset value multiplied by the first preset distance to obtain coordinates of sampling points on the surface of the model to be shaped, and also determining the first screening point as the sampling point to obtain the plurality of sampling points; When the total number of the plurality of screening points is greater than 2, a curve is fitted based on the coordinates of the plurality of screening points, and interpolation sampling is performed on the curve at a sampling interval of the second preset value multiplied by the first preset distance to obtain the plurality of sampling points.

5. The model shaping method according to claim 4, characterized in that: The coordinates of the screening points are the coordinates of the screening points when the model to be shaped has not been shaped, and when the total number of the plurality of screening points is greater than 2, a curve is fitted based on the coordinates of the plurality of screening points, and interpolation sampling is performed on the curve at a sampling interval of the second preset value multiplied by the first preset distance to obtain the plurality of sampling points, including: When the total number of the plurality of screening points is greater than 2, constructing a first queue including the Xth screening point, the X+1th screening point, and up to the X+Yth screening point, wherein X is a positive integer and its initial value is 1, Y is a positive integer greater than 1 and is a preset value, and the number of screening points included in the first queue is Y+1; Fitting a curve based on the coordinates of all the screening points in the first queue, and performing interpolation sampling on the curve at a sampling interval of the second preset value multiplied by the first preset distance, to obtain a plurality of sampling points including the Xth screening point in the first queue; Update the coordinates of the X+Yth screening point to the coordinates of the sampling point that is closest to the X+Yth screening point; Let X=X+1, and return to execute the construction of the first queue including the Xth screening point, the X+1th screening point, the X+2th screening point and the X+Yth screening point.

6. The model shaping method according to claim 5, characterized in that: The coordinate fitting curve based on all the screening points in the first queue and performing interpolation sampling on the curve according to a sampling interval of the second preset value multiplied by the first preset distance to obtain a plurality of sampling points including the Xth screening point in the first queue include: Calculate the average coordinate point of the X+Y-1th screening point and the X+Yth screening point in the first queue and use it as the interpolation point; Fitting the curve based on the coordinates of all the screening points in the first queue and the coordinates of the interpolation points; Interpolation sampling is performed on the curve based on the length of the curve and a sampling interval of the second preset value multiplied by the first preset distance to obtain a plurality of sampling points including the Xth screening point in the first queue.

7. The model shaping method according to claim 1, characterized in that: The model to be shaped is a mesh model composed of a plurality of polygonal patches, each of which has a plurality of vertices. The model to be shaped is shaped based on the coordinates of each sampling point and the coordinates of all neighboring points in the corresponding neighboring point set to obtain a shaped model, including: Determine a neighborhood patch set corresponding to each sampling point based on the coordinates of all neighborhood points in the neighborhood point set corresponding to each sampling point; Calculating the shaping direction vectors corresponding to all the neighboring points in the neighboring point set corresponding to the sampling point based on the normal vector of each of the neighboring face patches in the neighboring face patch set corresponding to each of the sampling points; Select the corresponding target calculation method according to the preset shaping type; Determine the shaping height of each of the neighborhood points by using the target calculation method based on the distance between the sampling point and each of the neighborhood points in the neighborhood point set corresponding to each of the sampling points; Based on the shaping direction vector and shaping height corresponding to each of the neighborhood points in the neighborhood point set, the neighborhood point is moved to shape the model to be shaped, thereby obtaining the shaped model.

8. The model shaping method according to claim 7, characterized in that: The calculating, based on the normal vector of each of the neighborhood facets in the neighborhood facet set corresponding to each of the sampling points, the shaping direction vectors corresponding to all the neighborhood points in the neighborhood point set corresponding to the sampling point comprises: Performing weighted calculation on the normal vectors of all the neighborhood facets according to the area of ​​each neighborhood facet in the neighborhood facet set corresponding to each sampling point, to obtain a weighted normal vector corresponding to the sampling point; Based on the weighted normal vector corresponding to each of the sampling points and the preset shaping type, a shaping direction vector of all neighborhood points in a neighborhood point set corresponding to the sampling point is determined.

9. The model shaping method according to claim 7, characterized in that: The method of using the target calculation method to determine the shaping height of each of the neighborhood points based on the distance between the sampling point and each of the neighborhood points in the neighborhood point set corresponding to each of the sampling points includes: For each of the neighborhood points in the neighborhood point set corresponding to each of the sampling points, when the neighborhood point has not moved, calculating a first distance between the neighborhood point and the sampling point based on the current coordinates of the neighborhood point and the coordinates of the sampling point; Determine the shaping height of the neighborhood point according to the first distance using the target calculation method; When the neighborhood point has moved, calculating a second distance between the neighborhood point and the sampling point based on the current coordinates of the neighborhood point and the coordinates of the sampling point; The target calculation method is used to update the shaping height of the neighborhood point according to the second distance.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the model shaping method according to any one of claims 1 to 9.

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