CN114445555A - Shoe tree modeling adjustment method, device, equipment and storage medium - Google Patents
Shoe tree modeling adjustment method, device, equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a shoe tree modeling adjustment method, a device, equipment and a storage medium, wherein the method comprises the following steps: carrying out three-dimensional modeling initialization on a shoe tree to generate an initial shoe tree three-dimensional model; determining a plurality of foot characteristic points based on foot big data analysis, and mapping the plurality of foot characteristic points to the initial shoe tree three-dimensional model to obtain a first shoe tree model containing model characteristic points; and receiving the adjustment operation of the first shoe tree model, adjusting the first shoe tree model according to the adjustment operation to generate a second shoe tree model, and displaying the second shoe tree model. This scheme is showing the operand that has reduced the shoe tree adjustment of modelling, has promoted shoe tree modeling efficiency, and intelligent degree is high.
Description
Technical Field
The embodiment of the application relates to the field of computers, in particular to a shoe tree modeling adjustment method, device, equipment and storage medium.
Background
In the existing shoe tree modeling process, a designer usually carries out three-dimensional design through design software or scans feet, and automatic modeling is realized according to scanning results, but the method has poor flexibility. When the modeling result needs to be adjusted, the process is complex and the adjusting effect is not good.
Disclosure of Invention
The embodiment of the invention provides a shoe tree modeling adjustment method, a shoe tree modeling adjustment device, shoe tree modeling adjustment equipment and a storage medium, which are used for remarkably reducing the calculation amount of shoe tree modeling adjustment, improving the shoe tree modeling efficiency and achieving high intelligent degree.
In a first aspect, an embodiment of the present invention provides a method for adjusting shoe last modeling, including:
carrying out three-dimensional modeling initialization on a shoe tree to generate an initial shoe tree three-dimensional model;
determining a plurality of foot characteristic points based on foot big data analysis, and mapping the plurality of foot characteristic points to the initial shoe tree three-dimensional model to obtain a first shoe tree model containing model characteristic points;
and receiving the adjustment operation of the first shoe tree model, adjusting the first shoe tree model according to the adjustment operation to generate a second shoe tree model, and displaying the second shoe tree model.
Optionally, the initializing the three-dimensional modeling of the shoe tree to generate an initial three-dimensional model of the shoe tree includes:
receiving selection operation of model initialization parameters, performing shoe tree three-dimensional modeling initialization according to the initialization parameters selected by the selection operation, and generating an initial shoe tree three-dimensional model, wherein the initialization parameters comprise gender information and foot fuzzy characteristic information.
Optionally, the determining a plurality of foot feature points based on the foot big data analysis, and mapping the plurality of foot feature points into the initial last three-dimensional model includes:
analyzing the three-dimensional foot image to obtain a plurality of characteristic areas, and determining corresponding foot characteristic points according to each characteristic area;
and mapping the position relation based on the foot characteristic points to the initial shoe tree three-dimensional model.
Optionally, the adjusting operation further includes a drag operation on the non-characteristic point region.
Optionally, adjusting the first last model according to the adjustment operation to generate a second last model, including:
when the adjustment operation is a feature point dragging operation, determining a correlation displacement distance of a correlation feature point according to the displacement distance of the feature point dragging operation;
and adjusting the first shoe tree model according to the displacement distance and the associated displacement distance to generate a second shoe tree model.
Optionally, the determining the associated displacement distance of the associated feature point according to the displacement distance of the feature point dragging operation includes:
and determining a plurality of associated feature points with different distance levels according to the feature points selected by the feature point dragging operation, and respectively determining associated displacement distances of the associated feature points for use according to the displacement distances of the feature point dragging operation and the different distance levels.
Optionally, adjusting the first last model according to the adjustment operation to generate a second last model, including:
when the adjustment operation is a non-feature point area dragging operation, determining an adjustment sub-area corresponding to a touch point of the non-feature point area dragging operation;
and adjusting the sub-adjustment area according to the dragging distance of the non-feature point area dragging operation.
In a second aspect, an embodiment of the present invention further provides a shoe last modeling adjustment apparatus, including:
the initialization module is used for carrying out shoe tree three-dimensional modeling initialization and generating an initial shoe tree three-dimensional model;
the mapping module is used for determining a plurality of foot characteristic points based on foot big data analysis, mapping the plurality of foot characteristic points to the initial shoe tree three-dimensional model to obtain a first shoe tree model containing model characteristic points;
and the adjusting module is used for receiving the adjusting operation of the first shoe tree model, adjusting the first shoe tree model according to the adjusting operation to generate a second shoe tree model, and displaying the second shoe tree model.
In a third aspect, an embodiment of the present invention further provides a shoe last modeling adjustment apparatus, including:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors implement the method for adjusting shoe tree modeling according to the embodiment of the present invention.
In a fourth aspect, embodiments of the present invention further provide a storage medium storing computer-executable instructions, which are used to execute the shoe tree modeling adjustment method according to the embodiments of the present invention when executed by a computer processor.
In the embodiment of the invention, an initial shoe tree three-dimensional model is generated by initializing shoe tree three-dimensional modeling; determining a plurality of foot characteristic points based on foot big data analysis, and mapping the plurality of foot characteristic points to the initial shoe tree three-dimensional model to obtain a first shoe tree model containing model characteristic points; and receiving the adjustment operation of the first shoe tree model, adjusting the first shoe tree model according to the adjustment operation to generate a second shoe tree model, and displaying the second shoe tree model. Therefore, the calculation amount of shoe tree modeling adjustment is remarkably reduced, the shoe tree modeling efficiency is improved, and the intelligent degree is high.
Drawings
Fig. 1 is a flowchart of a method for modeling and adjusting a shoe last according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for performing feature point mapping according to an embodiment of the present invention;
FIG. 3 is a flowchart of another shoe tree modeling adjustment method according to an embodiment of the present invention;
FIG. 4 is a flowchart of another shoe tree modeling adjustment method according to an embodiment of the present invention;
fig. 5 is a block diagram illustrating a structure of a shoe last modeling adjustment apparatus according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a shoe last modeling adjustment apparatus according to an embodiment of the present invention.
Detailed Description
The embodiments of the present invention will be described in further detail with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad invention. It should be further noted that, for convenience of description, only some structures, not all structures, relating to the embodiments of the present invention are shown in the drawings.
The terms first, second and the like in the description and in the claims of the present application are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that embodiments of the application may be practiced in sequences other than those illustrated or described herein, and that the terms "first," "second," and the like are generally used herein in a generic sense and do not limit the number of terms, e.g., the first term can be one or more than one. In addition, "and/or" in the specification and claims means at least one of connected objects, a character "/" generally means that a preceding and succeeding related objects are in an "or" relationship.
Fig. 1 is a flowchart of a shoe tree modeling adjustment method provided in an embodiment of the present invention, which can be executed by a server or a user terminal, and specifically includes the following steps:
and S101, initializing three-dimensional modeling of the shoe tree to generate an initial shoe tree three-dimensional model.
Wherein, the initial shoe tree three-dimensional model is an initialized model generated by the shoe tree according to preset parameters. For example, the initialization of the three-dimensional model of the last may be performed by loading the saved associated initialization file. Preferably, the three-dimensional model of the initial shoe tree is displayed through the display interface after the three-dimensional model of the initial shoe tree is generated.
In one embodiment, the initializing the three-dimensional last model includes: receiving selection operation of model initialization parameters, performing shoe tree three-dimensional modeling initialization according to the initialization parameters selected by the selection operation, and generating an initial shoe tree three-dimensional model, wherein the initialization parameters comprise gender information and foot fuzzy characteristic information. And initializing the corresponding model according to the selected initialization parameters in the initialization process of the three-dimensional model of the shoe tree, wherein the initialization parameters are sex information and foot fuzzy characteristic information. The gender information comprises males and females, and the foot fuzzy characteristic information represents information which roughly describes the size and shape of the feet and is in different shape types. Illustratively, the foot shape is thin or thick, and the like, according to the foot-back arc information in the foot.
Step S102, determining a plurality of foot characteristic points based on foot big data analysis, and mapping the plurality of foot characteristic points to the initial shoe tree three-dimensional model to obtain a first shoe tree model containing model characteristic points.
In one embodiment, a plurality of foot feature points are determined based on big data analysis, wherein the foot feature points characterize distinctive location points that are distinctive and readily distinguishable by foot features. And mapping the determined plurality of foot feature points to the initial shoe tree three-dimensional model to obtain a first shoe tree model containing the model feature points.
Optionally, fig. 2 is a flowchart of a method for performing feature point mapping according to an embodiment of the present invention, where the determining a plurality of foot feature points based on foot big data analysis, and mapping the plurality of foot feature points into the initial three-dimensional last model includes:
and S1021, analyzing the three-dimensional foot image to obtain a plurality of characteristic areas, and determining corresponding foot characteristic points according to each characteristic area.
Specifically, the image feature recognition may be performed on the three-dimensional image of the foot to obtain a plurality of feature regions, where the feature regions represent differentiated and non-identical regions. Illustratively, the toe area, the instep area, the heel area, etc. One or more foot feature points are determined for each feature region, respectively. Optionally, the number of foot feature points corresponding to the feature region may be determined according to the complexity of the feature region, where the higher the complexity is, the greater the number of foot feature points corresponding to the feature region is, and the lower the complexity is, that is, the number of foot feature points corresponding to a region with insignificant distinguishing features is relatively reduced. For example, the number of the foot characteristic points corresponding to the toe area may be 5, and the number of the characteristic points corresponding to the instep area and the heel area may be 3. For example, in the case that the number of feature regions and feature points has been determined, the points may be uniformly taken in the feature regions, or alternatively, the points may be randomly taken at fixed intervals between every two feature points.
And S1022, mapping the position relation based on the foot feature points to the initial shoe tree three-dimensional model.
And after obtaining a plurality of foot characteristic points, mapping the foot characteristic points to the initial shoe tree three-dimensional model to obtain a first shoe tree model. Specifically, after 5 feature points of the toe area are determined, the spatial position (taking a three-dimensional xyz coordinate system as an example, to ensure that the relative position coordinates between the 5 points are unchanged) relationship of the 5 feature points is kept unchanged, and the toe area is translated to the same position area of the first shoe tree model. Optionally, the first last model is obtained during the translation process to ensure that each feature point is inside the initial last three-dimensional model.
Step S103, receiving the adjustment operation of the first shoe tree model, adjusting the first shoe tree model according to the adjustment operation to generate a second shoe tree model, and displaying the second shoe tree model.
In one embodiment, the adjustment operation further comprises a drag operation on the non-characteristic point region. That is, the first last model is adjusted based on different adjustment operations to generate a second last model. Optionally, when the adjustment operation is a feature point dragging operation, determining an associated displacement distance of an associated feature point according to a displacement distance of the feature point dragging operation; and adjusting the first shoe tree model according to the displacement distance and the associated displacement distance to generate a second shoe tree model. When the adjustment operation is a non-feature point area dragging operation, determining an adjustment sub-area corresponding to a touch point of the non-feature point area dragging operation; and adjusting the sub-adjustment area according to the dragging distance of the non-feature point area dragging operation.
According to the scheme, the initial shoe tree three-dimensional model is generated by carrying out shoe tree three-dimensional modeling initialization; determining a plurality of foot characteristic points based on foot big data analysis, and mapping the plurality of foot characteristic points to the initial shoe tree three-dimensional model to obtain a first shoe tree model containing model characteristic points; and receiving the adjustment operation of the first shoe tree model, adjusting the first shoe tree model according to the adjustment operation to generate a second shoe tree model, and displaying the second shoe tree model. Therefore, the calculation amount of shoe tree modeling adjustment is remarkably reduced, the shoe tree modeling efficiency is improved, and the intelligent degree is high.
Fig. 3 is a flowchart of another method for adjusting shoe tree modeling according to an embodiment of the present invention, which provides a specific method for adjusting a first shoe tree model to generate a second shoe tree model, and as shown in fig. 3, the method specifically includes:
and step S201, initializing shoe tree three-dimensional modeling, and generating an initial shoe tree three-dimensional model.
Step S202, determining a plurality of foot characteristic points based on foot big data analysis, and mapping the plurality of foot characteristic points to the initial shoe tree three-dimensional model to obtain a first shoe tree model containing model characteristic points.
Step S203, receiving an adjustment operation on the first shoe tree model, and determining a correlation displacement distance of a correlation characteristic point according to the displacement distance of the characteristic point dragging operation when the adjustment operation is the characteristic point dragging operation.
In one embodiment, after determining the second last model including the model feature points, the second last model may be further adjusted according to the detected feature point dragging operation for the model feature points. Specifically, the displacement distance of the feature point dragging operation is the detected dragging displacement distance, and if the user selects the model feature point through the touch screen and then performs the dragging operation of finger sliding, the sliding distance is the corresponding dragging displacement distance. And when the displacement distance of the dragging operation is determined, correspondingly determining the associated displacement distance of the associated characteristic point, wherein the displacement distance of the associated characteristic point is different from the distance value of the displacement distance of the selected model characteristic point. And the related characteristic points are other characteristic points in the same characteristic region except the characteristic point currently controlled and selected.
Optionally, the determining the associated displacement distance of the associated feature point according to the displacement distance of the feature point dragging operation includes: and determining a plurality of associated feature points with different distance levels according to the feature points selected by the feature point dragging operation, and respectively determining associated displacement distances of the associated feature points for use according to the displacement distances of the feature point dragging operation and the different distance levels. The distance level is used for representing the difference of the distances between the selected model feature point and other associated feature points, and the distance level is higher when the distance is closer. For example, 1/2 defining the distance levels from top to bottom to three levels, where the displacement distance of the feature point corresponding to the first level is the displacement distance of the dragged feature point, the displacement distance of the feature point corresponding to the second level is 1/3 of the displacement distance of the dragged feature point, and the displacement distance of the feature point corresponding to the third level is 1/4 of the displacement distance of the dragged feature point may be set.
Alternatively, after the model feature points are given, the distance levels of the associated feature points may be determined by calculating an average distance between the associated feature points based on the feature points, determining the associated feature points having a distance value smaller than the average distance as a first level, determining the associated feature points having a distance value larger than the average distance and smaller than twice the average distance as a second level, and determining the remaining associated feature points as a third level.
And S204, adjusting the first shoe tree model according to the displacement distance and the associated displacement distance to generate a second shoe tree model, and displaying the second shoe tree model.
After the displacement distances of the characteristic points and the associated characteristic points are determined, the position of the final position point is correspondingly determined. Taking a certain feature point dragged horizontally as an example, coordinate translation corresponding to the displacement distance is performed along the horizontal dragging direction to obtain a new position point of the dragged feature point, and for the associated feature point, after the associated displacement distance is determined, coordinate translation is performed based on the same dragging position direction to obtain a position point after adjustment operation. And adjusting the corresponding three-dimensional model based on the position points determined after the adjustment. Specifically, the adjustment of the three-dimensional last model is the adjustment of the feature region where the feature point and the associated feature point are located, and the specific adjustment mode may be a size scaling adjustment based on the same displacement distance ratio.
According to the scheme, when the adjustment operation is the feature point dragging operation, the associated displacement distance of the associated feature point is determined according to the displacement distance of the feature point dragging operation, the first shoe tree model is adjusted according to the displacement distance and the associated displacement distance to generate the second shoe tree model, so that the adjustment of the shoe tree model based on the feature point is realized, and the accuracy of the model adjustment is directly adjusted by zooming.
Fig. 4 is a flowchart of another method for adjusting shoe tree modeling according to an embodiment of the present invention, which provides a specific method for adjusting a first shoe tree model to generate a second shoe tree model, and as shown in fig. 4, the method specifically includes:
and S301, initializing the three-dimensional modeling of the shoe tree to generate an initial three-dimensional model of the shoe tree.
Step S302, determining a plurality of foot characteristic points based on foot big data analysis, and mapping the plurality of foot characteristic points to the initial shoe tree three-dimensional model to obtain a first shoe tree model containing model characteristic points.
Step S303, when the adjustment operation is a non-feature point region dragging operation, determining an adjustment sub-region corresponding to a touch point of the non-feature point region dragging operation.
In another embodiment, the adjustment for the last model also includes an adjustment for a non-feature point dragging operation, that is, for a non-feature area, an adjustment sub-area corresponding to the touch point of the non-feature point area dragging operation is determined, and optionally, the adjustment sub-area may be an area of the last model covered by a sphere composed of a sphere with a preset radius and the selected touch point as a sphere center.
S304, adjusting the adjustment sub-area according to the dragging distance of the non-feature point area dragging operation to generate a second shoe tree model, and displaying the second shoe tree model.
Specifically, the adjustment process may be to perform scaling adjustment on the adjustment sub-region according to the dragging distance in an equal proportion.
According to the scheme, the adjustment of the characteristic point area and the adjustment of the non-characteristic point area are distinguished in the adjustment process of the shoe tree model, so that the adjustment mode is more flexible, the adjustment speed of the model is ensured, and the adjustment precision is also ensured.
Fig. 5 is a structural block diagram of a shoe tree modeling adjustment apparatus according to an embodiment of the present invention, which is used for executing the shoe tree modeling adjustment method according to the embodiment of the present invention, and has functional module units corresponding to the execution method and beneficial effects. As shown in fig. 5, the apparatus specifically includes: an initialization module 101, a mapping module 102, and an adjustment module 103, wherein,
the initialization module 101 is used for initializing last three-dimensional modeling and generating an initial last three-dimensional model;
the mapping module 102 is configured to determine a plurality of foot feature points based on foot big data analysis, map the plurality of foot feature points to the initial shoe tree three-dimensional model, and obtain a first shoe tree model including model feature points;
and the adjusting module 103 is configured to receive an adjusting operation on the first shoe tree model, adjust the first shoe tree model according to the adjusting operation to generate a second shoe tree model, and display the second shoe tree model.
According to the scheme, the initial shoe tree three-dimensional model is generated by carrying out shoe tree three-dimensional modeling initialization; determining a plurality of foot characteristic points based on foot big data analysis, and mapping the plurality of foot characteristic points to the initial shoe tree three-dimensional model to obtain a first shoe tree model containing model characteristic points; and receiving the adjustment operation of the first shoe tree model, adjusting the first shoe tree model according to the adjustment operation to generate a second shoe tree model, and displaying the second shoe tree model. This scheme is showing the operand that has reduced shoe tree modeling adjustment, has promoted shoe tree modeling efficiency, and intelligent degree is high.
In a possible embodiment, the initialization module is specifically configured to:
receiving selection operation of model initialization parameters, performing shoe tree three-dimensional modeling initialization according to the initialization parameters selected by the selection operation, and generating an initial shoe tree three-dimensional model, wherein the initialization parameters comprise gender information and foot fuzzy characteristic information.
In a possible embodiment, the mapping module is specifically configured to:
analyzing the three-dimensional foot image to obtain a plurality of characteristic areas, and determining corresponding foot characteristic points according to each characteristic area;
and mapping the position relation based on the foot characteristic points to the initial shoe tree three-dimensional model.
In one possible embodiment, the adjusting operation further comprises a drag operation on the non-feature point area.
In a possible embodiment, the adjusting module is specifically configured to:
when the adjustment operation is a feature point dragging operation, determining a correlation displacement distance of a correlation feature point according to the displacement distance of the feature point dragging operation;
and adjusting the first shoe tree model according to the displacement distance and the associated displacement distance to generate a second shoe tree model.
In a possible embodiment, the adjusting module is specifically configured to:
and determining a plurality of associated feature points with different distance levels according to the feature points selected by the feature point dragging operation, and respectively determining associated displacement distances of the associated feature points for use according to the displacement distances of the feature point dragging operation and the different distance levels.
In a possible embodiment, the adjusting module is specifically configured to:
when the adjustment operation is a non-feature point area dragging operation, determining an adjustment sub-area corresponding to a touch point of the non-feature point area dragging operation;
and adjusting the sub-adjustment area according to the dragging distance of the non-feature point area dragging operation.
Fig. 6 is a schematic structural diagram of a shoe last modeling adjustment apparatus according to an embodiment of the present invention, as shown in fig. 6, the apparatus includes a processor 201, a memory 202, an input device 203, and an output device 204; the number of the processors 201 in the device may be one or more, and one processor 201 is taken as an example in fig. 6; the processor 201, the memory 202, the input means 203 and the output means 204 in the device may be connected by a bus or other means, as exemplified by a bus connection in fig. 6. The memory 202 is used as a computer-readable storage medium for storing software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the shoe tree modeling adjustment method in the embodiment of the present invention. The processor 201 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory 202, so as to implement the above-mentioned last modeling adjustment method. The input device 203 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function controls of the apparatus. The output device 204 may include a display device such as a display screen.
Embodiments of the present invention also provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform a method for adjusting shoe last modeling, the method including:
carrying out three-dimensional modeling initialization on a shoe tree to generate an initial shoe tree three-dimensional model;
determining a plurality of foot characteristic points based on foot big data analysis, and mapping the plurality of foot characteristic points to the initial shoe tree three-dimensional model to obtain a first shoe tree model containing model characteristic points;
and receiving the adjustment operation of the first shoe tree model, adjusting the first shoe tree model according to the adjustment operation to generate a second shoe tree model, and displaying the second shoe tree model.
Optionally, the initializing the three-dimensional modeling of the shoe tree to generate an initial three-dimensional model of the shoe tree includes:
receiving selection operation of model initialization parameters, performing shoe tree three-dimensional modeling initialization according to the initialization parameters selected by the selection operation, and generating an initial shoe tree three-dimensional model, wherein the initialization parameters comprise gender information and foot fuzzy characteristic information.
Optionally, the determining a plurality of foot feature points based on the foot big data analysis, and mapping the plurality of foot feature points into the initial last three-dimensional model includes:
analyzing the three-dimensional foot image to obtain a plurality of characteristic areas, and determining corresponding foot characteristic points according to each characteristic area;
and mapping the position relation based on the foot characteristic points to the initial shoe tree three-dimensional model.
Optionally, the adjusting operation further includes a drag operation on the non-characteristic point region.
Optionally, adjusting the first last model according to the adjustment operation to generate a second last model, including:
when the adjustment operation is a feature point dragging operation, determining a correlation displacement distance of a correlation feature point according to the displacement distance of the feature point dragging operation;
and adjusting the first shoe tree model according to the displacement distance and the associated displacement distance to generate a second shoe tree model.
Optionally, the determining the associated displacement distance of the associated feature point according to the displacement distance of the feature point dragging operation includes:
and determining a plurality of associated feature points with different distance levels according to the feature points selected by the feature point dragging operation, and respectively determining associated displacement distances of the associated feature points for use according to the displacement distances of the feature point dragging operation and the different distance levels.
Optionally, adjusting the first last model according to the adjustment operation to generate a second last model, including:
when the adjustment operation is a non-feature point area dragging operation, determining an adjustment sub-area corresponding to a touch point of the non-feature point area dragging operation;
and adjusting the sub-adjustment area according to the dragging distance of the non-feature point area dragging operation.
It should be noted that, in the embodiment of the last modeling adjustment apparatus, the units and modules included in the embodiment are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the embodiment of the invention.
It should be noted that the foregoing is only a preferred embodiment of the present invention and the technical principles applied. Those skilled in the art will appreciate that the embodiments of the present invention are not limited to the specific embodiments described herein, and that various obvious changes, adaptations, and substitutions are possible, without departing from the scope of the embodiments of the present invention. Therefore, although the embodiments of the present invention have been described in more detail through the above embodiments, the embodiments of the present invention are not limited to the above embodiments, and many other equivalent embodiments may be included without departing from the concept of the embodiments of the present invention, and the scope of the embodiments of the present invention is determined by the scope of the appended claims.
Claims (10)
1. The shoe tree modeling and adjusting method is characterized by comprising the following steps:
carrying out three-dimensional modeling initialization on a shoe tree to generate an initial shoe tree three-dimensional model;
determining a plurality of foot characteristic points based on foot big data analysis, and mapping the plurality of foot characteristic points to the initial shoe tree three-dimensional model to obtain a first shoe tree model containing model characteristic points;
receiving adjustment operation on the first shoe tree model, adjusting the first shoe tree model according to the adjustment operation to generate a second shoe tree model, and displaying the second shoe tree model, wherein the adjustment operation comprises feature point dragging operation on the model feature points.
2. The method for adjusting shoe tree modeling according to claim 1, wherein said initializing shoe tree three-dimensional modeling and generating an initial shoe tree three-dimensional model comprises:
receiving selection operation of model initialization parameters, performing shoe tree three-dimensional modeling initialization according to the initialization parameters selected by the selection operation, and generating an initial shoe tree three-dimensional model, wherein the initialization parameters comprise gender information and foot fuzzy characteristic information.
3. The last modeling adjustment method according to claim 2, wherein said determining a plurality of foot feature points based on foot big data analysis, mapping said plurality of foot feature points into said initial last three-dimensional model, comprises:
analyzing the three-dimensional foot image to obtain a plurality of characteristic areas, and determining corresponding foot characteristic points according to each characteristic area;
and mapping the position relation based on the foot characteristic points to the initial shoe tree three-dimensional model.
4. The method for last modeling adjustment according to claim 1, wherein said adjustment operation further comprises a drag operation on a non-characteristic point area.
5. The last modeling adjustment method according to claim 4, wherein adjusting the first last model according to the adjustment operation generates a second last model, including:
when the adjustment operation is a feature point dragging operation, determining a correlation displacement distance of a correlation feature point according to the displacement distance of the feature point dragging operation;
and adjusting the first shoe tree model according to the displacement distance and the associated displacement distance to generate a second shoe tree model.
6. The method for shoe tree modeling adjustment according to claim 5, wherein said determining the associated displacement distance of the associated feature point according to the displacement distance of the feature point dragging operation comprises:
and determining a plurality of associated feature points with different distance levels according to the feature points selected by the feature point dragging operation, and respectively determining associated displacement distances of the associated feature points for use according to the displacement distances of the feature point dragging operation and the different distance levels.
7. The last modeling adjustment method according to claim 4, wherein adjusting the first last model according to the adjustment operation generates a second last model, comprising:
when the adjustment operation is a non-feature point area dragging operation, determining an adjustment sub-area corresponding to a touch point of the non-feature point area dragging operation;
and adjusting the sub-adjustment area according to the dragging distance of the non-feature point area dragging operation.
8. Shoe tree modeling adjusting device, its characterized in that includes:
the initialization module is used for carrying out shoe tree three-dimensional modeling initialization and generating an initial shoe tree three-dimensional model;
the mapping module is used for determining a plurality of foot characteristic points based on foot big data analysis, mapping the plurality of foot characteristic points to the initial shoe tree three-dimensional model to obtain a first shoe tree model containing model characteristic points;
and the adjusting module is used for receiving the adjusting operation of the first shoe tree model, adjusting the first shoe tree model according to the adjusting operation to generate a second shoe tree model, and displaying the second shoe tree model.
9. A shoe tree modeling adjustment apparatus, the apparatus comprising: one or more processors; a storage device for storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the last modeling adjustment method of any of claims 1-7.
10. A storage medium storing computer executable instructions for performing the last modeling adjustment method of any one of claims 1-7 when executed by a computer processor.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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