WO2023025269A1

WO2023025269A1 - Slice processing method, printing method, system, and device, and storage medium

Info

Publication number: WO2023025269A1
Application number: PCT/CN2022/114986
Authority: WO
Inventors: 刘鹏; 欧阳欣
Original assignee: 深圳市纵维立方科技有限公司
Priority date: 2021-08-27
Filing date: 2022-08-26
Publication date: 2023-03-02
Also published as: CN113681897A; CN113681897B

Abstract

The present invention provides a slice processing method, a printing method, system, and device, and a storage medium. The slice processing method comprises: on the basis of received N task requests, generating task bodies corresponding to the N task requests; and according to the processing strategies of the N task requests, sequentially and circularly performing slice processing on models to be sliced that are corresponding to the at least two task bodies until all layer slices of at least two said models are obtained. According to the present invention, said models corresponding to the at least two task bodies are sequentially and circularly sliced according to the processing strategies of the task requests, such that it is ensured that each slice task can be timely responded under the condition that multiple slice tasks are executed.

Description

Slice processing method, printing method, system, device and storage medium

technical field

The present application belongs to the technical field of printing, and in particular relates to a slice processing method, a printing method, a system, a device and a storage medium.

Background technique

3D printing technology is a new rapid prototyping technology based on digital models. It manufactures models by layer-by-layer printing. It is a completely different forming technology from traditional mold manufacturing. In the process of 3D printing, after using the modeling software to obtain the virtual 3D model, it is necessary to convert the model file into the action data of the printer. The above data conversion process can be understood as slicing the virtual 3D model.

At present, cloud slicing technology is widely sought after because it can provide slicing services for a large number of users in the cloud. However, the current slicing process only supports single-user single-task, that is, the slicing tasks are sorted according to the time when the user sends the slicing request, and only after the current slicing task is completed, the subsequent slicing task can be executed. This results in delays in getting responses for slice tasks that are sorted low, and for slice tasks that are sorted low, the slicing time is too long.

Contents of the invention

The purpose of the embodiment of the present application is to provide a slicing processing method, printing method, system, device, and storage medium, which can solve the problem that when the slicing tasks are performed using the cloud slicing technology, the slicing tasks that are ranked behind cannot get sliced responses in time.

In the first aspect, the embodiment of the present application provides a slice processing method, the method includes:

Based on the received N task requests, generate a task body corresponding to the N task requests;

According to the processing strategy of the N task requests, at least two models to be sliced corresponding to the task bodies are sequentially sliced until all layer slices of the at least two models to be sliced are obtained.

In a second aspect, an embodiment of the present application provides a printing method, the method including:

An image to be printed is acquired, and a model is printed according to the image to be printed; wherein, the image to be printed is a layer slice generated by the slice processing method as described in the first aspect.

In a third aspect, an embodiment of the present application provides a printing system, where the printing system includes an image processing device and a printing device;

The image processing device is configured to execute the slice processing method as described in the first aspect;

The printing device uses the layer slices output by the image processing device, and obtains a model to be printed according to the layer slices.

In a fourth aspect, an embodiment of the present application provides a printing device, which includes a processor, a memory, and a program or instruction stored in the memory and operable on the processor, and the program or instruction is executed by The processor implements the steps of the method described in the first aspect when executed.

In the fifth aspect, the embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented .

In the embodiment of the present application, based on the received N task requests, the task bodies corresponding to the N task requests are generated; according to the processing strategy of the N task requests, at least two models to be sliced corresponding to the task bodies are sequentially cyclically processed Slicing until all layer slices of at least two models to be sliced are obtained. In this way, according to the processing strategy of the task request, the slicing models corresponding to at least two task bodies are sequentially sliced, and then in the case of executing multiple slicing tasks, each slicing task can be guaranteed to get a timely response.

Description of drawings

Fig. 1 is the business flowchart of the cloud slice provided by the embodiment of the present application;

FIG. 2 is a flowchart of a slice processing method provided by an embodiment of the present application;

Fig. 3 is a structural diagram of a printing system provided by an embodiment of the present application;

FIG. 4 is a structural diagram of an electronic device provided by an embodiment of the present application.

Detailed ways

The following will clearly describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, but not all of them. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in this application belong to the protection scope of this application.

The terms "first", "second" and the like in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific sequence or sequence. It should be understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments of the application can be practiced in sequences other than those illustrated or described herein, and that references to "first," "second," etc. distinguish Objects are generally of one type, and the number of objects is not limited. For example, there may be one or more first objects. In addition, "and/or" in the specification and claims means at least one of the connected objects, and the character "/" generally means that the related objects are an "or" relationship.

Please refer to FIG. 1 . FIG. 1 is a service flow chart of a cloud slice provided by an embodiment of the present application. The business logic of the cloud slicing technology will be described below with reference to FIG. 1 .

As shown in Figure 1, the user can send a slice request to the terminal through the application program, and the terminal generates a task body based on the received slice request. The "task body 01" shown in Figure 1 represents a task body, and "task body 02" represents Another task body. Wherein, there is a one-to-one correspondence between the slice request and the task body, and the above-mentioned terminal may be a slice processing device.

The terminal sorts the task bodies in the task queue according to the order of the receiving time of the slice requests. As shown in Figure 1, the terminal includes a slicing thread and multiple compression threads. It should be understood that the above-mentioned slicing thread is used to perform slicing processing on the model to be sliced corresponding to the task body to obtain layer slicing; the above-mentioned compression thread is used for layer slicing The slice information is compressed, wherein one compression thread is used to compress the slice information of a layer slice.

Combining with Figure 1, it can be obtained that the cloud slicing technology supports the provision of slicing services for a large number of users in the cloud. However, since the terminal only has one slicing thread, the slicing process only supports a single task for a single user, which results in slices that are ranked lower in the task queue. The task is delayed in getting a response.

Based on the above existing technical problems, an embodiment of the present application provides a slice processing method.

The slice processing method provided by the embodiment of the present application will be described in detail below through specific embodiments and application scenarios with reference to the accompanying drawings.

Please refer to FIG. 2 . FIG. 2 is a flowchart of a slicing method provided by an embodiment of the present application. The slice processing method provided in the embodiment of the present application includes the following steps:

S101. Based on the received N task requests, generate task bodies corresponding to the N task requests.

It should be understood that the slice processing method provided in the embodiment of the present application is applied to a terminal, and the terminal may be a slice processing device or a 3D printing device, or other devices.

In this step, the terminal applying the slicing processing method receives multiple task requests. Here, the number of task requests can be set as N. Optionally, the above N task requests can be sent by N users, and each user sends one A task request; or, the above N task requests may also be sent by multiple users, and one user may send at least one task request; or, the above N task requests may also be sent by one user. Wherein, N is a positive integer greater than 1.

After receiving N task requests, generate task bodies corresponding to the N task requests.

An optional implementation manner is that one task request corresponds to one task body, then N task requests correspond to N task bodies, and the N task bodies are in one-to-one correspondence with the N task requests.

Another optional implementation manner is that one task request corresponds to two task entities, or corresponds to more than two task entities. Then, after receiving N task requests, the number of generated task bodies is greater than N.

It should be understood that the above task body includes relevant parameters of the model to be sliced, and the task body corresponds to the model to be sliced one by one. Further, the model to be sliced corresponding to the task body can be obtained by analyzing the relevant parameters in the task body .

S102. According to the processing strategy of the N task requests, sequentially perform slice processing on at least two models to be sliced corresponding to the task bodies until all layer slices of at least two models to be sliced are obtained.

In this step, the tasks can be sorted in the order of the receiving time of the corresponding task requests, please refer to Figure 1, it can be understood that the task queue stores N task bodies, and the N task bodies are sorted according to the receiving time of the corresponding task requests sorted in sequence.

In other embodiments, the tasks can also be sorted according to a preset order, or sorted according to the area of the corresponding model files from large to small, and no specific limitation is made here on the sorting manner of the tasks.

In this step, the slicing thread is invoked according to the processing strategy of N task requests, and sequentially slices the models to be sliced corresponding to at least two task bodies until all layer slices corresponding to each model to be sliced are obtained, and the slicing operation is stopped .

Wherein, the slicing process refers to the process of converting the model file of the model to be sliced into the action data of the 3D printing device.

Wherein, the processing strategy refers to the processing order of slicing the model to be sliced corresponding to the N task requests, and the above processing strategy may be to process the N task requests in the order of receiving time, and the model to be sliced corresponding to the N task requests Carry out slicing processing; the above-mentioned processing strategy can also be to perform slicing processing on the models to be sliced corresponding to N task requests according to the preset sequence set by the user; the above-mentioned processing strategy can also be in accordance with the model files corresponding to the task requests from large to small In order, perform slice processing on the models to be sliced corresponding to the N task requests. It should be understood that this embodiment does not specifically limit the processing strategy here.

Wherein, the process of slicing the models to be sliced corresponding to the N task requests is to sequentially perform slice processing on the models to be sliced corresponding to at least two task bodies.

For example, the number of N is 3, and one task request corresponds to one task body. In this case, this cycle can be used to perform slice processing on the models to be sliced corresponding to two task bodies among the three task bodies.

It should be understood that, in the process of slicing the to-be-sliced models corresponding to at least two task bodies sequentially, the order of processing the to-be-sliced models corresponding to the task bodies is not limited.

Exemplarily, the number of N is 3, and the tasks are set to be sorted according to the receiving time of the corresponding task requests, and the task body 01, the task body 02 and the task body 03 are obtained. It is set to perform slicing processing on the models to be sliced corresponding to the three task bodies in a cycle.

Then, in the process of sequentially slicing the models to be sliced corresponding to the three task bodies, an optional implementation method is that the model to be sliced corresponding to the task body 01 can be sliced first, and then the task The model to be sliced corresponding to body 02 is sliced, and finally the model to be sliced corresponding to task body 03 is sliced. Alternatively, the model to be sliced corresponding to task body 02 may be sliced first, then the model to be sliced corresponding to task body 03 may be sliced, and finally the model to be sliced corresponding to task body 01 may be sliced. or other order.

Wherein, when performing slicing processing on at least two models to be sliced sequentially, the number of slices of each process layer obtained is the same, and if any task body is detected to complete the slicing process, the task body ends and the task body exits the loop.

It should be understood that the above-mentioned number of layer slices in each process refers to the number of layer slices obtained by slicing the model to be sliced in each cycle. That is to say, the number of layer slices obtained by slicing the model to be sliced in each cycle is the same.

Define the number of slices in each process layer as M. For ease of understanding, the examples are as follows:

The terminal receives 3 task requests, generates task body 01, task body 02 and task body 03 based on these 3 task requests, sorts the above task bodies according to the order of receiving time of the task requests, and obtains that the order of task body 01 is before Task body 02, the order of task body 02 is prior to task body 03.

Perform cyclic slicing processing on the models to be sliced corresponding to the three task bodies, and set the value of M to 5. Here, the model to be sliced corresponding to task body 01 is called model 01, and the model to be sliced corresponding to task body 02 is called For model 02, the model to be sliced corresponding to task body 03 is called model 03. During each slicing process, 5 layer slices of model 01, 5 layer slices of model 02, and 5 layer slices of model 03 are obtained. When all layer slices corresponding to the above three models to be sliced are obtained, stop slicing the model to be sliced.

A possible situation is that the number of layer slices of model 02 is less than the number of layer slices of model 01 and model 03. In this way, in the process of cyclic slicing, all the layer slices corresponding to model 02 are obtained, but not Get all layer slices corresponding to model 01 and model 03. In this case, stop slicing for model 02 during the cyclic slicing process, and only slice for model 01 and model 03 until all layers corresponding to model 01 are obtained Slice and slice all layers corresponding to model 03.

In the embodiment of the present application, based on the received N task requests, the task bodies corresponding to the N task requests are generated; according to the processing strategy of the N task requests, at least two models to be sliced corresponding to the task bodies are sequentially cyclically processed Slicing until all layer slices corresponding to at least two models to be sliced are obtained. In this way, according to the processing strategy of the task request, the slicing models corresponding to at least two task bodies are sequentially sliced, and then in the case of executing multiple slicing tasks, each slicing task can be guaranteed to get a timely response.

The following describes the execution steps in each cycle:

The sequential looping of at least two models to be sliced corresponding to the task body includes:

For any model to be sliced, analyze the model slice information of the model to be sliced, and obtain the completed layer slice corresponding to the model to be sliced;

On the basis of the completed layer slicing, perform slicing processing on the model to be sliced to obtain process slicing information;

The process slicing information is stored in the model slicing information, and the model slicing information is refreshed.

It should be understood that the model to be sliced includes model slice information, and the model slice information is used to represent the completed layer slice corresponding to the model to be sliced. The above model slice information includes multiple layer slice information, that is to say, the above model slice information can be understood as is a collection of layer slice information corresponding to the model to be sliced.

The above process slicing information is the layer slicing information corresponding to the completed layer slicing obtained after slicing the model to be sliced in a cycle. Optionally, the above process slice information includes but not limited to the number of layer slices, slice images corresponding to each layer slice, and model parameters and scene parameters corresponding to the model to be printed.

In this embodiment, within one cycle, for a model to be sliced that has not been sliced, the model slicing information of the model to be sliced is first analyzed to obtain the completed layer slice of the model to be sliced and the layer corresponding to the model to be sliced The number of slices, wherein, the number of layer slices corresponding to the model to be sliced can be understood as the total number of layer slices corresponding to the model to be sliced; further, on the basis of the completed layer slices of the model to be sliced, continue to The model is sliced to obtain process slicing information.

In an implementation scenario, it is set that the process slicing information corresponds to M layer slices, then, by analyzing the model slicing information of the model to be sliced to obtain the completed layer slices of the model to be sliced, the number of the above-mentioned completed layer slices can be determined as A positive integer multiple of M.

Exemplarily, when the value of M is 5 and the number of layer slices of the model to be sliced is 10, in one cycle, the model slicing information of the model to be sliced is analyzed to obtain the model to be sliced The corresponding 10 layer slices have been completed; on the basis of these 10 layer slices, continue to slice the model to be sliced to obtain 5 layer slices, and store the layer slice information corresponding to these 5 layer slices in Model slicing information, that is, after this cycle period, the model slicing information corresponding to the model to be sliced is used to represent the completed 15 layer slices of the model to be sliced.

In this embodiment, at the end of each cycle, the process slicing information is saved to the model slicing information, and before the next cycle starts, slicing can be continued on the basis of the completed layer slicing without having to re-treat the slicing The model is sliced to improve slice efficiency.

Optionally, the preset total number of slicing layers of the task bodies is the same or different, and the task body with the least preset total number of slicing layers ends first and exits the cyclic slicing process.

It should be understood that the preset total number of slice layers of the N task bodies may be the same or may be different, which is not specifically limited here.

For any two task entities among the N task entities, the task entity with a smaller number of total slicing layers exits the cycle slicing process earlier than the task entity with a larger total number of slicing layers.

For any two task bodies among the N task bodies, the task body with the least number of total slice layers exits the loop slicing process first.

Exemplarily, it is set that the number of layer slices corresponding to the first task body is 2000, and the number of layer slices corresponding to the second task body is 20, then, since the number of layer slices corresponding to the first task body is greater than that of the second task body Therefore, the slicing time corresponding to the first task body is greater than the slicing time corresponding to the second task body, that is to say, the second task body first exits the loop slicing process.

Optionally, the task body includes model parameters and scene parameters, and after generating the task bodies corresponding to the N task requests, the method includes:

Obtain the model parameters corresponding to the task body, and obtain the model file corresponding to the task body according to the model parameters, wherein the cloud server stores the mapping relationship between the model parameters and the model file, and the cloud server receiving the model parameters for query and returning the corresponding model file;

The scene parameters corresponding to the task body are obtained, and the model file is linearly transformed according to the scene parameters to obtain the to-be-sliced model corresponding to the task body.

In this embodiment, the terminal applying the slice processing method can also communicate with the data storage device, and the above data storage device can be a cloud server or a local server.

In this embodiment, the task body generated according to the task request includes model parameters and scene parameters, wherein the above model parameters and scene parameters are determined based on the content of the task request input by the user, and the above model parameters are model files.

For easy understanding of model parameters and scene parameters, see the following examples:

If the model to be printed is "inverted rabbit", the model parameter corresponding to the model to be printed is the model file "rabbit", and the scene parameter corresponding to the model to be printed is "inverted", where the scene parameter can be a 4*4 including 16 The matrix sequence of elements is calculated by using the matrix sequence to calculate the model represented by the model parameters, and the model to be printed can be obtained.

The above-mentioned cloud server stores the mapping relationship between model parameters and model files. Specifically, the terminal applying the slice processing method provided by the embodiment of the present application sends model parameters to the cloud server, and the cloud server receives the model parameters, queries the model parameters, and feeds back the model file corresponding to the model parameters to the terminal. Wherein, the above-mentioned model file represents a model file without linear transformation, that is, a model file whose size and position of the model are not determined.

After obtaining the model file, obtain the scene parameters in the task body, and use the scene parameters to perform linear transformation on the model file to obtain the model to be sliced. It should be understood that the manner of linearly transforming the model file includes but not limited to moving, scaling or rotating the model.

Optionally, the scene parameter is a matrix sequence, the model file includes K model vertices, and K is a positive integer greater than 1;

The acquiring the scene parameters corresponding to the task body, and performing linear transformation on the model file according to the scene parameters, and obtaining the sliced model corresponding to the task body includes:

For the model file corresponding to the task body, perform a matrix transformation operation on the coordinate value of each model vertex corresponding to the model file and the matrix sequence to obtain K model vertices after linear transformation;

A model generated from the K model vertices after the linear transformation is determined as the model to be sliced corresponding to the task body.

It should be understood that after the user retrieves the 3D virtual model from the model library, the user uses the modeling software on the front end to perform linear transformation on the 3D virtual model, such as moving, scaling or stretching, to obtain the model to be sliced. The above-mentioned three-dimensional virtual model is a virtual model represented by a model file, and the above-mentioned process of linearly transforming the three-dimensional virtual model can be expressed by a matrix sequence.

In this embodiment, the scene parameters in the task body are read. As mentioned above, the scene parameters can be expressed as a matrix sequence. An optional implementation is to set the matrix sequence as a 4*4 matrix including 16 elements.

Use the coordinate values of each model vertex and the matrix sequence in turn to perform matrix transformation operations. The above matrix transformation operations can be matrix multiplication operations. In this way, change the coordinate values of each model vertex to obtain K model vertices after linear transformation. This implements the linear transformation of the model file, and determines the model generated by the K model vertices after the linear transformation as the task body corresponding to the model to be sliced.

Optionally, the task body also includes shelling parameters and support parameters, and after obtaining the model to be sliced corresponding to the task body, the method further includes:

According to the shelling parameters and/or the support parameters, respectively perform shelling processing and support processing on the model to be sliced.

In this embodiment, for some models to be sliced that need to be shelled, the task body also includes shelling parameters. The above-mentioned shelling parameters are determined based on the content of the task request input by the user. The shelling parameters are also called shelling commands. , the shelling parameter is used to instruct the model to be sliced to be shelled, and the shelling process refers to extracting the inside of the model to form a hollow area in the middle of the model.

If the task body includes shelling parameters, the sliced model needs to be shelled according to the shelling parameters to form a hollow area in the middle of the model.

In this embodiment, for some models to be sliced that need support processing, the task body also includes support parameters. The above support parameters are determined based on the content of the task request input by the user. The support parameters are also called support commands. The support parameters are used for Indicates that the model to be sliced should be supported. The support process refers to the printing of support materials in order to maintain the physical balance of the 3D printed item.

If the task body includes support parameters, the model to be sliced needs to be supported according to the support parameters, and the support material is printed on the model to be sliced. After the printed solid model is obtained, the printed support material in the solid model can be removed.

The embodiment of the present application also provides a printing method, the printing method comprising:

An image to be printed is acquired, and a model is printed according to the image to be printed; wherein, the image to be printed is a layer slice generated by the above slice processing method embodiment.

It should be understood that the printing method provided by the embodiment of the present application can implement the various processes of the above embodiments of the slice processing method, and can achieve the same technical effect. To avoid repetition, details are not repeated here.

The embodiment of the present application also provides a printing system, as shown in FIG. 3 , the printing system 200 includes an image processing device 201 and a printing device 202;

The image processing device 201 is configured to execute various processes in the above embodiments of the slice processing method;

The printing device 202 uses the layer slices output by the image processing device 201, and obtains a model to be printed according to each layer slice.

The embodiment of the present application also provides a printing device, including a processor, a memory, and a program or instruction stored in the memory and operable on the processor, and the program or instruction is executed by the processor Each process of the above embodiment of the slicing processing method can be realized at the same time, and the same technical effect can be achieved. To avoid repetition, details are not repeated here.

Optionally, as shown in FIG. 4 , the embodiment of the present application further provides an electronic device 300, including a processor 301, a memory 302, and programs or instructions stored in the memory 302 and operable on the processor 301, When the program or instruction is executed by the processor 301, the various processes of the above embodiments of the slice processing method can be realized, and the same technical effect can be achieved. To avoid repetition, details are not repeated here.

It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile electronic devices and non-mobile electronic devices.

The embodiment of the present application also provides a readable storage medium. The readable storage medium stores programs or instructions. When the program or instructions are executed by the processor, the processes of the above embodiments of the slice processing method are implemented, and the same To avoid repetition, the technical effects will not be repeated here.

Wherein, the processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer readable storage medium, such as computer read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk, etc.

It should be noted that, in this document, the term "comprising", "comprising" or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article or apparatus comprising a set of elements includes not only those elements, It also includes other elements not expressly listed, or elements inherent in the process, method, article, or device. Without further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus comprising that element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved. Functions are performed, for example, the described methods may be performed in an order different from that described, and various steps may also be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

Through the description of the above embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus a necessary general-purpose hardware platform, and of course also by hardware, but in many cases the former is better implementation. Based on such an understanding, the technical solution of the present application can be embodied in the form of computer software products, which are stored in a storage medium (such as ROM/RAM, magnetic disk, etc.) , optical disc), including several instructions to enable a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present application.

The embodiments of the present application have been described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementations. The above-mentioned specific implementations are only illustrative and not restrictive. Those of ordinary skill in the art will Under the inspiration of this application, without departing from the purpose of this application and the scope of protection of the claims, many forms can also be made, all of which belong to the protection of this application.

Claims

A slice processing method, characterized in that, comprising:

Based on the received N task requests, generate task bodies corresponding to the N task requests, where N is a positive integer greater than 1;

According to the processing strategy of the N task requests, at least two models to be sliced corresponding to the task bodies are sequentially sliced until all layer slices of the at least two models to be sliced are obtained.
The method according to claim 1, wherein the slicing processing of at least two models to be sliced corresponding to the task body in a sequential loop includes:

For any model to be sliced, analyze the model slice information corresponding to the model to be sliced, and obtain the completed layer slice corresponding to the model to be sliced;

On the basis of the completed layer slicing, perform slicing processing on the model to be sliced to obtain process slicing information;

The process slicing information is stored in the model slicing information, and the model slicing information is refreshed.
The method according to claim 1, wherein the preset total number of slice layers of the task bodies is the same or different, and the task body with the least preset total number of slice layers ends first and exits the cycle slice processing .
The method according to claim 1, wherein the task body includes model parameters and scene parameters, and after generating the task bodies corresponding to the N task requests, the method further includes:

Obtain the model parameters corresponding to the task body, and obtain the model file corresponding to the task body according to the model parameters, wherein the cloud server stores the mapping relationship between the model parameters and the model file, and the cloud server receiving the model parameters for query and returning the corresponding model file;

The scene parameters corresponding to the task body are obtained, and the model file is linearly transformed according to the scene parameters to obtain the to-be-sliced model corresponding to the task body.
The method according to claim 4, wherein the scene parameter is a matrix sequence, the model file includes K model vertices, and K is a positive integer greater than 1;

The acquisition of the scene parameters corresponding to the task body, and performing linear transformation on the model file according to the scene parameters to obtain the to-be-sliced model corresponding to the task body, including:

For the model file corresponding to the task body, perform a matrix transformation operation on the coordinate value of each model vertex corresponding to the model file and the matrix sequence to obtain K model vertices after linear transformation;

A model generated from the K model vertices after the linear transformation is determined as the model to be sliced corresponding to the task body.
The method according to claim 4, wherein the task body further includes shelling parameters and/or support parameters, the shelling parameters are used to indicate that the model to be sliced is to be shelled, and the support The parameter is used to indicate to perform support processing on the model to be sliced;

After obtaining the to-be-sliced model corresponding to the task body, the method further includes:

Perform shelling processing on the model to be sliced according to the shelling parameters and/or perform support processing on the model to be sliced according to the support parameters.
A printing method, characterized in that the method comprises:

Acquiring an image to be printed, and printing a model according to the image to be printed; wherein, the image to be printed is a layer slice generated by the slice processing method according to any one of claims 1-6.
A printing system, characterized in that it includes an image processing device and a printing device;

The image processing device is configured to execute the slice processing method according to any one of claims 1-6;

The printing device uses the layer slices output by the image processing device, and obtains a model to be printed according to the layer slices.
A printing device, characterized by comprising a processor, a memory, and a program or instruction stored in the memory and operable on the processor, when the program or instruction is executed by the processor, the following The steps of the slice processing method described in any one of claims 1-6.
A readable storage medium, characterized in that a program or an instruction is stored on the readable storage medium, and when the program or instruction is executed by a processor, the slice processing method according to any one of claims 1-6 is implemented. step.