WO2018137454A1

WO2018137454A1 - Method of adjusting object shape, and adjustment device

Info

Publication number: WO2018137454A1
Application number: PCT/CN2017/118807
Authority: WO
Inventors: 施扬; 雷宇; 付一洲; 金宇林; 伏英娜
Original assignee: 迈吉客科技（北京）有限公司
Priority date: 2017-01-25
Filing date: 2017-12-27
Publication date: 2018-08-02
Also published as: CN106846428A

Abstract

A method of adjusting an object shape, and an adjustment device for handling technical issues of complication and high energy consumption of object shape processing on a mobile apparatus. The method comprises: determining a complete object outline and an object attribute in an image (01); creating, using a regular shape, a continuous grid on the basis of the complete object outline and the object attribute (02); establishing a mapping relationship between a local object and a local grid (03); generating, by changing an attribute of the local grid, deformation data of the local object (04); and employing attributes of the continuous grids as a rendering parameter, and utilizing a GPU to process a complete object (05).

Description

Image shape adjustment method and adjusting device

The present invention claims priority from the applicant's application, which is filed on Jan. 25, 2017, and whose application number is CN201710060917.4, entitled "An Image Shape Adjustment Method and Adjustment Device." The entire contents of the above application are hereby incorporated by reference in its entirety.

Technical field

The present invention relates to the field of computer graphics processing, and in particular, to an image shape adjustment method and an adjustment apparatus.

Background of the invention

In the prior art, the processing of stereoscopic graphics changes by a computer is mainly done by a shader (a renderer for rendering of colors, textures, patterns). The shader has higher processing efficiency for the stereoscopic graphic object, but for the deformation processing of the planar image, there is uncertainty directly through the shader processing. For example, the deformation of the anthropomorphic image has a certain degree of ambiguity in rendering the vertices. It is difficult to debug the processing directly by the shader. Even by breaking the point, printing the log and the like cannot be solved well. Moreover, there are large compatibility problems between shaders implemented by different types of GPUs. Simple shader processing results can be consistent, and complex shaders have certain uncertainties in the processing results of different GPUs, which leads to Rendering error.

Moreover, the GPU processing highlights the real-time nature and lacks effective power management means. For mobile terminals, the power consumption is large, which is not conducive to the endurance duration.

Summary of the invention

In view of this, an embodiment of the present invention provides an image shape adjustment method and an adjustment apparatus for solving the technical problem of complexity and high energy consumption of image shape processing on a mobile device.

The image shape adjustment method of the embodiment of the invention includes:

Determining the complete object outline and object properties in the image;

Establishing a continuous mesh using regular graphics based on the complete object contour and object properties;

Mapping a local object with a local mesh;

Deformation data of the local object is formed by changing the properties of the local mesh;

Using continuous mesh attributes as rendering parameters, the GPU is used to form the processing of the complete object.

The determining the complete object outline and object attributes in the image includes:

Determining the contour of the face;

Determine the outline of the five senses;

Determine the key feature locations of the five senses.

The establishing a continuous grid based on the complete object contour and the object attribute using the regular pattern includes:

Set key feature points in the contour position of the face;

Set key feature points in key features of the five senses;

Form a continuous grid between key feature points.

The mapping between the local object and the local mesh includes:

Correlating each mesh with a unique corresponding partial face;

Each grid is associated with a texture pattern of a corresponding partial face.

The deformation data of the local object formed by changing the attributes of the local mesh includes:

Recording the active mesh that is pushed and pulled, the displacement position and vertex position of the active mesh;

Recording the passive mesh adjacent to the pushed-pull mesh, the displacement position and the vertex position of the passive mesh;

Updates the shape and position of the mesh in the continuous mesh to form rendering parameters.

The processing of the complete object by using the GPU as a rendering parameter includes:

The initial continuous mesh, the texture pattern of the partial face corresponding to the mesh, and the rendering parameters are passed to the GPU through the graphics processing interface.

The image shape adjustment device of the embodiment of the invention includes:

Object determination module: used to determine the complete object outline and object attributes in the image;

Grid building module: for constructing a continuous mesh using regular graphics based on complete object contours and object properties;

Mapping module: used to map a local object to a local mesh;

Grid adjustment module: used to form deformation data of a local object by changing attributes of the local grid;

Output module: used to use continuous grid properties as rendering parameters, using the GPU to form the processing of the complete object.

The object determination module includes:

Main contour determination sub-module: used to determine the contour of the face;

Secondary contour determination sub-module: used to determine the contour of the facial features;

Specific contour determination sub-module: used to determine the key feature location of the facial features.

The grid building module includes:

Contour feature positioning sub-module: used to set key feature points in the contour position of the face;

Key feature positioning sub-module: used to set key feature points in key feature positions of the five senses;

Grid Connection Submodule: Used to form a continuous mesh between key feature points.

The mapping module includes:

Image area mapping sub-module: for mapping each grid to a unique corresponding partial face;

An image attribute mapping sub-module: configured to form a correspondence between each mesh and a texture pattern of a corresponding partial face;

The grid adjustment module includes:

Active adjustment sub-module: used to record the active mesh being pushed and pulled, the displacement position and vertex position of the active mesh;

Passive adjustment sub-module: used to record the passive grid adjacent to the push-pull grid, the displacement position and vertex position of the passive grid;

Update submodule: Used to update the shape and position of the mesh in a continuous mesh to form rendering parameters.

The output module includes:

Interface Adaptation Sub-module: used to transfer the initial continuous mesh, the texture pattern of the partial face corresponding to the mesh, and the rendering parameters to the GPU through the graphics processing interface.

An image shape adjustment device according to an embodiment of the present invention includes a processor and a memory,

The memory is configured to store program code for performing the image shape adjustment method described above;

The processor is configured to execute the program code.

The image shape adjustment method and adjustment apparatus of the present invention can make full use of the feature attributes of a specific object to determine an accurate range of a specific object in an image, and at the same time determine a key feature position in a specific object. These key feature locations form the basic coordinate system of a particular object and are used to establish an accurate positional association between key features, ie a continuous mesh. By actively adjusting the position of the local key features, the change position coordinates of the actively adjusted local key features, that is, the local mesh attributes, and the influence of the locally adjusted key features, and the changes of other passively adjusted local key features can be obtained. Position coordinates, which are other grid properties. In this way, a general recognition algorithm can be used to perform a rendering parameter transformation process of a specific image on a general-purpose processor, and the resulting parameter can be directly applied to a basic stretching, warping or rendering process with rendering consistency, ensuring different types of GPUs. Rendering effect. It fully satisfies the versatility of GPUs on different mobile terminals, avoiding the high energy consumption of GPU advanced data processing.

BRIEF DESCRIPTION OF THE DRAWINGS

1 is a process flow diagram of an embodiment of an image shape adjustment method according to the present invention.

2 is a process flow diagram of another embodiment of an image shape adjustment method according to the present invention.

Fig. 3 is a flow chart showing the processing of an image shape adjusting device according to an embodiment of the present invention.

Fig. 4 is a flow chart showing the processing of another embodiment of the image shape adjusting device of the present invention.

Mode for carrying out the invention

The technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present invention. It is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.

The step numbers in the drawings are only used as reference numerals for the steps, and do not indicate the order of execution.

1 is a process flow diagram of an embodiment of an image shape adjustment method according to the present invention. As shown in FIG. 1 , an image shape adjustment method according to an embodiment of the present invention includes:

Step 01: Determine a complete object outline and an object attribute in the image;

Step 02: construct a continuous mesh using regular patterns based on the complete object contour and the object attribute;

Step 03: Establish a mapping relationship between the local object and the local mesh;

Step 04: Form deformation data of the local object by changing attributes of the local mesh;

Step 05: Using the continuous mesh attribute as a rendering parameter, the GPU is used to form a process for the complete object.

The image shape adjustment method according to an embodiment of the present invention can fully utilize the feature attributes of a specific object to determine an accurate range of a specific object in an image, and simultaneously determine a key feature position in a specific object. These key feature locations form the basic coordinate system of a particular object and are used to establish an accurate positional association between key features, ie a continuous mesh. By actively adjusting the position of the local key features, the change position coordinates of the actively adjusted local key features, that is, the local mesh attributes, and the influence of the locally adjusted key features, and the changes of other passively adjusted local key features can be obtained. Position coordinates, which are other grid properties. In this way, a general recognition algorithm can be used to perform a rendering parameter transformation process of a specific image on a general-purpose processor, and the resulting parameter can be directly applied to a basic stretching, warping or rendering process with rendering consistency, ensuring different types of GPUs. Rendering effect. It fully satisfies the versatility of GPUs on different mobile terminals, avoiding the high energy consumption of GPU advanced data processing.

In the image shape adjustment method according to an embodiment of the present invention, the complete object contour in the above step 01 is a facial contour or a head front contour, and the object attribute is a facial features, including but not limited to, the highest point of the humerus, the brow bone. Specific key features such as the highest point, inner corner of the eye, outer corner of the eye, corner of the mouth, inner tip of the eyebrow, outer eyebrow tip, nose, nose, and pupil.

In the above step 02, the largest object covering other objects in the complete object contour can be used as the reference boundary of the continuous mesh. When the largest object is a face, the contour edge of the file can be used as a reference boundary of the continuous mesh, and the reference boundary extension can form a follow-up extension mesh for adapting the changes of the face and the surrounding environment.

In the above step 04, the attributes of the local mesh include a shape attribute, and a vertex coordinate attribute of the shape.

In the above step 05, the rendering parameters include the changed mesh vertex coordinates. The GPU utilizes the vertex shader supported by both OpenGL and Direct3D to change the vertex coordinates of the mesh in real time, using texture mapping methods supported by both OpenGL and Direct3D to change the rendering to the screen.

2 is a process flow diagram of another embodiment of an image shape adjustment method according to the present invention. As shown in FIG. 2, in the image shape adjustment method according to an embodiment of the invention, the step 01 includes:

Step 11: Determine the outline of the face. After the color image is converted into a grayscale image, clustering processing is performed to obtain a contour of the face.

Step 12: Determine the outline of the facial features. After the color image is converted into a grayscale image, clustering is performed to obtain a contour of the facial features.

Step 13: Determine the key feature locations of the facial features. The physiological characteristics of the facial features can be used to identify irrelevant key feature locations.

In the image shape adjustment method of an embodiment of the invention, the step 02 includes:

Step 21: Set key feature points at the contour position of the face. The key feature points of the contour include, but are not limited to, the symmetry axis endpoint of the face, the maximum offset point and endpoint of the continuous dashed line, discrete symmetry points, and the like.

Step 22: Set key feature points in the key features of the facial features. Key features of the five senses include, but are not limited to, the above-mentioned points of physiological characteristics.

Step 23: Form a continuous grid between the key feature points. The mesh of the continuous mesh is a triangle or a triangle, and the continuous mesh is a two-dimensional mesh. The vertices of the triangle are adjacent points.

In an embodiment of the invention, the perimeter of the continuous mesh (ie, the contour of the face) extends outward to form an epitaxial grid of the following continuous mesh, and the epitaxial mesh is formed as a boundary of the continuous mesh and is formed by a triangle.

In an embodiment of the invention, the continuous mesh epitaxy forms a larger passive follower grid centered on respective image pixels comprising a continuous grid. The correlation between the edge mesh of the passive follower mesh and the central mesh is weakened with increasing distance.

In the image shape adjustment method of an embodiment of the invention, the step 03 includes:

Step 31: Correlate each grid with a unique corresponding partial face. The correspondence includes both the area correspondence of each mesh and the corresponding partial face of the overlay, and the correspondence with the vertex position of the partial face. In an embodiment of the invention, each mesh and the unique corresponding partial face may be replaced by a unique corresponding face or facial features corresponding to the corresponding set of meshes to form a corresponding relationship.

Step 32: Correspond relationship between each mesh and the texture pattern of the corresponding partial face. Image attributes including the area of each mesh and the corresponding partial face of the overlay, including but not limited to image attributes such as texture, color, and brightness.

In the image shape adjustment method of an embodiment of the invention, the step 04 includes:

Step 41: Record the active mesh that is pushed and pulled, the displacement position and the vertex position of the active mesh. The active mesh includes a grid that is controlled to change shape or/and position to change displacement.

Step 42: Record the passive mesh adjacent to the pushed-pull mesh, the displacement position and the vertex position of the passive mesh. The passive grid includes a grid that conducts active mesh changes, forming shapes or/and shifting positions.

Step 43: Update the shape and position of the mesh in the continuous mesh to form a rendering parameter. The modified coordinates of these formed mesh vertices are placed in the Vertex Shader to control the shape of the mesh.

In the image shape adjustment method according to an embodiment of the invention, the step 05 includes:

Step 51: Pass the initial continuous mesh, the texture pattern of the partial face corresponding to the mesh, and the rendering parameters to the GPU through the graphics processing interface. Graphics processing interfaces include, but are not limited to, standard interfaces or interface subsets such as DirectX, OpenGLES, and the like.

After obtaining the above data, the GPU completes the deformation and rendering of the original facial image according to the rendering parameters, and implements face adjustment. The image shape adjustment method according to an embodiment of the present invention fully utilizes the CPU to complete the acquisition of the main deformation parameters of the fine object face, thereby greatly shortening the GPU high-load processing time and reducing the energy consumption. The GPU obtains parameters only by completing a simple processing rendering process, maintaining compatibility and output consistency with the image processing software hardware.

The processing of the GPU includes:

Use the mechanism of texture mapping to change the position of the face pixels on the screen;

First draw the original full-screen texture for the follower mesh;

The deformed full-screen texture is then drawn for the extended face mesh.

In this way, it can be ensured that the face shape change can be limited to the extent of the epitaxial grid, and does not affect the deformation of the screen where it should not be accompanied by deformation.

Fig. 3 is a flow chart showing the processing of an image shape adjusting device according to an embodiment of the present invention. As shown in FIG. 3, in accordance with an image shape adjustment method according to an embodiment of the present invention, an image shape adjustment apparatus according to an embodiment of the present invention includes:

Object determination module 100: for determining a complete object outline and an object attribute in the image;

Grid building module 200: for constructing a continuous mesh using regular graphics based on the complete object contour and object attributes;

The mapping module 300 is configured to establish a mapping relationship between the local object and the local mesh.

The mesh adjustment module 400 is configured to form deformation data of the local object by changing attributes of the local mesh;

The output module 500 is configured to use a GPU to form a processing of a complete object by using a continuous mesh attribute as a rendering parameter.

Fig. 4 is a flow chart showing the processing of another embodiment of the image shape adjusting device of the present invention. As shown in FIG. 4, in the image shape adjustment device of an embodiment of the present invention, the object determination module 100 includes:

The main contour determining sub-module 110 is for determining the contour of the face. After the color image is converted into a grayscale image, clustering processing is performed to obtain a contour of the face.

Secondary contour determination sub-module 120: used to determine the contour of the facial features. After the color image is converted into a grayscale image, clustering is performed to obtain a contour of the facial features.

The specific contour determination sub-module 130 is used to determine the key feature position of the facial features. The physiological characteristics of the facial features can be used to identify irrelevant key feature locations.

In the image shape adjustment device of an embodiment of the present invention, the mesh creation module 200 includes:

The contour feature locating sub-module 210 is configured to set a key feature point at a contour position of the face. The key feature points of the contour include, but are not limited to, the symmetry axis endpoint of the face, the maximum offset point and endpoint of the continuous dashed line, discrete symmetry points, and the like.

The key feature locating sub-module 220 is configured to set a key feature point in a key feature position of the facial features. Key features of the five senses include, but are not limited to, the above-mentioned points of physiological characteristics.

Grid connection sub-module 230: for forming a continuous mesh between key feature points. The mesh of the continuous mesh is a triangle or a triangle, and the continuous mesh is a two-dimensional mesh. The vertices of the triangle are adjacent points.

Further, it is further used for extending the outer periphery of the continuous mesh (ie, the contour of the face) to form an epitaxial mesh of the following continuous mesh, and the epitaxial mesh is formed as a boundary of the continuous mesh by a triangle.

Further, it is further used to form a larger passive follower mesh by continuous mesh epitaxy centering on corresponding image pixels including continuous meshes. The correlation between the edge mesh of the passive follower mesh and the central mesh is weakened with increasing distance.

In the image shape adjustment device of an embodiment of the invention, the mapping module 300 includes:

The image area mapping sub-module 310 is configured to form each grid to correspond to a unique corresponding partial face. The correspondence includes both the area correspondence of each mesh and the corresponding partial face of the overlay, and the correspondence with the vertex position of the partial face.

The image attribute mapping sub-module 320 is configured to form a correspondence between each of the meshes and a texture pattern of the corresponding partial face. Image attributes including the area of each mesh and the corresponding partial face of the overlay, including but not limited to image attributes such as texture, color, brightness, and the like.

In the image shape adjustment device of an embodiment of the invention, the mesh adjustment module 400 includes:

The active adjustment sub-module 410 is configured to record the active mesh that is pushed and pulled, the displacement position and the vertex position of the active mesh. The active mesh includes a grid that is controlled to change shape or/and position to change displacement.

The passive adjustment sub-module 420 is configured to record a passive mesh adjacent to the pushed-pull mesh, a displacement position and a vertex position of the passive mesh. The passive grid includes a grid that conducts active mesh changes, forming shapes or/and shifting positions.

Update sub-module 430: for updating the shape and position of the mesh in the continuous mesh to form a rendering parameter.

In an image shape adjustment device according to an embodiment of the invention, the output module 500 includes:

The interface adaptation sub-module 510 is configured to pass the initial continuous mesh, the texture pattern of the partial face corresponding to the mesh, and the rendering parameters to the GPU through the graphics processing interface. Graphics processing interfaces include, but are not limited to, standard interfaces or interface subsets such as DirectX, OpenGLES, and the like.

The above is only the preferred embodiment of the present invention, and is not intended to limit the present invention. Any modifications, equivalent substitutions, etc., which are within the spirit and principles of the present invention, should be included in the scope of the present invention. within.

An image shape adjustment device according to an embodiment of the present invention includes a memory and a processor, wherein:

a memory for storing program code for implementing the processing steps of the image shape adjustment method of the above embodiment;

The processor is for executing program code for implementing the processing steps of the image shape adjustment method of the above embodiment.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the various examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the solution. A person skilled in the art can use different methods for implementing the described functions for each particular application, but such implementation should not be considered to be beyond the scope of the present invention.

A person skilled in the art can clearly understand that for the convenience and brevity of the description, the specific working process of the system, the device and the unit described above can refer to the corresponding process in the foregoing method embodiment, and details are not described herein again.

In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of the unit is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.

The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

Functionality, if implemented as a software functional unit and sold or used as a stand-alone product, can be stored on a computer readable storage medium. Based on such understanding, the technical solution of the present invention, which is essential or contributes to the prior art, or a part of the technical solution, may be embodied in the form of a software product, which is stored in a storage medium, including The instructions are used to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and the like, and can store a program check code. Medium.

The above is only a specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily think of changes or substitutions within the technical scope of the present invention. It should be covered by the scope of the present invention. Therefore, the scope of the invention should be determined by the scope of the claims.

Industrial applicability

The image shape adjustment method and adjustment apparatus of the present invention establish an accurate positional association between key features, forming an associated mesh attribute. It can realize the rendering parameter transformation processing of a specific image on a general-purpose processor by using a universal recognition algorithm, and the formed result parameters can be directly applied to the basic stretching, warping or rendering process with rendering consistency, and the rendering of different types of GPUs is guaranteed. effect. It fully satisfies the versatility of GPUs on different mobile terminals, avoiding the high energy consumption of GPU advanced data processing.

Claims

An image shape adjustment method includes:

Determining the complete object outline and object properties in the image;

Establishing a continuous mesh using regular graphics based on the complete object contour and object properties;

Mapping a local object with a local mesh;

Deformation data of the local object is formed by changing the properties of the local mesh;

Using continuous mesh attributes as rendering parameters, the GPU is used to form the processing of the complete object.
The image shape adjustment method according to claim 1, wherein the determining the complete object outline and the object attribute in the image comprises:

Determining the contour of the face;

Determine the outline of the five senses;

Determine the key feature locations of the five senses.
The image shape adjustment method according to claim 1, wherein the establishing a continuous mesh using the regular pattern based on the complete object contour and the object attribute comprises:

Set key feature points in the contour position of the face;

Set key feature points in key features of the five senses;

Form a continuous grid between key feature points.
The image shape adjustment method according to claim 1, wherein the mapping the local object to the local mesh comprises:

Correlating each mesh with a unique corresponding partial face;

Each grid is associated with a texture pattern of a corresponding partial face.
The image shape adjustment method according to claim 1, wherein the deforming data of the local object is formed by changing an attribute of the local mesh:

Recording the active mesh that is pushed and pulled, the displacement position and vertex position of the active mesh;

Recording the passive mesh adjacent to the pushed-pull mesh, the displacement position and the vertex position of the passive mesh;

Updates the shape and position of the mesh in the continuous mesh to form rendering parameters.
The image shape adjustment method according to claim 1, wherein the processing of the complete object by using the GPU as a rendering parameter comprises:

The initial continuous mesh, the texture pattern of the partial face corresponding to the mesh, and the rendering parameters are passed to the GPU through the graphics processing interface.
An image shape adjustment device includes:

Object determination module: used to determine the complete object outline and object attributes in the image;

Grid building module: for constructing a continuous mesh using regular graphics based on complete object contours and object properties;

Mapping module: used to map a local object to a local mesh;

Grid adjustment module: used to form deformation data of a local object by changing attributes of the local grid;

Output module: used to use continuous grid properties as rendering parameters, using the GPU to form the processing of the complete object.
The image shape adjustment device according to claim 7, wherein the object determination module comprises:

Main contour determination sub-module: used to determine the contour of the face;

Secondary contour determination sub-module: used to determine the contour of the facial features;

Specific contour determination sub-module: used to determine the key feature location of the facial features.
The image shape adjustment device according to claim 7, wherein the mesh creation module comprises:

Contour feature positioning sub-module: used to set key feature points in the contour position of the face;

Key feature positioning sub-module: used to set key feature points in key feature positions of the five senses;

Grid Connection Submodule: Used to form a continuous mesh between key feature points.
The image shape adjustment device according to claim 7, wherein the mapping module comprises:

Image area mapping sub-module: for mapping each grid to a unique corresponding partial face;

Image attribute mapping sub-module: for mapping each grid to a texture pattern of a corresponding partial face.
The image shape adjustment device according to claim 7, wherein the mesh adjustment module comprises:

Active adjustment sub-module: used to record the active mesh that is pushed and pulled, the displacement position and vertex position of the active mesh;

Passive adjustment sub-module: used to record the passive grid adjacent to the push-pull grid, the displacement position and vertex position of the passive grid;

Update submodule: Used to update the shape and position of the mesh in a continuous mesh to form rendering parameters.
The image shape adjustment device according to claim 7, wherein the output module comprises:

Interface Adaptation Sub-module: used to transfer the initial continuous mesh, the texture pattern of the partial face corresponding to the mesh, and the rendering parameters to the GPU through the graphics processing interface.
An image shape adjustment device includes a processor and a memory, wherein

The memory is configured to store program code for completing the image shape adjustment method according to any one of claims 1 to 6;

The processor is configured to execute the program code.