Method, device, equipment and storage medium for processing terrain data

Abstract

The present invention provides a method, apparatus, device, and storage medium for processing terrain data. The method comprises: utilizing an HDA node network to analyze terrain landscapes in three-dimensional terrain data, segmenting the analyzed terrain landscapes into blocks, and determining the positional mapping relationship between the segmented block images in the corresponding terrain landscapes to obtain corresponding block image sets; utilizing the HDA node network to stitch the block images in the block image sets to generate corresponding terrain landscape layers, and then stitching the terrain landscape layers together to obtain terrain image files. The HDA node network automatically saves three-dimensional terrain data in UE4 into a multi-layer file, wherein the blocks are managed, thereby achieving batch stitching of map data.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to a method, device, equipment and storage medium for processing terrain data. Background Art

[0002] X28 is an open-world SLG game. In order to ensure fast reading of game map data, it is necessary to uniformly manage and store the map data in the game. However, most of the current games are 3D map data, which requires a larger storage system to achieve.

[0003] With the development of information processing technology, converting 3D data into 2D information for storage has become a common method. In this regard, in games, the process of converting 3D terrain into 2D image information is called terrain backtracking. This process involves overwriting and reading back and forth of various map data, and the map data in the game is very large. For this, the most traditional version control method is used to back up files, but the intermediate data saving and reading still need to be done manually. The manual operation method often leads to some problems that may arise from manual editing, such as incorrect naming of data files, conflicts with other plot files, etc. When it comes to exporting data, the only solution is to use UE4's default method of exporting height maps. Other terrain information, such as material layer information, can only be saved and named one by one, which is very time-consuming and labor-intensive. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a method, device, equipment and storage medium for processing terrain data to solve the problem that in existing terrain import solutions, batch stitching and importing cannot be achieved to generate complete terrain information.

[0005] In a first aspect, an embodiment of the present invention provides a method for processing terrain data, the method comprising:

[0006] Get the 3D terrain data in the engine;

[0007] Utilizing the HDA node network to parse the terrain landscapes in the three-dimensional terrain data, dividing the terrain landscapes into blocks based on the parsed terrain landscapes, and determining the position mapping relationship of the divided block images in the corresponding terrain landscapes to obtain a corresponding block image set;

[0008] The HDA node network is used to stitch the plot images in each plot image set to generate a corresponding terrain landscape layer, and each terrain landscape layer is stitched layer by layer to obtain a terrain image file.

[0009] In a second aspect, an embodiment of the present invention provides a terrain data processing device, the terrain data processing device comprising:

[0010] Acquisition module, used to obtain three-dimensional terrain data in the engine;

[0011] A segmentation module is configured to analyze the terrain landscapes in the three-dimensional terrain data using an HDA node network, segment the terrain landscapes based on the segmentation results, and determine a position mapping relationship between the segmented plot images in the corresponding terrain landscapes to obtain a corresponding plot image set;

[0012] The stitching module is used to stitch the plot images in each plot image set using the HDA node network to generate corresponding terrain landscape layers, and stitch each terrain landscape layer layer to obtain a terrain image file.

[0013] In a third aspect, an embodiment of the present invention provides an electronic device including a processor and a memory, wherein the memory stores machine-executable instructions that can be executed by the processor, and the processor executes the machine-executable instructions to implement the above-mentioned terrain data processing method.

[0014] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the above-mentioned terrain data processing method.

[0015] The embodiments of the present invention bring the following beneficial effects:

[0016] The above-mentioned terrain data processing method, device, equipment and storage medium utilize an HDA node network to parse the terrain landscapes in the three-dimensional terrain data, and divide the terrain landscapes into blocks based on the parsed terrain landscapes, and determine the position mapping relationship of each block image in the corresponding terrain landscape to obtain a corresponding plot image set; utilize the HDA node network to stitch the plot images in each plot image set to generate a corresponding terrain landscape layer, and stitch the terrain landscape layers together to obtain a terrain image file. The three-dimensional terrain data in UE4 is automatically saved into a multi-layer file through the HDA node network, in which the plots are used as management objects, and batch stitching of map data is realized. Compared with the existing technology, no manual operation is required, and the automatic generation and storage of map data is realized.

[0017] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0018] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 A flow chart of a method for processing terrain data provided by an embodiment of the present invention;

[0021] Figure 2 A schematic diagram of a game terrain map provided by an embodiment of the present invention;

[0022] Figure 3 Another flow chart of a method for processing terrain data provided by an embodiment of the present invention;

[0023] Figure 4 A block diagram of a game terrain map provided by an embodiment of the present invention;

[0024] Figure 5 A position mapping relationship diagram between a plot image and three-dimensional terrain data provided by an embodiment of the present invention;

[0025] Figure 6 A schematic diagram of updating a plot image provided by an embodiment of the present invention;

[0026] FIG7 is a schematic diagram of a historical plot image and an edited plot image;

[0027] Figure 8 A schematic diagram of an incremental image provided by an embodiment of the present invention;

[0028] Figure 9 This is a schematic diagram of the modified historical plot image;

[0029] Figure 10 A schematic diagram of a game terrain map after deletion provided by an embodiment of the present invention;

[0030] Figure 11 A schematic diagram of a plot image after deletion provided by an embodiment of the present invention;

[0031] Figure 12 A schematic structural diagram of a terrain data processing device provided by an embodiment of the present invention;

[0032] Figure 13Another structural schematic diagram of a terrain data processing device provided by an embodiment of the present invention;

[0033] Figure 14 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0034] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work shall fall within the scope of protection of the present invention.

[0035] First, the application scenarios to which this application is applicable are introduced. This application can be applied in the field of image processing technology.

[0036] To facilitate understanding of this embodiment, a method for processing terrain data disclosed in an embodiment of the present invention is first described in detail. Figure 1 As shown, a graphical user interface is provided by a terminal, wherein the graphical user interface includes a terrain editing interface, and the terrain editing interface includes the voxel terrain to be edited. For example, this method can be applied to a terminal device capable of running 3D design software, and the graphical user interface can be an interactive interface provided by the 3D design software. The 3D design software can be Houdini, and the terrain data processing method includes the following steps:

[0037] Step S101: Acquire three-dimensional terrain data in the engine.

[0038] In this step, the three-dimensional terrain data in UE4 is obtained through Houdini and displayed on the terrain editing interface of the terminal device. The three-dimensional terrain data is preprocessed based on the interface to obtain the three-dimensional terrain data to be edited.

[0039] In this embodiment, preprocessing can be understood as landscape extraction of the 3D terrain data acquired from UE4. A complete game map contains at least information such as buildings, vegetation, transportation routes, and rivers. Based on these landscapes, the 3D terrain data is parsed, and each landscape type is formed into a separate image layer, resulting in editable 3D terrain data.

[0040] In step S102, the HDA node network is used to parse the terrain landscapes in the three-dimensional terrain data, and the terrain landscapes are divided into blocks based on the parsed terrain landscapes. The position mapping relationship of the divided block images in the corresponding terrain landscapes is determined to obtain a corresponding block image set.

[0041] In this embodiment, the HDA (Houdini Digital Asset) node network includes at least two core nodes, namely a three-dimensional map image conversion node and a map block synthesis node.

[0042] The 3D terrain data obtained from UE4 is received through the 3D map conversion image node, and the 3D terrain data is sent to the HDA node network according to the landscape to output the image. The image is divided into blocks and the corresponding coordinate information is configured. Based on the coordinate information, the position mapping relationship of each block image in the corresponding terrain landscape is constructed. Finally, the block-divided and configured coordinate information and position mapping relationship images are segmented to obtain the corresponding plot image set.

[0043] In one embodiment, when dividing the three-dimensional terrain data into blocks, firstly, terrain data is extracted from the three-dimensional terrain data using an HDA node network according to the landscape type of the terrain to obtain a plurality of terrain landscape images;

[0044] Then, each of the terrain landscape pictures is divided into blocks, and the block value determination rule is used to determine the block value of each block, and a position mapping relationship between the block and the corresponding terrain landscape picture is constructed to obtain a block picture set corresponding to the terrain landscape picture.

[0045] Among them, the plot value determination rule can be understood as a judgment code for a plot value. In actual application, after the terrain landscape image is divided into blocks, a serial number will be assigned to each plot. The serial number is specifically determined based on the pixel row and column coordinates of the terrain landscape image itself. For example: assuming that a map is divided into 20*20 blocks in length and width, then the row and column xy: x=int(i / 20), y=int(i%20), and the judgment code is used to read the row and column coordinates of the plot in the map landscape image to determine the plot value of the plot.

[0046] In practical applications, the terrain landscape picture is evenly divided into multiple plots according to the preset block strategy, and then a serial number is set for each plot, and the coordinate information of the plot corresponding to each serial number is calculated. That is, the plot value determination rule is used to determine the plot value of each plot, and finally, the position mapping relationship between the block and the corresponding terrain landscape picture is constructed based on the calculated coordinate information and the corresponding serial number.

[0047] Furthermore, after determining the position mapping relationship, it also includes querying whether the same plot exists in the storage disk based on the position mapping relationship and the plot value. If so, the corresponding historical plot is read, and the historical plot is compared with the current plot to determine the difference. The historical plot is updated based on the difference to obtain the corresponding plot image, thereby generating a corresponding plot image set.

[0048] Step S103: Using the HDA node network, the plot images in each plot image set are stitched together to generate corresponding terrain landscape layers, and the terrain landscape layers are stitched together to obtain a terrain image file.

[0049] Specifically, the names of the plot images in the plot image set are identified through the map block synthesis node in the HDA node network. The area of ​​each plot image in the three-dimensional terrain data is determined based on the name recognition result and the plot value determination rule. The plot images are split based on the area, and a sequence grammar is constructed for each category of plot images in the order of location information, where each sequence grammar corresponds to a type of landscape. Finally, the corresponding plot images are spliced ​​based on the sequence grammar to achieve the splicing of each landscape into a layer. Specifically, when splicing layers, it can be achieved by calling image processing software, such as PS software, loading various terrain landscape layers through PS software, and then using the layer merging function in PS software to merge multiple terrain landscape layers.

[0050] Furthermore, the layers are reassembled, linking them together to create a layered file. Based on this file, image processing software can then construct complete 3D terrain data. This method converts 3D terrain data into images and stores them in blocks. Based on the mapping relationships and the stitching relationships between layers, image processing software can quickly retrieve the corresponding images and layers to update and construct the 3D terrain data.

[0051] The above-mentioned terrain data processing method converts and segments the three-dimensional terrain data through the HDA node network to form a plot image set, then reads the plot image set based on the HDA node network for splicing, converts it into layers, and then splices the layers to obtain a complete image file, thereby realizing block-by-block batch management of map data, solving the problem in the existing technology that there is no way to splice the complete terrain information of an entire open world and the problem of simultaneous image data processing.

[0052] The following embodiment provides a specific implementation method for processing terrain data, which is described using a terrain map of a game scene as an example. Figure 2 This is an example of a terrain map for a game scene.

[0053] In this embodiment, the method is applied to a gaming device, which includes a client and a server. The client displays the game scene and the operation interface. The server runs the game program and displays the corresponding game scene according to the client's response to various operations, wherein the game scene includes a game terrain map. Based on this structure, a method for processing terrain data is provided. The method is mainly proposed in the environment of python environment and the open source library Photoshop Python API. The method is specifically implemented by pre-set code. The following describes the method in conjunction with the specific algorithm flow and hardware structure. First, all technical implementations of the method are encapsulated in Houdini's HDA and used in UE4 through HoudiniEngine. Houdini's PDG module is mainly used, and the Photoshop Pyhon console is started in the background through the Commain Chain node in the PDG module. Write a custom Command script (Python process code). The script can contain any PS operation logic, such as creating a new PS document, modifying the background color, modifying the layer name, adding and deleting layers, adding filters, etc. Finally, send the script to the photoshop's python console for execution to achieve the effect of an automated process. As Figure 2 For the sake of convenience, the following is a case where the game terrain map is divided into 16 plots. Every time the planner edits the terrain, new data will be updated. Figure 3 As shown, the method specifically includes the following steps:

[0054] Step S301: Install the Python environment and the open source library Photoshop Python API.

[0055] Step S302, acquiring three-dimensional terrain data in the engine;

[0056] In this embodiment, the game terrain map in UE4 is received through the HDA node network, and then the corresponding image is output.

[0057] In actual applications, after the HDA node network obtains the three-dimensional terrain data, it extracts the different landscape and material information in the three-dimensional terrain data, converts this information into two dimensions, and outputs the corresponding image. That is, the function of X28_pdg_layout3d is to output the multi-plot terrain information of UE4 into PNG, including the height map and all material information.

[0058] Step S303 : extracting terrain data from the three-dimensional terrain data using the HDA node network according to the terrain landscape type, and obtaining a plurality of terrain landscape pictures.

[0059] In this step, the HDA node network includes at least x28_terrain_to_pixel (3D terrain to image node) and x28_top_caotu_export (map block synthesis node). The x28_terrain_to_pixel node in the HDA node network is used to receive the UE4's three-dimensional terrain data. After the three-dimensional terrain data is parsed according to the landscape type through this node, it is connected to the HDA in sequence, and then the corresponding images are output to obtain multiple terrain landscape images.

[0060] Step S304 , dividing each terrain landscape picture into blocks, and determining the block value of each block using the block value determination rule, constructing a position mapping relationship between the block and the corresponding terrain landscape picture, and obtaining a block picture set corresponding to the terrain landscape picture.

[0061] In this embodiment, when the three-dimensional terrain data is input for the first time, the block value determination rule is used to re-assign values ​​to each block in the divided terrain landscape image to determine the position information of each block and obtain a block image.

[0062] If the three-dimensional terrain data is not input for the first time, the block value determination rule is used to identify whether the three-dimensional terrain data is a block image. If so, the block value is determined. If not, each of the terrain landscape images is divided into blocks and the block value determination rule is used to determine the block value of each block.

[0063] Using a preset landscape type identification code, identifying the type of each of the terrain landscape images, and determining a corresponding terrain layer derivation logic based on the type;

[0064] According to the terrain layer derivation logic and the land parcel values, a position mapping relationship between the blocks and the corresponding terrain landscape pictures is calculated to obtain a land parcel picture set corresponding to the terrain landscape picture.

[0065] Furthermore, the step of calculating the position mapping relationship between the blocks and the corresponding terrain landscape pictures according to the terrain layer derivation logic and the plot values ​​to obtain a plot picture set corresponding to the terrain landscape pictures includes:

[0066] Calculate the position information of the corresponding block in the corresponding terrain landscape image according to the terrain layer derivation logic and the block value;

[0067] Read the historical plot image that matches the plot value; wherein the historical plot image can be stored in a storage disk, or can be stored in a local cache or other storage device, such as a chip storage device.

[0068] Comparing the plot image corresponding to the plot value with the historical plot image, and extracting inconsistent parts of the plot image to generate an updated plot image;

[0069] Based on the location information, determining a location mapping relationship between the updated land parcel image and the corresponding terrain landscape image;

[0070] Based on the position mapping relationship, the updated plot image is updated to a plot image set corresponding to the terrain landscape image.

[0071] like Figure 4 As shown, the game terrain map in the figure is divided into blocks, that is, the UE4 terrain Landscape is selected and connected to the HDA as the input data of the node. The tile value of the block is determined by the code to determine which area of ​​the image the block information will eventually be mapped to.

[0072] Then determine the processing position of the current image based on the block xy coordinates passed in after the code calculation, such as Figure 5 The right half of the image in the figure is part of the left half. The x and y coordinates of the entire map are 0 to 1, and the coordinates are calculated according to the blocks they belong to.

[0073] In practical applications, when the three-dimensional terrain data is not input for the first time, after segmentation, it is necessary to compare the differences between the segmented plot images, and update the historical plot images with the differences to obtain a plot image set.

[0074] In this embodiment, it is divided into two parts: data increment and data deletion. For the purpose of explanation, the modification is deliberately exaggerated. Figure 6 One check mark is to incrementally modify the river information on the terrain.

[0075] In this embodiment, the step of comparing the plot image corresponding to the plot value with the historical plot image, extracting inconsistent parts of the plot image, and generating an updated plot image includes:

[0076] Expanding the historical land parcel image outward by a number of pixels;

[0077] Subtract the expanded historical plot image from the plot image corresponding to the plot value to obtain an incremental plot image;

[0078] The incremental image is merged with the historical plot image to obtain an updated plot image.

[0079] As shown in Figure 7, the original image stored in the storage disk is shown in Figure 7(a). After the terrain is edited and turned into a 2D layer, it is shown in Figure 7(b). As mentioned above, data comparison is required before final saving. Specifically, the original image is expanded by 3 pixels, and then the modified image is subtracted from the original image to isolate the incremental edited content. Figure 8 As shown, finally it is added to the original image to obtain the new content after incremental modification, as shown Figure 9 This processing method may not seem to change much, but it is mainly used to reduce the small errors that often occur between pixel operations. As shown in the figure, the left side is the target image and the right side is the original image. If some small areas are not processed according to the above steps, there will be errors, which is not allowed.

[0080] Furthermore, for the deleted part, the step of comparing the plot image corresponding to the plot value with the historical plot image, extracting inconsistent parts of the plot image, and generating an updated plot image includes:

[0081] Subtract the historical plot image from the plot image corresponding to the plot value to obtain a deleted plot image;

[0082] The content of the historical plot image belonging to the deleted image is deleted to obtain an updated plot image.

[0083] In actual application, in order to illustrate the principle, more than half of the river information is deleted as shown in the figure. Figure 10 As shown. Further, the result of the incremental modification is subtracted from the deleted result to obtain the final modified result, as shown Figure 11 As shown, finally, according to these steps, the incremental and subtractive operations are applied to other different layers of the terrain, such as the road layer, vegetation layer, etc., with the help of scripts, and then the final block terrain information is output and stored in the specified directory on the disk in the form of images.

[0084] Step S305 : using the HDA node network, identifying the names of the plot images in the plot image set based on regular expressions.

[0085] In this embodiment, after obtaining the final block terrain information based on the above steps, the x28_top_caotu_export node is then used to stitch the plots together. In actual applications, this stitching includes two parts: one is to stitch the block terrain information into complete terrain information in the previous step, and the other function is to call PS through the process code to finally stitch it into a layered file PSD.

[0086] Step S306 : classify the land parcel images in the land parcel image set based on the recognition result and construct a sequence grammar.

[0087] In this example, the regular expression re is used to identify image sequences. For example, height.001.png represents the city information in the first plot, and WaterRiver.016.png represents the river information in the 16th plot. For each sequence, we need to identify the content to which the name belongs, extract the height and WaterRiver keywords, and process these sequences separately. Next, we set the final name for each terrain layer and the final output path.

[0088] Step S307 : Using the sequence grammar as a variable, the corresponding land parcel images are combined by pattern merging in HDA to obtain the corresponding terrain landscape layer.

[0089] Specifically, multiple images are combined into a sequence syntax. For example, if WaterRiver.001.png to WaterRiver.016.png represent river images for plots 1 to 16, the sequence syntax should be WaterRiver.$F3.png. This variable is passed to hda_mosaic for calculation, thereby stitching the plot images together to obtain the corresponding layers. Finally, the output files are stitched together to form a complete 16-patch world river map.

[0090] Step S308: Combine the terrain landscape layers to obtain a terrain image file.

[0091] In this step, after all the map information sequences are stitched together, you need to call PS to complete the subsequent work. This part is fully programmable and can perform many image operations, such as creating new layers, renaming, scaling, rotating, etc.

[0092] Specifically, first set the global output path, then use the winreg library to automatically search the registry to obtain the installation path of Photoshop, ensuring that different users with different paths can recognize Photoshop, and then use the serverbegin node, combined with the found PS path, to start the PS Python console. The corresponding host and port must be filled in to correctly start the console remotely, and further use the command send node to write a custom process script. This step is crucial and also the most flexible. The process code written in the figure includes: creating a new background layer, batch importing the various terrain information pictures that have just been spliced, automatically saving as layered PSD files, rotating 90 degrees, and when the entire HDA is run, PS will automatically open in the background and load the final map.

[0093] In this embodiment, before the step of classifying the land parcel images in the land parcel image set based on the recognition results and constructing a sequence grammar, the following steps are further included:

[0094] Based on the recognition result, determining whether a plot is missing from the plot image set;

[0095] If so, the preset plot generation code is called to generate a blank plot, and the blank plot is added to the plot image collection.

[0096] In this embodiment, after the terrain landscape layers are stitched together to obtain a terrain image file, the following steps are further included:

[0097] Obtaining an editing command for the terrain image file;

[0098] The terrain image file is edited based on the editing command.

[0099] In summary, the HDA node network is used to parse the terrain landscapes in the three-dimensional terrain data, and the terrain landscapes are divided into blocks based on the parsed terrain landscapes. The position mapping relationship of the divided plot images in the corresponding terrain landscapes is determined to obtain the corresponding plot image set; the HDA node network is used to stitch the plot images in each plot image set to generate the corresponding terrain landscape layers, and the terrain landscape layers are stitched together to obtain the terrain image file. The three-dimensional terrain data in UE4 is automatically saved into a multi-layer file through the HDA node network, in which the plots are used as the management objects, and the batch stitching of map data is realized. Compared with the existing technology, no manual operation is required, and the automatic generation and storage of map data is realized.

[0100] At the same time, through the real-time use of the above method, the terrain information of the large world in UE4 can be automatically saved as a multi-layer PSD, including the height map and all terrain layers. After editing the terrain each time, just one click is required to export the newly edited terrain information. This solves the tedious problem of exporting multiple plots of information in the game. In addition, the editing of layers is completely programmable and highly liberalized, realizing the data backtracking of the earth type (conversion of 3D terrain to 2D map), with high precision, small error, and repeatable editing. In theory, the technology is suitable for any engine platform and the algorithm is portable.

[0101] Corresponding to the above method embodiment, see Figure 12 A schematic diagram of a terrain data processing device shown in FIG. 1 , the device comprising:

[0102] Acquisition module 1201, used to acquire three-dimensional terrain data in the engine;

[0103] A segmentation module 1202 is configured to analyze the terrain landscapes in the three-dimensional terrain data using an HDA node network, segment the terrain landscapes based on the segmentation results, and determine a position mapping relationship between the segmented plot images in the corresponding terrain landscapes to obtain a corresponding plot image set.

[0104] The stitching module 1203 is used to stitch the plot images in each plot image set using the HDA node network to generate corresponding terrain landscape layers, and stitch the terrain landscape layers to obtain a terrain image file.

[0105] The terrain data processing device utilizes an HDA node network to analyze the terrain landscapes in the three-dimensional terrain data, divides the terrain landscapes into blocks based on the analysis, and determines the positional mapping relationship between the divided block images in the corresponding terrain landscapes to obtain a corresponding block image set. The HDA node network is used to stitch the block images in each block image set to generate corresponding terrain landscape layers, and the layers are stitched together to obtain a terrain image file. The HDA node network automatically saves the three-dimensional terrain data in UE4 into a multi-layer file, in which the blocks are managed, thus achieving batch stitching of map data.

[0106] See also Figure 13 A second embodiment of the terrain data processing device according to the present invention includes:

[0107] Acquisition module 1201, used to acquire three-dimensional terrain data in the engine;

[0108] A segmentation module 1202 is configured to analyze the terrain landscapes in the three-dimensional terrain data using an HDA node network, segment the terrain landscapes based on the segmentation results, and determine a position mapping relationship between the segmented plot images in the corresponding terrain landscapes to obtain a corresponding plot image set.

[0109] The stitching module 1203 is used to stitch the plot images in each plot image set using the HDA node network to generate corresponding terrain landscape layers, and stitch the terrain landscape layers to obtain a terrain image file.

[0110] In this embodiment, the block module 1202 is specifically used to:

[0111] According to the landscape type of the terrain, the three-dimensional terrain data is extracted using the HDA node network to obtain a plurality of terrain landscape pictures;

[0112] Each of the terrain landscape pictures is divided into blocks, and the block value of each block is determined using the block value determination rule, and a position mapping relationship between the block and the corresponding terrain landscape picture is constructed to obtain a block picture set corresponding to the terrain landscape picture.

[0113] In this embodiment, the block module 1202 is specifically used to:

[0114] Divide each of the terrain landscape images into blocks, and determine the block value of each block using a block value determination rule;

[0115] Using a preset landscape type identification code, identifying the type of each of the terrain landscape images, and determining a corresponding terrain layer derivation logic based on the type;

[0116] According to the terrain layer derivation logic and the land parcel values, a position mapping relationship between the blocks and the corresponding terrain landscape pictures is calculated to obtain a land parcel picture set corresponding to the terrain landscape picture.

[0117] In this embodiment, the block module 1202 is specifically used to:

[0118] Calculate the position information of the corresponding block in the corresponding terrain landscape image according to the terrain layer derivation logic and the block value;

[0119] Read historical plot images that match the plot values;

[0120] Comparing the plot image corresponding to the plot value with the historical plot image, and extracting inconsistent parts of the plot image to generate an updated plot image;

[0121] Based on the location information, determining a location mapping relationship between the updated land parcel image and the corresponding terrain landscape image;

[0122] Based on the position mapping relationship, the updated plot image is updated to a plot image set corresponding to the terrain landscape image.

[0123] In this embodiment, the block module 1202 is specifically used to:

[0124] Expanding the historical land parcel image outward by a number of pixels;

[0125] Subtract the expanded historical plot image from the plot image corresponding to the plot value to obtain an incremental plot image;

[0126] The incremental image is merged with the historical plot image to obtain an updated plot image.

[0127] In this embodiment, the block module 1202 is specifically used to:

[0128] Subtract the historical plot image from the plot image corresponding to the plot value to obtain a deleted plot image;

[0129] The content of the historical plot image belonging to the deleted image is deleted to obtain an updated plot image.

[0130] In this embodiment, the merging module 1203 is specifically configured to:

[0131] Using the HDA node network, identifying the names of the plot images in each of the plot image sets based on regular expressions;

[0132] Classifying the land parcel images in the land parcel image set based on the recognition results and constructing a sequence grammar;

[0133] Using the sequence grammar as a variable, the corresponding plot images are stitched together through pattern merging in HDA to obtain the corresponding terrain landscape layer;

[0134] The terrain landscape layers are stitched together to obtain a terrain image file.

[0135] In this embodiment, the block module 1202 is further configured to:

[0136] Based on the recognition result, determining whether a plot is missing from the plot image set;

[0137] If so, the preset plot generation code is called to generate a blank plot, and the blank plot is added to the plot image collection.

[0138] In this embodiment, the terrain data processing device further includes an editing module 1204, which is specifically configured to:

[0139] Obtaining an editing command for the terrain image file;

[0140] The terrain image file is edited based on the editing command.

[0141] This embodiment further provides an electronic device including a processor and a memory, wherein the memory stores machine-executable instructions that can be executed by the processor, and the processor executes the machine-executable instructions to implement the above-mentioned terrain data processing method. The electronic device can be a server or a terminal device.

[0142] See also Figure 14 As shown, the electronic device includes a processor 1400 and a memory 1401 , wherein the memory 1401 stores machine executable instructions that can be executed by the processor 1400 , and the processor 1400 executes the machine executable instructions to implement the above-mentioned method for determining the false touch prevention area.

[0143] Furthermore, Figure 14 The electronic device shown further includes a bus 1402 and a communication interface 1403 , and the processor 1400 , the communication interface 1403 and the memory 1401 are connected via the bus 1402 .

[0144] Among them, the memory 1401 may include a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 1403 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used. The bus 1402 can be an ISA bus, a PCI bus, or an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 14 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0145] The processor 1400 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits or software instructions in the processor 1400. The above processor 1400 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in conjunction with the embodiments of the present invention can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other storage media well-known in the art. The storage medium is located in memory 1401. Processor 1400 reads the information in memory 1401 and, in conjunction with its hardware, completes the following steps:

[0146] Get the 3D terrain data in the engine;

[0147] Utilizing the HDA node network to parse the terrain landscapes in the three-dimensional terrain data, dividing the terrain landscapes into blocks based on the parsed terrain landscapes, and determining the position mapping relationship of the divided block images in the corresponding terrain landscapes to obtain a corresponding block image set;

[0148] The HDA node network is used to stitch the plot images in each plot image set to generate a corresponding terrain landscape layer, and each terrain landscape layer is stitched layer by layer to obtain a terrain image file.

[0149] The steps of parsing the terrain landscapes in the three-dimensional terrain data using the HDA node network, dividing the terrain landscapes into blocks based on the parsed terrain landscapes, and determining the position mapping relationship of the divided block images in the corresponding terrain landscapes to obtain the corresponding block image set include:

[0150] According to the landscape type of the terrain, the three-dimensional terrain data is extracted using the HDA node network to obtain a plurality of terrain landscape pictures;

[0151] Each of the terrain landscape pictures is divided into blocks, and the block value of each block is determined using the block value determination rule, and a position mapping relationship between the block and the corresponding terrain landscape picture is constructed to obtain a block picture set corresponding to the terrain landscape picture.

[0152] The above-mentioned steps of dividing each of the terrain landscape images into blocks, determining the block values ​​of each block using the block value determination rule, establishing a position mapping relationship between the blocks and the corresponding terrain landscape images, and obtaining a set of block images corresponding to the terrain landscape images include:

[0153] Divide each of the terrain landscape images into blocks, and determine the block value of each block using a block value determination rule;

[0154] Using a preset landscape type identification code, identifying the type of each of the terrain landscape images, and determining a corresponding terrain layer derivation logic based on the type;

[0155] According to the terrain layer derivation logic and the land parcel values, a position mapping relationship between the blocks and the corresponding terrain landscape pictures is calculated to obtain a land parcel picture set corresponding to the terrain landscape picture.

[0156] The above step of calculating the position mapping relationship between the blocks and the corresponding terrain landscape pictures based on the terrain layer derivation logic and the block values ​​to obtain the set of block pictures corresponding to the terrain landscape pictures includes:

[0157] Calculate the position information of the corresponding block in the corresponding terrain landscape image according to the terrain layer derivation logic and the block value;

[0158] Read historical plot images that match the plot values;

[0159] Comparing the plot image corresponding to the plot value with the historical plot image, and extracting inconsistent parts of the plot image to generate an updated plot image;

[0160] Based on the location information, determining a location mapping relationship between the updated land parcel image and the corresponding terrain landscape image;

[0161] Based on the position mapping relationship, the updated plot image is updated to a plot image set corresponding to the terrain landscape image.

[0162] The step of comparing the plot image corresponding to the plot value with the historical plot image, extracting inconsistent parts of the plot image, and generating an updated plot image includes:

[0163] Expanding the historical land parcel image outward by a number of pixels;

[0164] Subtract the expanded historical plot image from the plot image corresponding to the plot value to obtain an incremental plot image;

[0165] The incremental image is merged with the historical plot image to obtain an updated plot image.

[0166] The step of comparing the plot image corresponding to the plot value with the historical plot image, extracting inconsistent parts of the plot image, and generating an updated plot image includes:

[0167] Subtract the historical plot image from the plot image corresponding to the plot value to obtain a deleted plot image;

[0168] The content of the historical plot image belonging to the deleted image is deleted to obtain an updated plot image.

[0169] The above-mentioned steps of using the HDA node network to stitch the plot images in each plot image set to generate corresponding terrain landscape layers, and stitching each terrain landscape layer to obtain a terrain image file include:

[0170] Using the HDA node network, identifying the names of the plot images in each of the plot image sets based on regular expressions;

[0171] Classifying the land parcel images in the land parcel image set based on the recognition results and constructing a sequence grammar;

[0172] Using the sequence grammar as a variable, the corresponding plot images are stitched together through pattern merging in HDA to obtain the corresponding terrain landscape layer;

[0173] The terrain landscape layers are stitched together to obtain a terrain image file.

[0174] Before the step of classifying the land parcel images in the land parcel image set based on the recognition results and constructing a sequence grammar, the method further includes:

[0175] Based on the recognition result, determining whether a plot is missing from the plot image set;

[0176] If so, the preset plot generation code is called to generate a blank plot, and the blank plot is added to the plot image collection.

[0177] After the terrain landscape layers are combined to obtain a terrain image file, the following steps are also included:

[0178] Obtaining an editing command for the terrain image file;

[0179] The terrain image file is edited based on the editing command.

[0180] In summary, the three-dimensional terrain data is converted and segmented through the HDA node network to form a plot image set, which is then read based on the HDA node network for stitching. After converting it into layers, the layers are stitched again to obtain a complete image file, thereby realizing block-by-block batch management of map data. This solves the problem in existing technologies of being unable to stitch together the complete terrain information of an entire open world and simultaneously processing image data.

[0181] This embodiment further provides a computer-readable storage medium storing computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the following steps:

[0182] Get the 3D terrain data in the engine;

[0183] Utilizing the HDA node network to parse the terrain landscapes in the three-dimensional terrain data, dividing the terrain landscapes into blocks based on the parsed terrain landscapes, and determining the position mapping relationship of the divided block images in the corresponding terrain landscapes to obtain a corresponding block image set;

[0184] The HDA node network is used to stitch the plot images in each plot image set to generate a corresponding terrain landscape layer, and each terrain landscape layer is stitched layer by layer to obtain a terrain image file.

[0185] The steps of parsing the terrain landscapes in the three-dimensional terrain data using the HDA node network, dividing the terrain landscapes into blocks based on the parsed terrain landscapes, and determining the position mapping relationship of the divided block images in the corresponding terrain landscapes to obtain the corresponding block image set include:

[0186] According to the landscape type of the terrain, the three-dimensional terrain data is extracted using the HDA node network to obtain a plurality of terrain landscape pictures;

[0187] Each of the terrain landscape pictures is divided into blocks, and the block value of each block is determined using the block value determination rule, and a position mapping relationship between the block and the corresponding terrain landscape picture is constructed to obtain a block picture set corresponding to the terrain landscape picture.

[0188] The above-mentioned steps of dividing each of the terrain landscape images into blocks, determining the block values ​​of each block using the block value determination rule, establishing a position mapping relationship between the blocks and the corresponding terrain landscape images, and obtaining a set of block images corresponding to the terrain landscape images include:

[0189] Divide each of the terrain landscape images into blocks, and determine the block value of each block using a block value determination rule;

[0190] Using a preset landscape type identification code, identifying the type of each of the terrain landscape images, and determining a corresponding terrain layer derivation logic based on the type;

[0191] According to the terrain layer derivation logic and the land parcel values, a position mapping relationship between the blocks and the corresponding terrain landscape pictures is calculated to obtain a land parcel picture set corresponding to the terrain landscape picture.

[0192] The above step of calculating the position mapping relationship between the blocks and the corresponding terrain landscape pictures based on the terrain layer derivation logic and the block values ​​to obtain the set of block pictures corresponding to the terrain landscape pictures includes:

[0193] Calculate the position information of the corresponding block in the corresponding terrain landscape image according to the terrain layer derivation logic and the block value;

[0194] Read historical plot images that match the plot values;

[0195] Comparing the plot image corresponding to the plot value with the historical plot image, and extracting inconsistent parts of the plot image to generate an updated plot image;

[0196] Based on the location information, determining a location mapping relationship between the updated land parcel image and the corresponding terrain landscape image;

[0197] Based on the position mapping relationship, the updated plot image is updated to a plot image set corresponding to the terrain landscape image.

[0198] The step of comparing the plot image corresponding to the plot value with the historical plot image, extracting inconsistent parts of the plot image, and generating an updated plot image includes:

[0199] Expanding the historical land parcel image outward by a number of pixels;

[0200] Subtract the expanded historical plot image from the plot image corresponding to the plot value to obtain an incremental plot image;

[0201] The incremental image is merged with the historical plot image to obtain an updated plot image.

[0202] The step of comparing the plot image corresponding to the plot value with the historical plot image, extracting inconsistent parts of the plot image, and generating an updated plot image includes:

[0203] Subtract the historical plot image from the plot image corresponding to the plot value to obtain a deleted plot image;

[0204] The content of the historical plot image belonging to the deleted image is deleted to obtain an updated plot image.

[0205] The above-mentioned steps of using the HDA node network to stitch the plot images in each plot image set to generate corresponding terrain landscape layers, and stitching each terrain landscape layer to obtain a terrain image file include:

[0206] Using the HDA node network, identifying the names of the plot images in each of the plot image sets based on regular expressions;

[0207] Classifying the land parcel images in the land parcel image set based on the recognition results and constructing a sequence grammar;

[0208] Using the sequence grammar as a variable, the corresponding plot images are stitched together through pattern merging in HDA to obtain the corresponding terrain landscape layer;

[0209] The terrain landscape layers are stitched together to obtain a terrain image file.

[0210] Before the step of classifying the land parcel images in the land parcel image set based on the recognition results and constructing a sequence grammar, the method further includes:

[0211] Based on the recognition result, determining whether a plot is missing from the plot image set;

[0212] If so, the preset plot generation code is called to generate a blank plot, and the blank plot is added to the plot image collection.

[0213] After the terrain landscape layers are combined to obtain a terrain image file, the following steps are also included:

[0214] Obtaining an editing command for the terrain image file;

[0215] The terrain image file is edited based on the editing command.

[0216] In summary, the three-dimensional terrain data is converted and segmented through the HDA node network to form a plot image set, which is then read based on the HDA node network for stitching. After converting it into layers, the layers are stitched again to obtain a complete image file, thereby realizing block-by-block batch management of map data. This solves the problem in existing technologies of being unable to stitch together the complete terrain information of an entire open world and simultaneously processing image data.

[0217] The computer program product of the terrain data processing method, device, electronic device and storage medium provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the previous method embodiments. The specific implementation can be found in the method embodiments and will not be repeated here.

[0218] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems and devices can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0219] In addition, in the description of the embodiments of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0220] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0221] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0222] Finally, it should be noted that the above embodiments are only specific implementation methods of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for processing terrain data, characterized in that: The method for processing terrain data includes: Get the 3D terrain data in the engine; The three-dimensional terrain data is sent to the HDA node network according to the landscape to extract each terrain landscape, and the terrain landscape is divided into blocks based on the parsed terrain landscape, and the block value of each block is determined, and the position mapping relationship of each block image after the block is constructed in the corresponding terrain landscape based on the block value to obtain a corresponding block image set, where the block value is the block setting sequence number; The map block synthesis node in the HDA node network is used to construct the sequence grammar of the plot picture set, and the plot pictures in each plot picture set are spliced ​​based on the sequence grammar to generate the corresponding terrain landscape layer, and each terrain landscape layer is layer-spliced ​​to obtain a terrain picture file.

2. The method for processing terrain data according to claim 1, characterized in that: The steps of sending the three-dimensional terrain data to the HDA node network according to the landscape to extract each terrain landscape, dividing the terrain landscape into blocks based on the parsed terrain landscape, determining the block value of each block, and constructing a position mapping relationship of each block image in the corresponding terrain landscape based on the block value to obtain a corresponding block image set include: According to the landscape type of the terrain, the three-dimensional terrain data is extracted using the HDA node network to obtain a plurality of terrain landscape pictures; Each of the terrain landscape pictures is divided into blocks, and the block value of each block is determined using the block value determination rule, and a position mapping relationship between the block and the corresponding terrain landscape picture is constructed to obtain a block picture set corresponding to the terrain landscape picture.

3. The method for processing terrain data according to claim 2, characterized in that: The step of dividing each of the terrain landscape pictures into blocks, determining the block value of each block using a block value determination rule, establishing a position mapping relationship between the blocks and the corresponding terrain landscape pictures, and obtaining a set of block pictures corresponding to the terrain landscape pictures includes: Divide each of the terrain landscape images into blocks, and determine the block value of each block using a block value determination rule; Using a preset landscape type identification code, identifying the type of each of the terrain landscape images, and determining a corresponding terrain layer derivation logic based on the type; According to the terrain layer derivation logic and the land parcel values, a position mapping relationship between the blocks and the corresponding terrain landscape pictures is calculated to obtain a land parcel picture set corresponding to the terrain landscape picture.

4. The method for processing terrain data according to claim 3, characterized in that: The step of calculating the position mapping relationship between the blocks and the corresponding terrain landscape pictures according to the terrain layer derivation logic and the block values ​​to obtain the set of block pictures corresponding to the terrain landscape pictures includes: Calculate the position information of the corresponding block in the corresponding terrain landscape image according to the terrain layer derivation logic and the block value; Read historical plot images that match the plot values; Comparing the plot image corresponding to the plot value with the historical plot image, and extracting inconsistent parts of the plot image to generate an updated plot image; Based on the location information, determining a location mapping relationship between the updated land parcel image and the corresponding terrain landscape image; Based on the position mapping relationship, the updated plot image is updated to a plot image set corresponding to the terrain landscape image.

5. The method for processing terrain data according to claim 4, characterized in that: The step of comparing the plot image corresponding to the plot value with the historical plot image, extracting inconsistent parts of the plot image, and generating an updated plot image includes: Expanding the historical land parcel image outward by a number of pixels; Subtract the expanded historical plot image from the plot image corresponding to the plot value to obtain an incremental plot image; The incremental image is merged with the historical plot image to obtain an updated plot image.

6. The method for processing terrain data according to claim 4, characterized in that: The step of comparing the plot image corresponding to the plot value with the historical plot image, extracting inconsistent parts of the plot image, and generating an updated plot image includes: Subtract the historical plot image from the plot image corresponding to the plot value to obtain a deleted plot image; The content of the historical plot image belonging to the deleted image is deleted to obtain an updated plot image.

7. The method for processing terrain data according to claim 1, characterized in that: The steps of constructing a sequence grammar of the plot picture set using a map block synthesis node in an HDA node network, stitching the plot pictures in each plot picture set based on the sequence grammar to generate a corresponding terrain landscape layer, and stitching each terrain landscape layer to obtain a terrain picture file include: Using the HDA node network, identifying the names of the plot images in each of the plot image sets based on regular expressions; Classifying the land parcel images in the land parcel image set based on the recognition results and constructing a sequence grammar; Using the sequence grammar as a variable, the corresponding plot images are stitched together through pattern merging in HDA to obtain the corresponding terrain landscape layer; The terrain landscape layers are stitched together to obtain a terrain image file.

8. The method for processing terrain data according to claim 7, characterized in that: Before the step of classifying the land parcel images in the land parcel image set based on the recognition results and constructing a sequence grammar, the method further includes: Based on the recognition result, determining whether a plot is missing from the plot image set; If so, the preset plot generation code is called to generate a blank plot, and the blank plot is added to the plot image collection.

9. The method for processing terrain data according to claim 7, characterized in that: After the terrain landscape layers are combined to obtain a terrain image file, the method further includes: Obtaining an editing command for the terrain image file; The terrain image file is edited based on the editing command.

10. A terrain data processing device, characterized in that: The terrain data processing device includes: Acquisition module, used to obtain three-dimensional terrain data in the engine; A segmentation module is configured to send the three-dimensional terrain data to the HDA node network according to the landscape, extract each landscape, segment the landscape based on the parsed landscape, determine the plot value of each segment, and construct a position mapping relationship of each segmented plot image in the corresponding landscape based on the plot value to obtain a corresponding plot image set, where the plot value is a plot setting sequence number; The splicing module is used to use the map block synthesis node in the HDA node network to construct the sequence grammar of the plot image set, splice the plot images in each plot image set based on the sequence grammar, generate the corresponding terrain landscape layer, and perform layer splicing on each terrain landscape layer to obtain a terrain image file.

11. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores machine-executable instructions that can be executed by the processor, and the processor executes the machine-executable instructions to implement the terrain data processing method according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the terrain data processing method according to any one of claims 1 to 9.

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