Image reconstruction method and apparatus, device, and storage medium

Abstract

The present invention provides an image reconstruction method and apparatus, a device, and a storage medium, applicable to the field of smart logistics and the field of artificial intelligence. The method comprises: in response to an object reconstruction operation for a scenario image to be processed, determining, in the scenario image to be processed, a first scenario image area corresponding to the object reconstruction operation; in the first scenario image area, recognizing a first object to be reconstructed, wherein the first object is associated with a target index; on the basis of the target index associated with the first object, determining from a second object set a second object associated with the target index, wherein the spatial dimension of the first object is a first dimension, the spatial dimension of the second object is a second dimension, and the first dimension is different from the second dimension; and on the basis of image data of the second object, constructing a target scenario image.

Description

Image reconstruction method, device, equipment and storage medium

[0001] This application claims priority to Chinese patent application No. 202310707808.2 filed on June 15, 2023, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present disclosure relates to the fields of smart logistics and artificial intelligence, and more specifically, to an image reconstruction method, apparatus, device, storage medium, and computer program product. Background Art

[0003] With the rapid development of internet e-commerce, it is necessary to design and build intelligent warehousing and logistics centers to meet the growing demand for commodity logistics. For example, design software such as AutoCAD can be used to create design drawings for warehousing and logistics centers, and then the construction of the warehousing and logistics centers can be completed based on the design drawings.

[0004] In the process of realizing the concept disclosed herein, the inventors discovered that there are at least the following problems in the relevant technologies: as the scale of warehousing and logistics centers continues to expand and the diversity of logistics facilities and logistics equipment in warehousing and logistics centers increases, the design process of warehousing and logistics centers requires a lot of time, and the relevant design drawings are difficult to intuitively display the design details of the warehousing and logistics centers, which has a certain negative impact on the subsequent construction and operation processes of the warehousing and logistics centers.

[0005] Summary of the Invention

[0006] In view of this, the present disclosure provides an image reconstruction method, apparatus, device, storage medium, and computer program product.

[0007] One aspect of the present disclosure provides an image reconstruction method, comprising: in response to an object reconstruction operation for a scene image to be processed, determining a first scene image area corresponding to the object reconstruction operation in the scene image to be processed; identifying a first object to be reconstructed in the first scene image area, wherein the first object is associated with a target index; based on the target index associated with the first object, determining a second object associated with the target index from a second object set, wherein the spatial dimension of the first object is a first dimension, the spatial dimension of the second object is a second dimension, and the first dimension is different from the second dimension; and constructing a target scene image based on the image data of the second object.

[0008] According to an embodiment of the present disclosure, the image reconstruction method also includes: in a case where it is detected that the above-mentioned first scene image area is obtained, generating a first mirror reference element related to the above-mentioned first scene image area in a first interactive interface for displaying the above-mentioned scene image to be processed; based on the above-mentioned first mirror reference element, determining a second scene image area corresponding to the above-mentioned first scene image area in the above-mentioned scene image to be processed, wherein the above-mentioned first scene image area and the above-mentioned second scene image area are symmetrical with respect to the above-mentioned first mirror reference element; and based on the above-mentioned target index, identifying the above-mentioned first object associated with the above-mentioned target index from the above-mentioned second scene image area.

[0009] According to an embodiment of the present disclosure, the above-mentioned first object has first object position information; wherein, the above-mentioned construction of the target scene image based on the image data of the above-mentioned second object includes: generating a target scene image containing the above-mentioned second object in the second interactive interface based on the image data of the above-mentioned second object and the second object position information of the above-mentioned second object; wherein, the second object position information of the above-mentioned second object is determined based on the first object position information of each of the above-mentioned first objects.

[0010] According to an embodiment of the present disclosure, the above-mentioned first object includes multiple objects; the above-mentioned image reconstruction method also includes: determining a first object area surrounding the first object position information of each of the multiple first objects; according to the first area center position of the above-mentioned first object area, determining a baseline first object position information set and a mirrored first object position information set from the multiple first object position information, wherein the baseline first object position information in the above-mentioned baseline first object position information set and the baseline first object position information in the above-mentioned mirrored first object position information set are symmetrical with respect to the center position of the above-mentioned first area.

[0011] According to an embodiment of the present disclosure, the above-mentioned second object includes multiple objects; wherein, the above-mentioned target scene image containing the above-mentioned second object is generated in the second interactive interface based on the image data of the above-mentioned second object and the second object position information of the above-mentioned second object includes: generating a baseline second object in the above-mentioned second interactive interface based on the image data of the above-mentioned second object and the baseline second object position information, wherein the above-mentioned baseline second object position information is determined based on the baseline first object position information in the above-mentioned baseline first object position information set; mirroring the above-mentioned baseline second object according to the center position of the second area to obtain the mirrored second object generated in the above-mentioned second interactive interface, wherein the center position of the above-mentioned second area is determined based on the center position of the above-mentioned first area, and the multiple second objects include the above-mentioned mirrored second object and the above-mentioned baseline second object, and the above-mentioned mirrored second object and the above-mentioned baseline second object are symmetrical relative to the center position of the above-mentioned second area.

[0012] According to an embodiment of the present disclosure, the above-mentioned image reconstruction method also includes: updating the object display attribute information of the above-mentioned first object in the first interactive interface for displaying the above-mentioned scene image to be processed, and obtaining updated target object display attribute information; and generating a new first object in the above-mentioned first interactive interface based on the above-mentioned target object display attribute information.

[0013] According to an embodiment of the present disclosure, the object display attribute information includes at least one of the following: object color attribute information and object line attribute information.

[0014] According to an embodiment of the present disclosure, the above-mentioned determining the second object associated with the target index from the second object set based on the target index associated with the above-mentioned first object includes: determining a plurality of candidate second objects associated with the target index from the above-mentioned second object set based on the target index associated with the above-mentioned first object; generating a candidate second object floating window in a first interactive interface for displaying the above-mentioned scene image to be processed, wherein the above-mentioned candidate second object floating window includes candidate second object elements associated with each of the plurality of above-mentioned candidate second objects; in response to detecting an element determination operation for the candidate second object element in the above-mentioned candidate second object floating window, determining the candidate second object element corresponding to the above-mentioned element determination operation as the target second object element; and determining the candidate second object associated with the above-mentioned target second object element as the above-mentioned second object.

[0015] According to an embodiment of the present disclosure, identifying the first object to be reconstructed in the above-mentioned first scene image area includes: inputting the above-mentioned first scene image area into a target detection model constructed based on a neural network algorithm, outputting a target detection result; and determining the above-mentioned first object based on the above-mentioned target detection result.

[0016] According to an embodiment of the present disclosure, the above-mentioned target scene image includes a logistics operation scene image.

[0017] Another aspect of the present disclosure provides an image reconstruction device, including: a first scene image area determination module, for determining, in response to an object reconstruction operation on a scene image to be processed, a first scene image area corresponding to the object reconstruction operation in the scene image to be processed; a first object recognition module, for identifying a first object to be reconstructed in the first scene image area, wherein the first object is associated with a target index; a second object determination module, for determining, from a second object set, a second object associated with the target index based on the target index associated with the first object, wherein the spatial dimension of the first object is a first dimension, the spatial dimension of the second object is a second dimension, and the first dimension is different from the second dimension; and a target scene image construction module, for constructing a target scene image based on image data of the second object.

[0018] Another aspect of the present disclosure provides an electronic device, comprising:

[0019] one or more processors;

[0020] a memory for storing one or more programs,

[0021] When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described above.

[0022] Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the method described above when executed.

[0023] Another aspect of the present disclosure provides a computer program product comprising computer executable instructions, which are used to implement the method described above when the instructions are executed. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings.

[0025] FIG1 schematically shows an exemplary system architecture to which an image reconstruction method and apparatus according to an embodiment of the present disclosure can be applied.

[0026] FIG2 schematically shows a flow chart of an image reconstruction method according to an embodiment of the present disclosure.

[0027] FIG3 schematically shows an application scenario diagram of the image reconstruction method according to an embodiment of the present disclosure.

[0028] FIG4 schematically shows an application scenario diagram of an image reconstruction method according to another embodiment of the present disclosure.

[0029] FIG5 schematically shows an application scenario diagram of an image reconstruction method according to yet another embodiment of the present disclosure.

[0030] FIG6 schematically shows an application scenario diagram of an image reconstruction method according to yet another embodiment of the present disclosure.

[0031] FIG7A schematically shows a schematic diagram of a scene image to be processed according to an embodiment of the present disclosure.

[0032] FIG7B schematically shows a schematic diagram of a target scene image according to an embodiment of the present disclosure.

[0033] FIG8 schematically shows a block diagram of an image reconstruction apparatus according to an embodiment of the present disclosure.

[0034] FIG9 schematically shows a block diagram of an electronic device suitable for implementing the image reconstruction method described above according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0035] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. In the detailed description below, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0036] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise," "include," etc. used herein indicate the presence of the features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0037] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0038] When expressions such as "at least one of A, B and C, etc." are used, they should generally be interpreted in accordance with the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0039] In the embodiments of the present disclosure, the collection, updating, analysis, processing, use, transmission, provision, disclosure, and storage of the data involved (for example, including but not limited to user personal information) all comply with the provisions of relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures are taken with respect to user personal information to prevent unauthorized access to user personal information data and to maintain the security of user personal information, network security, and national security.

[0040] In the embodiments of the present disclosure, the user's authorization or consent is obtained before obtaining or collecting the user's personal information.

[0041] The inventors discovered that typical warehouse logistics design drawings are typically created using design software such as AutoCAD to create two-dimensional designs for warehouse logistics centers. To visually display the warehouse logistics center, these two-dimensional drawings are converted into three-dimensional designs to clearly showcase the warehouse logistics center's logistics equipment or facilities, such as shelves and intelligent robotic arms. Converting a two-dimensional design into a three-dimensional design requires identifying the images corresponding to all the logistics equipment in the two-dimensional design, determining the type of logistics equipment in the image, and then finding a three-dimensional model corresponding to that type. Based on the three-dimensional model, a three-dimensional design drawing is then generated.

[0042] However, for different warehousing and logistics center projects or different warehousing and logistics scenarios, the design specifications of the corresponding two-dimensional design drawings vary greatly. The image size, image clarity, and image appearance attributes of the two-dimensional design drawings also vary greatly. Therefore, it is difficult to accurately identify the type of logistics equipment in the two-dimensional design drawings, resulting in a large workload for manual verification of the type of logistics equipment, which reduces the overall construction efficiency of the warehousing and logistics center, as well as the operational efficiency of the warehousing and logistics center after completion.

[0043] Embodiments of the present disclosure provide an image reconstruction method, apparatus, device, storage medium, and computer program product. The image reconstruction method includes: in response to an object reconstruction operation on a scene image to be processed, determining a first scene image region corresponding to the object reconstruction operation in the scene image to be processed; identifying a first object to be reconstructed in the first scene image region, wherein the first object is associated with a target index; determining a second object associated with the target index from a second object set based on the target index associated with the first object, wherein the spatial dimension of the first object is a first dimension, the spatial dimension of the second object is a second dimension, and the first dimension is different from the second dimension; and constructing a target scene image based on image data of the second object.

[0044] According to an embodiment of the present disclosure, by identifying a first object in a first scene image area and screening a second object having a different spatial dimension from the first object based on a target index of the first object, the reconstruction rate and reconstruction accuracy of reconstructing the first object into a second dimension can be improved. Therefore, by further constructing a target scene image of a second dimension based on the image data of the second object, the reconstruction accuracy and reconstruction efficiency of reconstructing the first-dimensional processed image into a target scene image of a second dimension can be improved.

[0045] FIG1 schematically illustrates an exemplary system architecture 100 to which the image reconstruction method and apparatus according to an embodiment of the present disclosure can be applied. It should be noted that FIG1 merely illustrates an example of a system architecture to which the embodiments of the present disclosure can be applied, to help those skilled in the art understand the technical content of the present disclosure, and does not imply that the embodiments of the present disclosure cannot be applied to other devices, systems, environments, or scenarios.

[0046] As shown in FIG1 , a system architecture 100 according to this embodiment may include terminal devices 101, 102, and 103, a network 104, and a server 105. The network 104 is used as a medium for providing communication links between the terminal devices 101, 102, and 103 and the server 105. The network 104 may include various connection types, such as wired and / or wireless communication links.

[0047] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, and / or social platform software (for example only).

[0048] The terminal devices 101 , 102 , and 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers.

[0049] The server 105 may be a server that provides various services, such as a background management server (for example only) that supports websites browsed by users using the terminal devices 101, 102, and 103. The background management server may analyze and process received data such as user requests, and feed back processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0050] It should be noted that the image reconstruction method provided in the embodiments of the present disclosure can generally be executed by the terminal device 101, 102, or 103, or can also be executed by a terminal device other than the terminal device 101, 102, or 103. Accordingly, the image reconstruction apparatus provided in the embodiments of the present disclosure can generally be provided in the terminal device 101, 102, or 103, or can be provided in a terminal device other than the terminal device 101, 102, or 103. Alternatively, the image reconstruction method provided in the embodiments of the present disclosure can generally be executed by the server 105. Accordingly, the image reconstruction apparatus provided in the embodiments of the present disclosure can also generally be provided in the server 105. The image reconstruction method provided in the embodiments of the present disclosure can also be executed by a server or server cluster other than the server 105 that is capable of communicating with the terminal devices 101, 102, 103 and / or the server 105. Accordingly, the image reconstruction apparatus provided in the embodiments of the present disclosure can also be provided in a server or server cluster other than the server 105 that is capable of communicating with the terminal devices 101, 102, 103 and / or the server 105.

[0051] For example, the scene image to be processed may be originally stored in any one of the terminal devices 101, 102, or 103 (for example, the terminal device 101, but not limited thereto), or stored in an external storage device and imported into the terminal device 101. The terminal device 101 may then locally execute the image reconstruction method provided by the embodiment of the present disclosure, or send the scene image to be processed to other terminal devices, servers, or server clusters, and the other terminal devices, servers, or server clusters that receive the scene image to be processed may execute the image reconstruction method provided by the embodiment of the present disclosure.

[0052] It should be understood that the number of terminal devices, networks, and servers in Figure 1 is merely illustrative and any number of terminal devices, networks, and servers may be provided as required.

[0053] FIG2 schematically shows a flow chart of an image reconstruction method according to an embodiment of the present disclosure.

[0054] As shown in FIG. 2 , the method includes operations S210 to S240 .

[0055] In operation S210 , in response to an object reconstruction operation on a scene image to be processed, a first scene image region corresponding to the object reconstruction operation is determined in the scene image to be processed.

[0056] According to the embodiments of the present disclosure, the scene images to be processed may be images representing any type of scene, for example, images representing warehousing and logistics scenes, or images representing transportation scenes. The embodiments of the present disclosure do not limit the type of scene represented by the scene images to be processed, and those skilled in the art may make a choice based on actual needs.

[0057] According to an embodiment of the present disclosure, the first scene image area may be a partial image in the scene image to be processed, or may be the entire image in the scene image to be processed. The embodiment of the present disclosure does not limit the specific size or shape of the first scene image area.

[0058] It should be understood that the object reconstruction operation can be any type of operation, such as a box selection operation, a click operation, etc., or it can also be other types of operations such as voice operation, gesture operation, etc. The embodiments of the present disclosure do not limit the operation type of the object reconstruction operation, and those skilled in the art can design it according to actual needs.

[0059] In operation S220 , a first object to be reconstructed is identified in a first scene image region, wherein the first object is associated with a target index.

[0060] According to an embodiment of the present disclosure, the first object may represent an object of any object type in the first scene image area, for example, it may represent an object of a shelf, a transport vehicle, a package, or the like in the storage space image area.

[0061] According to embodiments of the present disclosure, the first object can be identified in any manner. For example, based on preset detection rules, at least one key line or at least one key point in the first scene image region can be detected to identify the first object corresponding to the preset detection rules. Alternatively, based on preset color rules, an image block in the first scene image region corresponding to the preset color rules can be identified as the first object. The embodiments of the present disclosure do not limit the specific method for identifying the first object, as long as it can meet actual needs.

[0062] In operation S230, a second object associated with the target index is determined from the second object set according to the target index associated with the first object, wherein the spatial dimension of the first object is a first dimension, the spatial dimension of the second object is a second dimension, and the first dimension is different from the second dimension.

[0063] According to the embodiments of the present disclosure, the first object may have two-dimensional spatial dimensions, the second object may have three-dimensional spatial dimensions, or the first object may have three-dimensional spatial dimensions, the second object may have two-dimensional spatial dimensions. The embodiments of the present disclosure do not limit the specific spatial dimension type of the first dimension or the second dimension, as long as the first dimension and the second dimension are different.

[0064] According to an embodiment of the present disclosure, the second object may have the same object attribute information as the first object, such as object type and object outline.

[0065] In operation S240, a target scene image is constructed based on the image data of the second object.

[0066] According to an embodiment of the present disclosure, by determining a second object having a second dimension corresponding to the first object through a target index associated with the first object, the image construction operation generated by constructing a second-dimensional image for representing the first object can be avoided, the reconstruction time for the first object can be reduced, and the reconstruction efficiency and reconstruction accuracy of reconstructing the first object of the first dimension into the second object of the second dimension can be improved, thereby improving the efficiency and reconstruction accuracy of reconstructing the scene image to be processed into the target scene image, so that the user can perform subsequent scene simulation work through the efficiently generated target scene image.

[0067] The image reconstruction method shown in FIG. 2 will be further described below through specific embodiments in conjunction with FIG. 3 to FIG. 6 .

[0068] In one embodiment of the present disclosure, the scene image to be processed can be a two-dimensional scene image generated by rendering the lines in an image file of a preset format into an identifiable object to be processed. For example, it can be a format conversion of an image file in a vector data format (such as DXF format) generated by a drawing software (such as Auto CAD software) to convert the lines in the DXF format image file into an object to be processed corresponding to THREE.js (also known as Three Javascript), thereby obtaining a scene image to be processed containing the object to be processed. Accordingly, the first object can be identified by identifying the key lines, key points, layer properties of the key lines, etc. in the first scene image area in the scene image to be processed. The image data of the identified first object can have a target index, for example, the object type identifier of the first object can be used as the target index, so that the second object associated with the target index can be quickly queried through the target index, thereby improving the reconstruction efficiency and reconstruction accuracy of reconstructing the first object into a second object of the second dimension.

[0069] According to embodiments of the present disclosure, there may be one or more first objects in the first scene image area. When multiple first objects are identified, the multiple first objects may each have the same object type. For example, the object type of each first object may be "shelf." Alternatively, the multiple first objects may each have a different object type. For example, the object type of the first first object may be "shelf," while the object type of the second first object may be "transport robot." It should be understood that first objects of the same object type may be associated with the same target index.

[0070] According to an embodiment of the present disclosure, in operation S220 , identifying a first object to be reconstructed in the first scene image region may include the following operations.

[0071] The first scene image area is input into a target detection model constructed based on a neural network algorithm, and a target detection result is output; and the first object is determined based on the target detection result.

[0072] According to an embodiment of the present disclosure, it is also possible to perform target detection on the first scene image area based on a target detection model constructed based on a neural network algorithm such as a residual network (ResNet), obtain a target detection frame (target detection result) in the first scene image area, determine the object type of the first object based on the type corresponding to the target detection frame, and use the object type as a target index to determine a second object corresponding to the first object.

[0073] According to an embodiment of the present disclosure, the first object may have first object position information.

[0074] According to an embodiment of the present disclosure, the first object position information may be the pixel position of any point of the first object in the scene image to be processed, for example, the pixel position of the center point of the first object in the scene image to be processed. The first object position information may be represented by a coordinate position.

[0075] It should be understood that, in the case where there are multiple first objects, each of the multiple first objects may have first object position information.

[0076] According to an embodiment of the present disclosure, the first object position information can be converted into the second object position information based on the coordinate system conversion parameters between the scene image to be processed and the target scene image to be generated, thereby generating the second object position information based on the first object position information of each first object.

[0077] According to an embodiment of the present disclosure, in operation S240, constructing a target scene image based on the image data of the second object may include: generating a target scene image containing the second object in the second interactive interface based on the image data of the second object and the second object position information of the second object; wherein the second object position information of the second object is determined based on the first object position information of each of the first objects.

[0078] According to an embodiment of the present disclosure, the image data of the second object may be data used to render the second object in the second interactive interface. For example, the second object may be rendered at the second object position based on pre-edited second object component data, thereby obtaining a target scene image containing the second object in the second interactive interface.

[0079] According to an embodiment of the present disclosure, the image reconstruction method may further include the following operations.

[0080] In a first interactive interface for displaying a scene image to be processed, object display attribute information of a first object is updated to obtain updated target object display attribute information; and a new first object is generated in the first interactive interface according to the target object display attribute information.

[0081] FIG3 schematically shows an application scenario diagram of the image reconstruction method according to an embodiment of the present disclosure.

[0082] As shown in FIG3 , in response to the object reconstruction operation, a first scene image region 311 can be obtained in the first interactive interface 310, and a first object 321 can be identified in the first scene image region 311. After the first object 321 is identified, the object line attribute information of the first object 321 can be updated to obtain a new first object 322.

[0083] It should be understood that the object display attribute information may include object line attribute information.

[0084] According to an embodiment of the present disclosure, object display attribute information may also include object color attribute information, so that the object color attribute information such as the fill color and line color of the first object in the first interactive interface can be updated, and then a new first object with new color attributes is obtained in the first interactive interface.

[0085] According to an embodiment of the present disclosure, the object color attribute information and the object line attribute information of the first object in the first interactive interface may also be updated simultaneously, thereby further enhancing the display effect of the first object in the first scene image area.

[0086] According to an embodiment of the present disclosure, in operation S230 , determining, from the second object set, a second object associated with a target index according to the target index associated with the first object may include the following operations.

[0087] Based on the target index associated with the first object, multiple candidate second objects associated with the target index are determined from the second object set; in a first interactive interface for displaying the scene image to be processed, a candidate second object pop-up window is generated, wherein the candidate second object pop-up window contains candidate second object elements associated with each of the multiple candidate second objects; in response to detecting an element determination operation for the candidate second object element in the candidate second object pop-up window, the candidate second object element corresponding to the element determination operation is determined as the target second object element; and the candidate second object associated with the target second object element is determined as the second object.

[0088] FIG4 schematically shows an application scenario diagram of an image reconstruction method according to another embodiment of the present disclosure.

[0089] As shown in Figure 4, first scene image area 411 of first interactive interface 410 may include a recognized first object 421. Based on a target index associated with first object 421, two candidate second objects associated with the target index may be retrieved. A floating window 401 is generated in first interactive interface 410, and candidate second object elements 431 and 432 representing the two candidate second objects may be displayed in floating window 401.

[0090] By detecting the user's determination operation on the candidate second object element 431 , the candidate second object element 431 may be determined as the target second object element, and then the second object corresponding to the first object 421 may be obtained according to the user's operation.

[0091] According to an embodiment of the present disclosure, the image reconstruction method may further include the following operations.

[0092] When it is detected that a first scene image area is obtained, a first mirror reference element related to the first scene image area is generated in a first interactive interface for displaying the scene image to be processed; based on the first mirror reference element, a second scene image area corresponding to the first scene image area is determined in the scene image to be processed, wherein the first scene image area and the second scene image area are symmetrical with respect to the first mirror reference element; and based on the target index, a first object associated with the target index is identified from the second scene image area.

[0093] FIG5 schematically shows an application scenario diagram of an image reconstruction method according to yet another embodiment of the present disclosure.

[0094] As shown in FIG5 , a first scene image region 511 is obtained in a scene image to be processed 510. The first scene image region 511 may include a first object 5111. When the first scene image region 511 is detected, a first mirror image reference element 501 may be generated based on a preset rule. Based on the positional information of the first mirror image reference element 501 and the first scene image region 511, a second scene image region 512 corresponding to the first scene image region 511 is generated in the scene image to be processed 510. The first scene image region 511 and the second scene image region 512 are axially symmetrical with respect to the first mirror image reference element 501. Based on the target index of the first object 5111, a first object 5121 to be reconstructed may be determined in the second scene image region 512.

[0095] According to the embodiments of the present disclosure, a second scene image region is generated by using a first scene image region and a first mirror reference element, thereby enabling rapid search for a second scene image region symmetrical to the first scene image region. Simultaneously, automated search for the first object in the scene image to be processed is achieved, thereby enabling rapid reconstruction of scenes with highly standardized equipment and facility arrangements, such as logistics warehousing scenes and industrial park scenes, thereby improving the efficiency of reconstructing the target scene image in the second dimension. This also avoids the problem of low accuracy in selecting the scene image region to be reconstructed, which results from determining the second scene image region based on intuitive observation by the user in an interactive interface, thereby improving the reconstruction accuracy of the target image.

[0096] It should be noted that the first mirror image reference element 501 shown in FIG5 is merely exemplary and is not intended to limit element attribute information such as the shape or size of the first mirror image reference element.

[0097] According to an embodiment of the present disclosure, the first scene image region 511 and the second scene image region 512 may also be centrally symmetrical relative to the first mirror reference element 501 , thereby flexibly adapting to user needs for target scene reconstruction.

[0098] It should be noted that the first mirror reference element can be generated based on any preset rule. For example, the preset rule can be set based on a preset mirror direction and a distance from the first scene image area, but is not limited to this. The preset rule can also be set based on the area of ​​the first scene image area and the distance from the first scene image area. The embodiments of the present disclosure are not limited to this.

[0099] As shown in FIG5 , after obtaining the first objects 5111 and 5121 to be reconstructed, the second object position information of each second object in the second interaction interface can be determined based on the first object position information of each first object 5111 and 5121 .

[0100] Accordingly, the second object can be queried through the target index, and based on the second object position information corresponding to the first object position information of the first objects 5111 and 5121 respectively, and the image data of the second object related to the target index, the second objects 5211 and 5221 are correspondingly generated in the second interactive interface, and then the target image 520 containing the second objects 5211 and 5221 can be obtained in the second interactive interface.

[0101] It should be understood that the number of first objects respectively included in the first scene image area 511 and the second scene image area 512 shown in FIG5 is merely exemplary and is not used to limit the number of first objects respectively included in the first scene image area and the second scene image area.

[0102] According to an embodiment of the present disclosure, in the case of a first scene image area, a first mirror reference element is generated in the first interactive interface, and a second image area is further generated in the scene image to be processed based on the first mirror reference element. This can realize the function of automatically searching for the first object in the scene image to be processed, thereby reducing the operation steps for the user to perform the object reconstruction operation again. In this way, the second object is generated based on the first object position of the first object obtained from the first scene image area and the second scene image area. When the number of first objects is large and the arrangement is relatively dense, the reconstructed second-dimensional target scene image can be quickly obtained, thereby improving the reconstruction accuracy and reconstruction efficiency of the scene image.

[0103] According to an embodiment of the present disclosure, the image reconstruction method may further include the following operations.

[0104] determining a first object area surrounding first object position information of each of the plurality of first objects;

[0105] Based on the first area center position of the first object area, a baseline first object position information set and a mirrored first object position information set are determined from multiple first object position information, wherein the baseline first object position information in the baseline first object position information set and the baseline first object position information in the mirrored first object position information set are symmetrical relative to the first area center position.

[0106] FIG6 schematically shows an application scenario diagram of an image reconstruction method according to yet another embodiment of the present disclosure.

[0107] As shown in FIG6 , in a scene image to be processed 610, first objects 6111, 6112, 6113, and 6114 can be identified. Based on the first object position information of each of the four first objects 6111, 6112, 6113, and 6114, a first object region 611 is obtained, encompassing the first object position information of each of the four first objects 6111, 6112, 6113, and 6114. Based on the first region center position of the first object region 611, the first object position information of each of the first objects 6111 and 6112 is determined as the reference first object position information. The first object position information of each of the first objects 6113 and 6114 is determined as the mirrored first object position information. Furthermore, based on the first region center position, a first region center element 601 is generated, so that the user can easily see that the first objects 6111 and 6113 are symmetrical with respect to the first region center element 601, and that the first objects 6112 and 6114 are symmetrical with respect to the first region center element 601. That is, the reference first object position information in the reference first object position information set and the reference first object position information in the mirror image first object position information set are symmetrical relative to the center position of the first area.

[0108] According to an embodiment of the present disclosure, generating a target scene image including the second object in the second interactive interface according to the image data of the second object and the second object position information of the second object may include the following operations.

[0109] A reference second object is generated in a second interactive interface based on image data of the second object and reference second object position information, wherein the reference second object position information is determined based on reference first object position information in a reference first object position information set; and the reference second object is mirrored based on a second area center position to obtain a mirrored second object generated in the second interactive interface, wherein the second area center position is determined based on the first area center position, the multiple second objects include a mirrored second object and a reference second object, and the mirrored second object and the reference second object are symmetrical relative to the second area center position.

[0110] As shown in Figure 6, the image data of the second object can be determined based on the target index of each of the first objects 6111, 6112, 6113, and 6114. Based on the first object position information of each of the first objects 6111 and 6112, that is, based on the reference first object position information, the reference second object position information can be obtained. Based on the reference second object position information and the image data of the second object, reference second objects 6211 and 6212 can be rendered.

[0111] The first region center position can be converted to obtain the second region center position, and a second region center element 602 is generated at the second region center position. Based on the second region center position, reference second objects 6211 and 6212 are mirrored to obtain mirrored second objects 6213 and 6214. Reference second object 6211 and mirrored second object 6213 are symmetrical with respect to second region center element 602, and reference second object 6212 and mirrored second object 6214 are symmetrical with respect to second region center element 602. Thus, a target scene image 620 containing reference second objects 6211 and 6212 and mirrored second objects 6213 and 6214 is obtained.

[0112] According to an embodiment of the present disclosure, a base second object is obtained by rendering in a second interactive page, and then the base second object is mirrored according to the center of the second area to obtain a mirrored second object at the position of the mirrored second object. This can avoid the problem of excessive computational overhead generated by obtaining the mirrored second object through the object rendering operation, reduce the computational overhead of reconstructing the target scene image of the second dimension, and improve the reconstruction efficiency of the target scene image.

[0113] According to an embodiment of the present disclosure, the target scene image includes a logistics operation scene image.

[0114] According to embodiments of the present disclosure, the logistics operation scene image can be a three-dimensional design image representing a warehousing and logistics center, or it can be a three-dimensional scene image used to represent the warehousing and logistics center during operation. The logistics operation scene image obtained based on the embodiments of the present disclosure can accurately represent the location, type, size, and other attribute information of the logistics equipment and logistics facilities in the warehousing and logistics center, thereby improving the reconstruction accuracy of the logistics operation scene, improving the overall construction efficiency of the warehousing and logistics center, and improving the operational efficiency of the warehousing and logistics center after completion.

[0115] FIG7A schematically shows a schematic diagram of a scene image to be processed according to an embodiment of the present disclosure.

[0116] As shown in Figure 7A, the scene image to be processed can be a two-dimensional image file based on the DXF format, and the two-dimensional image is rendered in the first interactive interface. The scene image to be processed can be a floor plan of a logistics storage area, and the scene image to be processed can include multiple first objects with rectangular outlines.

[0117] FIG7B schematically shows a schematic diagram of a target scene image according to an embodiment of the present disclosure.

[0118] As shown in FIG7B , based on the image reconstruction method provided by the embodiment of the present disclosure, the scene image to be processed can be reconstructed into a three-dimensional logistics operation scene image.

[0119] FIG8 schematically shows a block diagram of an image reconstruction apparatus according to an embodiment of the present disclosure.

[0120] As shown in FIG8 , the image reconstruction apparatus 800 includes: a first scene image region determination module 810 , a first object recognition module 820 , a second object determination module 830 and a target scene image construction module 840 .

[0121] The first scene image region determining module 810 is configured to determine, in response to an object reconstruction operation on the scene image to be processed, a first scene image region corresponding to the object reconstruction operation in the scene image to be processed.

[0122] The first object recognition module 820 is configured to recognize a first object to be reconstructed in a first scene image region, wherein the first object is associated with a target index.

[0123] The second object determination module 830 is used to determine the second object associated with the target index from the second object set based on the target index associated with the first object, wherein the spatial dimension of the first object is the first dimension, the spatial dimension of the second object is the second dimension, and the first dimension is different from the second dimension.

[0124] The target scene image constructing module 840 is configured to construct a target scene image according to the image data of the second object.

[0125] According to an embodiment of the present disclosure, the image reconstruction apparatus may further include: a first mirror reference element generation module, a second scene image region determination module, and a first recognition module.

[0126] The first mirror image reference element generation module is used to generate a first mirror image reference element related to the first scene image area in a first interactive interface for displaying the scene image to be processed when detecting that the first scene image area is obtained.

[0127] The second scene image area determination module is used to determine, in the scene image to be processed, a second scene image area corresponding to the first scene image area based on the first mirror reference element, wherein the first scene image area and the second scene image area are symmetrical with respect to the first mirror reference element.

[0128] The first recognition module is used to recognize a first object associated with the target index from the second scene image area according to the target index.

[0129] According to an embodiment of the present disclosure, the first object has first object position information.

[0130] Among them, the target scene image construction module includes a target scene image construction unit.

[0131] The target scene image construction unit is used to generate a target scene image containing the second object in the second interactive interface based on the image data of the second object and the second object position information of the second object; wherein the second object position information of the second object is determined based on the first object position information of each of the first objects.

[0132] According to an embodiment of the present disclosure, the first object includes a plurality.

[0133] The image reconstruction device further includes: a first object area determination module and a first determination module.

[0134] The first object region determining module is configured to determine a first object region surrounding first object position information of each of a plurality of first objects.

[0135] The first determination module is used to determine a baseline first object position information set and a mirrored first object position information set from multiple first object position information based on the first area center position of the first object area, wherein the baseline first object position information in the baseline first object position information set and the baseline first object position information in the mirrored first object position information set are symmetrical relative to the first area center position.

[0136] According to an embodiment of the present disclosure, the second object includes a plurality.

[0137] The target scene image construction unit includes:

[0138] The reference second object determination subunit is used to generate a reference second object in the second interactive interface based on the image data of the second object and the reference second object position information, wherein the reference second object position information is determined based on the reference first object position information in the reference first object position information set.

[0139] The mirrored second object determination subunit is used to mirror the reference second object according to the center position of the second area to obtain a mirrored second object generated in the second interactive interface, wherein the center position of the second area is determined based on the center position of the first area, and the multiple second objects include the mirrored second object and the reference second object, and the mirrored second object and the reference second object are symmetrical relative to the center position of the second area.

[0140] According to an embodiment of the present disclosure, the image reconstruction apparatus further includes: an updating module and a first object generating module.

[0141] The updating module is used to update the object display attribute information of the first object in the first interactive interface for displaying the scene image to be processed, and obtain the updated display attribute information of the target object.

[0142] The first object generation module is used to generate a new first object in the first interactive interface according to the target object display attribute information.

[0143] According to an embodiment of the present disclosure, the object display attribute information includes at least one of the following: object color attribute information, object line attribute information.

[0144] According to an embodiment of the present disclosure, the second object determination module includes: a candidate second object determination unit, a candidate second object floating window determination unit, a target second object element determination unit, and a second object determination unit.

[0145] The candidate second object determining unit is configured to determine, according to the target index associated with the first object, a plurality of candidate second objects associated with the target index from the second object set.

[0146] The candidate second object floating window determining unit is used to generate a candidate second object floating window in a first interactive interface for displaying the scene image to be processed, wherein the candidate second object floating window includes candidate second object elements associated with each of the multiple candidate second objects.

[0147] The target second object element determining unit is configured to, in response to detecting an element determination operation on a candidate second object element in the candidate second object floating window, determine the candidate second object element corresponding to the element determination operation as a target second object element.

[0148] The second object determining unit is configured to determine the candidate second object associated with the target second object element as the second object.

[0149] According to an embodiment of the present disclosure, the first scene image area determination module includes: a target detection result obtaining unit and a first object obtaining unit.

[0150] The target detection result obtaining unit is used to input the first scene image area into the target detection model constructed based on the neural network algorithm and output the target detection result.

[0151] The first object obtaining unit is used to determine the first object according to the target detection result.

[0152] According to an embodiment of the present disclosure, the target scene image includes a logistics operation scene image.

[0153] According to the modules, units, and subunits of the embodiments of the present invention, any multiple or at least part of the functions of any multiple thereof can be implemented in one module. According to the modules, units, and subunits of the embodiments of the present invention, any one or more thereof can be split into multiple modules for implementation. According to the modules, units, and subunits of the embodiments of the present invention, any one or more thereof can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware of any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation modes of software, hardware, and firmware or in an appropriate combination of any several thereof. Alternatively, according to the modules, units, and subunits of the embodiments of the present invention, one or more thereof can be at least partially implemented as a computer program module, which can perform the corresponding function when the computer program module is run.

[0154] For example, any multiple of the first scene image area determination module 810, the first object recognition module 820, the second object determination module 830, and the target scene image construction module 840 can be combined into one module / unit / sub-unit for implementation, or any one of the modules / units / sub-units can be split into multiple modules / units / sub-units. Alternatively, at least part of the functions of one or more of these modules / units / sub-units can be combined with at least part of the functions of other modules / units / sub-units and implemented in one module / unit / sub-unit. According to an embodiment of the present disclosure, at least one of the first scene image area determination module 810, the first object recognition module 820, the second object determination module 830, and the target scene image construction module 840 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging the circuit, or in any one of the three implementation modes of software, hardware, and firmware, or in an appropriate combination of any of them. Alternatively, at least one of the first scene image area determination module 810, the first object recognition module 820, the second object determination module 830 and the target scene image construction module 840 can be at least partially implemented as a computer program module, which can perform corresponding functions when executed.

[0155] It should be noted that the image reconstruction device part in the embodiment of the present disclosure corresponds to the image reconstruction method part in the embodiment of the present disclosure. The description of the image reconstruction device part specifically refers to the image reconstruction method part and will not be repeated here.

[0156] Figure 9 schematically shows a block diagram of an electronic device suitable for implementing the image reconstruction method described above according to an embodiment of the present disclosure. The electronic device shown in Figure 9 is only an example and should not bring any limitation to the functions and scope of use of the embodiment of the present disclosure.

[0157] As shown in Figure 9, the electronic device 900 according to an embodiment of the present disclosure includes a processor 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage part 908 into a random access memory (RAM) 903. The processor 901 may, for example, include a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a dedicated microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 901 may also include an onboard memory for caching purposes. The processor 901 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0158] Various programs and data required for the operation of the electronic device 900 are stored in the RAM 903. The processor 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. The processor 901 executes the various operations of the method flow according to the embodiment of the present disclosure by executing the programs in the ROM 902 and / or the RAM 903. It should be noted that the programs may also be stored in one or more memories other than the ROM 902 and the RAM 903. The processor 901 may also execute the various operations of the method flow according to the embodiment of the present disclosure by executing the programs stored in the one or more memories.

[0159] According to an embodiment of the present disclosure, the electronic device 900 may further include an input / output (I / O) interface 905, which is also connected to the bus 904. The system 900 may further include one or more of the following components connected to the I / O interface 905: an input section 906 including a keyboard, a mouse, etc.; an output section 907 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and speakers; a storage section 908 including a hard disk; and a communication section 909 including a network interface card such as a LAN card or a modem. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the I / O interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed in the drive 910 as needed, so that computer programs read therefrom can be installed into the storage section 908 as needed.

[0160] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 909, and / or installed from the removable medium 911. When the computer program is executed by the processor 901, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0161] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments, or may exist independently and not be incorporated into the device / apparatus / system. The computer-readable storage medium carries one or more programs, and when executed, implements the method according to the embodiments of the present disclosure.

[0162] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0163] For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 902 and / or the RAM 903 described above and / or one or more memories other than the ROM 902 and the RAM 903 .

[0164] An embodiment of the present disclosure also includes a computer program product, which includes a computer program, which contains program code for executing the method provided by the embodiment of the present disclosure. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the image reconstruction method provided by the embodiment of the present disclosure.

[0165] When the computer program is executed by the processor 901, the above functions defined in the system / device of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0166] In one embodiment, the computer program may be stored on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may be transmitted and distributed in the form of a signal on a network medium, downloaded and installed via the communication portion 909, and / or installed from a removable medium 911. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0167] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computer programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, python, "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect via the Internet).

[0168] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of the systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the boxes may occur in an order different from that marked in the accompanying drawings. For example, two boxes shown in succession may actually be executed substantially in parallel, or they may sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, as well as the combination of boxes in the block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or may be implemented using a combination of dedicated hardware and computer instructions. It will be understood by those skilled in the art that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or coupled in various ways, even if such combinations or couplings are not explicitly described in the present disclosure. In particular, without departing from the spirit and teachings of the present disclosure, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or coupled in various ways, and all such combinations and / or couplings fall within the scope of the present disclosure.

[0169] The embodiments of the present disclosure are described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although each embodiment has been described separately above, this does not mean that the measures in each embodiment cannot be used in combination to advantage. The scope of the present disclosure is defined by the appended claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. An image reconstruction method, include: In response to an object reconstruction operation on a scene image to be processed, determining a first scene image region corresponding to the object reconstruction operation in the scene image to be processed; In the first scene image region, identifying a first object to be reconstructed, wherein the first object is associated with a target index; Determining, from a second object set, a second object associated with the target index according to the target index associated with the first object, wherein the spatial dimension of the first object is a first dimension, the spatial dimension of the second object is a second dimension, and the first dimension is different from the second dimension; and A target scene image is constructed according to the image data of the second object.

2. The method according to claim 1, further comprising: include: In a case where it is detected that the first scene image area is obtained, generating a first mirror reference element related to the first scene image area in a first interactive interface for displaying the scene image to be processed; Determining, in the scene image to be processed, a second scene image region corresponding to the first scene image region according to the first mirror image reference element, wherein the first scene image region and the second scene image region are symmetrical with respect to the first mirror image reference element; and According to the target index, the first object associated with the target index is identified from the second scene image area.

3. The method according to claim 1 or 2, in, The first object has first object position information; Wherein, constructing the target scene image according to the image data of the second object comprises: generating a target scene image including the second object in a second interactive interface according to the image data of the second object and the second object position information of the second object; The second object position information of the second object is determined according to the first object position information of each of the first objects.

4. The method according to claim 3, in, The first object includes a plurality of; The image reconstruction method further comprises: Determine a first object area surrounding first object position information of each of the plurality of first objects; According to the first area center position of the first object area, a reference first object position information set and a mirror image first object position information set are determined from the plurality of first object position information, wherein the reference first object position information in the reference first object position information set and the reference first object position information in the mirror image first object position information set are The position information of an object is symmetrical relative to the center position of the first area.

5. The method according to claim 4, in, The second object includes a plurality of; The step of generating a target scene image including the second object in the second interactive interface according to the image data of the second object and the second object position information of the second object includes: generating a reference second object in the second interactive interface according to the image data of the second object and the reference second object position information, wherein the reference second object position information is determined according to the reference first object position information in the reference first object position information set; According to the center position of the second area, the reference second object is mirrored to obtain a mirrored second object generated in the second interactive interface, wherein the center position of the second area is determined based on the center position of the first area, the multiple second objects include the mirrored second object and the reference second object, and the mirrored second object and the reference second object are symmetrical relative to the center position of the second area.

6. The method according to claim 1 or 2, further comprising: include: In a first interactive interface for displaying the scene image to be processed, updating the object display attribute information of the first object to obtain updated display attribute information of the target object; as well as A new first object is generated in the first interactive interface according to the target object display attribute information.

7. The method according to claim 6, in, The object display attribute information includes at least one of the following: Object color attribute information, object line attribute information.

8. The method according to claim 1, in, The determining, according to the target index associated with the first object, from a second object set, a second object associated with the target index comprises: According to the target index associated with the first object, determining a plurality of candidate second objects associated with the target index from the second object set; In a first interactive interface for displaying the scene image to be processed, generating a candidate second object floating window, wherein the candidate second object floating window includes candidate second object elements associated with each of the plurality of candidate second objects; In response to detecting an element determination operation on a candidate second object element in the candidate second object floating window, determining the candidate second object element corresponding to the element determination operation as a target second object element; and A candidate second object associated with the target second object element is determined as the second object.

9. The method according to claim 1, in, The identifying, in the first scene image region, a first object to be reconstructed comprises: Inputting the first scene image area into a target detection model built based on a neural network algorithm, and outputting a target detection result; and The first object is determined according to the target detection result.

10. The method according to claim 1, in, The target scene image includes a logistics operation scene image.

11. An image reconstruction device, include: A first scene image region determining module, configured to, in response to an object reconstruction operation on a scene image to be processed, determine a first scene image region corresponding to the object reconstruction operation in the scene image to be processed; A first object recognition module, configured to recognize a first object to be reconstructed in the first scene image region, wherein the first object is associated with a target index; A second object determination module, configured to determine, from a second object set, a second object associated with a target index associated with the first object, wherein the spatial dimension of the first object is a first dimension, the spatial dimension of the second object is a second dimension, and the first dimension is different from the second dimension; and The target scene image construction module is used to construct a target scene image according to the image data of the second object.

12. An electronic device, include: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 10.

13. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enables the processor to implement the method according to any one of claims 1 to 10.

14. A computer program product comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 10.

Images