Electronic express sheet generation method and related device

Abstract

The embodiment of the invention provides a method for generating an electronic waybill. The method comprises the following steps: acquiring a to-be-processed electronic waybill image; identifying image content in the electronic express sheet image to determine an express sheet content area; performing image processing on the electronic express sheet image based on the express sheet content area to obtain a blank area; further inputting the blank area and the express sheet newly-added content corresponding to the target platform into the target large model to determine an adaptive area of the express sheet newly-added content in the blank area; and the electronic express sheet image is filled with express sheet newly-added content according to the adaptive area, so that a target electronic express sheet can be obtained. Therefore, the intelligent filling process of the newly added content of the electronic waybill is realized, the blank area on the electronic waybill can be accurately found out through content detection, then the specific area adaptive to the newly added content is confirmed through large model analysis, the reasonability of the selected area is ensured, the process does not need manual intervention, and the efficiency is improved. The efficiency and accuracy of electronic express sheet information adding are improved.

Description

Technical Field

[0001] This specification relates to the field of computer application technology, specifically to the technology for generating electronic waybills within the field of computer application technology, and more specifically to the method and related apparatus for generating electronic waybills. Background Technology

[0002] In the warehousing and logistics sector, electronic waybills are crucial for recording cargo transportation information. Basic information such as sender's address, recipient's address, and tracking number are displayed on them, facilitating identification and processing at each stage of the express delivery process. In some scenarios, additional information needs to be added to the electronic waybill, such as during warehousing and sorting.

[0003] Generally, the process of filling new waybill content into the blank areas of existing waybills is based on manually looking at the image to "find the empty space" and using text processing tools to process the text content; however, this process is time-consuming and labor-intensive, affecting the efficiency of electronic waybill content configuration. Summary of the Invention

[0004] This specification provides an embodiment of a method for generating electronic waybills and related apparatus, which improves the efficiency of configuring electronic waybill content.

[0005] To achieve the above technical objectives, the embodiments of this specification provide the following technical solutions:

[0006] Firstly, one embodiment of this specification provides a method for generating an electronic waybill, comprising:

[0007] Acquire the image of the electronic waybill to be processed;

[0008] The image content in the electronic waybill image is identified to determine the waybill content area;

[0009] Image processing is performed on the electronic waybill image based on the content area of ​​the waybill to obtain the blank area in the electronic waybill image;

[0010] The blank area and the new label content corresponding to the target platform are input into the target large model to determine the matching area of ​​the new label content in the blank area. The target large model is trained using the correspondence between the new content and the blank area in different business platforms.

[0011] The new content of the waybill is filled into the electronic waybill image according to the adaptation region to obtain the target electronic waybill. The target electronic waybill is used to guide the execution of business processes in the target platform, and the business processes are associated with the new content of the waybill.

[0012] Secondly, one embodiment of this specification provides an electronic waybill generation apparatus, comprising:

[0013] The acquisition unit is used to acquire the electronic waybill image to be processed;

[0014] The processing unit is used to identify the image content in the electronic waybill image to determine the waybill content area;

[0015] The processing unit is further configured to perform image processing on the electronic waybill image based on the content area of ​​the waybill, so as to obtain a blank area in the electronic waybill image;

[0016] The processing unit is further configured to input the blank area and the new content of the waybill corresponding to the target platform into the target large model to determine the matching area of ​​the new content of the waybill in the blank area. The target large model is trained using the correspondence between the new content and the blank area in different business platforms.

[0017] The generation unit is used to fill the new content of the waybill into the electronic waybill image according to the adaptation region to obtain a target electronic waybill. The target electronic waybill is used to guide the execution of business processes in the target platform, and the business processes are associated with the new content of the waybill.

[0018] Optionally, in one possible implementation, the processing unit is specifically used to perform noise reduction processing on the electronic waybill image to obtain a noise-reduced image, wherein the electronic waybill image comes from different business platforms and the layout information of the electronic waybill is different for different business platforms;

[0019] The processing unit is specifically used to determine the image gradient information corresponding to the electronic form image based on the denoised image;

[0020] The processing unit is specifically used to perform edge recognition based on image gradient information in order to determine the content edge information corresponding to the image content in the electronic waybill image.

[0021] The processing unit is specifically used to determine the content area of ​​the shipping label using the content edge information.

[0022] Optionally, in one possible implementation, the processing unit is specifically used to filter out the form content area from the electronic form image to obtain the processing area;

[0023] The processing unit is specifically used to obtain the filtering rules corresponding to the target platform, and the filtering rules include at least one of unit area size or edge distance.

[0024] The processing unit is specifically used to perform region filtering on the processing area based on the filtering rules to obtain blank areas in the electronic waybill image.

[0025] Optionally, in one possible implementation, the processing unit is specifically used to determine the business type identifier of the new content added to the waybill corresponding to the target platform;

[0026] The processing unit is specifically used to obtain a preset type identifier similar to the business type identifier if the business type identifier indicates that the new content of the waybill is the first new type. The new content corresponding to the preset type identifier is the pre-training data of the target large model.

[0027] The processing unit is specifically used to configure target prompt words based on the blank area, the new content added to the waybill corresponding to the target platform, and the preset type identifier.

[0028] The processing unit is specifically used to input the target prompt word into the target large model in order to determine the fitting area of ​​the newly added content on the waybill in the blank area.

[0029] Optionally, in one possible implementation, the processing unit is specifically used to determine the association dimension between the preset type identifier and the business type identifier;

[0030] The processing unit is specifically used to perform retrieval enhancement based on the association dimension, so as to serve as the annotation information of the preset type identifier;

[0031] The processing unit is specifically used to configure the target prompt word based on the blank area, the new content added to the waybill corresponding to the target platform, and the remarks information of the preset type identifier.

[0032] Optionally, in one possible implementation, the generating unit is specifically used to determine the filling range corresponding to the adaptation region;

[0033] The generation unit is specifically used to adjust the display parameters of the newly added content on the order based on the filling range, so as to obtain the adjusted content;

[0034] The generation unit is specifically used to fill the adjusted content into the electronic waybill image according to the adaptation area to obtain the target electronic waybill.

[0035] Optionally, in one possible implementation, the generating unit is specifically used to obtain the business scenario information corresponding to the newly added content on the waybill;

[0036] The generation unit is specifically used to determine the display feature parameters of the business scenario information indication;

[0037] The generation unit is specifically used to adjust the parameters of the newly added content of the order based on the filling range using the display feature parameters, so as to obtain the adjusted content.

[0038] Thirdly, one embodiment of this specification also provides a computing device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the electronic waybill generation method as described above.

[0039] Fourthly, one embodiment of this specification also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the electronic waybill generation method described above.

[0040] Fifthly, embodiments of this specification provide a computer program product or computer program, the computer program product including a computer program that can be stored in a computer-readable storage medium or in the cloud; the processor of the computer device reads the computer program, and when the processor executes the computer program, it implements the steps of the above-described method for generating electronic waybills.

[0041] As can be seen from the above technical solution, the electronic waybill generation method provided in this specification obtains an electronic waybill image to be processed; then, it identifies the image content in the electronic waybill image to determine the waybill content area; and performs image processing on the electronic waybill image based on the waybill content area to obtain blank areas in the electronic waybill image; further, it inputs the blank areas and the new waybill content corresponding to the target platform into a target large model to determine the adaptation area of ​​the new waybill content in the blank area. This target large model is trained using the correspondence between new content and blank areas in different business platforms; then, it fills the new waybill content into the electronic waybill image according to the adaptation area to obtain the target electronic waybill. This target electronic waybill is used to guide the execution of business processes in the target platform, and the business processes are associated with the new waybill content. This achieves an intelligent filling process for new electronic waybill content. Through content detection, blank areas on the electronic waybill can be accurately identified. Then, through large model analysis, specific areas adapted to the new content are confirmed, ensuring the rationality of the selected areas. Moreover, this process requires no manual intervention, improving the efficiency and accuracy of adding information to the electronic waybill. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this specification. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0043] Figure 1 Network architecture diagram for the electronic waybill generation system;

[0044] Figure 2 A flowchart illustrating the generation process of an electronic waybill, provided as an embodiment of this application;

[0045] Figure 3 A flowchart illustrating a method for generating an electronic waybill, as provided in one embodiment of this specification.

[0046] Figure 4 A schematic diagram illustrating a method for generating an electronic waybill as one embodiment of this specification;

[0047] Figure 5 A schematic diagram illustrating a scenario of another method for generating electronic waybills provided as one embodiment of this specification;

[0048] Figure 6 A schematic diagram of the functional modules of an electronic waybill generation device provided for one embodiment of this specification;

[0049] Figure 7 This is a schematic diagram of the structure of a computing device provided for one embodiment of this specification. Detailed Implementation

[0050] Unless otherwise defined, the technical or scientific terms used in the embodiments of this specification shall have the ordinary meaning understood by one of ordinary skill in the art to which this specification pertains. The terms "first," "second," and similar terms used in the embodiments of this specification do not indicate any order, quantity, or importance, but are merely used to avoid confusion of constituent elements.

[0051] Unless the context otherwise requires, throughout this specification, "a plurality of" means "at least two," and "including" is interpreted as open-ended or encompassing, that is, "including, but not limited to." In the description of this specification, terms such as "one embodiment," "some embodiments," "exemplary embodiment," "example," "specific example," or "some examples" are intended to indicate that a particular feature, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of this specification. The illustrative representations of the above terms do not necessarily refer to the same embodiment or example.

[0052] It should be understood that the electronic waybill generation method provided in this application can be applied to systems or programs in terminal devices that include electronic waybill generation functionality, such as logistics management applications. Specifically, the electronic waybill generation system can run on systems such as... Figure 1 In the network architecture shown, such as Figure 1 The diagram shows the network architecture of the electronic waybill generation system. As can be seen, the system can generate electronic waybills from multiple information sources. Specifically, it triggers the server to generate the target electronic form by requesting new content from the terminal. This means that… Figure 1 The document shows various terminal devices, which can be computer devices. In real-world scenarios, more or fewer types of terminal devices may participate in the generation of electronic waybills. The specific number and types depend on the actual scenario and are not limited here. Additionally, Figure 1 The example shows one server, but in real-world scenarios, multiple servers can be involved, especially in multidisciplinary output scenarios. The specific number of servers depends on the actual scenario.

[0053] In this embodiment, the server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. The terminal and server can be directly or indirectly connected via wired or wireless communication, and the terminal and server can be connected to form a blockchain network; this application does not impose any restrictions.

[0054] It is understood that the aforementioned electronic waybill generation system can run on personal mobile terminals, such as as an application for logistics management, or it can run on servers, or it can run on third-party devices to provide electronic waybill generation and obtain the electronic waybill generation processing results from the information source. Specifically, the electronic waybill generation system can run as a program on the aforementioned devices, or it can run as a system component of the aforementioned devices, or it can run as a cloud service program. The specific operating mode depends on the actual scenario and is not limited here.

[0055] First, the terms that may appear in this application will be explained.

[0056] Stock Keeping Unit (SKU): This refers to the basic unit for measuring the inflow and outflow of inventory. It can be a single item, a box of items, etc., and is used to distinguish different items.

[0057] Edge detection algorithm: an image processing technique used to identify areas in a digital image where brightness changes significantly, and these areas usually correspond to the edges of objects.

[0058] Large models: refer to artificial intelligence models with a large number of parameters and powerful computing capabilities, which can complete complex tasks such as recognition, comparison, and prediction by learning from a large amount of data.

[0059] In the warehousing and logistics sector, electronic waybills are crucial for recording cargo transportation information. Basic information such as sender's address, recipient's address, and tracking number are displayed on them, facilitating identification and processing at each stage of the express delivery process. Currently, different e-commerce platforms and courier companies have their own electronic waybill templates, which vary in style and layout.

[0060] As the industry develops, more information is needed in the cargo transportation process to improve efficiency and accuracy, such as SKU information (stock keeping unit, used to distinguish different products) and picking location (the storage location of goods in the warehouse). However, most existing electronic waybill templates only include basic logistics information and lack these necessary additional details. The usual practice is to print this information on a separate small label and then attach it to the package. This double printing and labeling is wasteful of paper, prone to errors, and, more importantly, increases labor costs, impacting the efficiency of configuring electronic waybill content.

[0061] Alternatively, this information can be filled into the blank areas of existing waybills. Common practices include: manually finding empty spaces by looking at the image and moving the text around using Photoshop or Word. This requires readjustment whenever the platform template is updated. Another method is to overlay fixed coordinates, where programmers write the coordinates for each template and forcibly overlay the text into a fixed position. However, if the template is changed or the user changes printers, the text may cover the barcode or logo, rendering the waybill invalid.

[0062] It is evident that the fixed coordinate method lacks universality; errors occur when changing templates. Existing electronic waybill templates vary significantly across platforms, lacking a unified standard. This makes it difficult to find suitable locations when adding essential information such as SKU information and picking locations. Forcing the addition of such information may result in unclear or obscured information due to inappropriate font size or placement, affecting the normal transportation and processing of goods.

[0063] Manually adjusting the position of shipping labels is inefficient, and template upgrades require manual intervention. Manually locating blank areas and adjusting the information format faces serious problems due to platform template changes. Electronic shipping label templates on various platforms may be adjusted periodically, but these adjustments are often not communicated to logistics companies or warehouses in advance. Only after the labels are printed in batches do problems such as incorrect placement or obstruction of information caused by template changes become apparent. This results in significant paper waste and increased costs. Furthermore, problematic labels need to be reprocessed, severely impacting warehouse outbound efficiency, and even manual adjustments to the shipping label template can lead to delays in shipments.

[0064] To address the aforementioned problems, this application proposes a method for generating electronic waybills, which is applied to... Figure 2 The workflow framework for generating electronic waybills shown is as follows: Figure 2 The diagram shown is a flowchart of the process architecture for generating an electronic waybill provided in an embodiment of this application. The terminal sends a new content request to the server, which then uses edge detection and blank area algorithms to identify blank areas on the electronic waybill. The server then compares the blank areas with a large model to confirm suitable areas and dynamically adjusts the font size, color, and position of the information to be added based on the size of the area, ensuring that the information is clearly and completely displayed on the electronic waybill.

[0065] It is understood that the electronic waybill generation method provided in this application can be a program written as processing logic in a hardware system, or it can be an electronic waybill generation device, implementing the above processing logic in an integrated or external manner. As one implementation, the electronic waybill generation device acquires an electronic waybill image to be processed; then identifies the image content in the electronic waybill image to determine the waybill content area; and performs image processing on the electronic waybill image based on the waybill content area to obtain a blank area in the electronic waybill image; further, it inputs the blank area and the new waybill content corresponding to the target platform into a target large model to determine the adaptation area of ​​the new waybill content in the blank area. This target large model is trained using the correspondence between new content and blank areas in different business platforms; then, based on the adaptation area, it fills the electronic waybill image with the new waybill content to obtain a target electronic waybill. This target electronic waybill is used to guide the execution of business processes in the target platform, and the business processes are associated with the new waybill content. This enables an intelligent filling process for new content on electronic waybills. Through content detection, blank areas on the electronic waybill can be accurately identified. Then, through large-scale model analysis, specific areas suitable for the new content are confirmed, ensuring the rationality of the selected areas. Moreover, this process does not require manual intervention, improving the efficiency and accuracy of adding information to electronic waybills.

[0066] Based on the above process architecture, the method for generating electronic waybills in this application will be described below. This process can be executed by a server or computer system. This method can process the electronic waybill image and add the required information. Please refer to [link / reference]. Figure 3 , Figure 3 A flowchart illustrating a method for generating an electronic waybill provided in this application embodiment, which includes at least the following steps:

[0067] 301. Obtain the electronic waybill image to be processed.

[0068] In this embodiment, the electronic waybill image to be processed can be an electronic waybill image from different business platforms, and the layout information of the electronic waybill corresponding to different business platforms is different. Therefore, it is necessary to configure an intelligent image recognition process that adapts to electronic waybill images with different layout information.

[0069] Specifically, the electronic waybill image is determined based on the electronic waybill of the business platform. The electronic waybill image to be processed can be obtained first, and then determined through a scanned copy or electronic file of the electronic waybill. The specific method depends on the actual scenario.

[0070] In one possible scenario, such as Figure 4 As shown, Figure 4 This is a schematic diagram illustrating a scenario of an electronic waybill generation method provided in one embodiment of this specification. By collecting electronic waybills from different business platforms, the electronic waybills from different business platforms can be adapted to local business needs. That is, electronic waybills from different platforms can be adapted to the input of new content for local business needs, realizing a cross-platform waybill content addition process.

[0071] It is understood that this embodiment processes electronic waybill images acquired in real time, and can automatically adapt to changes in templates across various platforms without relying on platform template change notifications. Even if the platform template is adjusted, it can accurately identify blank areas in the new template and add information appropriately, avoiding wasted waybill printing due to template changes and effectively ensuring warehouse outbound efficiency.

[0072] 302. Identify the image content in the electronic waybill image to determine the content area of ​​the waybill.

[0073] In this embodiment, the image content in the electronic waybill image is the data element containing the logistics information, such as recipient, sender, address, item type, etc., and the waybill content area is the area containing the above content. Since different information is partitioned or configured with corresponding area boxes for information display in the logistics field, the waybill content area can also be the area box corresponding to the logistics data element.

[0074] Specifically, the image content recognition process can involve processing the electronic waybill image using edge detection algorithms. This involves drawing an outline on the waybill, identifying the edges of existing information (such as text, barcodes, logos, etc.) to determine the location range of this information on the waybill. This process can begin by denoising the electronic waybill image to obtain a denoised image. Then, the image gradient information corresponding to the electronic waybill image is determined from the denoised image. Edge detection is then performed based on this gradient information to determine the content edge information corresponding to the image content in the electronic waybill image. Finally, the content area of ​​the waybill is determined using this content edge information.

[0075] In one possible scenario, the edge detection algorithm used in the above edge detection process could be the Canny algorithm. This algorithm effectively detects edges in an image by first denoising the image to reduce interference, then calculating the image gradient to determine the possible locations of edges, and finally filtering out the true edges. Specifically, the input color image is first converted to grayscale, simplifying the color information of each pixel into a single brightness value, laying the foundation for subsequent edge analysis and significantly reducing the amount of data to be processed. Subsequently, the algorithm enters a Gaussian filtering stage to deal with ubiquitous noise. Image noise, such as minor imperfections in the paper or graininess introduced by scanning, can severely interfere with edge detection. This stage uses a Gaussian convolution kernel to blur the image, effectively smoothing it and suppressing these high-frequency noises. This is a crucial trade-off: excessive blurring may erase subtle edges, while insufficient blurring will leave noise. Therefore, the choice of Gaussian kernel size is critical, ensuring that the image retains important structure while reducing noise. After obtaining the smoothed image, the core gradient calculation stage of the algorithm begins. It uses operators such as Sobel to calculate the rate of change of brightness (first derivative) of each pixel in the horizontal (x) and vertical (y) directions, respectively. Based on the derivatives in these two directions, it calculates the gradient intensity (the degree of brightness change) and gradient direction (the direction of the fastest brightness change, perpendicular to the edge direction) of each pixel. At this point, all potential edge points in the image have been preliminarily identified, and the magnitude of their edge intensity is characterized by the gradient value.

[0076] Understandably, in the selection of edge detection algorithms, in addition to the Canny algorithm, other edge detection algorithms such as the Sobel algorithm and the Prewitt algorithm can also be used to identify the edges of existing information on the waybill. The specific algorithm can be adjusted according to the actual scenario.

[0077] 303. Perform image processing on the electronic waybill image based on the content area of ​​the waybill to obtain the blank area in the electronic waybill image.

[0078] In this embodiment, the process of image processing on the electronic waybill image based on the waybill content area is the process of filtering out the waybill content area. For example... Figure 5 As shown, Figure 5 This is a schematic diagram of another method for generating electronic waybills provided in one embodiment of this specification; for the electronic form in the figure, based on the results of edge detection, a blank area algorithm is used to filter out blank areas from the waybill image that are not occupied by existing information.

[0079] In one possible scenario, to improve the effectiveness of subsequent content filling in blank areas, it's necessary to increase the usability of these blank areas. This means the blank area algorithm sets certain rules when filtering blank areas. Specifically, during image processing of the electronic waybill image based on its content area to obtain blank areas, the content area is filtered out to obtain the processed area. Then, the filtering rules corresponding to the target platform are obtained; and finally, the processed area is filtered based on these rules to obtain the blank areas in the electronic waybill image.

[0080] The filtering rules include at least one of the unit area size or edge distance. For example, areas that are too small (such as less than a certain number of square centimeters) will be excluded because such areas cannot contain valid information. At the same time, areas that are too close to the edge of the waybill will also be excluded to prevent information from exceeding the range of the waybill.

[0081] In addition, the filtering rules for blank areas can be adjusted according to actual needs. For example, for some special waybill templates, the restrictions on the area of ​​blank areas or the distance from the edge can be appropriately relaxed. The specific numerical requirements depend on the actual scenario.

[0082] 304. Input the blank area and the corresponding new content of the waybill on the target platform into the target large model to determine the matching area of ​​the new content of the waybill in the blank area. The target large model is trained by using the correspondence between the new content and the blank area in different business platforms.

[0083] In this embodiment, the target platform is the platform on which the current business is executed. That is, in order to adapt to the current business execution, the electronic waybill image to be processed needs to be added with corresponding waybill content during the input of the target platform. The source platform of the electronic waybill image to be processed can be the same business platform as the target platform or a different business platform. For example, when the goods of courier company A are transferred through the warehouse of courier company B, the warehouse identifier corresponding to courier company B needs to be added to improve the transfer efficiency, thereby realizing the cross-platform intelligent adaptation process of electronic waybills.

[0084] Specifically, considering that different business platforms have different electronic waybill templates, and that the process of adding new content to the waybill needs to be adapted to the current business operations of the target platform, the identified blank area information can be input into the large model, along with relevant information about the platform to which the electronic waybill belongs. The large model will compare the usage of blank areas in the platform's historical waybills with appropriate information addition standards, and identify the most suitable area for adding new information (such as SKU information, picking location, etc.) from the identified blank areas.

[0085] Understandably, the target large model, after being trained on a large amount of electronic waybill data from different platforms, can learn the layout characteristics of waybills on different platforms and the reasonable use of blank areas, thereby more accurately determining which blank area is most suitable for adding new information.

[0086] In one possible scenario, considering that the configuration requirements for new content may differ across different business processes—for example, warehouse identifiers are generally limited to areas near the edge of the form—if an unrepresented business scenario arises, to improve the adaptability of the large model, the business type identifier for the new content on the shipping label corresponding to the target platform can be determined first. If the business type identifier indicates that the new content on the shipping label is a first-time addition, a preset type identifier similar to the business type identifier is obtained, and the new content corresponding to the preset type identifier is the pre-training data of the target large model. Then, target prompt words are configured based on the blank area, the new content on the shipping label corresponding to the target platform, and the preset type identifier. The target prompt words are then input into the target large model to determine the adaptation area of ​​the new content on the shipping label in the blank area, thereby improving the adaptability of the content addition process to different business scenarios.

[0087] In addition, considering the differences in business processes across different platforms, to further improve the accuracy of the adaptation area for newly added types, the association dimension between the preset type identifier and the business type identifier (e.g., transit storage) can be determined. Then, retrieval enhancement can be performed based on the association dimension to serve as the remarks information for the preset type identifier (e.g., the differences and associations of newly added content configuration in transit storage on different platforms). Target prompts can be configured based on the blank area, the newly added content of the waybill corresponding to the target platform, and the remarks information of the preset type identifier, thereby further improving the adaptability of the content addition process to different business scenarios.

[0088] 305. Fill the electronic waybill image with new content according to the adaptation area to obtain the target electronic waybill. The target electronic waybill is used to guide the execution of business processes in the target platform. The business processes are associated with the new content on the waybill.

[0089] In this embodiment, during the process of filling new content into the electronic waybill image, display parameters can be adjusted to improve the prominence and completeness of the new content. Furthermore, the resulting target electronic waybill can be printed and affixed to the corresponding item, thus achieving the filling of new content under scene changes with only one printing.

[0090] Specifically, the process of adjusting display parameters involves first determining the fill range corresponding to the adaptation area; then adjusting the display parameters based on the fill range for the newly added content on the waybill to obtain the adjusted content; and finally, filling the adjusted content into the electronic waybill image according to the adaptation area to obtain the target electronic waybill. For example, based on the confirmed size and shape of the blank area, the font size of the new information is automatically adjusted (display parameter adjustment), such as using a larger font for a larger area and a smaller font for a smaller area; a suitable color is selected to ensure a clear contrast with the waybill background, making the information easy to read; and the specific position of the information within the blank area is determined to avoid it being too close to the edge, which could lead to incomplete printing or display. The adjusted new information is then added to the corresponding blank area of ​​the electronic waybill, generating a new electronic waybill (target electronic waybill), thereby improving the completeness of the target electronic waybill content.

[0091] Furthermore, during the adjustment of display parameters, it's important to consider that content display requirements may differ across various business scenarios. For instance, different warehouse storage scenarios may have different SKU recognition rules, leading to varying SKU display requirements. To improve the adaptability of content display across different business scenarios, we can obtain the business scenario information corresponding to the newly added content on the waybill. Then, we determine the display feature parameters indicated by the business scenario information (the display requirements for the waybill content in that scenario). Based on the filling range, we adjust the parameters of the newly added content on the waybill using these display feature parameters to obtain the adjusted content. This enhances the prominence of the adjusted content display.

[0092] As can be seen, the above embodiments can accurately identify blank areas on electronic waybills through edge detection and blank area algorithms, and then confirm the selection by comparison with an AI large model, ensuring the rationality of the selected areas. The font size, color, and position of the information are dynamically adjusted according to the blank areas, ensuring that necessary information such as SKU information and picking location are clearly and completely displayed on the electronic waybill without obscuring existing information or causing blurring due to formatting issues. This method requires no manual intervention, improving the efficiency and accuracy of adding information to electronic waybills, ensuring the effective transmission of information during cargo transportation, and enhancing the efficiency of logistics processing.

[0093] Meanwhile, since this method processes electronic waybill images acquired in real time, it can automatically adapt to changes in templates across various platforms without relying on platform template change notifications. Even if the platform template is adjusted, it can accurately identify blank areas in the new template and add information appropriately, avoiding wasted waybill printing due to template changes and effectively ensuring warehouse outbound efficiency.

[0094] In summary, this embodiment acquires an electronic waybill image to be processed; then identifies the image content in the electronic waybill image to determine the content area; and performs image processing on the electronic waybill image based on the content area to obtain blank areas in the electronic waybill image; further, the blank areas and the new waybill content corresponding to the target platform are input into a target large model to determine the fitting area of ​​the new waybill content in the blank area. This target large model is trained using the correspondence between new content and blank areas in different business platforms; then, the new waybill content is filled into the electronic waybill image according to the fitting area to obtain the target electronic waybill. This target electronic waybill is used to guide the execution of business processes in the target platform, and the business processes are associated with the new waybill content. This achieves an intelligent filling process for new content on the electronic waybill. Through content detection, blank areas on the electronic waybill can be accurately identified, and then the large model analysis confirms the specific area that fits the new content, ensuring the rationality of the selected area. Moreover, this process requires no manual intervention, improving the efficiency and accuracy of adding information to the electronic waybill.

[0095] It should be noted that the various embodiments described in this specification emphasize the parts that differ from other embodiments, and the embodiments can be explained by comparison with each other. Any combination of the various embodiments described in this specification based on general technical knowledge is covered within the scope of this specification.

[0096] In one exemplary embodiment of this specification, an electronic waybill generation apparatus 600 is also provided, such as... Figure 6 As shown, Figure 6 A functional module diagram of an electronic waybill generation device provided for one embodiment of this specification. The generation device 600 includes:

[0097] Acquisition unit 601 is used to acquire the electronic waybill image to be processed;

[0098] Processing unit 602 is used to identify the image content in the electronic waybill image in order to determine the waybill content area;

[0099] The processing unit 602 is further configured to perform image processing on the electronic waybill image based on the content area of ​​the waybill, so as to obtain a blank area in the electronic waybill image;

[0100] The processing unit 602 is further configured to input the blank area and the new label content corresponding to the target platform into the target large model to determine the matching area of ​​the new label content in the blank area. The target large model is trained using the correspondence between the new content and the blank area in different business platforms.

[0101] The generation unit 603 is used to fill the new content of the waybill into the electronic waybill image according to the adaptation area to obtain a target electronic waybill. The target electronic waybill is used to guide the execution of business processes in the target platform, and the business processes are associated with the new content of the waybill.

[0102] Optionally, in one possible implementation, the processing unit 602 is specifically used to perform noise reduction processing on the electronic waybill image to obtain a noise-reduced image, wherein the electronic waybill image comes from different business platforms and the layout information of the electronic waybill is different for different business platforms;

[0103] The processing unit 602 is specifically used to determine the image gradient information corresponding to the electronic form image based on the denoised image;

[0104] The processing unit 602 is specifically used to perform edge recognition based on image gradient information to determine the content edge information corresponding to the image content in the electronic waybill image.

[0105] The processing unit 602 is specifically used to determine the content area of ​​the form based on the content edge information.

[0106] Optionally, in one possible implementation, the processing unit 602 is specifically used to filter out the form content area from the electronic form image to obtain the processing area;

[0107] The processing unit 602 is specifically used to obtain the filtering rules corresponding to the target platform, and the filtering rules include at least one of unit area size or edge distance;

[0108] The processing unit 602 is specifically used to perform region filtering on the processing area based on the filtering rules to obtain blank areas in the electronic waybill image.

[0109] Optionally, in one possible implementation, the processing unit 602 is specifically used to determine the business type identifier of the new content added to the waybill corresponding to the target platform;

[0110] The processing unit 602 is specifically used to obtain a preset type identifier similar to the business type identifier if the business type identifier indicates that the new content of the waybill is the first new type. The new content corresponding to the preset type identifier is the pre-training data of the target large model.

[0111] The processing unit 602 is specifically used to configure target prompt words based on the blank area, the new content added to the waybill corresponding to the target platform, and the preset type identifier.

[0112] The processing unit 602 is specifically used to input the target prompt word into the target large model in order to determine the fitting area of ​​the newly added content on the waybill in the blank area.

[0113] Optionally, in one possible implementation, the processing unit 602 is specifically used to determine the association dimension between the preset type identifier and the business type identifier;

[0114] The processing unit 602 is specifically used to perform retrieval enhancement based on the association dimension, so as to serve as the annotation information of the preset type identifier;

[0115] The processing unit 602 is specifically used to configure the target prompt words based on the blank area, the new content added to the waybill corresponding to the target platform, and the remarks information of the preset type identifier.

[0116] Optionally, in one possible implementation, the generation unit 603 is specifically used to determine the filling range corresponding to the adaptation region;

[0117] The generation unit 603 is specifically used to adjust the display parameters of the newly added content on the order based on the filling range, so as to obtain the adjusted content;

[0118] The generation unit 603 is specifically used to fill the adjustment content into the electronic waybill image according to the adaptation area to obtain the target electronic waybill.

[0119] Optionally, in one possible implementation, the generation unit 603 is specifically used to obtain the business scenario information corresponding to the newly added content on the waybill;

[0120] The generation unit 603 is specifically used to determine the display feature parameters of the business scenario information indication;

[0121] The generation unit 603 is specifically used to adjust the parameters of the newly added content of the order based on the filling range using the display feature parameters, so as to obtain the adjusted content.

[0122] Specifically, the acquisition unit, processing unit, and generation unit in this embodiment can correspond to physical components. For example, the processing unit and generation unit can be processing modules such as CPU, GPU, and FPGA. The specific physical component can be any component or combination of components with the above functions. The specific method depends on the actual scenario and is not limited here.

[0123] The aforementioned generation device acquires an electronic waybill image to be processed; then identifies the image content in the electronic waybill image to determine the content area; and performs image processing on the electronic waybill image based on the content area to obtain blank areas in the electronic waybill image; further, it inputs the blank areas and the corresponding new content for the target platform into a target large model to determine the fitting area of ​​the new content in the blank areas. This target large model is trained using the correspondence between new content and blank areas in different business platforms; then, it fills the electronic waybill image with the new content according to the fitting area to obtain the target electronic waybill. This target electronic waybill is used to guide the execution of business processes in the target platform, and the business processes are associated with the new content. This achieves an intelligent filling process for new content on electronic waybills. Through content detection, blank areas on the electronic waybill can be accurately identified, and then the large model analysis confirms the specific area that fits the new content, ensuring the rationality of the selected area. Moreover, this process requires no manual intervention, improving the efficiency and accuracy of adding information to electronic waybills.

[0124] Specific limitations regarding the electronic waybill generation device can be found in the above description of the electronic waybill generation method, and will not be repeated here. Each unit module in the aforementioned electronic waybill generation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0125] Another embodiment of this application also proposes a computing device, see [link to relevant documentation] Figure 7 As shown, an exemplary embodiment of this specification also provides a computing device, including: a memory and a processor, the memory storing a computer program, the processor executing the computer program to perform the steps in the method for generating an electronic waybill according to various embodiments of this specification described above.

[0126] The internal structure of the computing device can be as follows: Figure 7As shown, the computing device includes a processor, memory, network interface, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it follows the steps of the electronic waybill generation method according to various embodiments of this specification as described in the above embodiments.

[0127] The processor may include the main processor, as well as baseband chips, modems, etc.

[0128] The memory stores a program that executes the technical solution of this invention, and may also store an operating system and other critical business functions. Specifically, the program may include program code, which includes computer operation instructions. More specifically, the memory may include read-only memory (ROM), other types of static storage devices capable of storing static information and instructions, random access memory (RAM), other types of dynamic storage devices capable of storing information and instructions, disk storage, flash memory, etc.

[0129] The processor can be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, etc., or an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the program of the present invention. It can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0130] Input devices may include devices that receive data and information input by the user, such as keyboards, mice, cameras, scanners, light pens, voice input devices, touch screens, pedometers, or gravity sensors.

[0131] Output devices may include devices that allow information to be output to the user, such as displays, printers, speakers, etc.

[0132] The communication interface may include any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), etc.

[0133] The processor executes the program stored in the memory and calls other devices, which can be used to implement the various steps of any of the electronic waybill generation methods provided in the above embodiments of this application.

[0134] The computing device may also include a display component and a voice component. The display component may be a liquid crystal display screen or an e-ink display screen. The input device of the computing device may be a touch layer covering the display component, or a button, trackball or touchpad set on the casing of the computing device, or an external keyboard, touchpad or mouse, etc.

[0135] Those skilled in the art will understand that Figure 7 The structures shown are merely block diagrams of some structures related to the solutions in this specification and do not constitute a limitation on the computing devices on which the solutions in this specification are applied. Specific computing devices may include more or fewer components than those shown in the figures, or combine certain components, or have different component arrangements.

[0136] In addition to the methods and devices described above, the method for generating electronic waybills provided in the embodiments of this specification can also be a computer program product, which includes a computer program that, when run by a processor, causes the processor to perform the steps in the electronic waybill generation method according to various embodiments of this specification as described in the "Exemplary Methods" section above.

[0137] The computer program product described herein can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments described herein. These programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0138] Furthermore, embodiments of this specification also provide a computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor of the steps in the electronic waybill generation method according to various embodiments of this specification as described in the "Exemplary Methods" section above.

[0139] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this specification can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0140] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0141] The embodiments described above are merely illustrative of several implementation methods outlined in this specification. While the descriptions are specific and detailed, they should not be construed as limiting the scope of the solutions provided in this specification. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this specification, and these all fall within the scope of protection of this specification. Therefore, the scope of protection for this patent should be determined by the appended claims.

Claims

1. A method for generating electronic waybills, characterized in that, include: Acquire the image of the electronic waybill to be processed; The image content in the electronic waybill image is identified to determine the waybill content area; Image processing is performed on the electronic waybill image based on the content area of ​​the waybill to obtain the blank area in the electronic waybill image; The blank area and the new label content corresponding to the target platform are input into the target large model to determine the matching area of ​​the new label content in the blank area. The target large model is trained using the correspondence between the new content and the blank area in different business platforms. The new content of the waybill is filled into the electronic waybill image according to the adaptation region to obtain the target electronic waybill. The target electronic waybill is used to guide the execution of business processes in the target platform, and the business processes are associated with the new content of the waybill.

2. The method according to claim 1, characterized in that, The step of identifying the image content in the electronic waybill image to determine the waybill content area includes: The electronic waybill image is subjected to noise reduction processing to obtain a noise-reduced image. The electronic waybill images come from different business platforms, and the layout information of the electronic waybills corresponding to different business platforms is different. Based on the denoised image, determine the image gradient information corresponding to the electronic faceplate image; Edge recognition is performed based on image gradient information to determine the content edge information corresponding to the image content in the electronic waybill image; The content area of ​​the shipping label is determined by the content edge information.

3. The method according to claim 1, characterized in that, The step of processing the electronic waybill image based on the content area of ​​the waybill to obtain the blank area in the electronic waybill image includes: The content area of ​​the waybill is filtered out from the electronic waybill image to obtain the processing area; Obtain the filtering rules corresponding to the target platform, wherein the filtering rules include at least one of unit area size or edge distance; Based on the filtering rules, the processing area is filtered to obtain the blank area in the electronic waybill image.

4. The method according to claim 1, characterized in that, The step of inputting the blank area and the corresponding new label content of the target platform into the target large model to determine the adaptation area of ​​the new label content in the blank area includes: Determine the business type identifier for the new content added to the waybill corresponding to the target platform; If the business type identifier indicates that the new content on the waybill is a new type for the first time, then a preset type identifier similar to the business type identifier is obtained, and the new content corresponding to the preset type identifier is the pre-training data of the target large model; Configure target prompt words based on the blank area, the new content added to the waybill corresponding to the target platform, and the preset type identifier; The target prompt is input into the target large model to determine the fitting area of ​​the newly added content on the waybill in the blank area.

5. The method according to claim 4, characterized in that, The configuration of target prompt words based on the blank area, the new content added to the waybill corresponding to the target platform, and the preset type identifier includes: Determine the association dimension between the preset type identifier and the business type identifier; The retrieval is enhanced based on the aforementioned association dimensions, serving as a note information for the preset type identifier; Configure the target prompt words based on the blank area, the new content added to the waybill corresponding to the target platform, and the remarks information of the preset type identifier.

6. The method according to claim 1, characterized in that, The step of filling the electronic waybill image with the new content of the waybill according to the adaptation region to obtain the target electronic waybill includes: Determine the filling range corresponding to the adaptation area; Based on the filled range, the display parameters of the newly added content on the order form are adjusted to obtain the adjusted content; The adjustment content is filled into the electronic waybill image according to the adaptation area to obtain the target electronic waybill.

7. The method according to claim 6, characterized in that, The adjustment of display parameters based on the filled range for newly added content on the order form to obtain the adjusted content includes: Obtain the business scenario information corresponding to the newly added content on the waybill; Determine the display feature parameters of the business scenario information indication; Based on the filling range, the parameters of the newly added content on the order are adjusted using the display feature parameters to obtain the adjusted content.

8. An apparatus for generating electronic waybills, characterized in that, include: The acquisition unit is used to acquire the electronic waybill image to be processed; The processing unit is used to identify the image content in the electronic waybill image to determine the waybill content area; The processing unit is further configured to perform image processing on the electronic waybill image based on the content area of ​​the waybill, so as to obtain a blank area in the electronic waybill image; The processing unit is further configured to input the blank area and the new content of the waybill corresponding to the target platform into the target large model to determine the matching area of ​​the new content of the waybill in the blank area. The target large model is trained using the correspondence between the new content and the blank area in different business platforms. The generation unit is used to fill the new content of the waybill into the electronic waybill image according to the adaptation region to obtain a target electronic waybill. The target electronic waybill is used to guide the execution of business processes in the target platform, and the business processes are associated with the new content of the waybill.

9. A computing device, characterized in that, The device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the electronic waybill generation method according to any one of claims 1 to 7.

10. A computer program product, characterized in that, include: A computer program, when executed by a processor, implements the method for generating electronic waybills according to any one of claims 1 to 7.

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