Commodity publishing method and system based on picture batch processing

Abstract

The invention discloses a commodity publishing method and system based on picture batch processing, and the method comprises the steps: selecting a target commodity option in a commodity collection page in response to a commodity selection instruction; obtaining commodity data corresponding to the target commodity option, and loading and generating a plurality of to-be-detected pictures on the picture editing page; a work queue is generated based on the picture editing page, the to-be-detected picture is put into the work queue to execute detection operation, and the task processing number of the work queue corresponds to the browser request number; generating a detection result on the picture editing page; in response to the processing instruction, executing an automatic processing operation on the commodity picture with the picture problem based on the automatic processing suggestion to obtain a target picture; and uploading the target picture to an e-commerce platform, and executing a commodity release operation based on the e-commerce platform. According to the method, batch detection operation is performed on the commodity pictures, picture modification convenience and respect of user willingness are considered, the commodity release failure probability is reduced, and the commodity release efficiency is greatly improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a commodity publishing method based on batch processing of images, and a corresponding system. Background Art

[0002] The e-commerce ERP system can be deeply connected with the e-commerce platform to help domestic small and medium-sized e-commerce users to uniformly manage their overseas stores, so that one operator can manage hundreds of e-commerce stores at the same time, greatly improving the efficiency of store operations. The functional modules of the existing commercialized e-commerce ERP systems are still in the stage of gradual functional update and improvement. The functional algorithms and rules formulated by various software companies when developing their own e-commerce ERP systems are basically different. As user needs change, each functional module will continue to develop new versions to be compatible with more usage scenarios.

[0003] In daily e-commerce activities, existing ERP products have the function of batch publishing products. Since the product publishing rules of various e-commerce platforms are different, the product images automatically collected by the e-commerce ERP system or uploaded by users are difficult to meet the requirements of the e-commerce platform, such as the wrong image size or invalid image link, which leads to multiple failures in the product publishing process, seriously affecting the efficiency of users in publishing products. On this basis, before the product is released, it takes a long time for the e-commerce ERP system to perform batch detection on the product images, causing users to wait for a long time. Therefore, the current e-commerce ERP system does not provide a batch detection function for images; in addition, if users blindly modify the product images in batches without detection, it will also damage the display effect of the product images, which will seriously affect the sales of the products.

[0004] Other technical issues related to this application will be further described later. The above content is only used to assist in understanding the technical solution of this application, and does not mean that all of the above content is prior art. Summary of the invention

[0005] The main purpose of the present invention is to provide a product release method and system based on batch processing of images, which can quickly perform batch detection operations on product images before the products are released. On the basis of ensuring the display effect of product images, the probability of product release failure is reduced, and the efficiency of product release is greatly improved.

[0006] To achieve the above purpose, the present application proposes a product publishing method based on batch processing of images, which is used in a product publishing module of an e-commerce ERP system or an e-commerce management system. The method comprises: Step S1: In response to a product selection instruction, a target product option for executing a product release operation is selected on a product collection page; Step S2: Acquire product data corresponding to the target product option, and load and generate multiple pictures to be detected on the picture editing page based on the product data; Step S3: Generate a work queue based on the picture editing page, and put the picture to be detected into the work queue to perform a detection operation, and the number of tasks processed in the work queue corresponds to the number of browser requests; Step S4: generating a detection result on the image editing page, wherein the detection result includes image problems corresponding to the detected product images and automatic processing suggestions corresponding to the image problems; Step S5: in response to the processing instruction, based on the automatic processing suggestion, an automatic processing operation is performed on the product image with the image problem to obtain a target image; Step S6: Upload the target image to the e-commerce platform, and perform a product publishing operation based on the e-commerce platform.

[0007] Other features and technical effects of this application are described in the following part of the specification. The technical problem solving ideas and related product design solutions of this application are: In daily e-commerce activities, users need to comply with the product publishing rules of the e-commerce platform when publishing various product images. For example, each e-commerce platform has different requirements for product image file size, image size, image type, and number of images. It is difficult for users to confirm which product images do not comply with the product publishing rules among a large number of product images, and modify the product images before executing the product publishing operation, resulting in product publishing failure due to non-compliant product images.

[0008] Among them, since the e-commerce platform's verification process for product images is to verify each image in turn based on a single issue, and immediately report an error when the image is found to be non-compliant, it is determined that the product release has failed; that is, if multiple product images of the same product are non-compliant or a single product image has multiple non-compliant items during the release process, the e-commerce platform will report errors multiple times, and users will need to modify the product images repeatedly, which will seriously affect the efficiency of users releasing products.

[0009] In addition, if the user blindly modifies the product images in batches in order to improve the success rate of product release before executing the product release operation, the display effect of the product images may be damaged, and the success rate of product release cannot be guaranteed.

[0010] On this basis, the applicant found that before uploading product images to the e-commerce platform to execute the product release operation, batch testing of product images based on the e-commerce ERP system and modifying the product images in advance based on the test results can greatly improve the verification pass rate of product images on the e-commerce platform, thereby improving product release efficiency.

[0011] The reason is that by performing batch detection on product images based on the e-commerce ERP system, multiple problems in parallel can be checked on product images. That is, multiple problems in one product image and problems in multiple product images can be displayed at one time in the form of detection results, allowing users to perform batch modifications on multiple product images, thereby avoiding multiple errors on the e-commerce platform.

[0012] Furthermore, the applicant proposed that the detection of product images based on the image editing page, that is, based on the front-end page of the browser, can effectively shorten the time consumed by performing detection operations on product images. It can be understood that based on the loading and generation of product images on the image editing page, the file size, dimensions, type and other attributes of the product images can be directly detected. The process is simple and takes less time. However, if the detection operation is performed on the product image based on the background system, it is necessary to perform a parsing and reading operation on the image file before the detection operation can be performed. This process requires uploading the image file to the database or server to achieve. The process is complicated and time-consuming, which seriously affects the efficiency of users publishing products and also reduces the user's operating experience.

[0013] In order to ensure that the e-commerce ERP system can complete the detection operation of the images to be detected at a high rate and avoid the browser from freezing or crashing due to too many tasks, the e-commerce ERP system of this application sets up a work queue, and determines the number of images involved in the batch detection operation of the images to be detected by the number of tasks processed by the work queue. The number of tasks processed by the work queue is determined according to the number of task requests that the browser can process simultaneously, which is usually 6-8.

[0014] In addition, since the e-commerce ERP system can only edit and modify product images based on relatively simple processing logic, in order to avoid the automatic processing operations causing significant damage to the display effect of the product images, the e-commerce ERP system will display the detection results on the image editing page, and will only perform automatic processing operations on the product images based on the detection results after obtaining user confirmation, thereby taking into account the convenience of image modification and respecting user wishes at the same time.

[0015] In this way, the product release method based on batch image processing provided by this application can quickly perform batch detection operations on product images before product release, while taking into account the convenience of image modification and respecting user wishes. On the basis of ensuring the display effect of product images, it reduces the probability of product release failure and greatly improves the efficiency of product release.

[0016] The present application also provides a system, which is an e-commerce ERP system or an e-commerce management system, and the system can execute the operating instructions of each method step of the present application.

[0017] The present application also provides a server, which includes a memory and a processor. The system in the present application is stored in the memory, and the processor can run the operating instructions of each method step of the present application.

[0018] The present application also provides a computer device, which includes a memory and a processor. The system in the present application is stored in the memory, and the processor can execute the operating instructions of each method step in the present application.

[0019] refer to Figure 1 The e-commerce ERP system of this application includes one or more of the functional modules such as product release module, sales module, procurement module, logistics module, warehouse module, financial module, advertising module, customer service module, tool module, promotion management module, authority management module and data analysis module. The functional modules can be integrated with each other or exist independently, and one functional module can be a submodule of another functional module. The users of the ERP system of this application can also be called store managers, sellers, operators, operation personnel, etc., and their identities are not strictly limited unless otherwise stated. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings are used to provide further understanding of the present application and do not constitute a limitation of the present application; the contents shown in the accompanying drawings may be real data of the embodiments and belong to the protection scope of the present application.

[0021] Figure 1 This is a schematic diagram of the functional modules of an e-commerce ERP system in one embodiment of the present application.

[0022] Figure 2 This is a schematic diagram of the principle of the product release process in one embodiment of the present application.

[0023] Figure 3 This is a flow chart of a method for publishing products based on batch processing of images in one embodiment of the present application.

[0024] Figure 4 This is a schematic diagram of the interface of the picture editing page in one embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solution and advantages of this application more clear, the following is a further detailed description of the embodiments of this application through specific implementation methods combined with the accompanying drawings. It should be understood that the specific embodiments described here are only used to explain this application and are not used to limit this application.

[0026] Figure 2 The schematic diagram of the principle of the commodity publishing process based on batch processing of pictures in one embodiment of the present application is shown. Figure 2As shown, the e-commerce ERP system generates the corresponding images to be detected on the image editing page based on the product data stored in the background system, and then performs batch detection operations on the images to be detected on the image editing page according to the platform verification rules and preset detection rules, and displays the detection results on the image editing page. When the user triggers the processing instruction to confirm the automatic processing suggestion, the e-commerce ERP system performs automatic processing operations on the product images with image problems according to the automatic processing suggestions, and obtains the target image for publishing the product. Finally, the e-commerce ERP system uploads the target image to the e-commerce platform to perform the product publishing operation based on the target image on the e-commerce platform.

[0027] Figure 3 A method for publishing products based on batch processing of images in one embodiment of the present application is shown, and the method mainly includes the following steps S1 to S6.

[0028] Step S1: In response to a product selection instruction, a target product option for executing a product release operation is selected on a product collection page; Step S2: Acquire product data corresponding to the target product option, and load and generate multiple pictures to be detected on the picture editing page based on the product data; Step S3: Generate a work queue based on the picture editing page, and put the picture to be detected into the work queue to perform a detection operation, and the number of tasks processed in the work queue corresponds to the number of browser requests; Step S4: generating a detection result on the image editing page, wherein the detection result includes image problems corresponding to the detected product images and automatic processing suggestions corresponding to the image problems; Step S5: in response to the processing instruction, based on the automatic processing suggestion, an automatic processing operation is performed on the product image with the image problem to obtain a target image; Step S6: Upload the target image to the e-commerce platform, and perform a product publishing operation based on the e-commerce platform.

[0029] In this way, the product release method based on batch image processing provided by this application can quickly perform batch detection operations on product images before product release, while taking into account the convenience of image modification and respecting user wishes. On the basis of ensuring the display effect of product images, it reduces the probability of product release failure and greatly improves the efficiency of product release.

[0030] The following is a detailed description of each method step in the product publishing method based on image batch processing.

[0031] Step S1: In response to a product selection instruction, a target product option for executing a product release operation is selected on a product collection page.

[0032] Specifically, the user interacts with the product collection page, and the product collection page selects a target product option for executing the product release operation from a plurality of product options in response to a product selection instruction triggered by the user.

[0033] Step S2: Obtain product data corresponding to the target product option, and load and generate multiple images to be detected on the image editing page based on the product data.

[0034] Specifically, the e-commerce ERP system obtains product data corresponding to the target product option, and the product data can be uploaded by the user or obtained based on the system database, and loads and generates multiple pictures to be detected on the picture editing page for the product data.

[0035] Step S3: Generate a work queue based on the picture editing page, and put the picture to be detected into the work queue to perform a detection operation, and the number of tasks processed in the work queue corresponds to the number of browser requests.

[0036] Specifically, in order to ensure that the e-commerce ERP system can complete the detection operation of the to-be-detected images at a high rate and avoid the browser from freezing or crashing due to too many tasks, the e-commerce ERP system of this embodiment is set to generate a work queue, and the number of images involved in the batch detection operation of the to-be-detected images is determined by the number of tasks processed by the work queue. The number of tasks processed by the work queue is determined according to the number of task requests that the browser can process simultaneously, and the number of task requests is usually 6-8.

[0037] Step S4: generating a detection result on the image editing page, wherein the detection result includes image problems corresponding to the detected product image and automatic processing suggestions corresponding to the image problems.

[0038] Specifically, after the e-commerce ERP system performs the inspection operation on the image to be inspected, it will not directly process the product images with image problems, but will display the inspection results on the image editing page; the inspection results are presented in a tabular form, indicating the image problems corresponding to the inspected product images, as well as automatic processing suggestions corresponding to the image problems.

[0039] Step S5: In response to the processing instruction, an automatic processing operation is performed on the product image with the image problem based on the automatic processing suggestion to obtain a target image.

[0040] Specifically, the user interacts with the image editing page, triggering a processing instruction; the e-commerce ERP system responds to the processing instruction and performs automatic processing operations on the product images with image problems according to the automatic processing suggestions corresponding to the processing instructions, such as adjusting the size of the product images, deleting duplicate uploaded product images, replacing invalid image links, etc., thereby obtaining the target image for uploading to the e-commerce platform.

[0041] Step S6: Upload the target image to the e-commerce platform, and perform a product publishing operation based on the e-commerce platform.

[0042] Specifically, the e-commerce ERP system uploads the processed target image to the e-commerce platform. Since the target image has been tested and modified in advance, the verification pass rate of the target image on the e-commerce platform is greatly improved, allowing users to successfully perform product release operations on the e-commerce platform.

[0043] Furthermore, in one embodiment, step S3 of placing the to-be-detected picture into the work queue to perform the detection operation includes the following steps S3.1 and 3.2.

[0044] Step S3.1: putting the image to be detected into the work queue; Step S3.2: Perform detection operations on the images to be detected in the work queue based on platform verification rules and preset detection rules, wherein the platform verification rules represent e-commerce platform standards that have a corresponding relationship with the e-commerce platform, and the preset detection rules represent conventional standards that do not have a corresponding relationship with the e-commerce platform.

[0045] Specifically, the detection operation for product images is performed based on the platform verification rules and preset detection rules. The platform verification rules correspond to the e-commerce platform that currently publishes the product. For example, each e-commerce platform has different requirements for the file size, dimensions, type, and quantity of product images. The e-commerce ERP system sets the corresponding platform verification rules according to the regulations of the e-commerce platform and performs detection operations on the product images to determine whether the product images comply with the regulations of the e-commerce platform that currently publishes the product.

[0046] In addition, the preset detection rules are unrelated to the e-commerce platform on which the product is currently published. They are used to perform routine detection on product images, including detecting whether the product images uploaded by users are duplicated, whether the product image links are invalid, etc., as well as setting other detection rules that meet current needs.

[0047] Further, based on the above embodiment, after step S3.2, the method further includes the following step S3.3.

[0048] Step S3.3: Monitor the task duration of the detection operation performed by the to-be-detected pictures in the working queue. If the task duration reaches a first preset threshold, remove the to-be-detected pictures in the working queue and put other to-be-detected pictures that have not performed the detection operation into the working queue.

[0049] Specifically, when the e-commerce ERP system performs a detection operation on the image to be detected in the work queue, the detection operation is timed. If the timing reaches the first preset threshold, and the image to be detected in the work queue has not completed the detection operation, the image to be detected is removed from the work queue, and other images to be detected that have not performed the detection operation are replaced and put into the work queue. It can be understood that some product images may have problems such as image files being too large and difficult to detect. The e-commerce ERP system in this example sets a time limit on the execution process of the detection operation, thereby ensuring that multiple images to be detected can complete the detection operation as a whole in a short time, avoiding users waiting too long for the detection operation of individual product images, thereby affecting the user experience.

[0050] Furthermore, in one embodiment, step S2 of generating multiple images to be detected by loading on the image editing page based on the product data includes the following step S2.1.

[0051] Step S2.1: Based on the product data, multiple pictures to be detected are loaded and generated on the picture editing page, wherein when the loading time of the pictures to be detected reaches a second preset threshold, the loading and generation process of the pictures to be detected is terminated and a corresponding timeout record is generated.

[0052] Specifically, if an abnormality occurs during the loading process of the image to be detected on the image editing page, such as an invalid image link, an image file that is too large to load and generate, an image data parsing error, etc., resulting in a long loading time for the image to be detected, reaching a second preset threshold (determined based on user feedback or historical data, using an empirical value of 10s-20s), the e-commerce ERP system terminates the loading and generation process of the image to be detected, and generates a corresponding timeout record for user reference and processing.

[0053] As a feasible implementation method, the user interacts with the image editing page to trigger an instruction, and the e-commerce ERP system restarts the loading process of the image to be detected that has been suspended; during the restarted loading process, the limit on the loading time of the image to be detected will be relatively extended. For example, when the loading time reaches 25s-30s, the loading generation process of the image to be detected will be suspended again.

[0054] Furthermore, in one embodiment, step S2 of generating multiple images to be detected by loading on the image editing page based on the product data includes the following steps S2.2 and S2.3.

[0055] Step S2.2: Based on the commodity data cached by the browser, multiple images to be detected are loaded and generated on the image editing page; or, Step S2.3: Analyze the product data, and load and generate multiple images to be detected on the image editing page based on the analysis results.

[0056] In this embodiment, the e-commerce ERP system pre-caches the image data in the product data through the image editing page of the browser, and when the user selects a product image to perform a detection operation, or the user performs a product publishing operation to automatically trigger the product image detection process, the image editing page can quickly load and generate some images to be detected. In addition, the e-commerce ERP system parses the product data stored in the system database and loads and generates multiple images to be detected on the image editing page.

[0057] Furthermore, in one embodiment, the picture editing page includes a first interactive area and a second interactive area, and the method further includes the following steps S6.1 to S6.4.

[0058] Step S6.1: Based on the first interactive area, the picture editing options are displayed, the picture editing options including a picture type option, a picture problem option, a modification method option and a modification content option, the picture type option is used to filter various types of product pictures corresponding to the target product option, the picture problem option is used to determine the picture problem type for performing a detection operation, the modification method option is used to determine the operation method for performing batch editing on the product pictures, the modification content option is used to determine the product pictures corresponding to the target product option for performing a batch editing operation, and the picture type option is associated with the modification method option; and, Step S6.2: displaying a target product option and a product image corresponding to the target product option based on the second interactive area; Step S6.3: In response to the product editing instruction, determining a batch editing mode based on the first interaction area, and determining target product images for performing a batch editing operation based on the second interaction area; Step S6.4: Edit the target product images based on the batch editing method.

[0059] Specifically, when the e-commerce ERP system performs a batch detection operation on product images, it jumps from the product collection page to the product editing page, and the user can perform a batch editing operation on the product images of multiple product options on the product editing page.

[0060] In one embodiment, if Figure 4 As shown, the first interactive area is located in the upper area of ​​the picture editing page, and is used to display picture type options, picture problem options, modification method options, and modification content options; the user determines the batch editing method for the product pictures through interactive operations with the first interactive area.

[0061] The second interactive area is located in the lower area of ​​the picture editing page, listing various product options and multiple product pictures corresponding to the product options; the user determines the product pictures to be batch edited through interactive operations with the second interactive area.

[0062] After the user performs interaction operations with the first interaction area and the second interaction area respectively, the e-commerce ERP system performs a batch editing operation on the product images in response to the interaction operations.

[0063] Furthermore, in one embodiment, the method further includes the following step S6.5.

[0064] Step S6.5: Setting a data structure corresponding to the type of the image to be detected, wherein the data structure is used to perform caching and detection operations on the image to be detected.

[0065] Specifically, since the product release process involves various types of product images, the content of product images includes product images, marketing images, color images and description images, and the types of product images include JPG and PNG, etc., and each type of product image has different type restrictions. This application sets a corresponding data structure according to the image type, and caches and detects each product image based on the data structure, thereby ensuring that the data structure is the most robust and stable, and the detection data has a high accuracy.

[0066] Further, in one embodiment, step S5 includes the following step S5.1.

[0067] Step S5.1: In response to the processing instruction, a cropping operation is performed on the product image with the image problem or a blank block is added to obtain a target image with adjusted size.

[0068] Specifically, in this embodiment, the initial size of the product image does not comply with the regulations of the e-commerce platform (for example, the initial size of the product image is 4:3, while the e-commerce platform stipulates that the image size is 5:4). The e-commerce ERP system provides automatic processing suggestions for the image size problem, including cropping the original product image, or adding blank blocks to the corresponding sides of the original product image, so as to achieve the purpose of resizing the product image and obtain a target image that complies with the regulations of the e-commerce platform.

[0069] Furthermore, in one embodiment, before step S5, the method further includes the following step S4.1.

[0070] Step S4.1: calling the detection interface of the e-commerce platform, and performing a detection operation on the image content of the image to be detected based on the detection interface.

[0071] Specifically, in this embodiment, the e-commerce ERP system only detects the format or form of the product image (such as file size, dimensions, quantity, image type, image link validity, etc.), but does not detect the image content of the product image, so as to shorten the time of performing the detection operation. However, some e-commerce platforms have special requirements for product images, such as stipulating that product images cannot have watermarks, or that the image clarity needs to meet specific standards; and the e-commerce platform provides a corresponding detection function to perform a detection function on the product image regarding the image content. On this basis, the e-commerce ERP system calls the detection interface with the image content detection function of the e-commerce platform, performs the detection operation on the product image, and generates the detection result of the image content of the product image.

[0072] Further, in one embodiment, step S5 includes the following steps S5.2 to S5.5.

[0073] Step S5.2: In response to the processing instruction, adjusting the formal parameters of the product image with the image problem based on the automatic processing suggestion to obtain a first processed image, wherein the formal parameters include one or more of the image file size, the image dimension, and the image type; Step S5.3: Analyze the quality and features of the first processed image, and adjust the quality parameters of the first processed image according to the analysis results to obtain a second processed image, wherein the quality parameters include one or more of image brightness, contrast, and sharpness; Step S5.4: identifying the main element of the second processed image, and determining the image style corresponding to the main element in the historical commodity data of the current store; Step S5.5: Process the second processed image based on the image style to obtain a target image.

[0074] Specifically, the product images used in product releases will greatly affect customers' cognition and perception of the products, and thus affect product sales; therefore, ensuring the quality of product images is the main content of e-commerce operations.

[0075] The applicant found that the current e-commerce ERP system only has the ability to perform detection operations on a single product image, or edit and modify batches of product images, thereby ensuring that the product images meet the regulations of the e-commerce platform with low efficiency, and failing to further ensure the content quality and display effect of the product images. Especially in the case of the distribution model, based on operating costs and product release efficiency considerations, it is difficult for sellers to use a large number of product images that have been carefully edited by artists during the product release process, which seriously affects product sales and increases the difficulty for sellers to discover products with hot-selling potential in the distribution model.

[0076] The applicant proposed that, based on the above-mentioned embodiments, the e-commerce ERP system, after adjusting the formal parameters of the product images according to the processing instructions triggered by the user, further performs automatic adjustment operations on the quality parameters of the product images, which can efficiently and conveniently improve the display effect of the product images and significantly increase product sales.

[0077] Specifically, when the e-commerce ERP system performs a detection operation on the image to be detected, it will simultaneously detect the formal parameters, quality parameters and image style of the product image, and generate relevant detection results. Among them, if the e-commerce ERP system detects that the quality parameters of the image to be detected (including one or more of the image brightness, contrast, sharpness, etc.) are lower than the preset standard, for example, the quality parameter is lower than the threshold set by the user, or lower than the image template pre-selected by the user, or lower than the parameters of similar product images displayed by big data, etc., then the e-commerce ERP system will generate relevant automatic processing suggestions for users to choose, so that users can quickly, efficiently and conveniently improve the display quality of product images.

[0078] Alternatively, the e-commerce ERP system determines whether the store's current operating mode is a distribution mode or a boutique mode based on the store's operating conditions; if the e-commerce ERP system determines that the store is currently using a distribution mode, it determines that the product images used to publish the products need to be optimized for display effects, and then adjusts the quality parameters of the product images. For example, when the e-commerce ERP system detects that the store has a large number of products on the shelves (such as more than 100 products), or detects that there are many types of products (such as more than 30 types of products), or the products on the shelves change frequently (such as a variety of products with only a small amount of inventory on the shelves, and are removed from the shelves in a short period of time), the e-commerce ERP system automatically determines that the store is currently using a distribution mode, and automatically adjusts the quality parameters of the product images in the distribution mode.

[0079] On this basis, the applicant also found that for the same store, if product pictures with the same picture style are used to publish products, the product pictures of the entire store can be visually coherent, the store's recognition can be improved, and thus the user stickiness of the store can be increased.

[0080] Specifically, the e-commerce ERP system determines the target products to be published by the multiple product images by identifying the main elements of the product images (i.e., objects that account for a relatively high proportion in the image, such as objects that account for 70% or more of the image; and common elements between multiple product images). Then, the e-commerce ERP system compares the target product with the historical product data of the current store to determine the image style used by the current store when publishing the product image corresponding to the target product; the image style includes simple style, fashionable style, retro style and other style types. Finally, the e-commerce ERP system applies the above image style to the current product image, which is ultimately used to upload the target image to the e-commerce platform and perform the product publishing operation.

[0081] As a feasible implementation method, the e-commerce ERP system can also call the AI ​​system or use big data analysis to determine the image style that corresponds to the target product and has high traffic, and apply the image style to the product image.

[0082] It should be noted that the above-mentioned process of applying the picture style to the product image may be to apply a specific image filter to the product image, or to delete or modify some areas or elements of the product image, etc. The process of adjusting the picture style of the product image is not specifically limited here.

[0083] In this way, after the e-commerce ERP system of this embodiment performs detection operations on product images and adjusts the formal parameters of product images to make the product images comply with the regulations of the e-commerce platform, it further adjusts the quality parameters and image style of the product images, optimizes the display effect of the product images under the premise of speed, efficiency and convenience, thereby greatly increasing product sales, helping sellers to discover products with hot-selling potential in the distribution mode, and improving e-commerce operation efficiency.

[0084] In addition, in a feasible embodiment, the e-commerce ERP system can provide a 3D simulated product display function based on multiple product images uploaded by users. For example, when users modify product images in batches, the e-commerce ERP system converts multiple two-dimensional product images in real time to achieve a simple 3D model preview effect, so that users can view the product display from different angles.

[0085] In addition, users can directly adjust the image in the 3D preview interface, such as rotating, adding light and shadow effects, adjusting colors, etc. These adjustment operations will be automatically synchronized to the batch processing operation of the original product image.

[0086] In this way, the e-commerce ERP system of this embodiment realizes the 3D model preview effect based on multiple two-dimensional product pictures. The user can directly edit the picture on the 3D model preview interface, which enriches the interaction method between the user and the picture and improves the convenience of users batch editing pictures; and the user can perform batch editing operations of pictures with a global view of the product objects, which optimizes the operational experience of the picture editing process.

[0087] The above description is only a preferred embodiment of the present application, and does not limit the patent scope of the present application. All equivalent transformations made by using the contents of the present application specification and drawings under the inventive concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A commodity publishing method based on image batch processing, characterized in that: A commodity publishing module for an e-commerce ERP system or an e-commerce management system, the method comprising: Step S1: In response to a product selection instruction, a target product option for executing a product release operation is selected on a product collection page; Step S2: Acquire product data corresponding to the target product option, and load and generate multiple pictures to be detected on the picture editing page based on the product data; Step S3: Generate a work queue based on the picture editing page, and put the picture to be detected into the work queue to perform a detection operation, and the number of tasks processed in the work queue corresponds to the number of browser requests; Step S4: generating a detection result on the image editing page, wherein the detection result includes image problems corresponding to the detected product images and automatic processing suggestions corresponding to the image problems; Step S5: in response to the processing instruction, based on the automatic processing suggestion, an automatic processing operation is performed on the product image with the image problem to obtain a target image; Step S6: Upload the target image to the e-commerce platform, and perform a product publishing operation based on the e-commerce platform.

2. The method according to claim 1, characterized in that Step S3 of placing the image to be detected into the work queue to perform the detection operation includes: Step S3.1: putting the image to be detected into the work queue; Step S3.2: Perform detection operations on the images to be detected in the work queue based on platform verification rules and preset detection rules, wherein the platform verification rules represent e-commerce platform standards that have a corresponding relationship with the e-commerce platform, and the preset detection rules represent conventional standards that do not have a corresponding relationship with the e-commerce platform.

3. The method according to claim 2, characterized in that After step S3.2, the method further comprises: Step S3.3: Monitor the task duration of the detection operation performed by the to-be-detected pictures in the working queue. If the task duration reaches a first preset threshold, remove the to-be-detected pictures in the working queue and put other to-be-detected pictures that have not performed the detection operation into the working queue.

4. The method according to claim 1, characterized in that Step S2 generates multiple images to be detected by loading on the image editing page based on the product data, including: Step S2.1: Based on the product data, multiple pictures to be detected are loaded and generated on the picture editing page, wherein when the loading time of the pictures to be detected reaches a second preset threshold, the loading and generation process of the pictures to be detected is terminated and a corresponding timeout record is generated.

5. The method according to claim 1, characterized in that Step S2 generates multiple images to be detected by loading on the image editing page based on the product data, including: Step S2.2: Based on the product data cached by the browser, multiple images to be detected are loaded and generated on the image editing page; or, Step S2.3: Analyze the product data, and load and generate multiple images to be detected on the image editing page based on the analysis results.

6. The method according to claim 1, characterized in that The picture editing page includes a first interaction area and a second interaction area, and the method further includes: Step S6.1: Based on the first interactive area, the picture editing options are displayed, the picture editing options including a picture type option, a picture problem option, a modification method option and a modification content option, the picture type option is used to filter various types of product pictures corresponding to the target product option, the picture problem option is used to determine the picture problem type for performing a detection operation, the modification method option is used to determine the operation method for performing batch editing on the product pictures, the modification content option is used to determine the product pictures corresponding to the target product option for performing a batch editing operation, and the picture type option is associated with the modification method option; and, Step S6.2: displaying a target product option and a product image corresponding to the target product option based on the second interactive area; Step S6.3: In response to the product editing instruction, determining a batch editing mode based on the first interaction area, and determining target product images for performing a batch editing operation based on the second interaction area; Step S6.4: Edit the target product images based on the batch editing method.

7. The method according to claim 1, characterized in that Step S5 includes: Step S5.1: In response to the processing instruction, a cropping operation is performed on the product image with the image problem or a blank block is added to obtain a target image with adjusted size.

8. The method according to claim 1, characterized in that Before step S5, the method further includes: Step S4.1: calling the detection interface of the e-commerce platform, and performing a detection operation on the image content of the image to be detected based on the detection interface.

9. The method according to claim 1, characterized in that Step S5 includes: Step S5.2: In response to the processing instruction, adjusting the formal parameters of the product image with the image problem based on the automatic processing suggestion to obtain a first processed image, wherein the formal parameters include one or more of the image file size, the image dimension, and the image type; Step S5.3: Analyze the quality and features of the first processed image, and adjust the quality parameters of the first processed image according to the analysis results to obtain a second processed image, wherein the quality parameters include one or more of image brightness, contrast, and sharpness; Step S5.4: identifying the main element of the second processed image, and determining the image style corresponding to the main element in the historical commodity data of the current store; Step S5.5: Process the second processed image based on the image style to obtain a target image.

10. A product release system, characterized in that: The system is an e-commerce ERP system or an e-commerce management system, and the system is used to execute the operation instructions contained in the commodity publishing method based on batch processing of pictures as claimed in any one of claims 1 to 9.

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