Printing optimization method based on screen display printer and related device

Abstract

The embodiment of the present invention provides a printing optimization method based on a screen display printer and related devices, belonging to the field of printer technology. The method includes: receiving a target network selected by a target user and target connection information of the target network; connecting a target printer and a target network according to the target connection information; receiving a target printing request sent by a user terminal that is connected to the target network, and parsing the target printing request to obtain target printing content; analyzing the target printing content using a printing loss model to obtain image noise parameters; performing image processing on the target printing content according to the image noise parameters to obtain an initial printing image; performing loss analysis on the target printing content according to the initial printing image to obtain a target printing strategy; and obtaining a target printing result of the target printing content according to the target printing strategy. This method not only improves the efficiency of users in the printer network configuration process, but also optimizes the user's printing experience during the printing process.

Description

Technical Field

[0001] The present invention relates to the field of printer technology, and in particular to a printing optimization method based on a screen display printer and related devices. Background Art

[0002] At present, most Wi-Fi printers on the market use technologies such as mobile phone Bluetooth network configuration, AP mode, and WPS mode to help printers configure the network and connect to the printer for printing. However, network configuration methods such as AP mode, WPS mode, data cable connection, and driver installation are relatively complicated to use, difficult for users to get started, and prone to network configuration failure. Mobile phone application Bluetooth network configuration requires downloading the mobile phone application and connecting the printer to Bluetooth. When using the mobile phone application Bluetooth connection, due to the mobile phone system permission requirements, it is easy to give users a sense of infringement of user privacy, resulting in users being unable to conveniently configure the printer. In addition, Wi-Fi printers also have the problem that the print quality is difficult to effectively evaluate before printing. Users can only observe the results after printing is completed. This means that if the print quality does not meet the standard, the user needs to reprint, which not only causes a waste of paper and ink, but also increases the user's economic burden, resulting in a poor user printing experience. Therefore, a printing optimization method is urgently needed to solve at least one of the above technical problems. Summary of the invention

[0003] The main purpose of the embodiments of the present invention is to provide a printing optimization method based on a screen display printer and related devices, aiming to solve the problem in the related technology that users cannot easily configure the printer network and the printing quality is difficult to effectively evaluate before printing, resulting in a poor user printing experience.

[0004] In a first aspect, an embodiment of the present invention provides a printing optimization method based on a screen display printer, comprising:

[0005] Obtaining an initial network corresponding to a target printer in a target area, and displaying the initial network on a target screen corresponding to the target printer;

[0006] receiving, from the target user, a target network corresponding to the initial network and target connection information corresponding to the target network selected in the target screen;

[0007] Establishing a communication connection between the target printer and the target network according to the target connection information;

[0008] Receiving a target printing request sent by a user terminal connected to the target network for communication, and parsing the target printing request to obtain corresponding target printing content;

[0009] Performing data analysis on the target print content using a print loss model to obtain image noise parameters corresponding to the target print content;

[0010] Performing image processing on the target printing content according to the image noise parameter to obtain an initial printing image corresponding to the target printing content after printing, wherein the initial printing image is an effect image of the target printing content presented on the printing paper after the target printing content is simulated by the image noise parameter;

[0011] Performing a printing loss analysis on the target printing content according to the initial printing image to obtain a target printing strategy corresponding to the target printing content;

[0012] A target printing result corresponding to the target printing content is obtained according to the target printing strategy.

[0013] In some optional embodiments, performing a printing loss analysis on the target printing content according to the initial printing image to obtain a target printing strategy corresponding to the target printing content includes:

[0014] Performing quality analysis on the initial print image to obtain a target print quality corresponding to the target print content;

[0015] The target printing strategy corresponding to the target printing content is determined according to the target printing quality.

[0016] In some optional embodiments, the step of performing data analysis on the target print content using a print loss model to obtain image noise parameters corresponding to the target print content includes:

[0017] Performing image extraction on the target printing content using the image extraction layer of the printing loss model to obtain a first to-be-printed image corresponding to the target printing content;

[0018] Performing pixel analysis on the first image to be printed using the matrix generation layer of the printing loss model to obtain a weighted correlation matrix corresponding to the first image to be printed;

[0019] Using the texture analysis layer of the printing loss model to perform texture feature analysis using the weighted correlation matrix and the known correlation matrix, to obtain the structural similarity between the first image to be printed and the second image to be printed corresponding to the known correlation matrix;

[0020] Obtaining a third image to be printed corresponding to the first image to be printed from the second image to be printed according to the structural similarity using the image determination layer of the printing loss model;

[0021] The image noise parameter corresponding to the first image to be printed is determined according to the third image to be printed and a known printed image corresponding to the third image to be printed by using the noise generation layer of the printing loss model.

[0022] In some optional embodiments, the performing quality analysis on the initial print image to obtain the target print quality corresponding to the target print content includes:

[0023] Performing image extraction on the initial print image to obtain a corresponding first print image, and obtaining a target description text corresponding to the first print image from the target print content;

[0024] Perform feature matching on the target description text and the first printed image to obtain a first image feature corresponding to the target description text in the first printed image;

[0025] Performing global feature extraction on the first printed image to obtain a second image feature corresponding to the first printed image;

[0026] fusing the first image feature and the second image feature to obtain a target image feature corresponding to the first printed image;

[0027] Performing text representation on the target description text to obtain target text features corresponding to the target description text;

[0028] The degree of correlation between the target image feature and the target text feature is calculated, and the target print quality corresponding to the target print content is determined according to the degree of correlation.

[0029] In some optional embodiments, the fusing the first image feature and the second image feature to obtain a target image feature corresponding to the first printed image includes:

[0030] Semantically decomposing the target description text to obtain multiple sub-description texts;

[0031] Performing vector representation on the sub-description text using a text representation model to obtain a text representation vector corresponding to the sub-description text;

[0032] Calculating a first distance between the text representation vector and the first image feature and calculating a second distance between the text representation vector and the second image feature;

[0033] fusing the first image feature and the second image feature according to the first distance and the second distance to obtain an initial image feature corresponding to the sub-description text;

[0034] Determining the importance of the sub-description text in the target description text, and determining the target weight corresponding to the sub-description text according to the importance;

[0035] fusing the initial image features according to the target weights to obtain the target image features corresponding to the first printed image;

[0036] The initial image features are obtained according to the following formula:

[0037]

[0038] in, represents the initial image feature corresponding to the i-th sub-description text, M represents the number of features corresponding to the first image feature, and N represents the number of features corresponding to the second image feature. represents the first distance between the i-th text representation vector and the m-th first image feature, represents the second distance between the i-th text representation vector and the n-th second image feature, e represents a natural constant, represents the adjustment parameter, represents the mth first image feature, represents the nth second image feature, represents the first distance between the i-th text representation vector and the x-th first image feature, represents the second distance between the i-th text representation vector and the y-th second image feature.

[0039] In some optional embodiments, obtaining a target printing result corresponding to the target printing content according to the target printing strategy includes:

[0040] Adjusting the initial printing image according to the target printing strategy to obtain a target printing image;

[0041] Displaying the initial print image and the target print image on the target screen to obtain a target display result, so that the target user can make a print selection according to the target display result;

[0042] The target printing method determined by the target user in the target display result is obtained, and the target printing content is printed according to the target printing method to obtain the target printing result corresponding to the target printing content.

[0043] In some optional embodiments, parsing the target printing request to obtain corresponding target printing content includes:

[0044] Obtaining a target printing password corresponding to the target printer from the target printing request;

[0045] Matching the target printing password with the preset printing password to obtain a matching result;

[0046] When the matching result is a matching failure, determining a target feedback result corresponding to the target print request, and sending the target feedback result to the user terminal;

[0047] When the matching result is a successful match, the target printing request is parsed to obtain the corresponding target printing content.

[0048] In a second aspect, an embodiment of the present invention provides a printing optimization device based on a screen display printer, comprising:

[0049] A network acquisition module, used for acquiring an initial network corresponding to a target printer in a target area, and displaying the initial network on a target screen corresponding to the target printer;

[0050] A network selection module, configured to receive a target network corresponding to the initial network and target connection information corresponding to the target network selected by a target user in the target screen;

[0051] A network connection module, used to establish a communication connection between the target printer and the target network according to the target connection information;

[0052] A request receiving module, used for receiving a target printing request sent by a user terminal connected to the target network for communication, and parsing the target printing request to obtain corresponding target printing content;

[0053] A parameter acquisition module, used for performing data analysis on the target print content using a print loss model to obtain image noise parameters corresponding to the target print content;

[0054] An image processing module, configured to perform image processing on the target printing content according to the image noise parameter to obtain an initial printing image corresponding to the target printing content after printing, wherein the initial printing image is an effect image of the target printing content presented on the printing paper after the target printing content is simulated and generated by the image noise parameter;

[0055] A loss analysis module, configured to perform a printing loss analysis on the target printing content according to the initial printing image, and obtain a target printing strategy corresponding to the target printing content;

[0056] The result obtaining module is used to obtain the target printing result corresponding to the target printing content according to the target printing strategy.

[0057] In some optional embodiments, the loss analysis module is further configured to:

[0058] A quality assessment module, configured to perform quality analysis on the initial print image to obtain a target print quality corresponding to the target print content;

[0059] The strategy acquisition module is used to determine the target printing strategy corresponding to the target printing content according to the target printing quality.

[0060] In some optional embodiments, the parameter acquisition module is further configured to:

[0061] An image extraction module, configured to use the image extraction layer of the printing loss model to perform image extraction on the target printing content to obtain a first to-be-printed image corresponding to the target printing content;

[0062] A pixel analysis module, configured to perform pixel analysis on the first image to be printed using the matrix generation layer of the printing loss model to obtain a weighted correlation matrix corresponding to the first image to be printed;

[0063] A structural analysis module, configured to use the texture analysis layer of the printing loss model to perform texture feature analysis using the weighted correlation matrix and the known correlation matrix to obtain a structural similarity between the first image to be printed and the second image to be printed corresponding to the known correlation matrix;

[0064] An image corresponding module, configured to obtain a third image to be printed corresponding to the first image to be printed from the second image to be printed according to the structural similarity by using the image determination layer of the printing loss model;

[0065] A noise generation module is used to determine the image noise parameter corresponding to the first image to be printed according to the third image to be printed and the known printed image corresponding to the third image to be printed by using the noise generation layer of the printing loss model.

[0066] In some optional embodiments, the quality assessment module is further configured to:

[0067] An information acquisition module, configured to extract the image from the initial print image to obtain a corresponding first print image, and to obtain a target description text corresponding to the first print image from the target print content;

[0068] A feature matching module, configured to perform feature matching based on the target description text and the first printed image, and obtain a first image feature corresponding to the target description text in the first printed image;

[0069] A global feature extraction module, used for performing global feature extraction on the first printed image to obtain a second image feature corresponding to the first printed image;

[0070] A feature fusion module, used for fusing the first image feature and the second image feature to obtain a target image feature corresponding to the first printed image;

[0071] A text representation module, used for performing text representation on the target description text to obtain target text features corresponding to the target description text;

[0072] The quality determination module is used to calculate the correlation between the target image feature and the target text feature, and determine the target print quality corresponding to the target print content according to the correlation.

[0073] In some optional embodiments, the feature fusion module is further configured to:

[0074] A semantic decomposition module, used for semantically decomposing the target description text to obtain multiple sub-description texts;

[0075] A text processing module, used for performing vector representation on the sub-description text using a text representation model to obtain a text representation vector corresponding to the sub-description text;

[0076] a distance calculation module, configured to calculate a first distance between the text representation vector and the first image feature and a second distance between the text representation vector and the second image feature;

[0077] a data fusion module, configured to fuse the first image feature and the second image feature according to the first distance and the second distance to obtain an initial image feature corresponding to the sub-description text;

[0078] A weight determination module, used to determine the importance of the sub-description text in the target description text, and determine the target weight corresponding to the sub-description text according to the importance;

[0079] A feature generation module, configured to fuse the initial image features according to the target weight to obtain the target image features corresponding to the first printed image;

[0080] The initial image features are obtained according to the following formula:

[0081]

[0082] in, represents the initial image feature corresponding to the i-th sub-description text, M represents the number of features corresponding to the first image feature, and N represents the number of features corresponding to the second image feature. represents the first distance between the i-th text representation vector and the m-th first image feature, represents the second distance between the i-th text representation vector and the n-th second image feature, e represents a natural constant, represents the adjustment parameter, represents the mth first image feature, represents the nth second image feature, represents the first distance between the i-th text representation vector and the x-th first image feature, represents the second distance between the i-th text representation vector and the y-th second image feature.

[0083] In some optional embodiments, the result obtaining module is further configured to:

[0084] An image adjustment module, used for adjusting the initial printing image according to the target printing strategy to obtain a target printing image;

[0085] An image display module, used for displaying the initial printing image and the target printing image on the target screen to obtain a target display result, so that the target user can make a printing selection according to the target display result;

[0086] The information printing module is used to obtain the target printing method determined by the target user in the target display result, and print the target printing content according to the target printing method to obtain the target printing result corresponding to the target printing content.

[0087] In some optional embodiments, the request receiving module is further configured to:

[0088] A password acquisition module, used to obtain a target printing password corresponding to the target printer from the target printing request;

[0089] A password matching module, used to match the target printing password with a preset printing password to obtain a matching result;

[0090] A first processing module, configured to determine a target feedback result corresponding to the target print request when the matching result is a matching failure, and send the target feedback result to the user terminal;

[0091] The second processing module is used to parse the target printing request to obtain the corresponding target printing content when the matching result is a successful match.

[0092] In a third aspect, an embodiment of the present invention further provides a terminal device, comprising a processor, a memory, a computer program stored in the memory and executable by the processor, and a data bus for realizing connection and communication between the processor and the memory, wherein when the computer program is executed by the processor, the steps of any one of the printing optimization methods based on a screen display printer provided in the specification of the present invention are implemented.

[0093] In a fourth aspect, an embodiment of the present invention further provides a storage medium for computer-readable storage, characterized in that the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of any one of the printing optimization methods based on a screen display printer provided in the specification of the present invention.

[0094] The embodiment of the present invention provides a printing optimization method based on a screen display printer and a related device, the method comprising: obtaining the initial network corresponding to the target printer in the target area, and displaying the initial network in the target screen corresponding to the target printer; thereby, by obtaining the initial network of the target printer in the target area and displaying it on the target screen, the target user can quickly identify and select a suitable network, thereby reducing the network configuration time. Then, the target user selects the target network corresponding to the initial network and the target connection information corresponding to the target network in the target screen, and then the target user directly selects the target network and the target connection information on the target screen, thereby reducing the complexity of the configuration, so that the target user can easily complete the connection settings of the target printer. Therefore, based on the selected target network and target connection information, the target printer can communicate efficiently with the target network to ensure the stability and accuracy of subsequent printing tasks. Then receive the target printing request sent by the user terminal connected to the target network communication, and parse the target printing request to obtain the corresponding target printing content; then use the printing loss model to perform data analysis on the target printing content to obtain the image noise parameters corresponding to the target printing content; perform image processing on the target printing content according to the image noise parameters to obtain the initial printing image corresponding to the target printing content after printing, wherein the initial printing image is the effect image of the target printing content generated by the target printing content through the image noise parameter simulation on the printing paper; perform printing loss analysis on the target printing content according to the initial printing image to obtain the target printing strategy corresponding to the target printing content; thereby, print the target printing content according to the target printing strategy to obtain the target printing result corresponding to the target printing content, and then by performing printing loss analysis on the target printing content, a more reasonable target printing strategy can be formulated, thereby improving the printing effect and reducing resource waste. This method not only significantly improves the efficiency of the target user in the printer network configuration process, but also improves the printing effect of the target printing content, reduces resource waste, and further improves the printing experience of the target user. BRIEF DESCRIPTION OF THE DRAWINGS

[0095] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0096] Figure 1 A schematic flow chart of a printing optimization method based on a screen display printer provided in an embodiment of the present invention;

[0097] Figure 2 A schematic diagram of a communication connection between a target printer and a target network provided by an embodiment of the present invention;

[0098] Figure 3 A schematic diagram of a user terminal establishing a connection with a target printer via a target network provided by an embodiment of the present invention;

[0099] Figure 4 A schematic diagram of the module structure of a printing optimization device based on a screen display printer provided in an embodiment of the present invention;

[0100] Figure 5 A schematic block diagram of the structure of a terminal device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0101] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0102] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0103] It should be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0104] The embodiment of the present invention provides a printing optimization method based on a screen display printer and a related device. The printing optimization method based on a screen display printer can be applied to a terminal device, which can be a printer such as a thermal printer, a ticket printer, a two-dimensional code printer, or an electronic device such as a tablet computer, a laptop computer, a desktop computer, a personal digital assistant, and a wearable device that is connected to the printer for communication. The electronic device can be a server or a server cluster.

[0105] Some embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0106] Please refer to Figure 1 , Figure 1 A schematic flow chart of a printing optimization method based on a screen display printer provided in an embodiment of the present invention.

[0107] like Figure 1 As shown, the printing optimization method based on the screen display printer includes steps S101 to S108.

[0108] Step S101: obtaining an initial network corresponding to a target printer in a target area, and displaying the initial network on a target screen corresponding to the target printer.

[0109] Exemplarily, the target printer is provided with a target screen. After receiving the target user's instruction that the target printer needs to connect to the network, the target printer uses the built-in wireless network module to scan the available network signals in the target area and identify all connectable Wi-Fi networks. The scanned Wi-Fi networks are evaluated for signal strength and then arranged from high to low according to signal strength, and the arrangement result is determined as the initial network corresponding to the target printer in the target area. Each Wi-Fi network in the initial network also includes network information such as network name, signal strength, encryption method, etc.

[0110] Exemplarily, the network information of each Wi-Fi network in the initial network is displayed on the target screen corresponding to the target printer, so that the target user can easily see the detailed information of the available networks. By obtaining the initial network of the target printer in the target area and displaying it on the target screen of the target printer, the foundation for subsequent network connection is laid.

[0111] Step S102: receiving a target network corresponding to the initial network and target connection information corresponding to the target network selected by a target user in the target screen.

[0112] Exemplarily, the target screen of the target printer has a touch or key input mechanism, allowing the target user to select the target network that the target user wants to connect to from the initial network. During the process of the target user selecting the target network, the initial network can be displayed using a list selection, a scroll bar, or a drop-down menu to facilitate the target user to perform the selection operation.

[0113] For example, after the target user selects the target network, the connection information required by the target network (such as a password input box) is displayed, and then when the target user completes input in the password input box, the input content corresponding to the target user is obtained and the input content and the network name corresponding to the target network are determined as the target connection information corresponding to the target network. In addition, if the target network is an open network, there is no need to enter a password, that is, the target connection information only contains the network name.

[0114] Step S103: establishing a communication connection between the target printer and the target network according to the target connection information.

[0115] For example, depending on the type of the target network (such as an open network or an encrypted network that requires a password), the corresponding connection method should be selected. When dealing with an encrypted network, Figure 2 As shown, you first need to extract the corresponding network password from the target connection information before you can make a communication connection; for an open network, you can directly initiate a connection without entering any password.

[0116] For example, during the connection process, if a connection failure occurs, the target screen of the target printer provides detailed error feedback in a timely manner. Such feedback should be classified according to different error types. For example, if the connection failure is caused by a wrong password, the target user is guided to re-enter the password; if the connection failure is caused by insufficient signal strength or unavailable network, the target user can be advised to select another network or adjust the location of the target printer to improve the signal.

[0117] For example, once the connection is successfully established, the target printer should clearly display a "Connection Successful" message on the target screen to confirm that the target printer has successfully established communication with the target network. This feedback not only enhances the confidence of the target user, but also lays the foundation for subsequent printing tasks.

[0118] Step S104: receiving a target printing request sent by a user terminal connected to the target network for communication, and parsing the target printing request to obtain corresponding target printing content.

[0119] For example, when the target printer establishes a communication connection with the target network, all user terminals that are in communication connection with the target network can print in the target printer through the target network. In addition, when there are two or more target printers in the target network, the target user can select any one of the two or more target printers to print.

[0120] For example, Figure 3 As shown, the target user searches for the printer through the user terminal and then establishes a connection with the target printer through the target network, so that the target user prints the content in the target printer through the user terminal.

[0121] Exemplarily, a receiving module of the target printer is set to wait for receiving a target print request from a user terminal. The target print request needs to meet the data format set by the target printer, such as JSON, XML or a specific protocol, so that the target print request sent by the user terminal can be correctly parsed.

[0122] Exemplarily, after receiving the target print request, the target printer needs to use a preset parsing mechanism to decode the target print request. For example, the target printer parses the received target print request according to a predefined data format such as JSON, XML, etc. The parsing process includes identifying and extracting key fields in the target print request. For example, the target print request usually contains a "print content" field, and the target printer needs to extract the specific content that the target user wants to print, that is, the target print content. In addition, the target print request may also contain other important information, such as print settings (paper size, print direction, color mode, etc.) and user identification.

[0123] In some embodiments, parsing the target printing request to obtain the corresponding target printing content includes: obtaining a target printing password corresponding to the target printer from the target printing request; matching the target printing password with a preset printing password to obtain a matching result; when the matching result is a matching failure, determining a target feedback result corresponding to the target printing request, and sending the target feedback result to the user terminal; when the matching result is a matching success, parsing the target printing request to obtain the corresponding target printing content.

[0124] For example, after receiving the target print request, the target print password contained in the target print request needs to be extracted first, so as to ensure the security of the target printer by calling the password comparison algorithm to match the target print password with the preset print password set by the target printer. The password comparison algorithm will determine whether the target print password is consistent with the preset print password and generate a matching result.

[0125] For example, when the matching result is a match failure, the terminal device will generate a target feedback message indicating that the password is incorrect and suggest that the target user re-enter the password or check the relevant settings. The terminal device will send the determined target feedback result to the user terminal through the target network to ensure that the target user can quickly obtain relevant information so as to take further actions.

[0126] In addition, it should be noted that the specific format and specific description content of the target feedback information are not specifically limited in this application and can be set according to actual needs.

[0127] For example, when the matching result is successful, the target printer will parse the received target print request according to a predefined data format (such as JSON, XML, etc.), identify key fields in the target print request, such as the "print content" field, and then extract the specific content that the target user wants to print, that is, the target print content, from the "print content" field.

[0128] Specifically, by verifying the target printing password, it ensures that only authorized target users can perform printing operations, effectively preventing unauthorized access and potential data leakage. When the match fails, timely generation and feedback of error information can help the target user quickly understand the problem, avoid confusion caused by incorrect passwords, and improve the overall experience. The above steps not only ensure the security of printing operations, but also improve the user experience.

[0129] Step S105: using the printing loss model to perform data analysis on the target printing content to obtain image noise parameters corresponding to the target printing content.

[0130] Exemplarily, the printing loss model is used to predict image noise relative to the target printing content in a target printing image obtained after the target printing content is printed by a target printer.

[0131] Exemplarily, historical printing contents and historical printing results corresponding to the historical printing contents are collected, the historical printing contents are in PDF format and can also be regarded as image format, and the historical printing results are paper information after the historical printing contents are printed by a printer and the corresponding photographed images after the paper information is photographed by a camera. That is, the historical printing results are photographed images corresponding to the actual printing results of the historical printing contents.

[0132] Exemplarily, the printing loss model is trained using historical printing content and historical printing results corresponding to the historical printing content. The input of the printing loss model is the historical printing content, and the output is the target noise that needs to be added when the historical printing content is converted to the historical printing result. That is, before training the printing loss model, it is necessary to first calculate the target noise that needs to be added when the historical printing content is converted to the historical printing result. For example, a preset noise is determined, and the preset noise is added to the historical printing content, thereby obtaining the historical printing content with noise, thereby calculating the similarity between the historical printing content with noise and the historical printing result. When the similarity is greater than or equal to the preset value, the preset noise is determined as the target noise between the historical printing content and the historical printing result. Thus, according to the characteristics of the printing loss model, a suitable machine learning or deep learning model is selected for training. Common models include random forests, support vector machines, neural networks, etc. The historical printing content is used as the input data of the printing loss model, and the target noise required to convert the historical printing content into the historical printing result is used as the output data of the printing loss model, and the model is trained to obtain the trained printing loss model. The printing loss model can predict the noise information that may be added after the target printing content is printed by the target printer.

[0133] Exemplarily, the printing loss model is used to perform noise prediction on the target printing content to obtain image noise parameters that may increase after the target printing content is printed by the target printer.

[0134] In some embodiments, the use of a printing loss model to perform data analysis on the target printing content to obtain image noise parameters corresponding to the target printing content includes: using the image extraction layer of the printing loss model to perform image extraction on the target printing content to obtain a first image to be printed corresponding to the target printing content; using the matrix generation layer of the printing loss model to perform pixel analysis on the first image to be printed to obtain a weighted correlation matrix corresponding to the first image to be printed; using the texture analysis layer of the printing loss model to perform texture feature analysis using the weighted correlation matrix and a known correlation matrix to obtain a structural similarity between the first image to be printed and a second image to be printed corresponding to the known correlation matrix; using the image determination layer of the printing loss model to obtain a third image to be printed corresponding to the first image to be printed from the second image to be printed according to the structural similarity; and using the noise generation layer of the printing loss model to determine the image noise parameters corresponding to the first image to be printed according to the third image to be printed and a known printing image corresponding to the third image to be printed.

[0135] For example, when the target printer prints the target print content, the text part usually has fewer abnormalities. Therefore, the present application mainly focuses on analyzing the noise information of the image to be printed in the target print content.

[0136] Exemplarily, the printing loss model includes an image extraction layer, a matrix generation layer, a texture analysis layer, an image determination layer, and a noise generation layer.

[0137] Exemplarily, the image extraction layer formats the target printing content, identifies the various components in the target printing content, and clearly marks and classifies them. The components include but are not limited to text, images, tables, etc., and then determines the information corresponding to the image mark in the target printing content as the first image to be printed.

[0138] Exemplarily, when the first image to be printed is a color image, the matrix generation layer converts the first image to be printed into a grayscale image by weighted averaging. Then select the direction when calculating the grayscale co-occurrence matrix, and the commonly used directions include horizontal (0°), vertical (90°), and diagonal (45° and 135°). And set the distance, for example, select the distance between adjacent pixels as 1 pixel to capture the most direct texture relationship. Thus, according to the different grayscale values ​​existing in the grayscale image, the size of the grayscale co-occurrence matrix is ​​determined, and then an empty grayscale co-occurrence matrix is ​​created, and all elements are initially 0. Then scan each pixel of the grayscale image row by row and column by column. According to the set direction and distance, find the pixels adjacent to the current pixel and obtain its grayscale value. According to the grayscale value of the adjacent pixel, update the count of the corresponding position in the grayscale co-occurrence matrix. In addition, the matrix generation layer continues to analyze the first image to be printed at the pixel level, including extracting the grayscale value of each pixel and generating a color histogram. According to the characteristics or entropy value information of different regions in the first image to be printed, a detailed analysis is performed. Thus, the gray-level co-occurrence matrix is ​​weighted by combining the features obtained from the pixel-level analysis to highlight specific detail features of the image, thereby obtaining a weighted correlation matrix.

[0139] Exemplarily, a second image to be printed in the historical printing content is obtained, and then according to the texture analysis layer of the printing loss model, the known correlation matrix corresponding to the second image to be printed is also saved, that is, the weighted correlation matrix corresponding to the second image to be printed is saved, and then the texture analysis layer is used to perform texture similarity analysis on the weighted correlation matrix and the known correlation matrix, and then the structural similarity between the first image to be printed and the second image to be printed corresponding to the known correlation matrix is ​​obtained.

[0140] Exemplarily, the image determination layer of the printing loss model is used to determine the image with the maximum structural similarity corresponding to the second image to be printed as the third image to be printed. Since the third image to be printed is an image in the historical printing content, the printing result corresponding to the third image to be printed is also known, so that the known printing image corresponding to the third image to be printed is obtained from the historical data. The known printing image is the actual printing effect of the third image to be printed.

[0141] Exemplarily, the noise generation layer of the printing loss model is finally used to determine the image noise parameters required when the third image to be printed is converted into a known printing image corresponding to the third image to be printed. Since the third image to be printed has a similar texture structure to the first image to be printed, the noise generation layer of the printing loss model converts the image noise parameters required when the third image to be printed is converted into the known printing image corresponding to the third image to be printed as the image noise parameters that may be increased after the first image to be printed is printed according to the target printer.

[0142] Specifically, the matrix generation layer performs an in-depth pixel analysis on the first image to be printed to obtain a weighted correlation matrix, which can more accurately capture the texture features of the image, thereby making the subsequent texture analysis more accurate and reliable. The texture analysis layer compares the structural similarity of the first image to be printed with the known correlation matrix to identify the third image to be printed that has similar texture features to the first image to be printed, which provides a basis for finding a suitable reference image. Finally, the image noise parameters of the first image to be printed can be accurately determined using the third image to be printed and its corresponding known printed image. Therefore, the image noise parameters can be used to identify the source of distortion generated during the printing process of the first image to be printed, thereby providing support for finding a more effective target printing strategy in the future.

[0143] Step S106, performing image processing on the target printing content according to the image noise parameters to obtain an initial printing image corresponding to the target printing content after printing, wherein the initial printing image is an effect image of the target printing content presented on the printing paper after the target printing content is simulated by the image noise parameters.

[0144] Exemplarily, the print loss model is used to predict the noise of the target print content to obtain the image noise parameters that may be increased after the target print content is printed by the target printer, and then the image noise parameters are added to the target print content to obtain the initial print image corresponding to the target print content after being printed by the target printer. The initial print image is the effect image of the target print content generated by the image noise parameter simulation on the printing paper.

[0145] Exemplarily, the initial printing image is an image of the printing effect of the target printing content after being processed by the image noise parameters and predicted by the target printing content after being printed by the target printer. That is, the initial printing image is an image of the target printing content obtained by estimating the image noise parameters of the target printing content and presented on the printing paper after being printed by the target printer, and the initial printing image is not an image of the printing result captured after the target printing content is actually printed by the target printer.

[0146] For example, adding the image noise parameter to the target print content can generate an initial print image, thereby simulating the actual effect of the target print content on the print paper. This method avoids reprinting after obtaining the real print result, reducing paper waste.

[0147] Step S107: performing a printing loss analysis on the target printing content according to the initial printing image to obtain a target printing strategy corresponding to the target printing content.

[0148] Exemplarily, first, a large amount of historical printing content and historical printing results corresponding to the historical printing content are collected. A loss analysis model is established using a machine learning algorithm (such as random forest, support vector machine) or a deep learning algorithm (such as a neural network). The input of the model is the historical printing content and the historical printing results, and the output is the printing loss information of the historical printing results relative to the historical printing content. Printing loss information includes but is not limited to information such as unclear images and blurred printing. The loss analysis model is then trained using the historical printing content and the corresponding historical printing results. During the training process, the model parameters are adjusted through an optimization algorithm to improve the prediction accuracy of the model, thereby obtaining a loss analysis model after the loss. Among them, the loss analysis model is used to predict the information about the loss of the printed content after printing.

[0149] Exemplarily, the target printing content and the initial printing image are input into the trained loss analysis model to obtain the target loss information corresponding to the initial printing image relative to the target printing content. The target loss information is the abnormal information that may be caused by the target printing content after being printed by the target printer, such as unclear image and blurred printing.

[0150] Exemplarily, the strategy mapping table is set according to expert experience or historical experience, so that the corresponding target printing strategy is obtained from the strategy mapping table according to the target loss information, so as to optimize the printing effect and reduce potential waste of resources.

[0151] For example, if the loss analysis model predicts that the target print content may result in blurry printing, the target print strategy can be to increase the ink parameters corresponding to the target print content, such as increasing the jetting frequency of the ink nozzle or adjusting the ink jetting amount to ensure that the target print content is clearer and avoids blurring; the speed setting of the target printer can also be adjusted to appropriately reduce the printing speed while ensuring efficiency to ensure that the ink has enough time to dry on the paper and avoid blurring.

[0152] In some embodiments, performing a printing loss analysis on the target printing content based on the initial printing image to obtain a target printing strategy corresponding to the target printing content includes: performing a quality analysis on the initial printing image to obtain a target printing quality corresponding to the target printing content; and determining the target printing strategy corresponding to the target printing content based on the target printing quality.

[0153] Exemplarily, the edge of the initial printed image is evaluated using an image sharpness index (such as edge strength) to obtain a first evaluation result, and the uniform distribution of color or brightness in the initial printed image is analyzed to obtain a second evaluation result. The first evaluation result and the second evaluation result are then combined to determine the target print quality corresponding to the target print content.

[0154] Exemplarily, the printing problems corresponding to the target printing content, such as low definition and large color deviation, are determined according to the target printing quality, so that the target printing strategy corresponding to the target printing content is obtained from the strategy mapping table according to the printing problems.

[0155] Specifically, based on the initial print image, a corresponding target printing strategy can be formulated, thereby effectively reducing resource waste and the need for repeated printing, thereby reducing the overall printing cost.

[0156] In some embodiments, the quality analysis of the initial printed image to obtain the target printing quality corresponding to the target printed content includes: performing image extraction on the initial printed image to obtain the corresponding first printed image, and obtaining a target description text corresponding to the first printed image from the target printed content; performing feature matching based on the target description text and the first printed image to obtain a first image feature corresponding to the target description text in the first printed image; performing global feature extraction on the first printed image to obtain a second image feature corresponding to the first printed image; fusing the first image feature and the second image feature to obtain a target image feature corresponding to the first printed image; performing text representation on the target description text to obtain a target text feature corresponding to the target description text; calculating the correlation between the target image feature and the target text feature, and determining the target printing quality corresponding to the target printed content based on the correlation.

[0157] Exemplarily, an information classification model such as a support vector machine, a decision tree, a random forest or a deep learning model is used to classify the data type of the initial printed image to obtain a first printed image corresponding to the initial printed image.

[0158] Exemplarily, the image number corresponding to the first printing image is extracted from the target printing content, and the image number is used to perform information retrieval in the target printing content to obtain the target description text related to the first printing image in the target printing content.

[0159] Exemplarily, keywords or phrases are extracted from the target description text through natural language processing techniques such as word segmentation, part-of-speech tagging, and named entity recognition. At the same time, edge detection, corner detection, and other algorithms are used to extract features from the first printed image. The extracted text features are compared with the image features, and a similarity metric such as Euclidean distance or cosine similarity is used to determine the first image feature corresponding to the target description text in the first printed image. When the similarity between the text feature and the image feature is greater than a preset value, the corresponding image feature is determined as the first image feature. The first image feature is used to characterize the most relevant image information of the target description text in the first printed image.

[0160] Exemplarily, global features of the first printed image are extracted using an image feature extraction model such as VGG16, ResNet, or Inception to obtain second image features, and the second image features can effectively represent the global information of the first printed image.

[0161] Exemplarily, the first image feature and the second image feature are vectorized or weightedly fused to obtain the target image feature corresponding to the first printed image. The target description text is then represented by a text representation based on the word embedding technology, and converted into a form that can be compared with the image feature to obtain the target text feature corresponding to the target description text.

[0162] Exemplarily, the degree of correlation between the target image features and the target text features is calculated using an appropriate similarity metric such as cosine similarity or Manhattan distance. Thus, the degree of matching between the target description text and the first printed image is quantified by the degree of correlation, and then the print quality of the target printed content is evaluated based on the calculated degree of correlation. If the degree of correlation is high, it means that the consistency between the target description text and the first printed image is strong, that is, the effect presented by the first printed image can show the content of the target description text, and then it shows that the printing effect of the first printed image meets the user's needs. Otherwise, it means that the consistency between the target description text and the first printed image is not strong, that is, the effect presented by the first printed image cannot show the content of the target description text, and then it shows that the printing effect of the first printed image cannot meet the user's needs, and further shows that the printing quality needs to be improved.

[0163] Specifically, by matching the target description text with the first printed image, the specific expression of the information corresponding to the target description text in the first printed image can be accurately identified. Thus, by calculating the correlation between the target image features and the target text features, the correlation between the target description text and the first printed image can be quantified. This provides important support for the subsequent evaluation of the quality of the target printed content.

[0164] In some embodiments, the fusing of the first image feature and the second image feature to obtain a target image feature corresponding to the first printed image includes: semantically decomposing the target description text to obtain a plurality of sub-description texts; using a text representation model to vectorize the sub-description text to obtain a text representation vector corresponding to the sub-description text; calculating a first distance between the text representation vector and the first image feature and a second distance between the text representation vector and the second image feature; fusing the first image feature and the second image feature according to the first distance and the second distance to obtain an initial image feature corresponding to the sub-description text; determining the importance of the sub-description text in the target description text, and determining a target weight corresponding to the sub-description text according to the importance; fusing the initial image features according to the target weight to obtain the target image feature corresponding to the first printed image; wherein the initial image feature is obtained according to the following formula:

[0165]

[0166] in, represents the initial image feature corresponding to the i-th sub-description text, M represents the number of features corresponding to the first image feature, and N represents the number of features corresponding to the second image feature. represents the first distance between the i-th text representation vector and the m-th first image feature, represents the second distance between the i-th text representation vector and the n-th second image feature, e represents a natural constant, represents the adjustment parameter, represents the mth first image feature, represents the nth second image feature, represents the first distance between the i-th text representation vector and the x-th first image feature, represents the second distance between the i-th text representation vector and the y-th second image feature.

[0167] For example, the target description text is split into multiple sub-description texts according to punctuation marks such as periods and commas, so as to use pre-trained text representation models such as Word2Vec and GloVe to perform vector representation on the sub-description texts to capture the context and semantic information of the sub-description texts and obtain corresponding text representation vectors.

[0168] Exemplarily, the first distance is obtained by calculating the similarity between the text representation vector and the first image feature using algorithms such as Euclidean distance and cosine similarity, and the second distance is obtained by calculating the similarity between the text representation vector and the second image feature using algorithms such as Euclidean distance and cosine similarity.

[0169] Exemplarily, the initial image features are obtained by performing feature fusion using the following formula according to the calculated first distance and second distance:

[0170]

[0171] in, represents the initial image feature corresponding to the i-th sub-description text, M represents the number of features corresponding to the first image feature, and N represents the number of features corresponding to the second image feature. represents the first distance between the i-th text representation vector and the m-th first image feature, represents the second distance between the i-th text representation vector and the n-th second image feature, e represents a natural constant, represents the adjustment parameter, represents the mth first image feature, represents the nth second image feature, represents the first distance between the i-th text representation vector and the x-th first image feature, represents the second distance between the i-th text representation vector and the y-th second image feature.

[0172] Exemplarily, by combining the first distance and the second distance to perform feature fusion through the above formula, the initial image features corresponding to the sub-description text can be effectively integrated. Thus, according to the position information of the sub-description text in the target description text, the importance of the sub-description text in the target description text is determined, and the target weight corresponding to each sub-description text is set according to the importance. Finally, the initial image features are weightedly fused according to the target weight to generate the final target image features.

[0173] Specifically, by calculating the distance between the text representation vector and the first image feature and the second image feature, the correlation between the sub-description text and the first printed image can be quantified. By fusing the first image feature and the second image feature in combination with the first distance and the second distance, a more comprehensive and accurate initial image feature can be formed. By evaluating the importance of the sub-description text in the target description text, a basis can be provided for the fusion of the initial image features, ensuring that the more critical sub-description text has a greater influence in the target image features so that the obtained target image features can better characterize the first printed image. The target image features thus obtained will provide a reliable basis for subsequent quality assessment, thereby providing support for the subsequent improvement of the ability and accuracy of printed image quality assessment.

[0174] Step S108: Obtain a target printing result corresponding to the target printing content according to the target printing strategy.

[0175] Exemplarily, the target printing content is printed using the target printing strategy to obtain a target printing result corresponding to the target printing content.

[0176] For example, if the target printing strategy is to appropriately reduce the printing speed, the printing speed can be appropriately reduced when printing the target printing content to ensure that the ink has enough time to dry on the paper to avoid blurring, thereby obtaining the target printing result corresponding to the target printing content.

[0177] In some embodiments, obtaining the target printing result corresponding to the target printing content according to the target printing policy includes: adjusting the initial printing image according to the target printing policy to obtain the target printing image; displaying the initial printing image and the target printing image in the target screen to obtain a target display result, so that the target user makes a printing selection according to the target display result; obtaining the target printing method determined by the target user in the target display result, and printing the target printing content according to the target printing method to obtain the target printing result corresponding to the target printing content.

[0178] Exemplarily, the initial print image is the predicted print effect after the target print content is printed by the target printer. That is, the effect of the target print content on the printing paper after being printed by the target printer. Thus, the initial print image is adjusted according to the target printing strategy to obtain the target print image. The target print image is the actual print effect after the target print content is printed by the target printer using the target printing strategy. That is, the effect of the target print content on the printing paper after being printed by the target printer using the target printing strategy.

[0179] For example, the initial print image and the adjusted target print image are displayed on the target screen. They can be displayed side by side or in an overlay manner to facilitate user comparison. Through visual display, the target user can intuitively see the difference between the initial print image and the target print image to help him make a better print choice. Thus, the target user can select the target print mode desired by the target user according to the target display result. The selection of the target print mode can be achieved through a touch screen, buttons or other interactive elements.

[0180] Exemplarily, an actual printing operation is performed on the target printing content according to the target printing mode determined by the target user, ensuring that printing is performed according to the settings selected by the target user, thereby obtaining a target printing result corresponding to the target printing content.

[0181] Specifically, the initial print image and the target print image are displayed on the target screen at the same time, so that the target user can intuitively compare the initial print image and the target print image, and thus the target user can make a more appropriate printing method selection based on the target display result. This feedback mechanism can ensure that the target printing result is more in line with user expectations, reduce resource waste, and further enhance the target user's printing experience.

[0182] See also Figure 4 , Figure 4A printing optimization device 200 based on a screen display printer is provided in an embodiment of the present application. The printing optimization device 200 based on a screen display printer includes a network acquisition module 201, a network selection module 202, a network connection module 203, a request receiving module 204, a parameter acquisition module 205, an image processing module 206, a loss analysis module 207, and a result acquisition module 208, wherein the network acquisition module 201 is used to obtain an initial network corresponding to a target printer in a target area, and display the initial network in a target screen corresponding to the target printer; the network selection module 202 is used to receive a target user selecting a target network corresponding to the initial network in the target screen and a target connection information corresponding to the target network; the network connection module 203 is used to connect the target printer to the target network according to the target connection information; the request receiving module 204 is used to receive a request to communicate with the target network A target printing request sent by a connected user terminal, and parsing the target printing request to obtain the corresponding target printing content; a parameter acquisition module 205, used to use a printing loss model to perform data analysis on the target printing content to obtain image noise parameters corresponding to the target printing content; an image processing module 206, used to perform image processing on the target printing content according to the image noise parameters to obtain an initial printing image corresponding to the target printing content after printing, wherein the initial printing image is an effect image of the target printing content generated by simulating the image noise parameters of the target printing content on the printing paper; a loss analysis module 207, used to perform printing loss analysis on the target printing content according to the initial printing image to obtain a target printing strategy corresponding to the target printing content; a result acquisition module 206, used to obtain a target printing result corresponding to the target printing content according to the target printing strategy.

[0183] In some optional embodiments, the loss analysis module is further configured to:

[0184] A quality assessment module, configured to perform quality analysis on the initial print image to obtain a target print quality corresponding to the target print content;

[0185] The strategy acquisition module is used to determine the target printing strategy corresponding to the target printing content according to the target printing quality.

[0186] In some optional embodiments, the parameter acquisition module is further configured to:

[0187] An image extraction module, configured to use the image extraction layer of the printing loss model to perform image extraction on the target printing content to obtain a first to-be-printed image corresponding to the target printing content;

[0188] A pixel analysis module, configured to perform pixel analysis on the first image to be printed using the matrix generation layer of the printing loss model to obtain a weighted correlation matrix corresponding to the first image to be printed;

[0189] A structural analysis module, configured to use the texture analysis layer of the printing loss model to perform texture feature analysis using the weighted correlation matrix and the known correlation matrix to obtain a structural similarity between the first image to be printed and the second image to be printed corresponding to the known correlation matrix;

[0190] An image corresponding module, configured to obtain a third image to be printed corresponding to the first image to be printed from the second image to be printed according to the structural similarity by using the image determination layer of the printing loss model;

[0191] A noise generation module is used to determine the image noise parameter corresponding to the first image to be printed according to the third image to be printed and the known printed image corresponding to the third image to be printed by using the noise generation layer of the printing loss model.

[0192] In some optional embodiments, the quality assessment module is further configured to:

[0193] An information acquisition module, configured to extract the image from the initial print image to obtain a corresponding first print image, and to obtain a target description text corresponding to the first print image from the target print content;

[0194] A feature matching module, configured to perform feature matching based on the target description text and the first printed image, and obtain a first image feature corresponding to the target description text in the first printed image;

[0195] A global feature extraction module, used for performing global feature extraction on the first printed image to obtain a second image feature corresponding to the first printed image;

[0196] A feature fusion module, used for fusing the first image feature and the second image feature to obtain a target image feature corresponding to the first printed image;

[0197] A text representation module, used for performing text representation on the target description text to obtain target text features corresponding to the target description text;

[0198] The quality determination module is used to calculate the correlation between the target image feature and the target text feature, and determine the target print quality corresponding to the target print content according to the correlation.

[0199] In some optional embodiments, the feature fusion module is further configured to:

[0200] A semantic decomposition module, used for semantically decomposing the target description text to obtain multiple sub-description texts;

[0201] A text processing module, used for performing vector representation on the sub-description text using a text representation model to obtain a text representation vector corresponding to the sub-description text;

[0202] a distance calculation module, configured to calculate a first distance between the text representation vector and the first image feature and a second distance between the text representation vector and the second image feature;

[0203] a data fusion module, configured to fuse the first image feature and the second image feature according to the first distance and the second distance to obtain an initial image feature corresponding to the sub-description text;

[0204] A weight determination module, used to determine the importance of the sub-description text in the target description text, and determine the target weight corresponding to the sub-description text according to the importance;

[0205] A feature generation module, configured to fuse the initial image features according to the target weight to obtain the target image features corresponding to the first printed image;

[0206] The initial image features are obtained according to the following formula:

[0207]

[0208] in, represents the initial image feature corresponding to the i-th sub-description text, M represents the number of features corresponding to the first image feature, and N represents the number of features corresponding to the second image feature. represents the first distance between the i-th text representation vector and the m-th first image feature, represents the second distance between the i-th text representation vector and the n-th second image feature, e represents a natural constant, represents the adjustment parameter, represents the mth first image feature, represents the nth second image feature, represents the first distance between the i-th text representation vector and the x-th first image feature, represents the second distance between the i-th text representation vector and the y-th second image feature.

[0209] In some optional embodiments, the result obtaining module is further configured to:

[0210] An image adjustment module, used for adjusting the initial printing image according to the target printing strategy to obtain a target printing image;

[0211] An image display module, used for displaying the initial printing image and the target printing image on the target screen to obtain a target display result, so that the target user can make a printing selection according to the target display result;

[0212] The information printing module is used to obtain the target printing method determined by the target user in the target display result, and print the target printing content according to the target printing method to obtain the target printing result corresponding to the target printing content.

[0213] In some optional embodiments, the request receiving module is further configured to:

[0214] A password acquisition module, used to obtain a target printing password corresponding to the target printer from the target printing request;

[0215] A password matching module, used to match the target printing password with a preset printing password to obtain a matching result;

[0216] A first processing module, configured to determine a target feedback result corresponding to the target print request when the matching result is a matching failure, and send the target feedback result to the user terminal;

[0217] The second processing module is used to parse the target printing request to obtain the corresponding target printing content when the matching result is a successful match.

[0218] In some implementations, the printing optimization apparatus 200 based on a screen printer may be applied to a terminal device.

[0219] It should be noted that technicians in the relevant field can clearly understand that for the convenience and simplicity of description, the specific working process of the printing optimization device 200 based on the screen display printer described above can refer to the corresponding process in the aforementioned printing optimization method embodiment based on the screen display printer, and will not be repeated here.

[0220] See also Figure 5 , Figure 5 A schematic block diagram of the structure of a terminal device provided in an embodiment of the present invention.

[0221] like Figure 5As shown, the terminal device 300 includes a processor 301 and a memory 302 , and the processor 301 and the memory 302 are connected via a bus 303 , such as an I2C (Inter-integrated Circuit) bus.

[0222] Specifically, the processor 301 is used to provide computing and control capabilities to support the operation of the entire terminal device. The processor 301 can be a central processing unit (CPU), and the processor 301 can also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0223] Specifically, the memory 302 may be a Flash chip, a read-only memory (ROM) disk, an optical disk, a USB flash drive, or a mobile hard disk.

[0224] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a partial structure related to the embodiment of the present invention, and does not constitute a limitation on the terminal device to which the embodiment of the present invention is applied. The specific server may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0225] The processor is used to run a computer program stored in the memory, and implement any one of the printing optimization methods based on a screen display printer provided by the embodiments of the present invention when executing the computer program.

[0226] In one embodiment, the processor is used to run a computer program stored in the memory, and implements the following steps when executing the computer program:

[0227] Obtaining an initial network corresponding to a target printer in a target area, and displaying the initial network on a target screen corresponding to the target printer;

[0228] receiving, from the target user, a target network corresponding to the initial network and target connection information corresponding to the target network selected in the target screen;

[0229] Establishing a communication connection between the target printer and the target network according to the target connection information;

[0230] Receiving a target printing request sent by a user terminal connected to the target network for communication, and parsing the target printing request to obtain corresponding target printing content;

[0231] Performing data analysis on the target print content using a print loss model to obtain image noise parameters corresponding to the target print content;

[0232] Performing image processing on the target printing content according to the image noise parameter to obtain an initial printing image corresponding to the target printing content after printing, wherein the initial printing image is an effect image of the target printing content presented on the printing paper after the target printing content is simulated by the image noise parameter;

[0233] Performing a printing loss analysis on the target printing content according to the initial printing image to obtain a target printing strategy corresponding to the target printing content;

[0234] A target printing result corresponding to the target printing content is obtained according to the target printing strategy.

[0235] In some optional embodiments, the processor 301, in the process of performing printing loss analysis on the target printing content according to the initial printing image to obtain the target printing strategy corresponding to the target printing content, executes:

[0236] Performing quality analysis on the initial print image to obtain a target print quality corresponding to the target print content;

[0237] The target printing strategy corresponding to the target printing content is determined according to the target printing quality.

[0238] In some optional embodiments, the processor 301, in the process of performing data analysis on the target printed content by using the printing loss model to obtain the image noise parameter corresponding to the target printed content, executes:

[0239] Performing image extraction on the target printing content using the image extraction layer of the printing loss model to obtain a first to-be-printed image corresponding to the target printing content;

[0240] Performing pixel analysis on the first image to be printed using the matrix generation layer of the printing loss model to obtain a weighted correlation matrix corresponding to the first image to be printed;

[0241] Using the texture analysis layer of the printing loss model to perform texture feature analysis using the weighted correlation matrix and the known correlation matrix, to obtain the structural similarity between the first image to be printed and the second image to be printed corresponding to the known correlation matrix;

[0242] Obtaining a third image to be printed corresponding to the first image to be printed from the second image to be printed according to the structural similarity using the image determination layer of the printing loss model;

[0243] The image noise parameter corresponding to the first image to be printed is determined according to the third image to be printed and a known printed image corresponding to the third image to be printed by using the noise generation layer of the printing loss model.

[0244] In some optional embodiments, during the process of performing quality analysis on the initial print image to obtain the target print quality corresponding to the target print content, the processor 301 executes:

[0245] Performing image extraction on the initial print image to obtain a corresponding first print image, and obtaining a target description text corresponding to the first print image from the target print content;

[0246] Perform feature matching on the target description text and the first printed image to obtain a first image feature corresponding to the target description text in the first printed image;

[0247] Performing global feature extraction on the first printed image to obtain a second image feature corresponding to the first printed image;

[0248] fusing the first image feature and the second image feature to obtain a target image feature corresponding to the first printed image;

[0249] Performing text representation on the target description text to obtain target text features corresponding to the target description text;

[0250] The degree of correlation between the target image feature and the target text feature is calculated, and the target print quality corresponding to the target print content is determined according to the degree of correlation.

[0251] In some optional embodiments, during the process of fusing the first image feature and the second image feature to obtain a target image feature corresponding to the first printed image, the processor 301 executes:

[0252] Semantically decomposing the target description text to obtain multiple sub-description texts;

[0253] Performing vector representation on the sub-description text using a text representation model to obtain a text representation vector corresponding to the sub-description text;

[0254] Calculating a first distance between the text representation vector and the first image feature and calculating a second distance between the text representation vector and the second image feature;

[0255] fusing the first image feature and the second image feature according to the first distance and the second distance to obtain an initial image feature corresponding to the sub-description text;

[0256] Determining the importance of the sub-description text in the target description text, and determining the target weight corresponding to the sub-description text according to the importance;

[0257] fusing the initial image features according to the target weights to obtain the target image features corresponding to the first printed image;

[0258] The initial image features are obtained according to the following formula:

[0259]

[0260] in, represents the initial image feature corresponding to the i-th sub-description text, M represents the number of features corresponding to the first image feature, and N represents the number of features corresponding to the second image feature. represents the first distance between the i-th text representation vector and the m-th first image feature, represents the second distance between the i-th text representation vector and the n-th second image feature, e represents a natural constant, represents the adjustment parameter, represents the mth first image feature, represents the nth second image feature, represents the first distance between the i-th text representation vector and the x-th first image feature, represents the second distance between the i-th text representation vector and the y-th second image feature.

[0261] In some optional embodiments, the processor 301, in the process of obtaining the target printing result corresponding to the target printing content according to the target printing strategy, executes:

[0262] Adjusting the initial printing image according to the target printing strategy to obtain a target printing image;

[0263] Displaying the initial print image and the target print image on the target screen to obtain a target display result, so that the target user can make a print selection according to the target display result;

[0264] The target printing method determined by the target user in the target display result is obtained, and the target printing content is printed according to the target printing method to obtain the target printing result corresponding to the target printing content.

[0265] In some optional embodiments, the processor 301, during the process of parsing the target printing request to obtain the corresponding target printing content, executes:

[0266] Obtaining a target printing password corresponding to the target printer from the target printing request;

[0267] Matching the target printing password with the preset printing password to obtain a matching result;

[0268] When the matching result is a matching failure, determining a target feedback result corresponding to the target print request, and sending the target feedback result to the user terminal;

[0269] When the matching result is a successful match, the target printing request is parsed to obtain the corresponding target printing content.

[0270] It should be noted that technicians in the relevant field can clearly understand that for the convenience and brevity of description, the specific working process of the terminal device described above can refer to the corresponding process in the aforementioned printing optimization method embodiment based on the screen display printer, and will not be repeated here.

[0271] An embodiment of the present invention also provides a storage medium for computer-readable storage, wherein the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of any one of the printing optimization methods based on a screen display printer provided in the description of the embodiment of the present invention.

[0272] The storage medium may be an internal storage unit of the terminal device described in the foregoing embodiment, such as a hard disk or memory of the terminal device. The storage medium may also be an external storage device of the terminal device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc., equipped on the terminal device.

[0273] It will be appreciated by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In a hardware embodiment, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or transient medium). As is known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0274] It should be understood that the term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, including these combinations. It should be noted that, in this article, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "including a..." does not exclude the presence of other identical elements in the process, method, article or system including the element.

[0275] The serial numbers of the embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments. The above description is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A printing optimization method based on a screen display printer, characterized in that: The method comprises: Obtaining an initial network corresponding to a target printer in a target area, and displaying the initial network on a target screen corresponding to the target printer; receiving, from the target user, a target network corresponding to the initial network and target connection information corresponding to the target network selected in the target screen; Establishing a communication connection between the target printer and the target network according to the target connection information; Receiving a target printing request sent by a user terminal connected to the target network for communication, and parsing the target printing request to obtain corresponding target printing content; Performing image extraction on the target printing content using the image extraction layer of the printing loss model to obtain a first to-be-printed image corresponding to the target printing content; Performing pixel analysis on the first image to be printed using the matrix generation layer of the printing loss model to obtain a weighted correlation matrix corresponding to the first image to be printed; Using the texture analysis layer of the printing loss model to perform texture feature analysis using the weighted correlation matrix and the known correlation matrix, to obtain the structural similarity between the first image to be printed and the second image to be printed corresponding to the known correlation matrix; Obtaining a third image to be printed corresponding to the first image to be printed from the second image to be printed according to the structural similarity using the image determination layer of the printing loss model; Determine the image noise parameter corresponding to the first image to be printed according to the third image to be printed and the known printed image corresponding to the third image to be printed by using the noise generation layer of the printing loss model; Performing image processing on the target printing content according to the image noise parameter to obtain an initial printing image corresponding to the target printing content after printing, wherein the initial printing image is an effect image of the target printing content presented on the printing paper after the target printing content is simulated by the image noise parameter; Performing image extraction on the initial print image to obtain a corresponding first print image, and obtaining a target description text corresponding to the first print image from the target print content; Perform feature matching on the target description text and the first printed image to obtain a first image feature corresponding to the target description text in the first printed image; Performing global feature extraction on the first printed image to obtain a second image feature corresponding to the first printed image; fusing the first image feature and the second image feature to obtain a target image feature corresponding to the first printed image; Performing text representation on the target description text to obtain target text features corresponding to the target description text; Calculating the correlation between the target image feature and the target text feature, and determining the target print quality corresponding to the target print content according to the correlation; Determining a target printing strategy corresponding to the target printing content according to the target printing quality; A target printing result corresponding to the target printing content is obtained according to the target printing strategy.

2. The method according to claim 1, characterized in that The step of fusing the first image feature and the second image feature to obtain a target image feature corresponding to the first printed image includes: Semantically decomposing the target description text to obtain multiple sub-description texts; Performing vector representation on the sub-description text using a text representation model to obtain a text representation vector corresponding to the sub-description text; Calculating a first distance between the text representation vector and the first image feature and calculating a second distance between the text representation vector and the second image feature; fusing the first image feature and the second image feature according to the first distance and the second distance to obtain an initial image feature corresponding to the sub-description text; Determining the importance of the sub-description text in the target description text, and determining the target weight corresponding to the sub-description text according to the importance; fusing the initial image features according to the target weights to obtain the target image features corresponding to the first printed image; The initial image features are obtained according to the following formula: ; in, represents the initial image feature corresponding to the i-th sub-description text, M represents the number of features corresponding to the first image feature, and N represents the number of features corresponding to the second image feature. represents the first distance between the i-th text representation vector and the m-th first image feature, represents the second distance between the i-th text representation vector and the n-th second image feature, e represents a natural constant, represents the adjustment parameter, represents the mth first image feature, represents the nth second image feature, represents the first distance between the i-th text representation vector and the x-th first image feature, represents the second distance between the i-th text representation vector and the y-th second image feature.

3. The method according to claim 1, characterized in that The obtaining, according to the target printing strategy, a target printing result corresponding to the target printing content includes: Adjusting the initial printing image according to the target printing strategy to obtain a target printing image; Displaying the initial print image and the target print image on the target screen to obtain a target display result, so that the target user can make a print selection according to the target display result; The target printing method determined by the target user in the target display result is obtained, and the target printing content is printed according to the target printing method to obtain the target printing result corresponding to the target printing content.

4. The method according to any one of claims 1 to 3, characterized in that The step of parsing the target printing request to obtain corresponding target printing content includes: Obtaining a target printing password corresponding to the target printer from the target printing request; Matching the target printing password with the preset printing password to obtain a matching result; When the matching result is a matching failure, determining a target feedback result corresponding to the target print request, and sending the target feedback result to the user terminal; When the matching result is a successful match, the target printing request is parsed to obtain the corresponding target printing content.

5. A printing optimization device based on a screen display printer, characterized in that: include: A network acquisition module, used for acquiring an initial network corresponding to a target printer in a target area, and displaying the initial network on a target screen corresponding to the target printer; A network selection module, configured to receive a target network corresponding to the initial network and target connection information corresponding to the target network selected by a target user in the target screen; A network connection module, used to establish a communication connection between the target printer and the target network according to the target connection information; A request receiving module, used for receiving a target printing request sent by a user terminal connected to the target network for communication, and parsing the target printing request to obtain corresponding target printing content; A parameter acquisition module, configured to perform image extraction on the target printing content using an image extraction layer of a printing loss model to obtain a first to-be-printed image corresponding to the target printing content; Performing pixel analysis on the first image to be printed using the matrix generation layer of the printing loss model to obtain a weighted correlation matrix corresponding to the first image to be printed; The texture analysis layer of the printing loss model uses the weighted correlation matrix and the known correlation matrix to perform texture feature analysis to obtain the structural similarity between the first image to be printed and the second image to be printed corresponding to the known correlation matrix; the image determination layer of the printing loss model uses the structural similarity to obtain a third image to be printed corresponding to the first image to be printed from the second image to be printed; Determine the image noise parameter corresponding to the first image to be printed according to the third image to be printed and the known printed image corresponding to the third image to be printed by using the noise generation layer of the printing loss model; An image processing module, configured to perform image processing on the target printing content according to the image noise parameter to obtain an initial printing image corresponding to the target printing content after printing, wherein the initial printing image is an effect image of the target printing content presented on the printing paper after the target printing content is simulated and generated by the image noise parameter; A loss analysis module is used to perform image extraction on the initial print image to obtain a corresponding first print image, and to obtain a target description text corresponding to the first print image from the target print content; perform feature matching based on the target description text and the first print image to obtain a first image feature corresponding to the target description text in the first print image; perform global feature extraction on the first print image to obtain a second image feature corresponding to the first print image; fuse the first image feature and the second image feature to obtain a target image feature corresponding to the first print image; perform text representation on the target description text to obtain a target text feature corresponding to the target description text; calculate the correlation between the target image feature and the target text feature, and determine a target print quality corresponding to the target print content according to the correlation; determine a target print strategy corresponding to the target print content according to the target print quality; The result obtaining module is used to obtain the target printing result corresponding to the target printing content according to the target printing strategy.

6. A terminal device, characterized in that: The terminal device includes a processor and a memory; The memory is used to store computer programs; The processor is used to execute the computer program and implement the printing optimization method based on a screen printer according to any one of claims 1 to 4 when executing the computer program.

7. A computer storage medium for computer storage, characterized in that: The computer storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of the printing optimization method based on a screen display printer as described in any one of claims 1 to 4.

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