A real-time printing based graphic printing method and system

Abstract

The present application relates to the technical field of graphic printing, and particularly relates to a graphic printing method and system based on real-time printing; the method comprises the following steps: receiving configuration information of a current printing task for multi-dimensional extraction, obtaining task attribute parameters, associating the task attribute parameters with each dimension feature, forming a mapping data set and outputting; based on label information of the mapping data set, performing frame-level real-time compression on a graphic data stream; setting a printing parameter reference value corresponding to the task attribute, dynamically adjusting the printing parameter and a transmission strategy based on data dynamic compression transmission according to collected data, and forming a closed-loop control; the system comprises a current task graphic data extraction module, a data dynamic compression transmission module and a current task real-time adjustment module; through the above-mentioned mode, real-time adaptation is performed in combination with dynamic changes of graphic data in a printing process, transmission states and printing quality feedback, when task requirements or printing environments change, quick response can be achieved, and printing efficiency and quality are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of graphic printing, in particular to a graphic printing method and system based on real-time printing. BACKGROUND

[0002] In the current graphic printing technology, the traditional graphic printing method usually needs to process and store the complete graphic data first, and then transmit it to the printing device for printing after all graphic data is prepared.

[0003] The existing graphic printing technology generally adopts the mode of "full data processing-storage-whole transmission-batch printing". The printing adjustment of this mode is mostly one-time parameter setting, which only configures parameters according to experience before printing, does not combine the dynamic changes of graphic data, transmission state and printing quality feedback in the printing process for real-time adaptation, and when the task demand or printing environment changes, it is difficult to respond quickly, resulting in the decline of printing efficiency and quality. SUMMARY

[0004] The present application aims to provide a graphic printing method and system based on real-time printing, which aims to solve the technical problems in the prior art that the parameters are configured according to experience before printing, the dynamic changes of graphic data, transmission state and printing quality feedback in the printing process are not combined for real-time adaptation, and when the task demand or printing environment changes, it is difficult to respond quickly, resulting in the decline of printing efficiency and quality.

[0005] To achieve the above-mentioned purpose, the present application adopts a graphic printing method based on real-time printing, which comprises the following steps:

[0006] Receiving the configuration information of the current printing task, performing multi-dimensional extraction on the real-time collected graphic original data stream, obtaining the task attribute parameters, associating the task attribute parameters with the dimensional features, forming a mapping data set and outputting;

[0007] Building a dynamic compression strategy library, based on the label information of the mapping data set, calling the matching compression scheme in the strategy library to perform frame-level real-time compression on the graphic data stream;

[0008] Setting the printing parameter reference value corresponding to the task attribute, dynamically adjusting the printing parameters and the transmission strategy based on data dynamic compression transmission according to the collected data, forming a closed loop control.

[0009] In the step of receiving the configuration information of the current printing task, performing multi-dimensional extraction on the real-time collected graphic original data stream, obtaining the task attribute parameters, associating the task attribute parameters with the dimensional features, forming a mapping data set and outputting:

[0010] Receiving configuration information of a current printing task, and converting the configuration information into quantization parameters; wherein the configuration information includes a type of the printing task, a task priority, a precision requirement, a data real-time level, and the like;

[0011] Real-time acquisition of original data stream of a to-be-printed graph, and multi-dimensional feature extraction on the real-time acquired graph original data stream based on the quantization parameters; wherein the multi-dimensional features include basic features, regional color features, task-specific features, and real-time features.

[0012] After the step of real-time acquisition of original data stream of a to-be-printed graph, and multi-dimensional feature extraction on the real-time acquired graph original data stream based on the quantization parameters:

[0013] Respectively associating and integrating the quantization parameters and the basic features, the regional color features, the task-specific features, and the real-time features.

[0014] In the step of respectively associating and integrating the quantization parameters and the basic features, the regional color features, the task-specific features, and the real-time features:

[0015] Labeling each feature information with a corresponding task attribute label to form a structured task-feature mapping dataset, and continuously outputting in frames.

[0016] In the step of constructing a dynamic compression strategy library, based on the label information of the mapping dataset, calling a matched compression scheme in the strategy library to perform frame-level real-time compression on the graph data stream:

[0017] Constructing a dynamic compression strategy library, and pre-setting corresponding parameters according to different attributes of the printing task to form a matching rule;

[0018] Receiving the mapping dataset, reading the task attribute label and the feature information label in the dataset frame by frame, and obtaining the printing requirement and feature attribute of each frame of graph data;

[0019] Comparing the read label information with the matching rule in the dynamic compression strategy library, and screening out a compression scheme.

[0020] After the step of comparing the read label information with the matching rule in the dynamic compression strategy library, and screening out a compression scheme:

[0021] According to the screened compression scheme, performing frame-level real-time compression processing on the graph data stream.

[0022] In the step of according to the screened compression scheme, performing frame-level real-time compression processing on the graph data stream:

[0023] After compression of each frame of data is completed, the compressed data packet is output immediately, and during the compression process, key information is retained according to the graphic feature label.

[0024] In the step of setting the printing parameter reference value corresponding to the task attribute, dynamically adjusting the printing parameter and the transmission strategy based on the dynamic compression transmission of data, and forming a closed-loop control, the following steps are performed:

[0025] According to the attribute information of the printing task, the corresponding printing parameter reference value is set.

[0026] Real-time acquisition of multi-dimensional feedback data during the printing process is performed, including task attribute change data, data transmission state data, and printing quality detection data.

[0027] The collected feedback data is analyzed and judged.

[0028] In the step of analyzing and judging the collected feedback data, the following steps are performed:

[0029] If the feedback data is abnormal, dynamic adjustment is performed according to the abnormal type until the feedback data returns to normal, forming a closed-loop control.

[0030] The application also provides a graphic printing system based on real-time printing, which comprises a current task graphic data extraction module, a data dynamic compression transmission module, and a current task real-time adjustment module.

[0031] The current task graphic data extraction module is used to receive the configuration information of the current printing task, perform multi-dimensional extraction on the real-time acquired graphic original data stream, acquire the task attribute parameters, associate the task attribute parameters with the dimensional features, form a mapping data set, and output the mapping data set.

[0032] The data dynamic compression transmission module is used to construct a dynamic compression strategy library, call the matching compression scheme in the strategy library based on the label information of the mapping data set, and perform frame-level real-time compression on the graphic data stream.

[0033] The current task real-time adjustment module is used to set the printing parameter reference value corresponding to the task attribute, dynamically adjust the printing parameter and the transmission strategy based on the dynamic compression transmission of data, and form a closed-loop control.

[0034] The application discloses a real-time printing-based graphic printing method and system, adopts the current task graphic data extraction module, the data dynamic compression transmission module and the current task real-time adjustment module to perform the following steps: receiving configuration information of a current printing task, performing multi-dimensional extraction on a real-time collected graphic original data stream, obtaining task attribute parameters, associating the task attribute parameters with various dimensional features, forming a mapping data set and outputting; constructing a dynamic compression strategy library, based on label information of the mapping data set, calling a matched compression scheme in the strategy library to perform frame-level real-time compression on the graphic data stream; setting a printing parameter reference value corresponding to the task attribute, dynamically adjusting the printing parameter and a transmission strategy based on the data dynamic compression transmission according to the collected data, and forming a closed loop control; through the above manner, the dynamic change of the graphic data in the printing process, the transmission state and the printing quality feedback are combined for real-time adaptation, when the task demand or the printing environment changes, quick response can be realized, and the printing efficiency and quality are improved. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0036] Figure 1 is the step flow chart of the real-time printing-based graphic printing method of the present application.

[0037] Figure 2 is the step flow chart of S100 of the present application.

[0038] Figure 3 is the step flow chart of S200 of the present application.

[0039] Figure 4 is the step flow chart of S300 of the present application.

[0040] Figure 5 is the structure principle diagram of the real-time printing-based graphic printing system of the present application.

[0041] Figure 6 is the structure principle diagram of the electronic device of the present application.

[0042] 401-current task graphic data extraction module, 402-data dynamic compression transmission module, 403-current task real-time adjustment module. DETAILED DESCRIPTION

[0043] The exemplary embodiments will be described in detail herein with reference to the attached drawings. In the following description, like reference numerals refer to like elements throughout the description. The following exemplary embodiments described herein represent the best currently known modes of implementing the application.

[0044] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0045] It is to be understood that the singular forms "a", "an", and "the" include plural referents unless the context clearly dictates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0046] Reference will now be made to Figures 1-4 The present application provides a real-time printing-based graphic printing method, comprising the following steps:

[0047] S100: receiving configuration information of a current printing task, performing multi-dimensional extraction on a real-time collected graphic original data stream, obtaining task attribute parameters, associating the task attribute parameters with each dimension feature, forming a mapping data set and outputting.

[0048] In the present embodiment, the configuration information of the current printing task is received, the real-time collected graphic original data stream is subjected to multi-dimensional extraction, the task attribute parameters are obtained, the task attribute parameters are associated with each dimension feature, a mapping data set is formed and outputted. The specific process is as follows:

[0049] S101: receiving configuration information of a current printing task, and converting the configuration information into quantization parameters; wherein the configuration information comprises a type of the printing task, a task priority, an accuracy requirement, a data real-time level, etc.

[0050] S102: obtaining a real-time original data stream of a graphic to be printed, and performing multi-dimensional feature extraction on the real-time collected graphic original data stream based on the quantization parameters; wherein the multi-dimensional features comprise basic features, regional color features, task-specific features, and real-time features.

[0051] S103: Integrate the quantization parameters and the basic features, regional color features, task-specific features, and real-time features respectively, label the corresponding task attribute tags for each feature information, form a structured task-feature mapping dataset, and continuously output in frame units.

[0052] In the above process, the configuration information of the current printing task is received, which includes the type of the printing task (such as mapping, data visualization, emergency labeling, etc.), the priority of the task (high / medium / low three levels), the precision requirement (such as the allowed range of contour error, the color deviation threshold, etc.), and the data real-time level (such as millisecond-level synchronization, second-level synchronization, etc.), and these configuration information is converted into quantization parameters that can be directly used for data extraction, such as "texture feature extraction accuracy is improved by 30%" for high-priority tasks, and "data extraction frame rate is not less than 50 frames / second" for millisecond-level real-time level. The original data stream of the to-be-printed graphics is obtained in real time by a data acquisition device (such as an industrial camera, a data receiving interface, etc.), which covers the image data (such as the graphics picture taken on site) and the vector data (such as the graphics coordinate information transmitted by external devices) of the graphics, ensuring that the data stream is continuously and stably output without interruption or delay accumulation.

[0053] Based on the quantization extraction parameters, multi-dimensional feature extraction is performed on the real-time collected graphics original data stream. Among them, the basic feature layer extracts the contour coordinates (recognizes the boundary of the graphics through edge detection) and the regional color information (distinguishes the color attributes of different regions of the graphics) of the graphics, which meets the general demand of various printing tasks; the task-specific feature layer extracts characteristic information according to the type of the task, such as extracting terrain slope texture and geological layer boundary for mapping tasks, extracting data fluctuation trend line and abnormal value labeling graphics for data visualization tasks, and extracting color contrast of highlighted warning area for emergency mapping tasks; the real-time feature layer extracts the generation time, update frequency, and data volume change amplitude of the data stream, providing reference for the subsequent link.

[0054] The task attribute quantization parameters are associated and integrated with the basic features, task-specific features, and real-time features, and the specific process is as follows:

[0055] Task attribute-basic feature association: associate the quantization parameters such as task type, priority, and precision requirement with the basic features (such as contour coordinates and regional color), and form the mapping relationship between task attribute and basic graphics feature; for example, high-precision tasks require more detailed contour extraction and color calibration.

[0056] Task attribute-task-specific feature association: according to the type of the task, associate the quantization parameters with the task-specific features; for example, in the mapping task, high-priority tasks need to extract more detailed terrain slope texture and geological layer boundary.

[0057] Task attribute-real-time feature association: associate data real-time level with real-time features to ensure that the generation time, update frequency, etc. of data stream meet the real-time requirements; for example, data stream with millisecond-level real-time requirement adopts higher update frequency.

[0058] Feature information labeling: label the corresponding task attribute tags for each associated feature information, including task type, priority, accuracy requirement, data real-time level, etc. to facilitate quick identification and application in subsequent processing.

[0059] Label the corresponding task attribute tags for each feature information (such as "geological stratification boundary feature - high priority - contour error ≤0.1mm"), form a structured task-feature mapping dataset, and continuously output to the next processing module in frames to ensure that each frame of data contains complete task attribute and feature association information.

[0060] S200: Construct a dynamic compression strategy library, based on the label information of the mapping dataset, call the matching compression scheme in the strategy library to perform frame-level real-time compression on the graphics data stream.

[0061] In this embodiment, a dynamic compression strategy library is constructed, based on the label information of the mapping dataset, the matching compression scheme in the strategy library is called to perform frame-level real-time compression on the graphics data stream. The specific process is as follows:

[0062] S201: Construct a dynamic compression strategy library, according to different attributes of the printing task, preset corresponding parameters, and form matching rules;

[0063] S202: Receive the mapping dataset, read the task attribute tags and feature information tags in the dataset frame by frame, and obtain the printing requirements and feature attributes of each frame of graphics data;

[0064] S203: Compare the read label information with the matching rules in the dynamic compression strategy library, and select the compression scheme;

[0065] S204: According to the selected compression scheme, perform frame-level real-time compression processing on the graphics data stream, output the compressed data packet immediately after completing the compression of each frame of data, and at the same time, during the compression process, retain the key information according to the graphics feature label.

[0066] In the above process, a dynamic compression strategy library is constructed, and according to different attributes (priority, accuracy requirement, real-time level) and graphic features (complexity, detail richness) of the printing task, multiple sets of compression algorithms and corresponding parameters are preset to form clear matching rules. For example, a high-priority and high-precision task (such as fine mapping) corresponds to a low-compression-ratio algorithm, which focuses on preserving texture, boundary and other exclusive features; a medium-priority and general-precision task (such as general data visualization) corresponds to a medium-compression-ratio algorithm, which balances feature preservation and data volume; a low-priority and fast-printing task (such as emergency draft annotation) corresponds to a high-compression-ratio algorithm, which prioritizes reducing data volume to improve transmission speed.

[0067] Receiving the task-feature mapping dataset, reading the task attribute labels (such as task priority, accuracy requirement) and feature information labels (such as graphic complexity, detail type) in the dataset frame by frame, and clearly defining the corresponding printing requirements and feature attributes of each frame of graphic data.

[0068] Comparing the read label information with the matching rules in the dynamic compression strategy library to automatically filter out the most suitable compression scheme, the specific process is as follows:

[0069] First, the task-feature mapping dataset label information is classified and disassembled to form a structured comparison dimension, ensuring that each type of label information can correspond to the strategy library rules, which specifically includes:

[0070] Task attribute class label: disassembled into three core sub-dimensions, namely task priority (high / medium / low), accuracy requirement (divided into A class ≤0.1mm, B class 0.1-0.15mm, C class >0.15mm according to contour error threshold; divided into I class ≤5%, II class 5%-7%, III class >7% according to color deviation threshold), real-time level (millisecond-level synchronization / second-level synchronization);

[0071] Graphic feature class label: disassembled into two core sub-dimensions, namely graphic complexity (divided into simple graphics <3 colors + no complex texture, medium graphics 3-5 colors + a small amount of texture, complex graphics >5 colors + rich texture according to texture quantity and color variety), key feature type (features that need to be preserved, such as terrain contour, geological stratification boundary, data trend line, warning area color, etc.);

[0072] Data state class label: disassembled into one core sub-dimension, namely single-frame data volume (small data volume <1MB, medium data volume between 1-3MB, large data volume >3MB), which is used to assist in determining whether the compressed data volume is suitable for the transmission bandwidth.

[0073] For example, after analyzing the label information of a certain frame of data, the structured result is: task attribute (priority: high, accuracy requirement: class A + class I, real-time level: millisecond level); graphic feature (complexity: complex, key feature: geological stratification boundary); data state (single frame data volume: large > 3MB).

[0074] Based on the structured label dimensions, the preset rules in the dynamic compression strategy library are compared in a hierarchical manner of "priority dimension first-feature dimension supplemented-data state dimension verification", and each layer of comparison corresponds to a dedicated rule module in the strategy library:

[0075] The first layer is the priority of the task and the accuracy requirement of the double-dimension priority comparison:

[0076] The dynamic compression strategy library takes the task priority and accuracy requirement as the core matching dimensions, and presets three groups of basic rule modules to determine the overall direction of the compression scheme:

[0077] High priority + high accuracy (such as high priority + class A + class I accuracy) rule module: trigger "low compression ratio + lossless core feature" strategy, the rule clearly requires the compression ratio to be controlled between 3:1~5:1, and must use a compression algorithm that supports local feature protection (such as JPEG2000, PNG), and prohibits the use of high compression ratio algorithms that may lose key details (such as LZ77);

[0078] Medium priority + general accuracy (such as medium priority + class B + class II accuracy) rule module: trigger "medium compression ratio + balance feature preservation and data volume" strategy, the rule requires the compression ratio to be controlled between 8:1~10:1, and can choose an algorithm that considers efficiency and quality (such as WebP, JPEGXR), allowing moderate compression of non-key features;

[0079] Low priority + low accuracy (such as low priority + class C + class III accuracy) rule module: trigger "high compression ratio + priority guarantee transmission speed" strategy, the rule allows the compression ratio to reach 15:1~20:1, and can use a fast compression algorithm (such as LZ77, JPEG) to reduce data volume as the primary goal, with higher tolerance for detail loss.

[0080] Taking the analyzed label as an example, "high priority + class A + class I accuracy" triggers the "low compression ratio + lossless core feature" strategy in the first layer rule, initially locks the compression ratio range to 3:1~5:1, and the candidate algorithms are JPEG2000 and PNG.

[0081] The second layer is the graphic complexity and key feature type supplementary comparison:

[0082] In the first layer, the candidate scheme range is further narrowed down by combining the graphic feature class label for supplementary screening, and the feature adaptation rule module in the corresponding strategy library is matched:

[0083] Graphic complexity adaptation rule: for complex graphics (> 5 colors + rich texture), the rule requires selecting the lower limit value within the basic compression ratio range (such as 3:1~5:1 in the basic range, prefer 3:1~4:1), to avoid texture and color detail loss due to too high compression ratio; for simple graphics, the upper limit value of the basic range can be selected to balance efficiency and quality;

[0084] Key feature protection rule: if the label is marked as "key feature type", the rule requires matching the algorithm that supports "feature area differentiated compression", for example, for linear key features such as "geological stratification boundary" and "data trend line", JPEG2000 (supporting area-adjusted compression ratio) is preferred, which can use 3:1 compression ratio for key feature area and 5:1 for non-key area; for color key features such as "warning area color", PNG (supporting lossless color compression) is preferred to avoid color deviation exceeding the accuracy requirement.

[0085] Continuing the above example, the graphic feature label is "complexity: complex, key feature: geological stratification boundary", combined with the second layer rule: complex graphics need to select the lower limit 3:1~4:1 of the basic compression ratio, and the key feature "geological stratification boundary" needs to support differentiated compression, so from the preliminary candidate algorithms (JPEG2000, PNG), JPEG2000 (PNG supports lossless compression, but does not have the ability to support area differentiated compression, which cannot meet the multi-area compression requirement of complex graphics) is selected. At this time, the selected scheme is refined to "JPEG2000 algorithm + 3:1~4:1 compression ratio + geological stratification boundary area differentiated compression".

[0086] Third layer, data state and real-time level check comparison:

[0087] Finally, the data state class label (single frame data volume) and real-time level label are combined to check the feasibility of the candidate scheme selected in the previous two layers, and the transmission adaptation rule module in the corresponding strategy library is matched:

[0088] Data volume-compression ratio adaptation rule: according to the single frame data volume, the theoretical data volume after compression of the candidate scheme is calculated, if the single frame image data of large data volume (i.e. single frame data volume > 3MB), the data volume is about 1MB after 3:1 compression ratio, and about 0.75MB after 4:1 compression ratio, which need to meet the "single frame data volume after compression ≤ single frame transmission upper limit corresponding to transmission bandwidth" (such as 2.5MB corresponding to single frame transmission upper limit under millisecond real-time requirement, transmission bandwidth 20Mbps), to ensure that data transmission is not blocked;

[0089] Real-time algorithm efficiency adaptation rule: millisecond-level real-time requirement compresses algorithm single-frame processing time ≤ 20ms, JPEG2000 algorithm under 3:1~4:1 compression ratio, single-frame processing time is about 15ms, which meets the requirements; if the processing time of the candidate algorithm exceeds the real-time threshold (such as an algorithm processing time of 30ms), the compression ratio range should be appropriately increased (such as from 3:1 to 4:1) to reduce the processing time and ensure synchronization with the data generation rhythm.

[0090] In the example, the single-frame data volume is "greater than 3MB", and after using the JPEG2000 algorithm with a compression ratio of 3:1, the data volume is about 1MB, and after using the JPEG2000 algorithm with a compression ratio of 4:1, the data volume is about 0.75MB, both of which are lower than the transmission upper limit of 2.5MB; and the processing time of JPEG2000 in this compression ratio range is 15ms, which meets the millisecond-level real-time requirement, and the candidate scheme passes the verification, and is determined as "JPEG2000 algorithm + 3:1~4:1 compression ratio + geological layered boundary area differential compression (key area 3:1, non-key area 4:1)".

[0091] Candidate scheme priority sorting and final determination:

[0092] If multiple candidate schemes meet the requirements after the above three comparisons (such as different algorithms meeting the requirements in compression ratio and processing efficiency), a priority sorting mechanism is started to determine the final scheme according to the following priority weights:

[0093] Accuracy matching degree weight (40%): preferentially select the scheme whose theoretical error (contour error, color deviation) after compression is closer to the accuracy requirement threshold;

[0094] Key feature preservation ability weight (30%): preferentially select the scheme with better protection effect on the labeled key features;

[0095] Transmission adaptation efficiency weight (20%): preferentially select the scheme with higher data volume adaptation to transmission bandwidth after compression;

[0096] Algorithm processing speed weight (10%): preferentially select the scheme with shorter single-frame processing time.

[0097] If there is only one candidate scheme that meets the requirements (such as the above example), it is directly determined as the final compression scheme without sorting.

[0098] The final determined compression scheme needs to be further refined to form a complete compression instruction, which specifically includes:

[0099] Core algorithm parameters: specify the compression algorithm (such as JPEG2000), the basic compression ratio (such as 4:1), and the differentiated compression area coordinate range (according to the location of the key feature "geological stratification boundary" in the graph, mark the area coordinates that need to use a 3:1 compression ratio);

[0100] Data processing parameters: specify the starting position of single-frame data compression, data slicing size (such as dividing 3MB data into 3 1MB slices and compressing them in turn);

[0101] Quality assurance parameters: specify the error monitoring threshold during compression (such as contour error ≤0.08mm, color deviation ≤4%), if the compressed data exceeds the threshold, the compression ratio needs to be automatically adjusted.

[0102] For example, the compression scheme instruction of the example final output is: using JPEG2000 algorithm, 3MB single-frame data is divided into 3 1MB slices and compressed in turn; the basic compression ratio is 4:1, and the compression ratio of the geological stratification boundary area with coordinates (X:100~500, Y:200~600) in the graph is 3:1; the error monitoring threshold after compression is: contour error ≤0.08mm, color deviation ≤4%.

[0103] According to the selected compression scheme, frame-level real-time compression processing is performed on the graph data stream. After completing the compression of each frame of data, the compressed data packet is immediately output without batch accumulation processing. At the same time, during the compression process, key information is retained according to the graph feature label, such as the feature data marked "geological stratification boundary", the compression ratio is reduced to avoid detail loss.

[0104] S300: Set the printing parameter reference value corresponding to the task attribute, dynamically adjust the printing parameter and the transmission strategy based on the dynamic compression transmission of data, and form a closed loop control.

[0105] In this embodiment, the printing parameter reference value corresponding to the task attribute is set, the printing parameter and the transmission strategy based on the dynamic compression transmission of data are dynamically adjusted according to the collected data, and a closed loop control is formed. The specific process is as follows:

[0106] S301: According to the attribute information of the printing task, set the corresponding printing parameter reference value;

[0107] S302: Real-time collection of multi-dimensional feedback data in the printing process, including task attribute change data, data transmission state data, and printing quality detection data;

[0108] S303: Analyze and judge the collected feedback data, if the feedback data is abnormal, dynamically adjust according to the abnormal type until the feedback data returns to normal, forming a closed loop control.

[0109] In the above process, according to the attribute information (priority, accuracy requirement, task type, etc.) of the printing task, the corresponding printing parameter reference value is set, covering the printing accuracy parameters (such as resolution 300dpi~2400dpi, printhead moving step 0.01mm~0.1mm), printing efficiency parameters (such as printing speed 10mm / s~50mm / s, data receiving buffer size), printing quality parameters (such as ink concentration 50%~100%, color calibration coefficient), to ensure that the reference value meets the basic requirements of the current task, for example, high priority and high accuracy tasks correspond to high resolution and low printhead moving step reference value.

[0110] In the printing process, real-time multi-dimensional feedback data is collected, including task attribute change data (such as a signal that the task suddenly changes from "rough mapping" to "fine labeling"), data transmission state data (such as network bandwidth, data packet loss rate, transmission delay, etc.), and printing quality detection data (by camera shooting the printed pattern, obtaining the profile error, color deviation, texture loss, etc.).

[0111] The collected feedback data is analyzed and judged. If the task attribute is not changed, the transmission state is stable (such as sufficient bandwidth and packet loss rate <1%), and the printing quality meets the requirements (the error does not exceed the task accuracy threshold), the current printing parameter reference value and the previous compression transmission strategy are maintained to ensure smooth printing process.

[0112] If the analysis finds that the feedback data is abnormal, such as task priority improvement, network bandwidth drop leading to transmission delay, and printed pattern profile error exceeding threshold, the printing parameters are dynamically adjusted according to the type of abnormality: when the task attribute changes, the printing parameters are adjusted upward or downward (such as increasing resolution and ink concentration when priority is improved), and the previous link is notified to switch the compression scheme; when the transmission is abnormal, the printing speed is temporarily reduced, the receiving buffer is expanded, and the compression ratio is adjusted (such as appropriately increasing the compression ratio of non-core features when the bandwidth is insufficient); when the printing quality deviates, the printhead moving step (when the error exceeds the limit, the step is reduced) and the color calibration coefficient (when the color deviation exceeds the limit, the coefficient is optimized) are adjusted accordingly until the feedback data returns to normal, forming a closed-loop control of collection-analysis-adjustment-re-collection.

[0113] Corresponding to the foregoing embodiment of the real-time printing-based graphic printing method, the present application also provides an embodiment of a real-time printing-based graphic printing system.

[0114] Figure 5 is a block diagram of a real-time printing-based graphic printing system according to an exemplary embodiment. Referring to Figure 5 , the system can include a current task graphic data extraction module 401, a data dynamic compression transmission module 402, and a current task real-time adjustment module 403; wherein:

[0115] The current task graphic data extraction module 401 is configured to receive configuration information of a current printing task, perform multi-dimensional extraction on a real-time collected graphic original data stream, obtain task attribute parameters, associate the task attribute parameters with each dimension feature, form a mapping data set, and output the mapping data set.

[0116] The data dynamic compression transmission module 402 is configured to construct a dynamic compression strategy library, call a matched compression scheme in the strategy library to perform frame-level real-time compression on the graphic data stream based on label information of the mapping data set.

[0117] The current task real-time adjustment module 403 is configured to set a printing parameter reference value corresponding to a task attribute, dynamically adjust a printing parameter and a transmission strategy based on data dynamic compression transmission based on collected data, and form a closed loop control.

[0118] In the embodiment, the current task graphic data extraction module 401 receives configuration information of a current printing task, performs multi-dimensional extraction on a real-time collected graphic original data stream, obtains task attribute parameters, associates the task attribute parameters with each dimension feature, forms a mapping data set, and outputs the mapping data set. The data dynamic compression transmission module 402 constructs a dynamic compression strategy library, calls a matched compression scheme in the strategy library to perform frame-level real-time compression on the graphic data stream based on label information of the mapping data set. The current task real-time adjustment module 403 sets a printing parameter reference value corresponding to a task attribute, dynamically adjusts a printing parameter and a transmission strategy based on data dynamic compression transmission based on collected data, and forms a closed loop control. Through the above manner, real-time adaptation is performed in combination with dynamic changes of graphic data in a printing process, transmission states, and printing quality feedback. When a task requirement or a printing environment changes, quick response can be achieved, and printing efficiency and quality can be improved.

[0119] As to the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be described in detail here.

[0120] For the system embodiment, since it basically corresponds to the method embodiment, the related parts can be referred to the part of the method embodiment. The above described device embodiment is only schematic, wherein the units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, i.e., can be located in one place or distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the present application. Those skilled in the art can understand and implement it without creative labor.

[0121] Correspondingly, the present application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the real-time printing based graphic printing method as described above. As Figure 6 As shown in the figure, a hardware structure diagram of an arbitrary data processing capable device where a real-time printing based graphic printing system provided by an embodiment of the present application is located, in addition to the processor, the memory and the network interface as shown in the figure, the arbitrary data processing capable device where the apparatus is located in the embodiment can also include other hardware according to the actual functions of the arbitrary data processing capable device, which will not be described in detail. Figure 6 As shown in the figure, a hardware structure diagram of an arbitrary data processing capable device where a real-time printing based graphic printing system provided by an embodiment of the present application is located, in addition to the processor, the memory and the network interface as shown in the figure, the arbitrary data processing capable device where the apparatus is located in the embodiment can also include other hardware according to the actual functions of the arbitrary data processing capable device, which will not be described in detail.

[0122] Correspondingly, the present application also provides a computer readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the real-time printing based graphic printing method as described above. The computer readable storage medium can be an internal storage unit of the arbitrary data processing capable device, such as a hard disk or a memory. The computer readable storage medium can also be an external storage device, such as a plug-in hard disk, a smart media card (SMC), an SD card, a flash card, etc. Further, the computer readable storage medium can include both the internal storage unit and the external storage device of the arbitrary data processing capable device. The computer readable storage medium is used to store the computer program and other programs and data required by the arbitrary data processing capable device, and can also be used to temporarily store data that has been output or will be output.

[0123] Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. The present application is intended to cover any variations, uses or adaptive changes of the present application following the general principles thereof and including those expressly disclosed in the specification and those which are not specifically disclosed in the specification but which would be apparent to one of ordinary skill in the art.

[0124] It should be understood that the present application is not limited to the precise construction that has been described above and shown in the accompanying drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the application.

Claims

1. A graphic printing method based on real-time printing, characterized in that, Includes the following steps: The system receives the configuration information for the current printing task, performs multi-dimensional extraction on the real-time acquired raw graphic data stream, obtains task attribute parameters, associates these parameters with features of each dimension, forms a mapped dataset, and outputs it. The specific process is as follows: Receive the configuration information of the current print job and convert it into quantitative parameters; the configuration information includes the type of print job, job priority, accuracy requirements, and data real-time level. The system acquires the raw data stream of the graphic to be printed in real time and performs multi-dimensional feature extraction on the acquired raw data stream based on quantization parameters. The multi-dimensional features include basic features, regional color features, task-specific features, and real-time features; The quantization parameters and basic features, regional color features, task-specific features, and real-time features are associated and integrated respectively. Each feature information is labeled with the corresponding task attribute label to form a structured task-feature mapping dataset, which is continuously output in frames. A dynamic compression strategy library is constructed. Based on the label information of the mapped dataset, the matching compression scheme in the strategy library is called to perform frame-level real-time compression of the image data stream. Set the baseline values ​​of printing parameters corresponding to the task attributes, and dynamically adjust the printing parameters and the transmission strategy based on dynamic data compression transmission according to the collected data to form a closed-loop control. In the steps of setting the baseline values ​​of printing parameters corresponding to the task attributes, dynamically adjusting the printing parameters based on the collected data, and forming a closed-loop control based on the transmission strategy of dynamic data compression transmission: Set the corresponding baseline values ​​for printing parameters based on the attribute information of the printing task; Real-time collection of multi-dimensional feedback data during the printing process, including task attribute change data, data transmission status data, and print quality detection data; The collected feedback data is analyzed and judged; if there are abnormalities in the feedback data, the system is dynamically adjusted according to the type of abnormality until the feedback data returns to normal, thus forming a closed-loop control.

2. The graphic printing method based on real-time printing as described in claim 1, characterized in that, In the step of constructing a dynamic compression strategy library, and based on the label information of the mapped dataset, calling the matching compression scheme in the strategy library to perform frame-level real-time compression of the graphics data stream: Build a dynamic compression strategy library, and preset corresponding parameters to form matching rules based on different attributes of printing tasks; Receive the mapped dataset, read the task attribute labels and feature information labels in the dataset frame by frame, and obtain the printing requirements and feature attributes of the current frame of graphic data. The read tag information is compared with the matching rules in the dynamic compression strategy library to select the compression scheme.

3. The graphic printing method based on real-time printing as described in claim 2, characterized in that, After comparing the read tag information with the matching rules in the dynamic compression strategy library to select the compression scheme: Based on the selected compression scheme, the graphics data stream is subjected to frame-level real-time compression processing.

4. The graphic printing method based on real-time printing as described in claim 3, characterized in that, In the step of performing frame-level real-time compression processing on the graphics data stream based on the selected compression scheme: After each frame of data is compressed, the compressed data packet is immediately output. At the same time, during the compression process, key information is retained based on the graphic feature labels.

5. A graphic printing system based on real-time printing, applied to the graphic printing method based on real-time printing as described in claim 1, characterized in that, This includes a current task graphics data extraction module, a dynamic data compression and transmission module, and a current task real-time adjustment module; among which: The current task graphic data extraction module is used to receive the configuration information of the current printing task, extract the raw graphic data stream collected in real time from multiple dimensions, obtain task attribute parameters, associate the task attribute parameters with the features of each dimension, form a mapping dataset and output it. The data dynamic compression and transmission module is used to construct a dynamic compression strategy library, and based on the label information of the mapped dataset, call the compression scheme matched in the strategy library to perform frame-level real-time compression of the graphics data stream. The current task real-time adjustment module is used to set the baseline value of printing parameters corresponding to the task attributes, dynamically adjust the printing parameters and the transmission strategy based on dynamic data compression transmission according to the collected data, and form a closed-loop control.

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