Examination data uploading method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses an examination data uploading method and device, electronic equipment and a storage medium. According to the method, after a scanning copy of a test paper after a paper test of an examinee is received, the scanning copy is associated with machine test data after the machine test of the examinee to obtain associated information between the paper test and the machine test of the examinee, the paper test and the machine test belong to the same test, and then the scanning copy and the machine test data are uploaded to a preset cloud platform based on the associated information. Furthermore, in the process that the examinee performs an examination, if the machine examination and the paper examination exist at the same time, data of the paper examination and data after the machine examination of the examinee can be accurately uploaded without errors, errors in the subsequent online paper marking process are avoided, meanwhile, the pressure of an online paper marking system can be reduced, and the online paper marking efficiency is greatly improved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and particularly to a method, device, electronic device and storage medium for uploading examination data. Background Art

[0002] Under the background of educational informatization, as a product of the combination of education and the Internet, the online marking system has been widely used in various examinations. Online Marking (OMR) is a way of using digital technology and network platforms to mark examination papers, and is widely used in scenarios such as the high school entrance examination, college entrance examination, qualification certification examinations, and school final examinations. Its core processes include paper scanning, image processing, network transmission, marking management, score synthesis, etc. To ensure the security of online marking, it is necessary to ensure from multiple aspects such as technology, management, and law. However, in the actual operation process, how to improve the efficiency of marking, ensure the accuracy of candidates' scores, and further improve the quality and efficiency of educational evaluation are the main challenges currently faced. Summary of the Invention

[0003] This application provides a method, device, electronic device and storage medium for uploading examination data, which can avoid mistakes in the subsequent online marking process, ensure the accuracy of candidates' scores, and at the same time reduce the pressure on the online marking system, greatly improving the efficiency of online marking.

[0004] In a first aspect, this application provides a method for uploading examination data, which includes:

[0005] Receiving a scanned copy of the candidate's paper-based examination paper;

[0006] Associating the scanned copy with the computer-based examination data after the candidate's computer-based examination to obtain the association information between the candidate's paper-based examination and computer-based examination; the paper-based examination and the computer-based examination belong to the same examination;

[0007] Based on the association information, uploading the scanned copy and the computer-based examination data to a preset cloud platform.

[0008] In a second aspect, this application further provides an apparatus for uploading examination data, which includes:

[0009] A receiving unit, configured to receive a scanned copy of the candidate's paper-based examination paper;

[0010] An associating unit, configured to associate the scanned copy with the computer-based examination data after the candidate's computer-based examination to obtain the association information between the candidate's paper-based examination and computer-based examination; the paper-based examination and the computer-based examination belong to the same examination;

[0011] An uploading unit, configured to upload the scanned copy and the computer-based examination data to a preset cloud platform based on the association information.

[0012] In a third aspect, an embodiment of the present application further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the method for uploading examination data provided in the first aspect above is implemented.

[0013] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to execute the method for uploading examination data provided in the first aspect above.

[0014] In a fifth aspect, an embodiment of the present application further provides a computer program product, including a computer program or instruction, and the computer program or instruction is executed by a processor to implement the method for uploading examination data provided in the first aspect.

[0015] An embodiment of the present application provides a method, device, electronic device, and storage medium for uploading examination data. After receiving a scanned copy of the paper-based examination paper of a candidate, the method associates the scanned copy with the computer-based examination data of the candidate after the computer-based examination to obtain the association information between the paper-based examination and the computer-based examination of the candidate. At the same time, the paper-based examination and the computer-based examination belong to the same examination. Then, based on the association information, the scanned copy and the computer-based examination data are uploaded to a preset cloud platform. Thus, when a candidate takes an examination and there are both computer-based and paper-based examinations, the data after the candidate's paper-based and computer-based examinations can be accurately uploaded without error, avoiding mistakes in the subsequent online marking process, ensuring the accuracy of the candidate's scores, and at the same time reducing the pressure on the online marking system and greatly improving the efficiency of online marking. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for description in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 It is an architecture diagram of the method for uploading examination data provided by an embodiment of the present application;

[0018] Figure 2 It is a flowchart of the method for uploading examination data provided by an embodiment of the present application;

[0019] Figure 3 It is a schematic block diagram of the device for uploading examination data provided by an embodiment of the present application;

[0020] Figure 4 It is a schematic block diagram of the electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0022] It should be understood that when used in this specification and the appended claims, the terms "comprises" and "comprising" indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0023] It should also be understood that the terms used in this specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in this specification of the present application and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0024] It should be further understood that the term " / and" as used in this specification of the present application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0025] Please refer to Figure 1 , Figure 1 which is the architecture diagram of the method for uploading examination data provided by the embodiments of the present application. The method for uploading examination data provided by the embodiments of the present application is applied to the cloud box 103. The cloud box 103 is respectively connected to the scanning device 101 and the computer-based examination device 104 and communicates therewith. The scanning device 101 can scan the test papers of the candidates after the paper-based examination to form scanned copies. At the same time, the candidates take the examination in the cloud computer room. The examination items include computer-based examination and paper-based examination, that is, the same examination requires both paper-based examination and computer-based examination. For example, the GRE examination, or examinations such as drawing and modeling.

[0026] After the candidate completes the paper-based exam, the paper-based exam papers are scanned by the scanning device 101 and sent to the cloud box 103. At the same time, after the candidate completes the computer-based exam, the computer-based exam data of the candidate in the computer-based exam device 104 can also be sent to the cloud box 103. After receiving the scanned copy of the candidate's paper-based exam papers and the computer-based exam data sent by the computer-based exam device 104, the cloud box 103 can execute the exam data uploading method provided by this application, and then accurately upload the data of the candidate's paper-based exam and computer-based exam to the cloud platform 102 without error. Subsequently, online marking can be carried out based on the cloud platform 102, which not only avoids mistakes in the subsequent online marking process, but also ensures the accuracy of the candidate's scores. At the same time, it can also reduce the pressure on the online marking system and greatly improve the efficiency of online marking.

[0027] The cloud box 103 mentioned in this application can be an intelligent cloud box 103. The intelligent cloud box 103 is a device that combines cloud computing technology with local hardware devices, supports multiple connection methods, including Wi-Fi, Ethernet, and 5G, etc. At the same time, the intelligent cloud box 103 can be flexibly connected to the local network or the Internet. The VR device and the display device are connected by the cloud box 103. It can achieve an intranet connection or a cloud connection between the VR device and the display device, and at the same time, it can provide flexible and efficient computing and data processing capabilities, which are suitable for various edge computing and Internet of Things application scenarios. At the same time, using the cloud box 103 can push the computing tasks from the cloud to the local, reduce latency, reduce bandwidth requirements, and provide a faster response speed and a better user experience.

[0028] It should be noted that the application scenarios described in the embodiments of this application below are for more clearly explaining the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. Those of ordinary skill in the art know that with the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0029] The following will detail the exam data uploading method provided by this application.

[0030] As Figure 2 shown, this method includes the following steps S210 to S230.

[0031] S210. Receive the scanned copy of the candidate's paper-based exam papers;

[0032] S220. Associate the scanned copy with the computer-based exam data of the candidate after the computer-based exam to obtain the association information between the candidate's paper-based exam and computer-based exam; the paper-based exam and the computer-based exam belong to the same exam;

[0033] S230. Based on the association information, upload the scanned copy and the computer-based exam data to the preset cloud platform 102.

[0034] In this application, the scanned copy is the scanned copy formed after the paper-based test papers of the candidates are scanned by a scanning device. It can be a scanned copy in PDF format, a scanned copy in JPEG format, or a scanned copy in PNG format. The format of the scanned copy can be selected according to actual applications, and this application does not make specific limitations.

[0035] Specifically, the paper-based test and computer-based test mentioned in this application can be understood as that while the computer-based test is being conducted on the computer-based test device, a paper-based test is also being conducted, that is, the computer-based test and the paper-based test are conducted simultaneously. Therefore, after the cloud box receives the scanned copy, it has actually received the computer-based test data after the candidates' computer-based test. In order to be able to transmit the candidates' paper-based test papers and computer-based test papers to the cloud platform simultaneously and avoid subsequent re-classification and storage on the cloud platform, this application can directly associate the scanned copy with the computer-based test data after the candidates' computer-based test in the cloud box to obtain the association information between the candidates' paper-based test and computer-based test. Then, based on the association information, the scanned copy and the computer-based test data are uploaded to the preset cloud platform, so that the data after the candidates' paper-based test and computer-based test can be accurately uploaded to the cloud platform 102. Subsequently, online marking can be carried out based on the cloud platform 102, which not only avoids mistakes in the subsequent online marking process, but also ensures the accuracy of the candidates' scores. At the same time, it can also reduce the pressure on the online marking system and greatly improve the efficiency of online marking.

[0036] Among them, the association information can be understood as the identification information of the candidates taking a certain exam, and it can also be understood as the identity information of the candidates. The association information can be represented by at least one of the admission ticket number, ID number, and name.

[0037] In some embodiments, in step S220, the scanned copy can be preprocessed to extract the first information of the candidates from the scanned copy; extract the second information of the candidates from the computer-based test data; and based on the first information and the second information, associate the scanned copy with the computer-based test data to obtain the association information.

[0038] In this application, in the process of preprocessing the scanned copy to extract the first information of the candidates, the scanned copy can be subjected to image enhancement, layout analysis, and character recognition to extract the first information of the candidates. The first information can be at least one of the ID number, admission ticket number, and name filled in by the candidates on the test paper.

[0039] Specifically, in the process of image enhancement, if there are problems such as inclination, black-and-white inversion, or noise in the scanned copy, image processing tools such as Open CV can be used for correction and noise reduction. For example, after reading the image using the corresponding function in Open CV, it is converted into a binary image by setting a threshold, and then operations such as rotation and projection transformation are performed on the image to correct the inclination and black-and-white problems, and the noise is removed by median filtering and other methods.

[0040] During the process of page layout analysis of this application, the enhanced image can be used for page layout analysis to determine the positions and boundaries of text regions, table regions, and other elements. Specifically, it can be achieved through methods such as connected component analysis and projection analysis, so as to provide more accurate region positioning for subsequent text recognition.

[0041] During the process of text recognition, optical character recognition (OCR) technology, such as tools like Tesseract, can be used to convert the text regions in the image into an editable text format, and extract the candidate's admission ticket number, name, gender, ID number, etc.

[0042] At the same time, during the process of extracting the candidate's second information from the computer-based examination data of this application, steps such as data import and cleaning, and information extraction can be carried out respectively to extract the candidate's second information from the computer-based examination data. At the same time, the second information can be at least one of the ID number, admission ticket number, and name filled in by the candidate on the test paper.

[0043] During the process of data import and cleaning of this application, the computer-based examination data can be imported into a database or a data processing tool to clean the data, remove duplicate, incorrect, or invalid information, and ensure the accuracy and integrity of the data. For example, check for null values and outliers in the data and perform corresponding processing.

[0044] During the process of information extraction of this application, according to actual needs, SQL query statements or other data processing codes can be written to extract the candidate's examination scores, answer records, examination time, etc. (second information) from the computer-based examination data table. For example, extract the candidate's subject scores, total scores, etc. from the score table, and extract the candidate's answer order, answering time for each question, etc. from the answer record table.

[0045] Furthermore, during the process of associating the scanned copy with the computer-based examination data based on the first information and the second information of this application, the first information and the second information can be associated to obtain associated information. Specifically, the association key, data association operation, and result verification and output can be determined to output the associated information.

[0046] During the process of determining the association key of this application, the candidate's admission ticket number can be used as the association key because the admission ticket number is unique and identifying information in both the scanned copy and the computer-based examination data, and can accurately match the corresponding candidate.

[0047] Meanwhile, during the data association operation of this application, the JOIN statement of SQL can be used to associate the first information table extracted from the scanned document with the second information table extracted from the computer-based examination data according to the admission ticket number, generating a new data table containing all the associated information of the candidates. For example, an inner join is performed between the scanned document information table (including the first information such as the admission ticket number and name) and the computer-based examination score table (including the second information such as the admission ticket number and score) to obtain an associated table containing the basic information and score information of the candidates.

[0048] Finally, during the result verification and output process of this application, the associated data can be verified to ensure that the scanned document information and computer-based examination data of each candidate can be correctly matched without omission or incorrect association, and then the associated information can be output in a suitable format, such as generating an Excel table, a CSV file, or a database view, etc., for subsequent use and analysis.

[0049] In some embodiments, preprocessing is performed on the scanned document to extract the first information of the candidate from the scanned document, including: cropping the scanned document to obtain a cropped scanned document; denoising the cropped scanned document to obtain a denoised scanned document; converting the format of the denoised scanned document to obtain a format-converted scanned document; and extracting the first information from the format-converted scanned document.

[0050] In this application, during the process of cropping the scanned document, the cropping area can be determined and the cropping operation can be performed to ensure that the first information can be accurately extracted subsequently.

[0051] Among them, during the process of determining the cropping area, the effective area containing the candidate information in the scanned document, such as the positions where the admission ticket number, name, photo, etc. are located, can be determined through the image viewing and marking functions in image processing software (such as Photoshop, GIMP, etc.) or programming languages (such as the OpenCV library in Python) for subsequent precise cropping.

[0052] During the process of performing the cropping operation, in the image processing software, the determined area can be manually cropped using the cropping tool; if programming libraries such as OpenCV are used, the image can be cropped by setting the coordinate parameters of the cropping area and using the corresponding cropping function to obtain a cropped scanned document containing only the key information part of the candidate.

[0053] Meanwhile, during the process of denoising the cropped scanned document in this application, a denoising algorithm can be preselected and then applied to denoise the cropped scanned image to obtain a denoised scanned document.

[0054] Among them, in the process of selecting a denoising algorithm, common ones include median filtering, Gaussian filtering, mean filtering, etc. Median filtering has a good effect on removing salt-and-pepper noise, Gaussian filtering is effective for removing Gaussian noise, and mean filtering is relatively simple but may blur the image edges. Therefore, this application can select an appropriate algorithm according to the type and characteristics of the noise in the scanned document.

[0055] In the process of applying the denoising algorithm, in an image processing software, the corresponding filter can be searched for and applied for denoising; in a programming environment, using filtering functions such as those in OpenCV (such as medianBlur() for median filtering, GaussianBlur() for Gaussian filtering, etc.), the cropped scanned document image is denoised to obtain a denoised scanned document.

[0056] In the process of this application performing format conversion on the denoised scanned document, the target format can be determined in advance, and after determining the target format, format conversion is performed. Among them, in the process of determining the target format, the image format to be converted can be determined according to the needs of subsequent processing. Common ones include JPEG, PNG, PDF, etc. For example, if OCR text recognition is to be performed, formats such as JPEG and PNG are more commonly used; if document integration is to be performed, the PDF format may be more suitable. And in the process of performing format conversion, the save or save as function of the image processing software can be used to save the denoised scanned document as the target format; in programming, with the help of the save() function in an image processing library (such as the Pillow library in Python), the corresponding format parameters are specified for format conversion to obtain a scanned document after format conversion.

[0057] Finally, in the process of this application extracting the first information from the scanned document after format conversion, a text recognition tool or technology can be selected, and then text recognition and information extraction are performed, and the first information can be obtained from the scanned document. Among them, in the process of selecting a text recognition tool or technology, commonly used ones include software such as Tesseract OCR and Adobe Acrobat, or corresponding OCR libraries are used in programming. These tools and technologies can recognize the text in the image and convert it into an editable text format.

[0058] In the process of performing text recognition and information extraction, the scanned document after format conversion can be loaded into the selected text recognition tool for text recognition operations. Among the recognized text results, by writing regular expressions or using the search function of the software, the first information of the candidate is extracted, such as the admission ticket number (usually a string of numbers or alphanumeric combinations), name (a sequence of Chinese characters), gender ("male" or "female", etc.), ID number (an 18-digit combination of numbers and letters), etc. key information, and it is stored in a suitable data structure or database for subsequent association with the computer-based examination data for use.

[0059] In this application, when cropping the scanned document to obtain the cropped scanned document, and then denoising the cropped scanned document to obtain the denoised scanned document; performing format conversion on the denoised scanned document to obtain the format-converted scanned document, and finally extracting the first information from the format-converted scanned document, it is necessary to adjust and optimize the parameters according to the actual situation of different scanned documents to ensure the accuracy and effectiveness of the processing effect.

[0060] In some embodiments, performing format conversion on the denoised scanned document to obtain the format-converted scanned document includes: enhancing the contrast of the denoised scanned document to obtain the scanned document with enhanced contrast; performing format conversion on the scanned document with enhanced contrast to obtain the format-converted scanned document.

[0061] In this application, before performing format conversion on the scanned document, it is also necessary to enhance the contrast to improve the accuracy of extracting the first information. For example, the contrast of the denoised scanned document can be enhanced to obtain the scanned document with enhanced contrast, and then format conversion is performed on the scanned document with enhanced contrast to obtain the format-converted scanned document.

[0062] Specifically, in the process of enhancing the contrast of the denoised scanned document, it is necessary to pre-select a contrast enhancement algorithm and then apply the contrast enhancement algorithm, and then it is possible to enhance the contrast of the denoised scanned document to obtain the scanned document with enhanced contrast.

[0063] Among them, in the process of selecting the contrast enhancement algorithm, histogram equalization or adaptive histogram equalization can be performed. Histogram equalization can redistribute the gray values of the image pixels to make the gray histogram of the image evenly distributed, thereby enhancing the contrast of the image. Adaptive histogram equalization can better enhance the contrast for different regions of the image. It divides the image into multiple small blocks and then performs histogram equalization on each small block. In OpenCV, the cv2.createCLAHE() function can be used to implement adaptive histogram equalization.

[0064] At the same time, in the process of applying the contrast enhancement algorithm, if an image processing software (such as Photoshop) is used, the contrast can be manually enhanced by adjusting the brightness and contrast sliders of the image, or the curve adjustment tool can be used to increase the contrast of the image by changing the shape of the curve.

[0065] In some embodiments, after extracting the second information of the candidate from the computer-based examination data, it further includes: if the first information does not match the second information, determining the similarity between the target area where the first information is located in the scanned document and the preset area; if the similarity is lower than the preset threshold, preprocessing the scanned document again to extract the first information of the candidate from the scanned document.

[0066] Specifically, after extracting the second information of the candidate from the computer-based examination data, the present application can match the first information with the second information to determine whether the candidate in the scanned document is consistent with the candidate in the computer-based examination data. If the first information does not match the second information, it indicates that the candidates in the computer-based examination and the paper-based examination are inconsistent. However, for the sake of insurance, the present application also needs to determine whether there is an error in extracting the first information. For this purpose, the present application can determine the similarity between the target area where the first information is located in the scanned document and the preset area; if the similarity is lower than the preset threshold, preprocessing the scanned document again to extract the first information of the candidate from the scanned document.

[0067] In the present application, during the process of determining the target area, the scanned document can be carefully viewed again through the image viewing and marking functions in image processing software or programming languages to determine the approximate position where the first information is located in the scanned document and mark it as the target area. This may be because during the previous information extraction process, due to various reasons (such as the quality problem of the scanned document, character recognition error, etc.), the first information was misrecognized or not accurately extracted, so it is necessary to reposition the target area.

[0068] Among them, the preset area refers to the area that should contain the first information preset according to the scanned document format and information layout under normal circumstances. For example, the admission ticket number is usually located at a fixed position in the upper right corner of the scanned document, and this position is the preset area. This preset area is determined based on the understanding of the standard scanned document format and is used to compare and judge whether there is a deviation in the position of the first information in the actual scanned document.

[0069] During the process of determining the similarity between the target area and the preset area, the similarity of gray values can be calculated, or the similarity calculation of template matching can be used to achieve it.

[0070] Among them, during the process of calculating the similarity based on gray values, the images of the target area and the preset area can be converted into grayscale images, and then the similarity of the gray histograms of the two areas can be calculated. The gray histogram reflects the distribution of pixels with different gray values in the image, and the similarity between the two areas can be measured by comparing the histograms of the two areas. Commonly used methods include histogram intersection, correlation coefficient, etc.

[0071] In the process of calculating similarity based on template matching, a preset region can be used as a template to perform template matching near the target region and calculate the similarity score of the match. Template matching determines the best matching position and similarity by sliding the template in the image and comparing the similarity between the template and the corresponding region of the image. Multiple template matching methods are provided in OpenCV, such as sum of squared differences matching, correlation coefficient matching, etc.

[0072] In addition, the preset threshold mentioned in this application can be set according to the actual application scenario and requirements, and it can be used to judge the degree of difference between the target region where the first information is located in the scanned document and the preset region. For example, the threshold can be set to 0.7, indicating that when the similarity is lower than 0.7, it is considered that the difference between the target region and the preset region is large, and the scanned document needs to be preprocessed again to extract the first information.

[0073] After the similarity is lower than the preset threshold, the scanned document can be preprocessed again to extract the first information of the examinee from the scanned document. Among them, in the process of preprocessing the scanned document again, the scanned document after the first preprocessing can be cropped, denoised, contrast enhanced, etc. again.

[0074] In the second cropping process: according to the re-determined target region, the scanned document is cropped more precisely to ensure that the cropped region contains the possible first information.

[0075] In the process of performing the second denoising, the cropped region can be denoised, and different denoising algorithms can be tried or the denoising parameters can be adjusted to better remove the noise and improve the image quality. In the process of performing the second contrast enhancement, the contrast of the denoised image can be enhanced to further highlight important information such as text in the image and make it easier to be recognized. In the process of performing the second format conversion, the image after contrast enhancement can be format-converted for subsequent information extraction operations.

[0076] In some embodiments, the second information of the examinee is extracted from the computer-based examination data, and the second information is matched with the first information to obtain the matching information between the first information and the second information, including: extracting multiple second information from multiple computer-based examination data that are not associated with the scanned document.

[0077] Specifically, when the present application extracts the second information of the examinee from the machine examination data and matches the second information with the first information, since there are multiple examinees, there will be multiple scanned copies and multiple machine examination data. To ensure the matching and association of each scanned copy with each machine examination data, the present application can extract multiple second information from multiple machine examination data that have not been associated with the scanned copies, and then match each second information with the first information respectively to determine at least one second information that matches the first information from the multiple second information; based on at least one second information that matches the first information, the scanned copy is associated with the machine examination data to obtain associated information.

[0078] In some embodiments, based on the associated information, uploading the scanned copy and the machine examination data to a preset cloud platform 102 includes: based on the associated information, determining whether there are multiple scanned copies; if so, uploading the multiple scanned copies and the machine examination data to the cloud platform 102.

[0079] In the present application, since there may be multiple copies of the test papers during the paper-based examination of the examinee, there will be multiple scanned copies after the scanning device performs scanning. For this reason, the present application can determine the corresponding examination item based on the associated information, and determine whether there are multiple scanned copies according to the examination item. If so, it is necessary to upload the multiple scanned copies and the machine examination data to the cloud platform 102, thereby ensuring the integrity of the examination data uploaded to the cloud platform.

[0080] In the method for uploading examination data provided in the embodiments of the present application, after receiving the scanned copy of the test paper after the examinee's paper-based examination, the scanned copy is associated with the machine examination data after the examinee's machine examination to obtain the associated information between the examinee's paper-based examination and machine examination. At the same time, the paper-based examination and the machine examination belong to the same examination. Then, based on the associated information, the scanned copy and the machine examination data are uploaded to a preset cloud platform 102. Furthermore, when the examinee takes an examination, if there are both machine examination and paper-based examination at the same time, the data after the examinee's paper-based examination and machine examination can be accurately uploaded without error, avoiding mistakes in the subsequent online marking process, and at the same time reducing the pressure on the online marking system, greatly improving the efficiency of online marking.

[0081] The embodiments of the present application further provide an examination data uploading device 300, which is used to execute any one of the foregoing embodiments of the examination data uploading method.

[0082] Specifically, please refer to Figure 3 , Figure 3 which is a schematic block diagram of the examination data uploading device 300 provided by the embodiments of the present application.

[0083] As Figure 3 shown, the examination data uploading device 300 provided by the present application includes: a receiving unit 310, an associating unit 320, and an uploading unit 330.

[0084] A receiving unit 310 is configured to receive a scanned copy of the test paper after the candidate takes the paper-based exam; an association unit 320 is configured to associate the scanned copy with the computer-based exam data after the candidate takes the computer-based exam to obtain the association information between the candidate's paper-based exam and computer-based exam; the paper-based exam and the computer-based exam belong to the same exam; an uploading unit 330 is configured to upload the scanned copy and the computer-based exam data to a preset cloud platform 102 based on the association information.

[0085] In some embodiments, the association unit 320 is further configured to preprocess the scanned copy to extract the first information of the candidate from the scanned copy; extract the second information of the candidate from the computer-based exam data; and associate the scanned copy with the computer-based exam data based on the first information and the second information to obtain the association information.

[0086] In some embodiments, the association unit 320 is further configured to crop the scanned copy to obtain a cropped scanned copy; denoise the cropped scanned copy to obtain a denoised scanned copy; convert the format of the denoised scanned copy to obtain a format-converted scanned copy; and extract the first information from the format-converted scanned copy.

[0087] In some embodiments, the association unit 320 is further configured to enhance the contrast of the denoised scanned copy to obtain a contrast-enhanced scanned copy; and convert the format of the contrast-enhanced scanned copy to obtain a format-converted scanned copy.

[0088] In some embodiments, the association unit 320 is further configured to, if the first information does not match the second information, determine the similarity between the target area where the first information is located in the scanned copy and a preset area; and if the similarity is lower than a preset threshold, preprocess the scanned copy again to extract the first information of the candidate from the scanned copy.

[0089] In some embodiments, the association unit 320 is further configured to extract multiple second information from multiple computer-based exam data that have not been associated with the scanned copy.

[0090] In some embodiments, the association unit 320 is further configured to match each second information with the first information respectively to determine at least one second information that matches the first information from the multiple second information; and associate the scanned copy with the computer-based exam data based on at least one second information that matches the first information to obtain the association information.

[0091] In some embodiments, the uploading unit is further configured to determine whether there are multiple scanned copies based on the association information; and if so, upload the multiple scanned copies and the computer-based exam data to the cloud platform 102.

[0092] The examination data uploading device 300 provided by the embodiments of the present application can, after receiving the scanned copy of the paper-based examination paper of a candidate, associate the scanned copy with the computer-based examination data of the candidate after the computer-based examination to obtain the association information between the paper-based examination and the computer-based examination of the candidate. At the same time, the paper-based examination and the computer-based examination belong to the same examination. Then, based on the association information, the scanned copy and the computer-based examination data are uploaded to the preset cloud platform 102. Furthermore, when a candidate takes an examination and there are both computer-based examinations and paper-based examinations, the data after the candidate's paper-based examination and computer-based examination can be accurately uploaded without error, avoiding mistakes in the subsequent online marking process and reducing the pressure on the online marking system, greatly improving the efficiency of online marking.

[0093] It should be noted that those skilled in the art can clearly understand that the specific implementation processes of the above-mentioned examination data uploading device 300 and each unit can refer to the corresponding descriptions in the foregoing method embodiments. For the sake of convenience and brevity of description, they will not be elaborated here.

[0094] The above-mentioned examination data uploading device 300 can be implemented in the form of a computer program, and this computer program can run on an electronic device as shown in Figure 4 the figure.

[0095] Please refer to Figure 4 , Figure 4 which is a schematic block diagram of the electronic device provided by the embodiments of the present application.

[0096] Refer to Figure 4 , the device 400 includes a processor 402, a memory, and a network interface 405 connected through a system bus 401. Among them, the memory can include a storage medium 403 and an internal memory 404.

[0097] The storage medium 403 can store an operating system 4031 and a computer program 4032. When the computer program 4032 is executed, the processor 402 can be made to execute the examination data uploading method.

[0098] The processor 402 is used to provide computing and control capabilities to support the operation of the entire device 400.

[0099] The internal memory 404 provides an environment for the operation of the computer program 4032 in the non-volatile storage medium 403. When the computer program 4032 is executed by the processor 402, the processor 402 can be made to execute the examination data uploading method.

[0100] The network interface 405 is used for network communication, such as providing the transmission of data information, etc. Those skilled in the art can understand that Figure 4The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the device 400 to which the solution of this application is applied. The specific device 400 may include more or fewer components than those shown in the figure, or combine some components, or have a different component arrangement.

[0101] Among them, the processor 402 is used to run the computer program 4032 stored in the memory to implement the following functions: receiving the scanned copy of the candidate's paper-based exam paper; associating the scanned copy with the computer-based exam data after the candidate's computer-based exam to obtain the association information between the candidate's paper-based exam and computer-based exam; the paper-based exam and the computer-based exam belong to the same exam; based on the association information, uploading the scanned copy and the computer-based exam data to the preset cloud platform 102.

[0102] In some embodiments, when the processor 402 realizes associating the scanned copy with the computer-based exam data after the candidate's computer-based exam to obtain the association information between the candidate's paper-based exam and computer-based exam, the following steps are specifically implemented: preprocessing the scanned copy to extract the first information of the candidate from the scanned copy; extracting the second information of the candidate from the computer-based exam data; based on the first information and the second information, associating the scanned copy with the computer-based exam data to obtain the association information.

[0103] In some embodiments, when the processor 402 realizes preprocessing the scanned copy to extract the first information of the candidate from the scanned copy, the following steps are specifically implemented: performing a cropping process on the scanned copy to obtain a cropped scanned copy; performing a denoising process on the cropped scanned copy to obtain a denoised scanned copy; performing a format conversion on the denoised scanned copy to obtain a format-converted scanned copy; extracting the first information from the format-converted scanned copy.

[0104] In some embodiments, when the processor 402 realizes performing a format conversion on the denoised scanned copy to obtain a format-converted scanned copy, the following steps are specifically implemented: enhancing the contrast of the denoised scanned copy to obtain a scanned copy with enhanced contrast; performing a format conversion on the scanned copy with enhanced contrast to obtain a format-converted scanned copy.

[0105] In some embodiments, after the processor 402 realizes extracting the second information of the candidate from the computer-based exam data, the following steps are specifically implemented: if the first information and the second information do not match, determining the similarity between the target area where the first information is located in the scanned copy and the preset area; if the similarity is lower than the preset threshold, preprocessing the scanned copy again to extract the first information of the candidate from the scanned copy.

[0106] In some embodiments, when the processor 402 extracts the second information of the examinee from the computer-based examination data and matches the second information with the first information to obtain the matching information between the first information and the second information, the following steps are specifically implemented: extracting multiple second information from multiple computer-based examination data that are not associated with the scanned documents;

[0107] In some embodiments, when the processor 402 associates the scanned document with the computer-based examination data based on the first information and the second information to obtain the association information, the following steps are specifically implemented: respectively matching each second information with the first information to determine at least one second information that matches the first information from multiple second information; based on at least one second information that matches the first information, associating the scanned document with the computer-based examination data to obtain the association information.

[0108] In some embodiments, when the processor 402 uploads the scanned document and the computer-based examination data to the preset cloud platform 102 based on the association information, the following steps are specifically implemented: determining whether there are multiple scanned documents based on the association information; if so, uploading the multiple scanned documents and the computer-based examination data to the cloud platform 102.

[0109] Those skilled in the art can understand that Figure 4 the embodiments of the device 400 shown in Figure 4 do not constitute a limitation on the specific composition of the device 400. In other embodiments, the device 400 may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements. For example, in some embodiments, the device 400 may only include a memory and the processor 402. In such an embodiment, the structures and functions of the memory and the processor 402 are the same as those in

[0110] the embodiments shown and will not be described herein again.

[0111] According to one aspect of the present application, there is also provided a computer program product or a computer program. The computer program product or the computer program includes computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to enable the electronic device to implement the following steps: receiving a scanned copy of a candidate's paper-based exam paper; associating the scanned copy with the computer-based exam data after the candidate's computer-based exam to obtain association information between the candidate's paper-based exam and computer-based exam; the paper-based exam and the computer-based exam belong to the same exam; based on the association information, uploading the scanned copy and the computer-based exam data to a preset cloud platform 102.

[0112] Those of ordinary skill in the art can understand that all or part of the processes of the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, and the storage medium is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0113] In another embodiment of the present application, a computer storage medium is provided. The storage medium can be a non-volatile computer-readable storage medium or a volatile storage medium. The storage medium stores a computer program 4032, and when the computer program 4032 is executed by a processor 402, the following steps are implemented: receiving a scanned copy of a candidate's paper-based exam paper; associating the scanned copy with the computer-based exam data after the candidate's computer-based exam to obtain association information between the candidate's paper-based exam and computer-based exam; the paper-based exam and the computer-based exam belong to the same exam; based on the association information, uploading the scanned copy and the computer-based exam data to a preset cloud platform 102.

[0114] In some embodiments, when the processor executes the program instructions to associate the scanned copy with the computer-based exam data after the candidate's computer-based exam to obtain the association information between the candidate's paper-based exam and computer-based exam, the following steps are specifically implemented: preprocessing the scanned copy to extract first information of the candidate from the scanned copy; extracting second information of the candidate from the computer-based exam data; based on the first information and the second information, associating the scanned copy with the computer-based exam data to obtain the association information.

[0115] In some embodiments, when the processor executes the program instructions to preprocess the scanned copy to extract the first information of the candidate from the scanned copy, the following steps are specifically implemented: performing a cropping process on the scanned copy to obtain a cropped scanned copy; performing a denoising process on the cropped scanned copy to obtain a denoised scanned copy; performing a format conversion on the denoised scanned copy to obtain a format-converted scanned copy; extracting the first information from the format-converted scanned copy.

[0116] In some embodiments, when the processor executes program instructions to implement format conversion of the denoised scanned document to obtain the scanned document after format conversion, the following steps are specifically implemented: enhancing the contrast of the denoised scanned document to obtain the scanned document with enhanced contrast; performing format conversion on the scanned document with enhanced contrast to obtain the scanned document after format conversion.

[0117] In some embodiments, after the processor executes program instructions to extract the second information of the examinee from the computer-based examination data, the following steps are specifically implemented: if the first information does not match the second information, determining the similarity between the target area where the first information is located in the scanned document and the preset area; if the similarity is lower than the preset threshold, preprocessing the scanned document again to extract the first information of the examinee from the scanned document.

[0118] In some embodiments, when the processor executes program instructions to extract the second information of the examinee from the computer-based examination data and match the second information with the first information to obtain the matching information between the first information and the second information, the following steps are specifically implemented: extracting multiple second information from multiple computer-based examination data that are not associated with the scanned document;

[0119] In some embodiments, when the processor executes program instructions to implement associating the scanned document with the computer-based examination data based on the first information and the second information to obtain the association information, the following steps are specifically implemented: matching each second information with the first information respectively to determine at least one second information that matches the first information from multiple second information; based on at least one second information that matches the first information, associating the scanned document with the computer-based examination data to obtain the association information.

[0120] In some embodiments, when the processor executes program instructions to upload the scanned document and the computer-based examination data to the preset cloud platform 102 based on the association information, the following steps are specifically implemented: determining whether there are multiple scanned documents based on the association information; if so, uploading multiple scanned documents and the computer-based examination data to the cloud platform 102.

[0121] The storage medium can be various computer-readable storage media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disc that can store program codes.

[0122] Those of ordinary skill in the art will appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the components and steps of the examples have been generally described according to their functions in the above description. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0123] In several embodiments provided by this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of each unit is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0124] The steps in the method embodiments of this application can be adjusted, combined, and deleted according to actual needs. The units in the device embodiments of this application can be combined, divided, and deleted according to actual needs. In addition, the functional units in each embodiment of this application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0125] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing an electronic device (which can be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods provided in each embodiment of this application.

[0126] As described above, only the specific implementation manners of this application are provided, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed by this application can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A method for uploading examination data, characterized in that, Including: Receiving a scanned copy of the test paper after the candidate's paper-based exam; Associating the scanned copy with the computer-based exam data after the candidate's computer-based exam to obtain the association information between the candidate's paper-based exam and the computer-based exam; the paper-based exam and the computer-based exam belong to the same exam; Based on the association information, uploading the scanned copy and the computer-based exam data to a pre-set cloud platform.

2. The method for uploading examination data according to claim 1, wherein The associating the scanned copy with the computer-based exam data after the candidate's computer-based exam to obtain the association information between the candidate's paper-based exam and the computer-based exam includes: Preprocessing the scanned copy to extract the first information of the candidate from the scanned copy; Extracting the second information of the candidate from the computer-based exam data; Based on the first information and the second information, associating the scanned copy with the computer-based exam data to obtain the association information.

3. The method for uploading examination data according to claim 2, wherein, The preprocessing the scanned copy to extract the first information of the candidate from the scanned copy includes: Performing a cropping process on the scanned copy to obtain a cropped scanned copy; Performing a denoising process on the cropped scanned copy to obtain a denoised scanned copy; Performing a format conversion on the denoised scanned copy to obtain a format-converted scanned copy; Extracting the first information from the format-converted scanned copy.

4. The method for uploading examination data according to claim 3, wherein The performing a format conversion on the denoised scanned copy to obtain a format-converted scanned copy includes: Performing a contrast enhancement on the denoised scanned copy to obtain a contrast-enhanced scanned copy; Performing a format conversion on the contrast-enhanced scanned copy to obtain a format-converted scanned copy.

5. The method for uploading examination data according to claim 2, characterized in that, After the extracting the second information of the candidate from the computer-based exam data, it further includes: If the first information does not match the second information, determining the similarity between the target area where the first information is located in the scanned copy and a preset area; If the similarity is lower than a preset threshold, preprocessing the scanned copy again to extract the first information of the candidate from the scanned copy.

6. The method for uploading examination data according to claim 2, wherein The extracting the second information of the candidate from the computer-based exam data and matching the second information with the first information to obtain the matching information between the first information and the second information includes: Extracting multiple pieces of the second information from multiple pieces of computer-based exam data that have not been associated with the scanned copy; The based on the first information and the second information, associating the scanned copy with the computer-based exam data to obtain the association information includes: Matching each piece of the second information with the first information respectively to determine at least one piece of the second information that matches the first information from multiple pieces of the second information; Based on at least one piece of the second information that matches the first information, associating the scanned copy with the computer-based exam data to obtain the association information.

7. The method for uploading examination data according to claim 6, wherein The based on the association information, uploading the scanned copy and the computer-based exam data to a pre-set cloud platform includes: Based on the association information, determining whether there are multiple scanned copies; If so, uploading multiple scanned copies and the computer-based exam data to the cloud platform.

8. An uploading device for examination data, characterized in that, Including: A receiving unit for receiving a scanned copy of the test paper after the candidate's paper-based exam; An association unit, configured to associate the scanned document with the computer-based examination data after the candidate takes the computer-based examination, so as to obtain the association information between the candidate's paper-based examination and the computer-based examination; the paper-based examination and the computer-based examination belong to the same examination; An upload unit, configured to upload the scanned document and the computer-based examination data to a preset cloud platform based on the association information.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, the method for uploading examination data as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to execute the method for uploading examination data as described in any one of claims 1 to 7.

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