CN114003873A - Processing method, equipment and storage medium for private collection atlas directory - Google Patents
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Abstract
The application provides a processing method of a private collection atlas directory, which is applied to the technical field of culture collection databases and has the beneficial effects that: the big data and electronic file classification technology can be applied to summarize and sort a large number of collected product pictures to generate a collector atlas directory; private collections can be liberated from heavy paper catalogues, so that the data collection of a large number of precious private collections is realized, and the large data statistical analysis of massive collections is facilitated to be completed; the gradual change watermark is added to the collection picture, so that the anti-counterfeiting performance of the collection picture is effectively improved, the watermark cannot be completely removed from the picture, and the risk of stealing the collection picture is avoided; the private collection atlas directory is established, so that the configuration and mapping mode of shared files can be flexible, the directory is accessed by browsing paths, the access speed can be improved, the atlas is prevented from being copied, the database is prevented from being attacked, and the online viewing, online sharing and online transaction of electronic collection images among users are facilitated.
Description
Technical Field
The application relates to the technical field of cultural collection databases, in particular to a processing method, equipment and a storage medium for a private collection atlas directory.
Background
The collection picture is an important comparison data in the collection process, the variety of the collection is countless, even the collection gallery of hundreds of thousands of pictures has a large amount of loss, a large amount of manual photographing and editing are needed for establishing the collection gallery, the source of the collection is a problem which is difficult to solve, even if the collection of a collector is photographed and scanned on site and is recorded into the collection gallery, the risk of the loss or damage of the collection is also existed, the collection of the collection in a large amount is difficult to realize, and the collection gallery in the current stage mainly comprises the following three types: the first gallery is mainly searched by massive pictures, and the gallery does not have a directory function and lacks of specialty; the second professional collection organization is a data gallery, which can only look up pictures, cannot realize interaction between users, and lacks expandability; and a third collector self-defines a gallery, and although the gallery realizes the collection records of the user, the gallery lacks professional systematization and diversified management, and cannot realize the online communication interaction and online transaction problems of the user.
Disclosure of Invention
In view of this, the embodiment of the present application provides a method for processing a collection catalog of a private collection, which can liberate the private collection from a heavy paper catalog, realize the data collection of a large number of precious private collections, add a gradual watermark to the pictures of the private collection, and process the precision, so as to effectively improve the anti-counterfeiting performance of the pictures of the collections, and simultaneously establish the collection catalog of the pictures of the private collection, which is favorable for the full-text retrieval of the catalog, and the web page reading and browsing speed is fast, which does not affect the network speed, and can avoid being copied, thereby facilitating the sharing of the electronic collection pictures among users.
In a first aspect, an embodiment of the present application provides a method for processing a private collection atlas directory, including:
sharpening the binary gray level image of the private collection image through a machine vision model to obtain a high-definition gray level image;
adding a gradient watermark to the high-definition gray-scale image in an equivalent accumulation mode to obtain an anti-counterfeiting high-definition image added with the gradient watermark, and performing precision reduction processing on the anti-counterfeiting high-definition image added with the gradient watermark to obtain a prepositive calling image;
recognizing character information from the prepositive calling picture through a picture-text recognizer;
intelligently matching the character information collection category in the prepositive calling picture with a preset dictionary and a regular expression, and storing a matching result in an atlas database of the character information collection category;
calculating a first cosine similarity between the semantic vector of the collection atlas category in each atlas database and the semantic vectors of all text classifications of the topic units in the preset catalogue, and calculating a second cosine similarity between the semantic vector of the text information collection category in the preposed calling picture and the semantic vector of the text classification of the topic units in the preset catalogue;
and determining the collection atlas catalog of the private user according to the incidence relation between the collection atlas category and the first cosine similarity of all text classifications of the topic units in the preset catalog and the second cosine similarity of the text classification of the subcatalog units in the preposed calling picture.
With reference to the first aspect, an embodiment of the present application provides a first possible implementation manner of the first aspect, where sharpening is performed on a binary grayscale image of a private collection picture through a machine vision model to obtain a high-definition grayscale image, and the method includes:
detecting a peak value of the binary gray-scale image through a Laplace energy function or an energy gradient function or a variance function of the machine vision model, and determining a first definition image according to the peak value;
sharpening the first definition picture according to a preset gray threshold to obtain a second definition picture;
and fusing the first definition picture and the second definition picture to obtain a high-definition gray image.
With reference to the first possible implementation manner of the first aspect, an embodiment of the present application provides a second possible implementation manner of the first aspect, where an equivalent accumulation manner is adopted, a gradient watermark is added to the high-definition grayscale image, so as to obtain an anti-counterfeiting high-definition image to which the gradient watermark is added, and precision reduction processing is performed on the anti-counterfeiting high-definition image to which the gradient watermark is added, so as to obtain a pre-call image, and the method includes:
calculating by adopting the equivalent accumulation mode aiming at each pixel point of the high-definition gray scale image to obtain a counter value and a true value corresponding to each pixel point;
aiming at the inverse code value and the true value of each pixel point, carrying out color replacement on RGB (red, green and blue) three-color spectrum numerical values corresponding to the preset character gradient watermarks line by line according to random offset to obtain the anti-counterfeiting high-definition picture added with the gradient watermarks;
and respectively calculating a first loss value and a second loss value of the anti-counterfeiting high-definition picture according to the inverse code value and the true value of each digital pixel point of the anti-counterfeiting high-definition picture, and fusing the calculated first loss value and the calculated second loss value to obtain a fused access high-definition picture as a preposed calling picture.
With reference to the first possible implementation manner or the second possible implementation manner of the first aspect, an embodiment of the present application provides a third possible implementation manner of the first aspect, where calculating a first loss value according to an inverse value and a true value of each digital pixel point of the anti-counterfeiting high definition picture includes:
the first loss value is calculated according to the following formula:
wherein: q. q.smnRepresenting the code reversal value of the nth digital pixel point in the mth anti-counterfeiting high-definition picture data set; p is a radical ofmnRepresenting the true value of the nth digital pixel point in the mth anti-counterfeiting high-definition picture data set; loss (q)mn,pmn) Representing a first loss value between an inverse code value and a true value of an nth digital pixel point in an mth anti-counterfeiting high-definition picture data set, and c representing a digital pixel in the mth anti-counterfeiting high-definition picture data setThe total number of dots; t represents the total number of pixel classes.
With reference to the first possible implementation manner or the second possible implementation manner of the first aspect, an embodiment of the present application provides a fourth possible implementation manner of the first aspect, where calculating a second loss value according to an inverse value and a true value of each digital pixel point of the anti-counterfeiting high definition picture includes:
the second loss value is calculated according to the following formula:
wherein q isuvRepresenting the code reversal value of the v-th digital pixel point in the u-th anti-counterfeiting high-definition picture data set; p is a radical ofuvRepresenting the true value of the v-th digital pixel point in the u-th anti-counterfeiting high-definition picture data set; loss (q)uv,puv) Representing a second loss value between the inverse code value and the true value of the v-th digital pixel point in the u-th anti-counterfeiting high-definition picture data set; h represents the total number of digital pixel points in the u-th anti-counterfeiting high-definition picture data set; g represents the total number of digital pixel points.
With reference to the first possible implementation manner or the second possible implementation manner of the first aspect, an embodiment of the present application provides a fifth possible implementation manner of the first aspect, where the intelligently matching the text information collection category in the pre-call picture with a preset dictionary and a regular expression, and storing the matching result in an atlas database of the text information collection category includes:
aiming at the recognized character information collection category of each prepositive calling picture, determining a text vector corresponding to the character information of each prepositive calling picture by using a multi-dimensional semantic algorithm according to the semantics of the character information;
intelligently matching and matching the text vector of each preposed calling picture with a preset dictionary and a regular expression through the image-text recognizer to obtain a collection atlas category;
and respectively storing each preposed calling picture in the corresponding atlas database according to the category of the collection atlas.
With reference to the first possible implementation manner or the second possible implementation manner of the first aspect, an embodiment of the present application provides a sixth possible implementation manner of the first aspect, and the determining a collection atlas category of a private user according to an association relationship between the collection atlas category and first cosine similarities of all text classifications of topic units in a preset catalog and between the text information collection category in the preposition invocation picture and second cosine similarities of text classifications of the topic units in the preset catalog includes:
calculating a first cosine similarity according to the semantic vector of the collection atlas category in each atlas database and the semantic vectors of all text classifications of the topic units in a preset directory, wherein the collection atlas category comprises: coin class atlas, ticket class atlas, stamp class atlas, commemorative stamp class atlas, other miscellaneous class atlas; the number of the preset catalogues is multiple;
aiming at the calculated first cosine similarity, establishing an incidence relation between the collection atlas category and a title unit in a preset catalogue;
calculating a second cosine similarity according to the semantic vector of the text information collection category in the prepositive calling picture and the semantic vector of the text classification of the sub-directory unit in the preset directory, wherein the text information collection category of the prepositive calling picture comprises: the system comprises picture name information, picture province information, affiliated picture address information, picture provider information, picture release year information and picture release unit information;
establishing an incidence relation between the text information collection category in the prepositive calling picture and a sub-directory unit in a preset directory according to the calculated second cosine similarity;
and determining the collection atlas directory of the private user according to the incidence relation between the first cosine similarity and the second cosine similarity.
With reference to the first possible implementation manner or the second possible implementation manner of the first aspect, an embodiment of the present application provides a seventh possible implementation manner of the first aspect, and further includes:
responding to a calling request initiated by a private user, reading the collection atlas directory from the atlas database according to an API (application program interface) data interface, and displaying a front calling picture in the collection atlas directory;
responding to a calling request initiated by a private user, and displaying the preposed calling picture stored in the atlas database to a third-party user according to a catalogue rule of the atlas database;
responding to a calling request initiated by a private user, and carrying out online transaction according to the preposed calling picture in the collection atlas directory through a WeChat interface and a Paibao online interface.
In a second aspect, the present application further provides a computer device, including a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method for processing the private collection atlas directory of any one of the preceding claims 1 to 8 when executing the computer program.
In a third aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon a computer program, which when executed by a processor performs the steps of the method of processing, such as the private collection atlas directory.
According to the processing method of the private collection atlas directory, the collection atlas directory of the private user is adopted, and compared with the existing collection atlas directory which lacks a directory function and cannot record and store private collections in a personalized manner, the collection atlas directory can be established based on different databases to form a private electronic directory of collectors, and online check, directory sharing and private collection data statistics of the private user; the method comprises the steps of converting a collection object of a private collection enthusiast into a digital picture, importing the picture into a data warehouse in a binary data stream mode, carrying out gray processing on the collection picture in the data warehouse, obtaining a binary gray image after the processing, extracting a peak value of the binary gray image through a machine vision model, determining a first definition picture and a second definition picture according to the peak value, and fusing the definition pictures to obtain a high-definition gray image; by uploading the collection pictures to the data warehouse, the private collections can be released from heavy paper catalogues, so that the data collection of a large number of precious private collections is realized, and the large data statistical analysis of a large number of collections is facilitated; the method comprises the steps of adding a gradual-change watermark to a high-definition gray-scale image in an equivalent accumulation mode, performing precision reduction processing on an anti-counterfeiting high-definition image added with the watermark to obtain a preposed calling image at the front end of a webpage, effectively improving anti-counterfeiting performance of a collection image, and simultaneously enabling the watermark to have randomness so that the watermark cannot be completely removed from the image, managing the collection image in a professional manner, and avoiding the risk of theft of the collection image; all the character information in the pre-call picture is recognized through the image-text recognizer respectively, the collection category of the character information in the pre-call picture is intelligently matched with a preset dictionary and a regular expression, the online specialization of a private collector and the construction of a systematized database are realized, and the classified storage of an atlas database is completed by recording the collection category of the private collection picture; determining the collection atlas catalog of a private user according to the incidence relation between the semantic vector of the collection atlas category in each atlas database and the semantic vectors of all text classifications of the topic units in the preset catalog and the semantic vector of the text classification of the sub-catalog units in the preposed calling picture; the method has the advantages that the incidence relation between the atlas database and the preposed calling picture and the preset directory is established, the configuration and mapping mode of the shared file can be flexible by establishing the incidence directory, the directory is accessed through a browsing path, the access speed can be improved, the collection atlas directory of a private user is beneficial to full-text retrieval of the directory, the webpage reading and browsing speed is high, the network speed cannot be influenced, the copying can be avoided, and the sharing of the electronic collection picture among users is facilitated.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a flowchart illustrating a processing method of a private collection atlas directory provided in an embodiment of the present application.
Fig. 2 is a schematic flow chart illustrating a method for processing a catalog of a personal collection atlas to obtain a high definition grayscale chart according to an embodiment of the present application.
Fig. 3 is a schematic flow chart illustrating a process of adding a gradual watermark and reducing precision in a processing method for a private collection atlas directory according to an embodiment of the present application.
Fig. 4 is a schematic flow chart illustrating intelligent matching of the text information collection type and the preset dictionary in the processing method of the album directory of the private collection according to the embodiment of the present application.
Fig. 5 is a schematic view illustrating a process of determining a collection atlas directory of a private user in a processing method of a private collection atlas directory according to an embodiment of the present application.
Fig. 6 is a flowchart illustrating a user-initiated call request in a method for processing a collection directory of private collections according to an embodiment of the present application.
Fig. 7 shows a schematic structural diagram of a computer device provided in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
The method has the advantages that collection enthusiasts are liberated from heavy paper catalogues, a large number of collected matter pictures are summarized and sorted by using big data and electronic file classification technology, a private electronic catalog of the collectors is formed by different filing modes, the collected matter data can be quickly and conveniently looked up and compared through a mobile phone terminal, the private collected matters are managed online, the states and characteristic data of the private collected matters are recorded, and meanwhile, the information such as the number of the collected matters, the types of the collected matters, the distribution set number of the collected matters, the collected matter sharing data and the like can be counted.
Considering that the private collection gallery at the present stage lacks a directory function, cannot store personalized records, and cannot realize gallery expansibility; based on this, the embodiment of the present application provides a processing method for a private collection atlas directory, which is described below by way of an embodiment.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
Fig. 1 is a flow chart illustrating a processing method of a private collection atlas directory provided in an embodiment of the present application; as shown in fig. 1, the method specifically comprises the following steps:
and step S10, sharpening the binary gray-scale image of the private collection image through the machine vision model to obtain a high-definition gray-scale image.
Step S10, in a specific implementation, before obtaining the high-definition grayscale image, the processing method further needs to perform graying processing on the private collection image in the data warehouse to obtain a binary grayscale image; the method comprises the steps of detecting a peak value of a binary gray scale image through five definition algorithm functions of a machine vision model, determining a first definition image according to the peak value, sharpening the first definition image to obtain a second definition image, fusing data of the first definition image and the second definition image to obtain a high-definition gray scale image, converting a private collection object into a digital collection image through the steps, fusing the data of the collected digital collection image through the machine vision model to obtain a high-definition collection image, uploading the collection image to a data warehouse, freeing the private collection from a heavy paper catalogue, realizing the data collection of a large number of precious private collections, and contributing to the large data statistical analysis of mass collections.
And step S20, adding a gradient watermark to the high-definition gray-scale image in an equivalent accumulation mode to obtain the anti-counterfeiting high-definition image added with the gradient watermark, and performing precision reduction processing on the anti-counterfeiting high-definition image added with the gradient watermark to obtain a prepositive calling image.
Step S20 is implemented specifically, according to the gray value of each pixel point of the high-definition gray image, generating a nonzero-to-one double-transformation inverse code value and a true value, and performing color replacement on the RGB color values of the preset character watermark line by line from the random offset according to three groups of numerical value forms of red, green and blue by adopting an equivalent accumulation mode aiming at the inverse code value and the true value to obtain the anti-counterfeiting high-definition image added with the gradient watermark; calculating a first loss value and a second loss value of each digital pixel point of the anti-counterfeiting high-definition picture according to the counter value and the real value of each digital pixel point in the anti-counterfeiting high-definition picture after the gradual change watermark is added, and fusing the calculated first loss value and the calculated second loss value to obtain a fused high-definition picture as a prepositive calling picture; the steps add the gradual change watermark to the private collection picture and process the precision, so that the anti-counterfeiting performance of the collection picture can be effectively improved, and meanwhile, the watermark has randomness, so that the watermark cannot be completely removed from the picture, the collection picture is specially managed, and the risk that the collection picture is stolen is avoided.
And step S30, recognizing the text information from the pre-call picture through the image-text recognizer.
Step S30, when the method is implemented specifically, according to the image-text recognizer trained by the deep learning ResNeXt network, recognizing all the character information in the pre-call pictures respectively through the image-text recognizer, and recognizing the character information collection category of each pre-call picture according to the semantics of all the character information in the pre-call pictures; the step can accurately identify the character collection type according to the semantics of the character information according to the deep learning.
And step S40, intelligently matching the character information collection type in the preposed calling picture with a preset dictionary and a regular expression, and storing the matching result in an atlas database of the character information collection type.
Step S40, when the method is implemented specifically, a multi-dimensional semantic algorithm is used for obtaining a text vector of each pre-call picture text information collection category according to the semantics of the text information collection category in each pre-call picture, the obtained text vector of the text information collection category is semantically matched with a dictionary and a regular expression preset in a picture-text recognizer, and the matching result is stored in an image collection database corresponding to the text information collection category; the steps can carry out semantic matching on the preposed calling pictures of the collection by using a multi-dimensional semantic algorithm, and store the collection pictures in the corresponding atlas database according to the semantic matching, thereby realizing the online specialization of private collectors, systematized database construction and finishing the classified storage of the atlas database by recording the collection types of the private collection pictures.
Step S50, calculating a first cosine similarity between the semantic vector of the collection atlas category in each atlas database and the semantic vectors of all text classifications of the topic units in the preset catalogue, and calculating a second cosine similarity between the semantic vector of the text information collection category in the preposed calling picture and the semantic vector of the text classification of the topic units in the preset catalogue.
When the step S50 is implemented specifically, a multi-dimensional semantic algorithm or a space vector algorithm is used, a first cosine similarity is calculated according to the semantic vector of the collection atlas category in each atlas database and the semantic vectors of all text classifications of the question units in the preset directory, a second cosine similarity is calculated according to the semantic vector of the text information collection category in each prepositive call picture and the semantic vector of the text classification of the sub-directory unit in the preset directory, the association relationship between the atlas database and the prepositive call picture and the preset directory is established, the association directory is established, the configuration and the mapping mode of the shared file can be flexible, the directory is accessed through a browsing path, and the access speed can be improved.
Step S60, determining the collection atlas catalog of the private user according to the incidence relation between the collection atlas category and the first cosine similarity of all text classifications of the topic units in the preset catalog and the second cosine similarity of the text classification of the sub catalog units in the pre-calling picture.
Step S60, when the method is implemented, establishing the incidence relation between the collection atlas category and the title unit in the preset catalogue according to the first cosine similarity calculated by the collection atlas category and all the text classifications of the title unit in the preset catalogue; according to the second cosine similarity between the text classification of the text information collection category in the prepositive calling picture and the sub-directory unit in the preset directory, establishing the association relation between the text information collection category in the prepositive calling picture and the sub-directory unit in the preset directory, wherein the title unit in the preset directory corresponds to the collection atlas category, and the text classification of the text information collection category in the prepositive calling picture corresponds to the sub-directory unit in the preset directory; determining a collection atlas directory of the private user according to the incidence relation between the first cosine similarity and the second cosine similarity; the steps determine the collection atlas catalog of the private user, store the pictures in the catalog form, are beneficial to full-text retrieval of the catalog, have the advantages of high webpage reading and browsing speed, no influence on network speed and the like, can avoid being copied, and are convenient for sharing the electronic collection pictures among the users.
In one possible implementation, fig. 2 is a schematic flow chart illustrating a high-definition grayscale chart obtained in a processing method of a private collection atlas directory provided in an embodiment of the present application; in step S10, the method for sharpening the binary gray scale image of the private collection picture by using the machine vision model to obtain a high-definition gray scale image includes:
and S101, detecting a peak value of the binary gray-scale image through a Laplace energy function, an energy gradient function or a variance function of the machine vision model, and determining a first definition image according to the peak value.
And S102, sharpening the first definition picture according to a preset gray threshold to obtain a second definition picture.
And S103, fusing the first definition image and the second definition image to obtain a high-definition gray image.
When the steps S101, S102, and S103 are specifically implemented, a peak value of a binary gray scale image is detected by a machine vision model laplacian energy function, an energy gradient function, a variance function, a Brenner function, or a tenebad function, a peak value analysis result of the sharpness is displayed by using a histogram according to the binary gray scale image corresponding to the peak value, a first gray scale image is determined according to the analysis result of the peak value, a gray scale average value of each adjacent pixel of the first gray scale image is calculated by a multi-image averaging method, a median filtering method, a maximum averaging method, or an adaptive filtering method, a preset gray scale threshold is replaced by the calculated gray scale average value, a second gray scale image is obtained, a gray scale value of the first gray scale image and a gray scale value of the second gray scale image are subjected to high-definition or weighted averaging, and a gray scale image is obtained after fusion.
In a possible implementation scheme, fig. 3 shows a schematic flow chart of adding a gradual watermark and reducing precision in a processing method for a private collection atlas directory provided by an embodiment of the present application; in the step S20, an equivalent accumulation manner is adopted, a gradient watermark is added to the high-definition grayscale image, so as to obtain an anti-counterfeiting high-definition image to which the gradient watermark is added, and precision reduction processing is performed on the anti-counterfeiting high-definition image to which the gradient watermark is added, so as to obtain a pre-call image, including:
step S201, calculating each pixel point of the high-definition gray scale image in an equivalent accumulation mode to obtain a counter value and a true value corresponding to each pixel point.
And S202, aiming at the inverse code value and the true value of each pixel point, carrying out color replacement on the RGB three-color spectrum numerical value corresponding to the preset character gradient watermark line by line according to the random offset, and obtaining the anti-counterfeiting high-definition picture added with the gradient watermark.
And S203, respectively calculating a first loss value and a second loss value of the anti-counterfeiting high-definition picture according to the counter value and the real value of each digital pixel point of the anti-counterfeiting high-definition picture, and fusing the calculated first loss value and the calculated second loss value to obtain a fused access high-definition picture as a prepositive calling picture.
The steps S201, S202 and S203 are implemented specifically, an equivalent accumulation mode is adopted for each pixel point of the high-definition gray scale image, an inverse code value and a true value corresponding to each pixel point of the high-definition gray scale image are generated in a non-zero one-taking mode, an inverse code value and a true value corresponding to each pixel point of the high-definition gray scale image are replaced line by line from random offset according to three groups of numerical value forms of red, green and blue in an equivalent accumulation mode, each pixel point of the high-definition gray scale image is replaced by selecting a three-color spectrum numerical value of the character gradient watermark, an anti-counterfeiting high-definition image added with the gradient watermark is obtained, a first loss value and a second loss value of the anti-counterfeiting high-definition image are respectively calculated according to the inverse code value and the true value of each digital pixel point of the anti-counterfeiting high-definition image, and the first loss value and the second loss value are fused, obtaining a fused access high-definition picture as a prepositive calling picture;
the method comprises the following steps of calculating a first loss value according to an inverse code value and a true value of each digital pixel point of an anti-counterfeiting high-definition picture according to the following formula:
wherein: q. q.smnRepresenting the code reversal value of the nth digital pixel point in the mth anti-counterfeiting high-definition picture data set; p is a radical ofmnRepresenting the true value of the nth digital pixel point in the mth anti-counterfeiting high-definition picture data set; loss (q)mn,pmn) Representing the mth anti-counterfeiting high-definition graphA first loss value between an anti-code value and a true value of the nth digital pixel point in the slice data set, wherein c represents the total number of the digital pixel points in the mth anti-counterfeiting high-definition picture data set; t represents the total number of pixel classes;
and calculating a second loss value according to the inverse code value and the true value of each digital pixel point of the anti-counterfeiting high-definition picture according to the following formula:
wherein q isuvRepresenting the code reversal value of the v-th digital pixel point in the u-th anti-counterfeiting high-definition picture data set; p is a radical ofuvRepresenting the true value of the v-th digital pixel point in the u-th anti-counterfeiting high-definition picture data set; loss (q)uv,puv) Representing a second loss value between the inverse code value and the true value of the v-th digital pixel point in the u-th anti-counterfeiting high-definition picture data set; h represents the total number of digital pixel points in the u-th anti-counterfeiting high-definition picture data set; g represents the total number of digital pixel points.
In a possible implementation scheme, fig. 4 is a schematic flow chart illustrating intelligent matching of a text information collection type and a preset dictionary in a processing method for a private collection atlas directory provided in an embodiment of the present application; in step S40, the intelligent matching of the text information collection category in the pre-call picture with the preset dictionary and the regular expression is performed, and the matching result is stored in the atlas database of the text information collection category, including:
step S401, aiming at the recognized character information collection category of each pre-call picture, a multi-dimensional semantic algorithm is used for determining a text vector corresponding to the character information of each pre-call picture according to the semantics of the character information.
And S402, intelligently matching the text vector of each pre-call picture with a preset dictionary and a regular expression through a picture-text recognizer to obtain the collection atlas category.
And step S403, storing each pre-calling picture in a corresponding atlas database according to the type of the collection atlas.
In specific implementation, after the text information collection category of each pre-call picture is identified according to the image-text identifier, determining a text vector of the text information of each pre-call picture according to the semantics of the text information collection category by using a multi-dimensional semantic algorithm, wherein the text information collection category comprises: the system comprises picture name information, picture province information, affiliated picture address information, picture provider information, picture release year information and picture release unit information; carrying out vector feature intelligent matching on a text vector of each pre-called picture and a regular expression of a preset dictionary in the picture-text recognizer through the picture-text recognizer, obtaining a collection atlas category after intelligent matching, and respectively storing each pre-called picture in a corresponding atlas database according to the collection atlas category; the collection atlas categories include: coin class atlas, ticket class atlas, stamp class atlas, commemorative stamp class atlas, other miscellaneous class atlas;
for example: determining a text vector of a preposed calling picture by using a picture-text recognizer according to the semantics of picture name information in the character information, performing vector feature matching according to the determined text vector and a regular expression of a preset dictionary in the picture-text recognizer to obtain a collection atlas category corresponding to the character information, and storing the preposed calling picture in a corresponding coin class atlas database if the character information collection category in the preposed calling picture corresponds to the coin class atlas; if the collection type of the character information in the prepositive calling picture corresponds to the ticket class atlas, the prepositive calling picture is stored in a database of the corresponding ticket class atlas.
In a possible implementation scheme, in step 50, a first cosine similarity between the semantic vector of the atlas category of the collection in each atlas database and the semantic vectors of all text classifications of the topic units in the preset catalog is calculated, and a second cosine similarity between the semantic vector of the text information collection category in the pre-call picture and the semantic vector of the text classification of the sub-catalog unit in the preset catalog is calculated.
In the specific implementation of step 50, a multi-dimensional semantic algorithm or a space vector algorithm is used, a first cosine similarity is calculated according to the semantic vector of the collection atlas category in each atlas database and the semantic vectors of all text classifications of the topic units in the preset catalogue, and a second cosine similarity is calculated according to the semantic vector of the text classification of the word information collection category in each preposed calling picture and the semantic vector of the text classification of the topic units in the preset catalogue.
In one possible implementation, fig. 5 illustrates a schematic flow chart of determining a collection atlas directory of a private user in a processing method of a private collection atlas directory provided in an embodiment of the present application; in step S60, determining the collection atlas directory of the private user according to the association between the collection atlas category and the first cosine similarity of all text classifications of the topic units in the preset directory and the second cosine similarity of the text classification of the sub-directory unit in the preset directory, includes:
step S601, calculating a first cosine similarity according to the semantic vector of the collection atlas category in each atlas database and the semantic vectors of all text classifications of the topic units in the preset catalog, wherein the collection atlas category comprises: coin class atlas, ticket class atlas, stamp class atlas, commemorative stamp class atlas, other miscellaneous class atlas; the preset directory is multiple.
Step S602, establishing an association relationship between the collection atlas category and the title unit in the preset directory according to the calculated first cosine similarity.
Step S603, calculating a second cosine similarity according to the semantic vector of the text information collection category in the pre-call picture and the semantic vector of the text classification of the sub-directory unit in the preset directory, where the text information collection category of the pre-call picture includes: picture name information, picture province information, belonging picture address information, picture provider information, picture release year information, and picture release unit information.
Step S604, aiming at the calculated second cosine similarity, establishing an incidence relation between the text information collection category in the prepositive calling picture and the sub-directory unit in the preset directory.
Step S605, determining the collection atlas directory of the private user according to the association relationship between the first cosine similarity and the second cosine similarity.
When the steps S601, S602, S603, S604 and S605 are implemented specifically, according to the semantic vectors of the money class atlas, the ticket class atlas, the stamp class atlas, the memorial stamp class atlas or other miscellaneous atlases and the semantic vectors of the text classification in the preset directory, the first cosine similarity between the individual semantic vectors is calculated according to a cosine function formula in a two-dimensional space, the cosine similarity value approaches 1, the included angle approaches 0, the more similar the two semantic vectors are, the cosine similarity value approaches 0, the included angle approaches 90 degrees, and the more dissimilar the two semantic vectors are; aiming at the calculated first cosine similarity, establishing an incidence relation between the category of the collection atlas and the question unit in the preset catalogue; then, calculating a second cosine similarity according to picture name information, picture province information, belonging picture address information, picture provider information, picture release year information, picture release unit information and semantic vectors of text classification of sub-directory units in a preset directory in the pre-call picture, wherein the preset directory sub-directory units comprise a plurality of task nodes (such as a first node, a second node and an Nth node …), and establishing an association relation between a text information collection category in the pre-call picture and the sub-directory units in the preset directory according to the calculated second cosine similarity; determining a collection atlas catalog of a private user according to the incidence relation between the collection atlas category corresponding to the first cosine similarity and the title unit in the preset catalog and the incidence relation between the text information collection category in the picture and the sub-catalog unit in the preset catalog corresponding to the second cosine similarity;
for example: according to the semantic vector of the coin type atlas and the semantic vector of the subject unit text classification in the preset directory, the semantic vector coordinates of the coin type atlas in the rectangular coordinate system and the length of the semantic vector coordinates of the subject unit text classification in the preset directory are substituted into a triangular cosine function formula according to a triangular cosine function formula in a two-dimensional space, and a cosine value between the included angles of two semantic vectors in the vector space is obtained to be used for measuring the difference between the two individual semantic vectors, wherein the cosine similarity value is close to 1, the included angle tends to 0, the more similar the two semantic vectors are, the cosine similarity value is close to 0, the included angle tends to 90 degrees, and the more dissimilar the two semantic vectors are.
In a possible implementation scheme, fig. 6 is a schematic diagram illustrating a flow of a user-initiated call request in a processing method for a private collection atlas directory provided in an embodiment of the present application; further comprising:
step S701, responding to a calling request initiated by a private user, reading a collection album directory from an album database according to an API (application program interface) data interface, and displaying a front calling picture in the collection album directory;
step S702, responding to a calling request initiated by a private user, and displaying a front calling picture stored in an atlas database to a third-party user according to a catalogue rule of the atlas database;
and step S703, responding to a calling request initiated by a private user, and calling pictures according to the front in the collection atlas directory to perform online transaction through the WeChat interface and the Paibao online interface.
When the steps S701, S702, and S703 are implemented specifically, in response to a call request initiated by a private user, a collection album directory created by the private user is read from a coin type album, a ticket type album, a stamp type album, a memorial stamp type album, or other miscellaneous albums according to the API data interface, and a pre-call picture in the collection album directory is displayed to the front end of the web page, so that the access speed and the access speed of the front end of the web page can be increased.
Responding to a calling request initiated by a private user, pre-calling pictures respectively stored in a money type atlas, a ticket type atlas, a stamp type atlas, a commemorative stamp type atlas or other miscellaneous image sets according to a catalogue rule of each atlas database, and displaying the pre-called pictures to a third-party user for viewing through an API (application programming interface) data interface, so that online interaction and sharing viewing of the private user can be realized.
The method comprises the steps of responding to a calling request initiated by a private user, reading a collection atlas directory established by the private user from a coin type atlas, a ticket type atlas, a stamp type atlas, a commemorative stamp type atlas or other miscellaneous atlas according to an API data interface, and carrying out online transaction on a front calling picture in the collection atlas directory through a WeChat interface and a Payment treasure online interface transaction function, so that the problem of limited remote transaction among private users can be solved.
Corresponding to the processing method of the private collection atlas directory in fig. 1, the embodiment of the present application further provides a computer device 80, fig. 7, as shown in fig. 7, the device includes a memory 801, a processor 802, and a computer program stored on the memory 801 and operable on the processor 802, wherein the above method is implemented when the above computer program is executed by the above processor 802.
Sharpening the binary gray level image of the private collection image through a machine vision model to obtain a high-definition gray level image;
adding a gradient watermark to the high-definition gray-scale image by adopting an equivalent accumulation mode to obtain an anti-counterfeiting high-definition image added with the gradient watermark, and performing precision reduction processing on the anti-counterfeiting high-definition image added with the gradient watermark to obtain a prepositive calling image;
recognizing character information from the prepositive calling picture through a picture-text recognizer;
intelligently matching the character information collection category in the preposed calling picture with a preset dictionary and a regular expression, and storing a matching result in an atlas database of the character information collection category;
calculating a first cosine similarity between the semantic vector of the collection atlas category in each atlas database and the semantic vectors of all text classifications of the topic units in the preset catalogue, and calculating a second cosine similarity between the semantic vector of the text information collection category in the preposed calling picture and the semantic vector of the text classification of the topic units in the preset catalogue;
and determining the collection atlas catalog of the private user according to the incidence relation between the collection atlas category and the first cosine similarity of all text classifications of the topic units in the preset catalog and the second cosine similarity of the text classification of the subcatalog units in the preposed calling picture.
Corresponding to the processing method of the private collection atlas directory in fig. 1, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to perform the following steps:
sharpening the binary gray level image of the private collection image through a machine vision model to obtain a high-definition gray level image;
adding a gradient watermark to the high-definition gray-scale image by adopting an equivalent accumulation mode to obtain an anti-counterfeiting high-definition image added with the gradient watermark, and performing precision reduction processing on the anti-counterfeiting high-definition image added with the gradient watermark to obtain a prepositive calling image;
recognizing character information from the prepositive calling picture through a picture-text recognizer;
intelligently matching the character information collection category in the preposed calling picture with a preset dictionary and a regular expression, and storing a matching result in an atlas database of the character information collection category;
calculating a first cosine similarity between the semantic vector of the collection atlas category in each atlas database and the semantic vectors of all text classifications of the topic units in the preset catalogue, and calculating a second cosine similarity between the semantic vector of the text information collection category in the preposed calling picture and the semantic vector of the text classification of the topic units in the preset catalogue;
and determining the collection atlas catalog of the private user according to the incidence relation between the collection atlas category and the first cosine similarity of all text classifications of the topic units in the preset catalog and the second cosine similarity of the text classification of the subcatalog units in the preposed calling picture.
Based on the analysis, compared with the collection gallery in the related technology, the collection gallery directory of the private user provided by the embodiment of the application utilizes big data and electronic file classification technology to summarize and arrange a large number of collection pictures, and constructs the collection catalog file through different databases to form the private electronic directory of the collector, so that the collection of the online management user and the data statistics of the private collection are realized.
In the embodiments provided in the present application, it should be understood that the disclosed method can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, a division of a unit is merely a division of one logic function, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus once an item is defined in one figure, it need not be further defined and explained in subsequent figures, and moreover, the terms "first", "second", "third", etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the present disclosure, which should be construed in light of the above teachings. Are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method for processing a collection of private collections, comprising:
sharpening the binary gray level image of the private collection image through a machine vision model to obtain a high-definition gray level image;
adding a gradient watermark to the high-definition gray-scale image in an equivalent accumulation mode to obtain an anti-counterfeiting high-definition image added with the gradient watermark, and performing precision reduction processing on the anti-counterfeiting high-definition image added with the gradient watermark to obtain a prepositive calling image;
recognizing character information from the prepositive calling picture through a picture-text recognizer;
intelligently matching the character information collection category in the prepositive calling picture with a preset dictionary and a regular expression, and storing a matching result in an atlas database of the character information collection category;
calculating a first cosine similarity between the semantic vector of the collection atlas category in each atlas database and the semantic vectors of all text classifications of the topic units in the preset catalogue, and calculating a second cosine similarity between the semantic vector of the text information collection category in the preposed calling picture and the semantic vector of the text classification of the topic units in the preset catalogue;
and determining the collection atlas catalog of the private user according to the incidence relation between the collection atlas category and the first cosine similarity of all text classifications of the topic units in the preset catalog and the second cosine similarity of the text classification of the subcatalog units in the preposed calling picture.
2. The method of claim 1 wherein sharpening the binary grayscale image of the collection image to obtain a high definition grayscale image by a machine vision model comprises:
detecting a peak value of the binary gray-scale image through a Laplace energy function or an energy gradient function or a variance function of the machine vision model, and determining a first definition image according to the peak value;
sharpening the first definition picture according to a preset gray threshold to obtain a second definition picture;
and fusing the first definition picture and the second definition picture to obtain a high-definition gray image.
3. The method for processing the collection catalog of the private collection according to claim 1, wherein the method of adding the gradient watermark to the high-definition gray-scale image in an equivalent accumulation manner to obtain the anti-counterfeiting high-definition image after the gradient watermark is added, and performing precision reduction processing on the anti-counterfeiting high-definition image after the gradient watermark is added to obtain the pre-call image comprises the steps of:
calculating by adopting the equivalent accumulation mode aiming at each pixel point of the high-definition gray scale image to obtain a counter value and a true value corresponding to each pixel point;
aiming at the inverse code value and the true value of each pixel point, carrying out color replacement on RGB (red, green and blue) three-color spectrum numerical values corresponding to the preset character gradient watermarks line by line according to random offset to obtain the anti-counterfeiting high-definition picture added with the gradient watermarks;
and respectively calculating a first loss value and a second loss value of the anti-counterfeiting high-definition picture according to the inverse code value and the true value of each digital pixel point of the anti-counterfeiting high-definition picture, and fusing the calculated first loss value and the calculated second loss value to obtain a fused access high-definition picture as a preposed calling picture.
4. The method for processing the album catalog of personal collectibles according to claim 3 wherein calculating a first loss value based on the inverse code value and the real value of each digital pixel of said security high definition picture comprises:
the first loss value is calculated according to the following formula:
wherein: q. q.smnRepresenting the code reversal value of the nth digital pixel point in the mth anti-counterfeiting high-definition picture data set; p is a radical ofmnRepresenting the true value of the nth digital pixel point in the mth anti-counterfeiting high-definition picture data set; loss (q)mn,pmn) Representing a first loss value between an inverse code value and a true value of an nth digital pixel point in an mth anti-counterfeiting high-definition picture data set, and c representing the total number of the digital pixel points in the mth anti-counterfeiting high-definition picture data set; t represents the total number of pixel classes.
5. The method of claim 3, wherein calculating a second loss value based on the inverse code value and the true value of each digital pixel of the anti-counterfeit high definition picture comprises:
the second loss value is calculated according to the following formula:
wherein q isuvRepresenting the code reversal value of the v-th digital pixel point in the u-th anti-counterfeiting high-definition picture data set; p is a radical ofuvRepresenting the true value of the v-th digital pixel point in the u-th anti-counterfeiting high-definition picture data set; loss (q)uv,puv) Representing a second loss value between the inverse code value and the true value of the v-th digital pixel point in the u-th anti-counterfeiting high-definition picture data set; h represents the total number of digital pixel points in the u-th anti-counterfeiting high-definition picture data set; g represents the total number of digital pixel points.
6. The method of claim 1, wherein intelligently matching the text information collection category in the pre-call picture with a predetermined dictionary and regular expression and storing the matching results in an album database of text information collection categories comprises:
aiming at the recognized character information collection category of each prepositive calling picture, determining a text vector corresponding to the character information of each prepositive calling picture by using a multi-dimensional semantic algorithm according to the semantics of the character information;
intelligently matching and matching the text vector of each preposed calling picture with a preset dictionary and a regular expression through the image-text recognizer to obtain a collection atlas category;
and respectively storing each preposed calling picture in the corresponding atlas database according to the category of the collection atlas.
7. The method of claim 1, wherein determining the collection atlas directory of the private user based on the correlation between the first cosine similarity of the collection atlas category and all text classifications of the topic unit in the preset directory and the second cosine similarity of the text classification of the sub-directory unit in the preset directory comprises:
calculating a first cosine similarity according to the semantic vector of the collection atlas category in each atlas database and the semantic vectors of all text classifications of the topic units in a preset directory, wherein the collection atlas category comprises: coin class atlas, ticket class atlas, stamp class atlas, commemorative stamp class atlas, other miscellaneous class atlas; the number of the preset catalogues is multiple;
aiming at the calculated first cosine similarity, establishing an incidence relation between the collection atlas category and a title unit in a preset catalogue;
calculating a second cosine similarity according to the semantic vector of the text information collection category in the prepositive calling picture and the semantic vector of the text classification of the sub-directory unit in the preset directory, wherein the text information collection category of the prepositive calling picture comprises: the system comprises picture name information, picture province information, affiliated picture address information, picture provider information, picture release year information and picture release unit information;
establishing an incidence relation between the text information collection category in the prepositive calling picture and a sub-directory unit in a preset directory according to the calculated second cosine similarity;
and determining the collection atlas directory of the private user according to the incidence relation between the first cosine similarity and the second cosine similarity.
8. The method of processing a personal collection atlas directory of claim 1, further comprising:
responding to a calling request initiated by a private user, reading the collection atlas directory from the atlas database according to an API (application program interface) data interface, and displaying a front calling picture in the collection atlas directory;
responding to a calling request initiated by a private user, and displaying the preposed calling picture stored in the atlas database to a third-party user according to a catalogue rule of the atlas database;
responding to a calling request initiated by a private user, and carrying out online transaction according to the preposed calling picture in the collection atlas directory through a WeChat interface and a Paibao online interface.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of the preceding claims 1 to 8 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, is adapted to carry out the steps of the method according to any one of claims 1 to 8.
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