CN112329841B - Picture processing method, device, electronic equipment and computer readable medium - Google Patents
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Abstract
The disclosure provides a picture processing method, and relates to the technical fields of image processing, artificial intelligence and cloud computing. The method comprises the following steps: classifying the picture content of a first picture in the page at a preset stage of loading the opened page to obtain different classified picture contents in the first picture, wherein the first picture is any picture in the page; and determining target picture content from the picture content of different classifications in response to the received picture content identification request so as to identify the target picture content and obtain an identification result of the first picture. The disclosure also provides a picture processing device, an electronic device and a computer readable medium. According to the picture processing method, the picture processing device, the electronic equipment and the computer readable medium, before picture content identification is started, the content in the picture of the current page can be analyzed in advance, the classification of the content of the picture is determined, and the aim of quickly identifying the picture is fulfilled.
Description
Technical Field
The present disclosure relates to the field of image processing, artificial intelligence, and cloud computing technologies, and in particular, to a method, an apparatus, an electronic device, and a computer readable medium for processing a picture.
Background
With the rapid development of artificial intelligence, image recognition capability is widely applied in a plurality of application scenes and the like. Particularly in mobile equipment, the content in the acquired picture can be browsed and interacted at any time through the image acquisition device of the mobile equipment.
Due to the diversity of the contents in the pictures, when picture identification is performed, in the case where the content of the picture to be identified is uncertain, there is uncertainty in the identified content.
BRIEF SUMMARY OF THE PRESENT DISCLOSURE
The embodiment of the disclosure provides a picture processing method, a picture processing device, electronic equipment and a computer readable medium.
In a first aspect, an embodiment of the present disclosure provides a method for processing a picture, including: classifying the picture content of a first picture in the page at a preset stage of loading the opened page to obtain different classified picture contents in the first picture, wherein the first picture is any picture in the page; and determining target picture content from the picture content of different classifications in response to the received picture content identification request so as to identify the target picture content and obtain an identification result of the first picture.
In a second aspect, an embodiment of the present disclosure provides a picture processing apparatus, including: the image content classification module is used for classifying image contents of a first image in the page at a preset stage of loading the opened page to obtain image contents of different classifications in the first image, wherein the first image is any image in the page; and the picture content identification module is used for responding to the received picture content identification request, determining target picture content from the picture content with different classifications so as to identify the target picture content and obtain the identification result of the first picture.
In a third aspect, embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a memory having one or more programs stored thereon, which when executed by one or more processors cause the one or more processors to perform the method of any of the above-described xxxx; one or more I/O interfaces coupled between the processor and the memory configured to enable information interaction of the processor with the memory.
In a fourth aspect, an embodiment of the present disclosure provides a computer readable medium having stored thereon a computer program, which when executed by a processor implements any one of the above-described picture processing methods.
According to the picture processing method, the picture processing device, the electronic equipment and the computer readable medium, the picture is classified by the content of the picture in the page in a preset stage of loading the opened page, so that before a user starts picture content identification, the content in the picture of the current page is analyzed in advance, the classification of the content of the picture is determined, the aim of quickly identifying the picture is fulfilled, the time consumption for starting to determine the classification of the content of the picture when the user invokes an image identification function is reduced, the waiting time of the user is shortened, the experience of the user in using the picture identification and picture searching process is improved, and the commercial value of search business on the mobile equipment can be improved.
Drawings
The accompanying drawings are included to provide a further understanding of embodiments of the disclosure, and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure, without limitation to the disclosure. The above and other features and advantages will become more readily apparent to those skilled in the art by describing in detail exemplary embodiments with reference to the attached drawings, in which:
Fig. 1 is a schematic view of a scenario provided in an embodiment of the present disclosure;
fig. 2 is a flowchart of a picture processing method according to an embodiment of the disclosure;
fig. 3 is a flowchart of a picture processing method according to another embodiment of the present disclosure;
fig. 4 is a block diagram of a picture processing apparatus according to an embodiment of the present disclosure;
FIG. 5 shows a block diagram of an electronic device provided by an embodiment of the present disclosure;
fig. 6 is a block diagram of a computer readable medium according to an embodiment of the present disclosure.
Detailed Description
In order to better understand the technical solutions of the present disclosure, the following describes in detail a picture processing method, a device, an electronic apparatus, and a computer readable medium provided by the present disclosure with reference to the accompanying drawings.
Example embodiments will be described more fully hereinafter with reference to the accompanying drawings, but may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Embodiments of the disclosure and features of embodiments may be combined with each other without conflict. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and the present disclosure, and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The image recognition capability described in the embodiments herein may include two-dimensional code recognition, person recognition, object recognition, and text recognition (e.g., photograph answering, etc.) in an image. In an actual application scene, the content in the acquired picture can be browsed and interacted through a camera of the mobile device.
In some specific scenarios, the efficiency and effect of the identification of images is significant. For example, in an application scenario of code scanning payment, when a two-dimensional code is displayed in a picture, the picture is scanned in a two-dimensional code manner using an application (for example, payment software) dedicated to two-dimensional code recognition. In the scene, the purpose of acquiring the specified content in the picture is achieved, the scene is used clearly, the scanning expectation of acquiring the specified content in the picture is achieved, and the picture processing process is high in quality and efficiency.
In other situations, when a user browses a web page, the user usually performs image recognition on the content in the picture without explicit image content acquisition expectation, and if the content in the picture in the web page includes one or more of a text, a star photo and a bar code, the result of image recognition will be uncertain. When the picture is identified, whether the two-dimensional code is identified by image decoding and image identification or the face identification is firstly identified by the image decoding and image identification cannot be determined. Whichever of the picture contents is finally selected for processing, this selection process will result in resource consumption and more processing time.
As is apparent from the above description, the image information in the inputted picture is different, and the recognition result is different. When the specific scene and the content of the specific image are identified, the decoding and identifying process of the image is clear, and the image processing efficiency and the identifying effect are good. However, in a non-specific scenario, the image content identification requirement of the user is not clear, and the identified content has uncertainty, so that the overall picture processing performance is directly affected, the system performance is reduced (for example, in the order of ten to hundred milliseconds), and the overall use experience of the user is affected.
In the embodiment of the disclosure, the identification of the content in the picture is required in the scene with the undefined identification requirement, and the method for preprocessing and identifying the picture in the page browsed by the user (the webpage or the user-defined page) is provided, so that the problem that the picture identification is too slow in the scene with the undefined identification requirement is solved, and the search experience is improved.
Fig. 1 is a schematic view of a scenario of an embodiment of the present disclosure. In the scenario shown in fig. 1, there are included a terminal device 10, a web page 20 opened by the terminal device, and a network 30. An image acquisition device, such as a camera, may be included in the terminal device 10 for image acquisition, code scanning, etc.
When the terminal device 10 browses the web page 20, one or more pictures in the web page, such as a picture 21, a picture 22, … …, and a picture 2M, may be acquired, where M is an integer greater than or equal to 1.
The terminal device 10 may access the internet, and the terminal device 10 may illustratively include, but is not limited to, a cell phone, a personal computer, a tablet computer, a smart wearable device, a desktop computer, a notebook computer, and the like. They may each be installed with various applications.
The network 30 is a medium for providing a communication link between the terminal device 10 and the web page 20. In particular, the network 30 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
Fig. 2 is a flowchart of a picture processing method according to an embodiment of the disclosure.
In a first aspect, referring to fig. 2, an embodiment of the present disclosure provides a picture processing method, which may include the following steps.
S110, classifying the picture content of a first picture in the page at a preset stage of loading the opened page to obtain different classified picture contents in the first picture, wherein the first picture is any picture in the page.
S120, determining target picture content from the picture content with different classifications in response to the received picture content identification request so as to identify the target picture content and obtain an identification result of the first picture.
According to the picture processing method, at the preset stage of loading the opened page, the content of the picture in the page is classified, so that before picture content identification is started, the content in the picture of the current page is analyzed in advance, the classification of the content of the picture is determined, and the aim of quickly identifying the picture is fulfilled.
In some embodiments, the differently classified picture content may include at least one of the following picture content: scannable identification codes, characters, and predetermined types of items.
By way of example, the scannable identification code may be, for example, a two-dimensional code, a bar code, or other scannable standard code; the characters can be, for example, questions to be solved or words to be translated; the predetermined type of item may be, for example, an animal, a brand or model of merchandise, or the like; the character may be, for example, a history character, a cartoon character, a star, etc.
In some embodiments, the predetermined phases include a page load phase and a page complete load phase; before classifying the picture content of the first picture in the page in step S110, the picture processing method may further include: s21, in a page loading stage of an opened page, acquiring a currently added picture as a first picture in the page according to a picture adding event monitored in the page; or S22, sequentially acquiring the pictures added in the page according to a preset sequence as a first picture in the page loading stage of the opened page.
In the embodiment, a picture adding event in a page is monitored in a page loading stage to obtain currently added picture information, so that before picture content identification is started, the content in the picture of the current page is analyzed in advance, the classification of the content of the picture is determined, and the aim of quickly identifying the picture is fulfilled.
In some embodiments, the predetermined phase is a page complete load phase; sequentially acquiring pictures added in a page according to a preset sequence as a first picture in the page, wherein the method comprises the following steps: before classifying the picture content of the first picture in the page in step S110, the picture processing method may further include: s31, responding to the received picture browsing request, and taking the picture requested to be browsed in the picture browsing request as a picture being browsed; and S32, preferentially acquiring the picture being browsed as a first picture in the page.
In the embodiment, the pictures in the web page which are being browsed can be preferentially acquired for processing, so that the response speed and the processing efficiency of picture processing are improved, the requirement of users for browsing the pictures in real time is met, and the user experience is improved.
In some embodiments, before step S120, the picture processing method may further include: s41, setting classification mark information of each classified picture content for the picture content of different classifications in the first picture; s42, sorting the picture contents with different classifications in the first picture according to preset display attribute information, and displaying at least one piece of ordered picture content and classification mark information of the at least one piece of ordered picture content.
In the embodiment, before starting to identify the content of the picture, the content in the picture of the current page is analyzed in advance, the classification of the content of the picture is determined, and related prompts are given to the content in the picture when the picture is browsed, so that the aim of quickly identifying the picture is fulfilled.
In addition, in the embodiment, when the content of the previous at least one picture and the classification mark information of the content of the previous at least one picture are displayed, and the number of the displayed picture contents is less than the total number of the contents in the picture, the content in the picture can be filtered, and the user can conveniently select the content to be identified in the picture according to the related prompt by using the displayed picture content with more obvious attribute information, so that the picture identification efficiency is improved.
In some embodiments, the picture content identification request is a selection request for specified category label information; step S120 may specifically include: and taking the belonging classification of the picture content corresponding to the specified classification mark information as the target classification in different classifications.
In this embodiment, when a selection request for the classification mark information is monitored or received, the classification of the content in the picture to be identified is determined according to the belonging classification of the picture content corresponding to the selected classification mark information, so that identification can be quickly performed according to the classification of the content in the selected picture, and a picture identification result is obtained, thereby reducing the waiting time of a user for identifying the picture and improving the picture identification efficiency.
In some embodiments, if the picture content identification request is a selection request for the first picture, step S120 may specifically include: s51, sorting the picture contents of different classifications in the first picture according to preset display attribute information, and taking the picture contents of the sorted first picture as target picture contents.
In this embodiment, if the user directly selects the picture to identify when monitoring or receiving the selection request for the picture in the page, the user may default to sort the content in the first picture to identify the image, so that the time consumption of the user for determining the sorting of the content of the picture when starting to identify the content of the picture (for example, invoking the image identification function) is reduced, thereby reducing the waiting time of the user for identifying the picture and improving the picture identification efficiency.
In some embodiments, the presentation attribute information includes at least one of the following information items of differently classified picture content: size information, region position in the first picture and preset priority information; in this embodiment, step S51 may specifically include: and sorting the picture contents with different classifications according to at least one of the size information, the region position in the first picture and the preset priority information to obtain the sorted picture contents with different classifications.
In the embodiment, the ordered picture contents with different classifications can be displayed according to the display attribute information, so that the browsing and interaction of the contents in the pictures can be facilitated by displaying the classification and identification results.
According to the picture processing method, the content in the picture of the current page is analyzed in advance before picture content identification starts in the page browsed by the user, and the classification of the content of the picture is determined, so that the aim of quickly identifying the picture is fulfilled.
And by quickly recognizing the pictures, the problem that the picture recognition is too slow in a scene where a user is ambiguous is solved, the time consumption of firstly determining the classification of the content of the pictures and then carrying out recognition when the user invokes the image recognition function is reduced, the waiting time of the user is reduced, for example, the benefit of hundred milliseconds grade is obtained on the whole, the use times of the picture recognition function of the pictures in the page and the display times of the related content are improved, the experience of the user in the picture recognition and picture searching processes is improved, the gap between searching and competition can be pulled open, the searching experience is improved, and the whole searching ecology is improved. Further, the difference between the product and the competition product using the picture processing method can be pulled, and the commercial value of the search service on the mobile equipment is improved.
In order to better understand the picture processing method of the present disclosure, the picture processing method of an exemplary embodiment of the present disclosure is described in detail below in conjunction with fig. 3.
Fig. 3 is a flowchart of a picture processing method according to another embodiment of the present disclosure. As shown in fig. 3, in one embodiment, the picture processing method may include the following steps.
S301, opening and loading a page.
S302, preprocessing the content of the picture in the page to obtain the classification of the content in the picture and the display attribute information of the content in the picture.
In this step, the pretreatment can be performed in two ways.
One way is: and monitoring a picture adding event in the page to obtain the currently added picture information and cached data, and pre-analyzing the content in the picture.
Another way is: after the page loading is completed, all the pictures in the page are acquired, and the acquired pictures are stored in a picture array, so that the acquired pictures can be sequentially added, and the currently added picture information and the cached data can be obtained once. In this manner, if a picture browsing request for a certain picture in a page is monitored, the picture requested to browse may be preferentially acquired in response to the picture browsing request.
In this step, classification flag information of each classified picture content may be set for different classified picture contents in the first picture.
As an example, when the picture includes a scannable identification code, such as a two-dimensional code, a bar code, or other scannable standard code, the marking information of the scannable identification code in the picture may be set, for example, the scannable identification code included in the picture is marked as a scannable code; when the picture contains characters, the marking information of the characters in the picture can be set, for example, the characters contained in the picture are marked as being capable of optical character recognition (Optical Character Recognition, OCR) or being capable of character recognition; when a person such as a well-known person like a star is present in the picture, the mark information of the person in the picture may be set, for example: marking as a person to find; when the picture contains other specific preset objects, for example: one or more commodity shoes, computers, accessories, animals and the like can be provided with marking information corresponding to the specific preset articles in the pictures.
In the embodiment of the present disclosure, the picture may be decoded and the content in the picture may be classified by a preset picture content classification model, for example, model parameters for identifying multiple pictures may be preset, and the classification of the content in the picture is only an adaptive description, and in the embodiment of the present disclosure, the classification of the content in the picture is not specifically limited.
In this step, the size information of the different contents and the coordinate information of the different contents in the picture may also be recorded, and the size of the region occupied by the different contents in the picture may be determined according to the recorded size information of the different contents, and the region position of the different contents in the picture may be determined according to the coordinate information of the different contents in the picture.
S303, showing the result of classification and identification.
In this step, the contents of different classifications may be ordered according to the size of the area occupied by the contents of different classifications and the position of the area where the contents of different classifications are located, and the first n (Topn) contents of the ordering result are displayed, where n is an integer greater than or equal to 1.
In one embodiment, if the content of different classifications is ordered only according to the size of the occupied area, the content of the picture with larger occupied area is ordered before the content of the picture with smaller occupied area; and if the content of different classifications is ordered only according to the position of the region, ordering the content of smaller region with larger region position in the picture.
In one embodiment, if the content of different classifications is ranked according to the size of the area occupied by the content of different classifications and the position of the area occupied by the content of different classifications, the content of different classifications can be ranked according to the position of the area occupied by the content of different classifications to obtain a first ranking result, and then the first ranking result is ranked according to the size of the area occupied by the content of different classifications to obtain a ranking result of the content of different classifications; or the second sorting result can be obtained by sorting according to the size of the occupied area, and then sorting is carried out according to the position of the occupied area, so that the sorting results of the contents with different classifications are obtained.
As an example, the content of different classifications in a picture includes stars, packets, and two-dimensional codes. If the picture star is wrapped in the middle of the screen, the two-dimensional code is in the lower right corner. After stars, packages and two-dimensional codes are sequenced according to the size of the area occupied by the contents of different classifications and the position of the area, when n is 2, the classification and identification results are displayed as stars and packages, and marking information is respectively added to the stars and the packages to identify objects and find people.
In this step, the content of different classifications may also be ranked according to the priorities of the content of different classifications, and the content of the ranking result Topn in the picture may be displayed.
As an example, for example, priority information of contents of different classifications in a picture is: two-dimensional codes, text, objects, and characters. And for the star, the packet and the two-dimensional code in the picture, when the sorting result according to the priority information is the two-dimensional code, the packet and the star, and n is 2, the classification recognition result can be displayed as the two-dimensional code and the packet, and the two-dimensional code and the packet are respectively added with the marking information as the scanning code and the object recognition.
S304, classifying and identifying the pictures according to the received interaction information.
In this step, if the received interaction information is a received selection request for a certain classification flag information of the picture content in the web page, the content in the picture to be identified may be determined according to the selected classification flag information. For example, if the user selects the classification flag information classified as the scannable identification code, the image is classified by two-dimensional code as a default identification image when the picture is identified.
In this step, if the received interaction information is the received selection request for the pictures in the web page, the content identification images in the first picture may be sorted in a classification.
According to the picture processing method disclosed by the embodiment of the invention, different types of contents in a picture can be classified when the page is loaded or under the condition that the page is loaded, for example, the type prejudgment of the contents in the picture is finished through text recognition, image recognition, bar code recognition and the like, so that in a scene aiming at uncertain user targets (such as uncertain picture contents), the time consumption for determining the classification of the contents of the picture when the user invokes an image recognition function is reduced, the waiting time of the user is shortened, the use times of related image recognition functions and the display times of related contents are improved, the use experience of the user in the process of using the picture recognition (or search) is improved, the difference between the user and the product is pulled, and the commercial value of search service on mobile equipment is improved.
Fig. 4 is a block diagram of a picture processing apparatus according to an embodiment of the present disclosure.
In a second aspect, referring to fig. 4, an embodiment of the present disclosure provides an apparatus, which may include the following modules.
The picture content classification module 410 is configured to classify the picture content of a first picture in the page at a predetermined stage of loading the opened page, to obtain different classified picture contents in the first picture, where the first picture is any picture in the page.
The picture content identifying module 420 is configured to determine, in response to the received picture content identifying request, target picture content from the differently classified picture content, so as to identify the target picture content, and obtain an identification result of the first picture.
According to the picture processing device disclosed by the embodiment of the disclosure, the content of the picture in the page is classified in a preset stage of loading the opened page, so that before picture content identification is started, the content in the picture of the current page is analyzed in advance, the classification of the content of the picture is determined, the aim of quickly identifying the picture is fulfilled, the time consumption for determining the classification of the content of the picture only when a user invokes an image identification function is reduced, the waiting time of the user is reduced, the experience of the user in using the picture identification and picture searching process is improved, and the commercial value of search service on mobile equipment is improved.
In some embodiments, the predetermined phase includes the loading process and the completion of the loading; the picture processing apparatus may further include: the image acquisition module is used for acquiring a currently added image as a first image in the page according to an image adding event monitored in the page in a page loading stage of the opened page before classifying the image content of the first image in the page; or in the loading stage of the page of the opened page, sequentially acquiring the pictures added in the page according to a preset sequence to serve as a first picture in the page.
In some embodiments, the predetermined phase is a page complete load phase; the image acquisition module is used for sequentially acquiring images added in the page according to a preset sequence, and is specifically used for: responding to the received picture browsing request, and taking the picture requested to be browsed in the picture browsing request as a picture being browsed; and preferentially acquiring the picture being browsed as a first picture in the page.
In some embodiments, the picture processing apparatus may further include: a tag information device module, configured to set classification tag information of each classified picture content for different classified picture contents in the first picture before determining a target picture content from the different classified picture contents in response to the received picture content identification request; and the content display module is used for sorting the picture contents with different classifications in the first picture according to preset display attribute information and displaying at least one picture content before the sorting and classification mark information of the at least one picture content before the sorting.
In some embodiments, the picture content identification request is a selection request for specified category label information; the picture content identification module 420 is specifically configured to, in response to a received picture content identification request, determine target picture content from among different classified picture content: and taking the belonging classification of the picture content corresponding to the specified classification mark information as the target classification in different classifications.
In some embodiments, the picture content identification request is a selection request for the first picture, and the picture processing apparatus may further include: the target picture content determining module is used for sorting the picture contents of different classifications in the first picture according to the preset display attribute information, and taking the picture contents of the sorted first picture as target picture contents.
In some embodiments, the presentation attribute information includes at least one of the following information items of differently classified picture content: the size of the occupied area in the first picture, the position of the area in the first picture and preset priority information; the content ordering module is further configured to: and ordering the picture contents with different classifications according to at least one of the area size, the area position and the preset priority information to obtain ordered picture contents with different classifications.
In some embodiments, the differently classified picture content includes at least one of the following picture content: scannable identification codes, characters, and predetermined types of items.
According to the picture processing device disclosed by the embodiment of the invention, the content in the picture can be identified in the scene with an undefined identification requirement, a method for preprocessing and identifying the picture in the page browsed by a user (a webpage or a user-defined page) is provided, the problem that the picture identification is too slow in the scene with the undefined picture identification requirement is solved, and the search experience is improved.
It should be clear that the invention is not limited to the specific arrangements and processes described in the foregoing embodiments and shown in the drawings. For convenience and brevity of description, detailed descriptions of known methods are omitted herein, and specific working processes of the systems, modules and units described above may refer to corresponding processes in the foregoing method embodiments, which are not repeated herein.
Fig. 5 shows a block diagram of an electronic device provided by an embodiment of the present disclosure.
In a third aspect, referring to fig. 5, an embodiment of the present disclosure provides an electronic device, including: one or more processors 501; a memory 502 having one or more programs stored thereon, which when executed by one or more processors, cause the one or more processors to implement the method of any of the above; one or more I/O interfaces 503, coupled between the processor and the memory, are configured to enable information interaction of the processor with the memory.
Wherein the processor 501 is a device having data processing capabilities, including but not limited to a Central Processing Unit (CPU) or the like; memory 502 is a device with data storage capability including, but not limited to, random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically charged erasable programmable read-only memory (EEPROM), FLASH memory (FLASH); an I/O interface (read/write interface) 503 is coupled between the processor 501 and the memory 502 to enable information interaction between the processor 501 and the memory 502, including but not limited to a data Bus (Bus) or the like.
In some embodiments, processor 501, memory 502, and I/O interface 503 are interconnected by a bus, which in turn is connected to other components of a computing device.
Fig. 6 shows a block diagram of one computer-readable medium provided by an embodiment of the present disclosure.
In a fourth aspect, referring to fig. 6, an embodiment of the present disclosure provides a computer readable medium having a computer program stored thereon, which when executed by a processor implements any one of the above-described picture processing methods.
In the disclosed embodiments, artificial intelligence is the discipline of studying the process of making a computer simulate certain thinking and intelligent behavior (e.g., learning, reasoning, planning, etc.) of a person, both hardware-level and software-level techniques. The artificial intelligence hardware technology generally comprises technologies such as a sensor, a special artificial intelligence chip, cloud computing, distributed storage, big data processing and the like; the artificial intelligence software technology comprises a computer vision technology, a voice recognition technology, a natural language processing technology, a machine learning/deep learning technology, a big data processing technology, a knowledge graph technology and the like.
Those of ordinary skill in the art will appreciate that all or some of the steps, systems, functional modules/units in the apparatus, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between the functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed cooperatively by several physical components. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
According to an embodiment of the present disclosure, there is also provided a computer program product comprising a computer program which, when executed by a processor, implements any of the above-mentioned picture processing methods.
Example embodiments have been disclosed herein, and although specific terms are employed, they are used and should be interpreted in a generic and descriptive sense only and not for purpose of limitation. In some instances, it will be apparent to one skilled in the art that features, characteristics, and/or elements described in connection with a particular embodiment may be used alone or in combination with other embodiments unless explicitly stated otherwise. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the disclosure as set forth in the appended claims.
Claims (11)
1. A picture processing method, comprising:
Classifying the picture content of a first picture in the page at a preset stage of loading the opened page to obtain picture content of different classifications in the first picture, wherein the first picture is any picture in the page;
Determining target picture content from the picture content of different classifications in response to a received picture content identification request so as to identify the target picture content and obtain an identification result of the first picture;
wherein the differently classified picture content includes at least one of the following picture content: scannable identification codes, characters, and predetermined types of items;
Wherein, before determining the target picture content from the picture content of different classifications in response to the received picture content identification request, the method further comprises: setting classification mark information of each classified picture content for the picture content of different classifications in the first picture; the picture content identification request is a selection request of the classification mark information; wherein, different classification mark information corresponds to different picture content identification modes.
2. The method of claim 1, wherein the predetermined phases include a page load phase and a page complete load phase; before classifying the picture content of the first picture in the page, the method further comprises:
In a page loading stage of an opened page, acquiring a currently added picture as a first picture in the page according to a picture adding event monitored in the page; or alternatively
And in the page loading stage of the opened page, sequentially acquiring pictures added in the page according to a preset sequence to serve as a first picture in the page.
3. The method of claim 2, wherein the predetermined stage is a page complete load stage; the step of sequentially acquiring the pictures added in the page according to a preset sequence, as a first picture in the page, comprises the following steps:
responding to a received picture browsing request, and taking a picture requested to be browsed in the picture browsing request as a picture being browsed;
and preferentially acquiring the picture being browsed as a first picture in the page.
4. The method of claim 1, wherein after setting the classification flag information of each classified picture content for the different classified picture content in the first picture, further comprises:
And sorting the picture contents of different classifications in the first picture according to preset display attribute information, and displaying at least one piece of ordered picture content and classification mark information of the at least one piece of ordered picture content.
5. The method of claim 4, wherein the determining, in response to the received picture content identification request, target picture content from the differently-classified picture content comprises:
And taking the belonging classification of the picture content corresponding to the selected classification mark information as the target classification in the different classifications.
6. The method of claim 1, wherein the determining, in response to the received picture content identification request, target picture content from the differently-classified picture content comprises:
and sorting the picture contents of different classifications in the first picture according to the preset display attribute information, and taking the picture content of the sorted first picture as target picture content.
7. The method of any of claims 4-6, wherein the presentation attribute information comprises at least one of the following information items of the differently classified picture content: the size of the occupied area in the first picture, the position of the area in the first picture and preset priority information;
the sorting the picture contents of different classifications in the first picture according to the predetermined display attribute information includes:
And sorting the picture contents with different classifications according to at least one of the area size, the area position and the preset priority information to obtain the sorted picture contents with different classifications.
8. A picture processing device, comprising:
the image content classification module is used for classifying image contents of a first image in the page at a preset stage of loading the opened page to obtain image contents of different classifications in the first image, wherein the first image is any image in the page;
the picture content identification module is used for responding to the received picture content identification request, determining target picture content from the picture content with different classifications so as to identify the target picture content and obtain an identification result of the first picture;
wherein the differently classified picture content includes at least one of the following picture content: scannable identification codes, characters, and predetermined types of items;
Wherein, the picture content classification module is further used for: setting classification mark information of each classified picture content for the picture content of different classifications in the first picture; the picture content identification request is a selection request of the classification mark information; wherein, different classification mark information corresponds to different picture content identification modes.
9. An electronic device, comprising:
One or more processors;
Storage means having stored thereon one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the picture processing method according to any of claims 1-7;
one or more I/O interfaces coupled between the processor and the memory configured to enable information interaction of the processor with the memory.
10. A computer readable medium having stored thereon a computer program which when executed by a processor implements a picture processing method according to any of claims 1-7.
11. A computer program product comprising a computer program which, when executed by a processor, implements the picture processing method according to any one of claims 1-7.
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| CN103050025A (en) * | 2012-12-20 | 2013-04-17 | 广东欧珀移动通信有限公司 | Mobile terminal learning method and learning system thereof |
| CN109947967A (en) * | 2017-10-10 | 2019-06-28 | 腾讯科技（深圳）有限公司 | Image-recognizing method, device, storage medium and computer equipment |
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| CN109145786B (en) * | 2018-08-07 | 2021-11-26 | 深圳市知育科技有限公司 | Picture identification method, device, equipment, medium and product |
| CN111783786B (en) * | 2020-07-06 | 2024-07-26 | 上海摩勤智能技术有限公司 | Picture identification method, system, electronic device and storage medium |
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| CN103050025A (en) * | 2012-12-20 | 2013-04-17 | 广东欧珀移动通信有限公司 | Mobile terminal learning method and learning system thereof |
| CN109947967A (en) * | 2017-10-10 | 2019-06-28 | 腾讯科技（深圳）有限公司 | Image-recognizing method, device, storage medium and computer equipment |
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