CN112328824A - Picture detection method and system, computer system and computer readable medium - Google Patents
Picture detection method and system, computer system and computer readable medium Download PDFInfo
- Publication number
- CN112328824A CN112328824A CN202010707675.5A CN202010707675A CN112328824A CN 112328824 A CN112328824 A CN 112328824A CN 202010707675 A CN202010707675 A CN 202010707675A CN 112328824 A CN112328824 A CN 112328824A
- Authority
- CN
- China
- Prior art keywords
- picture
- initial
- target
- module
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 76
- 238000012545 processing Methods 0.000 claims abstract description 62
- 238000004806 packaging method and process Methods 0.000 claims abstract description 28
- 238000000034 method Methods 0.000 claims description 44
- 238000007689 inspection Methods 0.000 claims description 2
- 230000008569 process Effects 0.000 description 20
- 238000012856 packing Methods 0.000 description 14
- 238000004590 computer program Methods 0.000 description 9
- 230000015654 memory Effects 0.000 description 9
- 238000010586 diagram Methods 0.000 description 8
- 238000004891 communication Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 5
- 230000003287 optical effect Effects 0.000 description 4
- 238000013515 script Methods 0.000 description 4
- 239000003086 colorant Substances 0.000 description 3
- 230000006835 compression Effects 0.000 description 3
- 238000007906 compression Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012827 research and development Methods 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 239000000835 fiber Substances 0.000 description 2
- 238000012858 packaging process Methods 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 239000004065 semiconductor Substances 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000006837 decompression Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000008676 import Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000011112 process operation Methods 0.000 description 1
- 239000000758 substrate Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
- G06F16/5838—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using colour
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/40—Transformation of program code
- G06F8/41—Compilation
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Library & Information Science (AREA)
- Software Systems (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Image Processing (AREA)
Abstract
The present disclosure provides a picture detection method, including: acquiring an initial picture set, wherein each picture in the initial picture set is a picture before compiling and packaging processing operation is executed; detecting whether a color profile object exists or not for each picture; retrieving a target picture existing in the initial picture set based on the detected color profile object, wherein the color gamut of the target picture is larger than a preset range; and performing compiling and packaging processing operation on the target picture sets except the target picture in the initial picture set. In addition, the present disclosure also provides a picture detection system, a computer system and a computer readable medium.
Description
Technical Field
The present disclosure relates to the field of picture processing, and more particularly, to a picture detection method and system, a computer system, and a computer readable medium.
Background
To win more users and provide a good user experience for the users, most applications set the adaptation system of the os of the lowest iPhone to be greater than or equal to 8.0. However, due to differences between iOS, when a system below iOS 10 loads some (for example, P3 with a projection range of all colors on a standard color space, that is, a color gamut greater than a preset range), an abnormal flash back phenomenon occurs in an application Store (App Store) package. Therefore, the introduction of the P3 picture brings great hidden trouble to the application program.
The prior art does not provide a direct interface for acquiring the information of the picture P3, the P3 picture inspection is carried out by decompressing by using an assettil tool provided by apple company to obtain an assets.json file, and then the assets.json file is searched for a P3 word for investigation. The assettil tool has great limitation in use, the mode depends on the acquisition of high-level authority of a computer system, even if a script is used for checking, full automation cannot be achieved, and the coverage rate is low.
Disclosure of Invention
In view of the above, the present disclosure provides a picture detection method and system, a computer system, and a computer readable medium.
One aspect of the present disclosure provides a picture detection method, including: acquiring an initial picture set, wherein each picture in the initial picture set is a picture before compiling and packaging processing operation is executed, detecting whether a color characteristic file object exists or not aiming at each picture, retrieving a target picture existing in the initial picture set based on the detected color characteristic file object, wherein the color gamut of the target picture is larger than a preset range, and executing compiling and packaging processing operation on the target picture sets except the target picture in the initial picture set.
According to an embodiment of the present disclosure, the detecting whether there is a color profile object for each picture includes: and reading the summary information of the pictures aiming at each picture, and detecting whether the color characteristic file object exists or not based on the summary information of the pictures.
According to an embodiment of the present disclosure, the reading the picture summary information includes: and creating an image processing library object, and reading the picture abstract information by using the image processing library object.
According to an embodiment of the present disclosure, the retrieving, based on the detected color profile object, a target picture existing in the initial picture set includes: and detecting whether the picture abstract information contains appointed display type information or not based on the detected color profile object, wherein the appointed display type information is used for representing that the color gamut of the picture is larger than the preset range, and taking the picture containing the appointed display type information in the picture abstract information as a target picture which is searched and exists in the initial picture set.
According to an embodiment of the present disclosure, after retrieving a target picture existing in the initial picture set, the method further includes: and saving the picture abstract information of the target picture.
Another aspect of the present disclosure provides a picture detection system, including: the device comprises an acquisition module, a detection module, a retrieval module and a processing module, wherein the acquisition module is used for acquiring an initial picture set, each picture in the initial picture set is a picture before compiling and packaging processing operation is executed, the detection module is used for detecting whether a color characteristic file object exists or not aiming at each picture, the retrieval module is used for retrieving a target picture existing in the initial picture set based on the detected color characteristic file object, the color gamut of the target picture is larger than a preset range, and the processing module is used for executing compiling and packaging processing operation on the target picture sets except the target picture in the initial picture set.
According to an embodiment of the present disclosure, the detection module includes: a reading sub-module for reading the summary information of the picture for each picture, and a first detecting sub-module for detecting whether the color profile object exists based on the summary information of the picture.
According to an embodiment of the present disclosure, the reading submodule includes: the image processing system comprises a creating unit used for creating an image processing library object and a reading unit used for reading the picture abstract information by using the image processing library object.
According to an embodiment of the present disclosure, the search module includes: a second detection submodule, configured to detect whether the picture summary information includes specified display type information based on the detected color profile object, where the specified display type information is used to represent that a color gamut of a picture is larger than the preset range, and the processing submodule is configured to use a picture, which includes the specified display type information in the picture summary information, as a target picture, which is retrieved and exists in the initial picture set.
According to an embodiment of the present disclosure, after retrieving the target picture existing in the initial picture set, the system further includes: and the storage module is used for storing the picture abstract information of the target picture.
Another aspect of the present disclosure provides a computer system comprising: one or more processors; a storage device to store one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of the above.
Another aspect of the disclosure provides a computer-readable medium having stored thereon executable instructions that, when executed by a processor, cause the processor to implement the method of any of the above.
According to the embodiment of the disclosure, for a target picture P3 in an iOS project, before compiling and packing processing operation is performed on each picture in an initial picture set, a color feature file object of each picture is detected to retrieve the target picture existing in the initial picture set, and finally compiling and packing processing operation is performed on the target picture set except the target picture in the initial picture set, so that detection of the target picture is fully automated, and under the condition of not depending on compiling and packing, all pictures used in the iOS project can be comprehensively checked one by one, manual detection is thoroughly released, picture detection efficiency is effectively improved, and potential safety hazards of a system are reduced.
Drawings
The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments of the present disclosure with reference to the accompanying drawings, in which:
fig. 1 schematically shows an exemplary system architecture to which the picture detection method and system thereof of the embodiments of the present disclosure may be applied;
fig. 2 schematically shows a flow chart of a picture detection method according to an embodiment of the present disclosure;
fig. 3 schematically shows a flow chart of a picture detection method according to another embodiment of the present disclosure;
fig. 4 schematically shows a flow chart of a picture detection method according to another embodiment of the present disclosure;
FIG. 5 schematically shows a block diagram of a picture detection system according to an embodiment of the present disclosure; and
FIG. 6 schematically illustrates a block diagram of a computer system suitable for implementing a picture detection method and system thereof according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.
Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). Where a convention analogous to "A, B or at least one of C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B or C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). It will be further understood by those within the art that virtually any disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase "a or B" should be understood to include the possibility of "a" or "B", or "a and B".
The present disclosure provides a picture detection method, including: firstly, an initial picture set is obtained, and each picture in the initial picture set is a picture before compiling and packaging processing operation is executed. Then, for each picture, it is detected whether or not a color profile object exists. Then, based on the detected color profile object, a target picture existing in the initial picture set is retrieved, and the color gamut of the target picture is larger than a preset range. And finally, performing compiling and packaging processing operation on the target picture sets except the target picture in the initial picture set.
According to the embodiment of the disclosure, for a target picture P3 in an iOS project, before compiling and packing processing operation is performed on each picture in an initial picture set, a color feature file object of each picture is detected to retrieve the target picture existing in the initial picture set, and finally compiling and packing processing operation is performed on the target picture set except the target picture in the initial picture set, so that detection of the target picture is fully automated, and under the condition of not depending on compiling and packing, all pictures used in the iOS project can be comprehensively checked one by one, manual detection is thoroughly released, picture detection efficiency is effectively improved, and potential safety hazards of a system are reduced.
Fig. 1 schematically illustrates an exemplary system architecture 100 to which the picture detection method and system thereof of the embodiments of the present disclosure may be applied. It should be noted that fig. 1 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios.
As shown in fig. 1, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (for example only) providing support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and perform other processing on the received data such as the user request, and feed back a processing result (e.g., a webpage, information, or data obtained or generated according to the user request) to the terminal device.
It should be noted that the picture detection method provided by the embodiment of the present disclosure may be generally executed by the server 105. Accordingly, the photo detection system provided by the embodiment of the present disclosure may be generally disposed in the server 105. The picture detection method provided by the embodiment of the present disclosure may also be executed by a server or a server cluster that is different from the server 105 and is capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Accordingly, the picture detection system provided by the embodiment of the present disclosure may also be disposed in a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Fig. 2 schematically shows a flow chart of a picture detection method according to an embodiment of the present disclosure.
As shown in fig. 2, the method may include operations S210 to S240.
In operation S210, an initial picture set is obtained, where each picture in the initial picture set is a picture before performing a compiling and packaging processing operation.
According to an embodiment of the present disclosure, the initial picture set may be a picture set composed of pictures available in the iOS system engineering. Preferably, the picture set is composed of all pictures available in the iOS system engineering. The pictures in the initial picture set may be pictures in a jpg format, and may also be pictures in a png format, which is not limited in this disclosure.
In order to overcome the technical problem that in the related art, due to the normative or application program execution performance of research and development personnel, the pictures are compiled and packaged to be omitted, or even if the compiling and packaging are not omitted, the effect of identifying the P3 pictures after the compiling and packaging is poor, a detection and identification process of the P3 pictures is innovatively executed before the compiling and packaging processing operation according to several embodiments of the disclosure.
In operation S220, for each picture, whether a color profile object exists is detected.
According to the embodiment of the present disclosure, the Color profile (ICC _ profile) object is the core of a standard Color management system created by the International Color Consortium (ICC), and is a file for describing Color characteristics of a certain Color device, which represents the correspondence between the Color description mode of the Color device and the standard Color space, and the description of colors between different devices is linked to the ICC _ profile of the devices through the standard Color space. The range of projection of all the colors of the device, respectively, onto the standard color space is called the color gamut. The P3 picture in this disclosure has a larger gamut space range than the gamut space range of other pictures.
Specifically, for any one jpg or png picture, after being opened, of more information in the picture attribute information, a picture with a color description file of Display P3 is referred to as a P3 picture.
In operation S230, a target picture existing in the initial picture set is retrieved based on the detected color profile object, and a color gamut of the target picture is greater than a preset range.
When hidden information of a picture is studied, according to the embodiment of the present disclosure, for the picture in which a color feature file is detected, whether the picture contains a P3 character is searched, and if yes, the picture is a target picture.
In operation S240, a compilation and packing process operation is performed on a target picture set other than the target picture in the initial picture set.
According to the embodiment of the disclosure, compiling and packaging processing operations are not executed on the retrieved target pictures, so that the technical problem of abnormal flash back of the application package can be effectively avoided, and the application package can normally run without flash back.
In the related art, the P3 picture detection method specifically includes: the method comprises the steps that a picture compression packet generated after packing pictures placed into imageset in the IOS project is an asset.car compression packet, dependent on a high-level system authority management command sudo of a system (the command allows a system administrator to be a tool for executing some or all root commands), the asset.car is decompressed by using an asset tool provided for developers after decompressing the pictures and packing to obtain an asset.json (summary of picture information generated by picture compression), then the asset.json file is searched, namely the file is scanned, whether the displayGamut contains a P3 character or not is searched, if the displayGamut contains the P3 character, the picture is thrown out, and if the displayGamut does not contain the P3 character, the search is ended. In the P3 picture detection method in the related art, as an asseutil tool is used, each examination needs to be packed, a good solution is not provided in the industry, the method depends on the acquisition of high-level authority of a computer system, even if the examination is carried out by using scripts, the full automation cannot be achieved, and the coverage rate is low. In the traditional process, the searches.car need to be decompressed to obtain the searches.json, and then the scanning of the P3 characters can be started, the decompression process also depends on the support of high-level authority of a computer, the compiling and packaging process is long and unpredictable, and the detection process is complicated.
In the related art, a technical scheme for detecting the P3 picture by using the color profile is not provided, and the method can completely abandon the detection mode of the P3 picture provided by the related art, and timely find and completely solve the problem.
Furthermore, the picture detection method provided by the disclosure is separated from the traditional detection process after compiling, and the whole detection process is implemented in a stage before compiling. On the premise that compiling and packaging processing operations are not executed on each picture in the initial picture set, color characteristic file information of all picture information in the iOS project is detected, and whether a target picture containing P3 information exists is searched. As the assets.car is not generated in the whole process, a series of subsequent processing operations of decompressing by using an assets _ tool to obtain assets.json and searching the target picture containing the P3 information from the assets.json can be avoided, all the P3 pictures can be successfully obtained from the initial picture set, and the possibility that the search range of the related technology process is incomplete and omission easily occurs is avoided.
As an alternative embodiment, for each picture, detecting whether a color profile object exists includes: reading the abstract information of each picture; and detecting whether a color profile object exists or not based on the picture abstract information.
As an alternative embodiment, reading the picture summary information includes: creating an image processing library object; and reading the picture abstract information by using the image processing library object.
According to the embodiment of the disclosure, the picture summary information includes explicit information of the picture and also includes hidden information of the picture. Summary information is various information used to describe the attributes of a picture and may include, but is not limited to, general information, more information, and name and extension information. The general information may include, but is not limited to, category, size, location, creation time, and modification time. More information may include, but is not limited to, size, color space, color description file, and Alpha channel.
Whether the color profile object is included or not can be detected by the summary information. Specifically, the picture summary information may be read by the image processing library object.
Alternatively, the Image processing Library object may be an Image object of a Python Image Library (PIL). As an alternative embodiment, retrieving the target picture present in the initial picture set based on the detected color profile object comprises: detecting whether the picture abstract information contains appointed display type information or not based on the detected color profile object, wherein the appointed display type information is used for representing that the color gamut of the picture is larger than a preset range; and taking the picture containing the specified display type information in the picture abstract information as the searched target picture existing in the initial picture set.
As an optional embodiment, after retrieving the target picture existing in the initial picture set, the method further includes: and saving the picture abstract information of the target picture.
According to the embodiment of the present disclosure, for a picture detected to contain a color profile object, whether a display type (DiaplayType) is contained may be further detected, and the value of the display type is P3. If yes, the picture is the P3 picture, and the picture summary information of the target picture is stored. If not, the picture is not the P3 picture and does not need to be saved.
Fig. 3 schematically shows a flow chart of a picture detection method according to another embodiment of the present disclosure.
As shown in fig. 3, the picture detection method includes operations S310 to S360.
In operation S310, the code is submitted.
In operation S320, a P3 picture is detected.
In operation S330, it is detected whether a P3 picture is included. If so, operation S340 is performed. If not, operation S350 is performed.
In operation S340, the packing process is ended and terminated.
In operation S350, a compiling operation is performed.
In operation S360, a packing operation is performed.
The method for detecting the picture by using the assettil tool in the related technology is completely abandoned, so that the whole picture detection process does not need to acquire the high-level authority of the system, the picture detection process is executed before compiling and packaging, the compiling and packaging and the high-level authority support of the system are not relied on, and research and development personnel can detect the picture at any time.
Fig. 4 schematically shows a flow chart of a picture detection method according to another embodiment of the present disclosure.
As shown in fig. 4, the picture detection method includes operations S410 to S4100.
In operation S410, all files and folders under the project directory are scanned.
In operation S420, a subfolder iterator object is created.
In operation S430, each jpg and png picture is traversed.
In operation S440, a PIL image object is created.
In operation S450, it is detected whether an icc _ profile object is included. If so, operation S470 is performed. If not, operation S460 is performed.
In operation S460, the current picture is skipped and the next picture is continuously detected.
In operation S470, it is detected whether DisplayType is included and the value is P3. If yes, operation S480 is performed. If not, operation S460 is performed.
In operation S480, a P3 picture is detected, and the P3 file context is saved. The context may include summary information, i.e., attribute information.
In operation S490, it is detected whether the scanning is completed. If so, operation S4100 is performed. If not, operation S460 is performed.
In operation S4100, the detection process is ended.
According to the embodiment of the disclosure, all picture files are read from the engineering directory before compiling and packaging the pictures, and the P3 information hidden in the icc _ profile is retrieved from the engineering directory, so that the information of the P3 picture is determined, and various technical problems of the picture detection method provided by the related art are successfully avoided.
Through actual measurement, for a certain shopping website application program project of hundred million daily lives, three thousand of jpg pictures and png pictures are scanned for only 10 seconds by using the picture detection method provided by the disclosure, compared with the traditional picture detection method which probably consumes time in the minute level, the detection time is greatly reduced, through multiple test comparison, the picture detection method provided by the disclosure is completely consistent with the scanned assets.
As an optional embodiment, the embodiment of the present disclosure may implement the picture detection method through a script. For example, P3check4py2.py may be used as a detection script, and a path to be detected is taken as a parameter, and a P3 graph detected under the path and sub-paths thereof may be finally output by the embodiments of the present disclosure. The scheme is applied to the daily packaging process of a main station application program of a certain shopping website, and 2 possible online problems caused by P3 picture import are successfully avoided in the continuous 10 version iteration processes.
According to the picture detection method, when the hidden information of the picture is researched, a set of complete solution is provided, the icc _ profile information of all picture information in the engineering is detected on the premise of not compiling and packaging, and the inclusion condition of the P3 information is searched. Car is not generated in the process, so that all pictures can be successfully acquired, and the possibility of missing in the traditional process is avoided. In addition, the method can completely break away from the traditional detection process, the detection process is placed in the stage before compiling to be executed, and the method does not depend on compiling and packaging, so that the pictures used in all iOS projects can be comprehensively checked one by one, and manual detection is completely liberated.
Fig. 5 schematically shows a block diagram of a picture detection system according to an embodiment of the present disclosure.
As shown in fig. 5, the system 500 may include an acquisition module 510, a detection module 520, a retrieval module 530, and a processing module 540.
The obtaining module 510 is configured to obtain an initial picture set, where each picture in the initial picture set is a picture before performing a compiling and packaging processing operation.
A detecting module 520, configured to detect whether there is a color profile object for each picture.
A retrieving module 530, configured to retrieve a target picture existing in the initial picture set based on the detected color profile object, where a color gamut of the target picture is larger than a preset range.
And a processing module 540, configured to perform a compiling and packaging processing operation on the target picture set except the target picture in the initial picture set.
According to the embodiment of the disclosure, for a target picture P3 in an iOS project, before compiling and packing processing operation is performed on each picture in an initial picture set, a color feature file object of each picture is detected to retrieve the target picture existing in the initial picture set, and finally compiling and packing processing operation is performed on the target picture set except the target picture in the initial picture set, so that detection of the target picture is fully automated, and under the condition of not depending on compiling and packing, all pictures used in the iOS project can be comprehensively checked one by one, manual detection is thoroughly released, picture detection efficiency is effectively improved, and potential safety hazards of a system are reduced.
As an alternative embodiment, the detection module comprises: the reading sub-module is used for reading the picture abstract information aiming at each picture; and the first detection submodule is used for detecting whether a color characteristic file object exists or not based on the picture abstract information.
As an alternative embodiment, the reading submodule includes: a creating unit for creating an image processing library object; and the reading unit is used for reading the picture abstract information by utilizing the image processing library object.
As an alternative embodiment, the retrieval module comprises: the second detection submodule is used for detecting whether the picture abstract information contains appointed display type information or not based on the detected color characteristic file object, wherein the appointed display type information is used for representing that the color gamut of the picture is larger than a preset range; and the processing submodule is used for taking the picture containing the specified display type information in the picture abstract information as the searched target picture existing in the initial picture set.
As an optional embodiment, after retrieving the target picture existing in the initial picture set, the system further includes: and the storage module is used for storing the picture abstract information of the target picture.
The method for detecting the picture by using the assettil tool in the related technology is completely abandoned, so that the whole picture detection process does not need to acquire the high-level authority of the system, the picture detection process is executed before compiling and packaging, the compiling and packaging and the high-level authority support of the system are not relied on, and research and development personnel can detect the picture at any time.
It is understood that the obtaining module 510, the detecting module 520, the retrieving module 530, the processing module 540, the reading sub-module, the first detecting sub-module, the creating unit, the reading unit, the second detecting sub-module, the processing sub-module, and the storing module may be combined to be implemented in one module, or any one of the modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to an embodiment of the present invention, at least one of the obtaining module 510, the detecting module 520, the retrieving module 530, the processing module 540, the reading sub-module, the first detecting sub-module, the creating unit, the reading unit, the second detecting sub-module, the processing sub-module, and the saving module may be at least partially implemented as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or implemented in a suitable combination of three implementations of software, hardware, and firmware. Alternatively, at least one of the obtaining module 510, the detecting module 520, the retrieving module 530, the processing module 540, the reading sub-module, the first detecting sub-module, the creating unit, the reading unit, the second detecting sub-module, the processing sub-module, and the saving module may be at least partially implemented as a computer program module, which may perform the functions of the respective modules when the program is executed by a computer.
FIG. 6 schematically illustrates a block diagram of a computer system suitable for implementing a picture detection method and system thereof according to an embodiment of the present disclosure. The computer system illustrated in FIG. 6 is only one example and should not impose any limitations on the scope of use or functionality of embodiments of the disclosure.
As shown in fig. 6, a computer system 600 according to an embodiment of the present disclosure includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. Processor 601 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 601 may also include onboard memory for caching purposes. The processor 601 may comprise a single processing unit or a plurality of processing units for performing the different actions of the method flows according to embodiments of the present disclosure as described above.
In the RAM 603, various programs and data necessary for the operation of the system 600 are stored. The processor 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. The processor 601 performs various operations of the picture detection method described above by executing programs in the ROM 602 and/or the RAM 603. It is to be noted that the program may also be stored in one or more memories other than the ROM 602 and the RAM 603. The processor 601 may also perform various operations of the picture detection method described above by executing programs stored in one or more memories.
According to an embodiment of the present disclosure, system 600 may also include an input/output (I/O) interface 605, input/output (I/O) interface 605 also connected to bus 604. The system 600 may also include one or more of the following components connected to the I/O interface 605: an input portion 601 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
According to an embodiment of the present disclosure, the method described above with reference to the flow chart may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program, when executed by the processor 601, performs the above-described functions defined in the system of the embodiments of the present disclosure. The systems, devices, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.
It should be noted that the computer readable media shown in the present disclosure may be computer readable signal media or computer readable storage media or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer-readable signal medium may include a propagated data signal with computer-readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing. According to embodiments of the present disclosure, a computer-readable medium may include the ROM 602 and/or RAM 603 described above and/or one or more memories other than the ROM 602 and RAM 603.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
As another aspect, the present disclosure also provides a computer-readable medium, which may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to perform a picture detection method.
The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.
Claims (12)
1. A picture detection method comprises the following steps:
acquiring an initial picture set, wherein each picture in the initial picture set is a picture before compiling and packaging processing operation is executed;
detecting whether a color profile object exists or not for each picture;
retrieving a target picture existing in the initial picture set based on the detected color profile object, wherein the color gamut of the target picture is larger than a preset range;
and performing compiling and packaging processing operation on the target picture sets except the target picture in the initial picture set.
2. The method of claim 1, wherein said detecting, for said each picture, whether a color profile object is present comprises:
reading the abstract information of the picture aiming at each picture;
and detecting whether the color profile object exists or not based on the picture abstract information.
3. The method of claim 2, wherein the reading the picture summary information comprises:
creating an image processing library object;
and reading the picture abstract information by using the image processing library object.
4. The method of claim 1, wherein said retrieving a target picture present in said initial picture set based on said detected color profile object comprises:
detecting whether the picture abstract information contains appointed display type information or not based on the detected color profile object, wherein the appointed display type information is used for representing that the color gamut of a picture is larger than the preset range;
and taking the picture containing the specified display type information in the picture abstract information as a target picture which is searched and exists in the initial picture set.
5. The method of claim 1, wherein after retrieving a target picture present in the initial picture set, the method further comprises:
and saving the picture abstract information of the target picture.
6. A picture inspection system comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring an initial picture set, and each picture in the initial picture set is a picture before compiling and packaging processing operation is executed;
the detection module is used for detecting whether a color characteristic file object exists or not aiming at each picture;
the retrieval module is used for retrieving a target picture existing in the initial picture set based on the detected color profile object, and the color gamut of the target picture is larger than a preset range;
and the processing module is used for executing compiling and packaging processing operation on the target picture sets except the target picture in the initial picture set.
7. The system of claim 6, wherein the detection module comprises:
the reading sub-module is used for reading the picture abstract information aiming at each picture;
and the first detection submodule is used for detecting whether the color characteristic file object exists or not based on the picture abstract information.
8. The system of claim 7, wherein the read submodule comprises:
a creating unit for creating an image processing library object;
and the reading unit is used for reading the picture abstract information by utilizing the image processing library object.
9. The system of claim 6, wherein the retrieval module comprises:
the second detection submodule is used for detecting whether the picture abstract information contains appointed display type information or not based on the detected color profile object, wherein the appointed display type information is used for representing that the color gamut of the picture is larger than the preset range;
and the processing submodule is used for taking the picture containing the specified display type information in the picture abstract information as the retrieved target picture existing in the initial picture set.
10. The system of claim 6, wherein after retrieving a target picture present in the initial set of pictures, the system further comprises:
and the storage module is used for storing the picture abstract information of the target picture.
11. A computer system, comprising:
one or more processors; and
a storage device for storing one or more programs,
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-6.
12. A computer readable medium having stored thereon executable instructions which, when executed by a processor, cause the processor to carry out the method of any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010707675.5A CN112328824A (en) | 2020-07-21 | 2020-07-21 | Picture detection method and system, computer system and computer readable medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010707675.5A CN112328824A (en) | 2020-07-21 | 2020-07-21 | Picture detection method and system, computer system and computer readable medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112328824A true CN112328824A (en) | 2021-02-05 |
Family
ID=74303631
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010707675.5A Pending CN112328824A (en) | 2020-07-21 | 2020-07-21 | Picture detection method and system, computer system and computer readable medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112328824A (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060280360A1 (en) * | 1996-02-26 | 2006-12-14 | Holub Richard A | Color calibration of color image rendering devices |
| US20160286058A1 (en) * | 2015-03-25 | 2016-09-29 | Konica Minolta, Inc. | Information processing terminal and non-transitory readable recording medium |
| CN108563578A (en) * | 2018-04-20 | 2018-09-21 | 平安科技（深圳）有限公司 | SDK compatibility detection method, device, equipment and readable storage medium storing program for executing |
| CN109614064A (en) * | 2018-12-13 | 2019-04-12 | Oppo广东移动通信有限公司 | A kind of image display method, image display apparatus and terminal device |
| CN109710499A (en) * | 2018-11-13 | 2019-05-03 | 平安科技（深圳）有限公司 | The recognition methods of computer equipment performance and device |
| CN110209591A (en) * | 2019-06-05 | 2019-09-06 | 北京字节跳动网络技术有限公司 | Picture searching method, apparatus, electronic equipment and storage medium |
| CN110365962A (en) * | 2019-07-17 | 2019-10-22 | Oppo广东移动通信有限公司 | Color gamut conversion processing method, device and electronic equipment |
-
2020
- 2020-07-21 CN CN202010707675.5A patent/CN112328824A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060280360A1 (en) * | 1996-02-26 | 2006-12-14 | Holub Richard A | Color calibration of color image rendering devices |
| US20160286058A1 (en) * | 2015-03-25 | 2016-09-29 | Konica Minolta, Inc. | Information processing terminal and non-transitory readable recording medium |
| CN108563578A (en) * | 2018-04-20 | 2018-09-21 | 平安科技（深圳）有限公司 | SDK compatibility detection method, device, equipment and readable storage medium storing program for executing |
| CN109710499A (en) * | 2018-11-13 | 2019-05-03 | 平安科技（深圳）有限公司 | The recognition methods of computer equipment performance and device |
| CN109614064A (en) * | 2018-12-13 | 2019-04-12 | Oppo广东移动通信有限公司 | A kind of image display method, image display apparatus and terminal device |
| CN110209591A (en) * | 2019-06-05 | 2019-09-06 | 北京字节跳动网络技术有限公司 | Picture searching method, apparatus, electronic equipment and storage medium |
| CN110365962A (en) * | 2019-07-17 | 2019-10-22 | Oppo广东移动通信有限公司 | Color gamut conversion processing method, device and electronic equipment |
Non-Patent Citations (2)
| Title |
|---|
| 何敏丽;成刚虎;: "ICC Profile及基于ICC的色彩管理技术", 广东印刷, no. 06, 25 December 2006 (2006-12-25) * |
| 张晓燕;胡涛;: "Windows 98与Windows NT5.0的色彩管理系统――ICM2.0", 中国印刷, no. 09, 19 September 2000 (2000-09-19) * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109062563B (en) | Method and device for generating page | |
| CN109862100B (en) | Method and device for pushing information | |
| CN110858172A (en) | Automatic test code generation method and device | |
| CN113138757B (en) | Front-end code automatic generation method, device, server, system and medium | |
| CN106886594B (en) | Method and device for displaying information | |
| CN108764374B (en) | Image classification method, system, medium, and electronic device | |
| CN107402878B (en) | Test method and device | |
| CN113962597A (en) | Data analysis method and device, electronic equipment and storage medium | |
| CN111813685B (en) | Automatic test method and device | |
| CN113535577A (en) | Application testing method and device based on knowledge graph, electronic equipment and medium | |
| CN108984221B (en) | Method and device for acquiring multi-platform user behavior logs | |
| CN112328824A (en) | Picture detection method and system, computer system and computer readable medium | |
| CN113138974B (en) | Method and device for detecting database compliance | |
| CN113590447B (en) | Buried point processing method and device | |
| CN113377376A (en) | Data packet generation method, data packet generation device, electronic device, and storage medium | |
| CN110020906B (en) | Order information detection method and device | |
| CN106777403B (en) | Information pushing method and device | |
| CN113760706B (en) | Webpage debugging method and device | |
| CN112579553B (en) | Method and apparatus for recording information | |
| CN114095494B (en) | Method and system for quickly downloading files | |
| CN108399223B (en) | Data acquisition method and device and electronic equipment | |
| US10579696B2 (en) | Save session storage space by identifying similar contents and computing difference | |
| CN112800051A (en) | Recovery method and device for deleted records of PostGresSQL database | |
| CN115629983A (en) | Test case set generation method, device, equipment and medium | |
| CN117708463A (en) | Page loading method, device, electronic equipment and computer readable medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |