CN112328824B - Picture detection method and system, computer system and computer readable medium - Google Patents
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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 characteristic file object exists for each picture; searching out 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 performing compiling and packaging processing operation on the target picture set 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 thereof.
Background
In order to gain more users and provide a good user experience for the users, most applications set the adaptation system of the operating system iOS of the lowest iPhone to be greater than or equal to 8.0. However, due to the differences between iOS, when some (e.g., P3 with a color gamut greater than a preset range for all colors) pictures are loaded on the system below iOS10, an abnormal flash back phenomenon occurs in an application Store (App Store) package. Therefore, the introduction of the P3 picture can bring about a huge hidden trouble to the application program.
In the prior art, no interface for directly acquiring P3 information of a picture is provided, P3 picture inspection is carried out by decompressing by using a assetutil tool to obtain an assembly.json file, and then searching the assembly.json file for a P3 word sample for inspection. The assetutil tool has great limitation in use, and the mode depends on the acquisition of advanced authority of a computer system, even if a script is used for investigation, full automation cannot be realized, and the coverage rate is low.
Disclosure of Invention
In view of this, the present disclosure provides a picture detection method and system, a computer system and a computer readable medium thereof.
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 performed, detecting whether a color characteristic file object exists for each picture, searching a target picture existing in the initial picture set based on the detected color characteristic file object, and performing compiling and packaging processing operation on the target picture set except the target picture in the initial picture set, wherein the color gamut of the target picture is larger than a preset range.
According to an embodiment of the present disclosure, the detecting whether the color profile object exists for each of the pictures includes: and reading the picture summary information for each picture, and detecting whether the color characteristic file object exists or not based on the picture summary information.
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 the target picture existing in the initial picture set based on the detected color profile object includes: and detecting whether the picture summary 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 the preset range, and taking the picture containing the appointed display type information in the picture summary information as a target picture 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 method further includes: and saving the picture abstract information of the target picture.
Another aspect of the present disclosure provides a picture detection system, comprising: the system 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 for 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 for the target picture set except the target picture in the initial picture set.
According to an embodiment of the present disclosure, the detection module includes: the first detection sub-module is used for detecting whether the color characteristic file object exists or not based on the picture summary information.
According to an embodiment of the present disclosure, the reading sub-module includes: the image processing library object is used for generating image processing library objects, and the reading unit is used for reading the picture abstract information by utilizing the image processing library objects.
According to an embodiment of the present disclosure, the above-mentioned retrieval module includes: the second detection sub-module is used for detecting whether the picture summary 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 the preset range, and the processing sub-module is used for taking the picture containing the appointed display type information in the picture summary information as a searched target picture existing 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; and a storage means 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 the preceding claims.
Another aspect of the present 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, aiming at the P3 target picture in the iOS engineering, before compiling and packing processing operation is carried out on each picture in the initial picture set, the color characteristic file object of each picture is detected to search out the target picture existing in the initial picture set, and finally compiling and packing processing operation is carried out on the target picture set except the target picture in the initial picture set, so that the detection of the target picture is fully automatic, and the pictures used in all the iOS engineering can be thoroughly and individually examined without depending on compiling and packing, thereby thoroughly freeing up manual detection, effectively improving the picture detection efficiency and reducing the potential safety hazard of a system.
Drawings
The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments thereof with reference to the accompanying drawings in which:
FIG. 1 schematically illustrates an exemplary system architecture to which the picture detection methods and systems of embodiments of the present disclosure may be applied;
fig. 2 schematically illustrates a flow chart of a picture detection method according to an embodiment of the present disclosure;
Fig. 3 schematically illustrates a flow chart of a picture detection method according to another embodiment of the present disclosure;
fig. 4 schematically illustrates a flow chart of a picture detection method according to another embodiment of the present disclosure;
FIG. 5 schematically illustrates a block diagram of a picture detection system according to an embodiment of the disclosure; and
Fig. 6 schematically illustrates a block diagram of a computer system suitable for implementing a picture detection method and a system thereof, in accordance with 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 only exemplary and is not intended to limit the scope of the present disclosure. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to 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/or 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 should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.
Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a convention should be interpreted in accordance with the meaning of one of skill in the art having generally understood the convention (e.g., "a system having at least one of A, B and C" would include, but not be limited to, systems having 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 formulation similar to at least one of "A, B or C, etc." is used, in general such a formulation should be interpreted in accordance with the ordinary understanding of one skilled in the art (e.g. "a system with at least one of A, B or C" would include but not be limited to systems with 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 should also be appreciated by those skilled in the art that virtually any disjunctive word and/or phrase presenting two or more alternative items, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the items, either of the items, or both. 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: first, an initial picture set is acquired, 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 there is a color profile object. Then, based on the detected color characteristic file 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 set except the target picture in the initial picture set.
According to the embodiment of the disclosure, aiming at the P3 target picture in the iOS engineering, before compiling and packing processing operation is carried out on each picture in the initial picture set, the color characteristic file object of each picture is detected to search out the target picture existing in the initial picture set, and finally compiling and packing processing operation is carried out on the target picture set except the target picture in the initial picture set, so that the detection of the target picture is fully automatic, and the pictures used in all the iOS engineering can be thoroughly and individually examined without depending on compiling and packing, thereby thoroughly freeing up manual detection, effectively improving the picture detection efficiency and reducing the potential safety hazard of a system.
Fig. 1 schematically illustrates an exemplary system architecture 100 to which the picture detection methods and systems of 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 embodiments of the present disclosure may be applied to assist those skilled in the art in understanding the technical content of the present disclosure, but does not mean that embodiments of the present disclosure may not be used in other devices, systems, environments, or scenarios.
As shown in fig. 1, a system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications, such as shopping class applications, web browser applications, search class applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only) may be installed on the terminal devices 101, 102, 103.
The terminal devices 101, 102, 103 may be a variety of electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop and desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (by way of example only) providing support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and process the received data such as the user request, and feed back the processing result (e.g., the web page, information, data, etc. acquired or generated according to the user request) to the terminal device.
It should be noted that the method for detecting a picture provided by the embodiments of the present disclosure may be generally performed by the server 105. Accordingly, the picture detection system provided by the embodiments of the present disclosure may be generally disposed in the server 105. The picture detection method provided by the embodiments of the present disclosure may also be performed 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 embodiments of the present disclosure may also be provided 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 flowchart 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 acquired, each picture in the initial picture set being a picture before the compiling and packing process operation is performed.
According to an embodiment of the present disclosure, the initial picture set may be a picture set composed of pictures that can be used in iOS system engineering. Preferably, the image set is composed of all the images used in the iOS system engineering. The pictures in the initial picture set may be jpg format pictures or png format pictures, which is not limited in this disclosure.
In order to overcome the technical problems that in the related art, due to the standardability of research personnel or the execution performance of an application program, the compiling and packaging of the picture is omitted, or even if the compiling and packaging are not omitted, the effect of identifying the P3 picture is poor after the compiling and packaging, the detection and identification process of the P3 picture is creatively executed before the compiling and packaging processing operation in a plurality of embodiments of the disclosure.
In operation S220, it is detected whether a color profile object exists for each picture.
According to an embodiment of the present disclosure, a color profile (icc_profile) object is a core of a standard color management system created by the international color consortium (International Color Consortium, ICC), is a file for describing color characteristics of a certain color device, and represents a correspondence between a color description manner of the color device and a standard color space, and descriptions of colors between different devices are related by the standard color space and icc_profiles of the devices. The projection range of all the respective colors of the device onto the standard color space is called the color gamut. The P3 picture in the present disclosure has a larger color gamut spatial range than that of other pictures.
Specifically, for any one jpg or png picture, the picture with the color description file being Display P3 is called P3 picture in more information in the picture attribute information after being opened.
In operation S230, a target picture existing in the initial picture set is retrieved based on the detected color profile object, and the color gamut of the target picture is greater than the preset range.
When researching the hidden information of the picture, according to the embodiment of the disclosure, for the picture with the detected color feature file, whether the picture contains the P3 word or not is searched, and if so, the picture is the target picture.
In operation S240, a compilation packaging 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 flashing back of the application program package can be effectively avoided, and the application program package can normally run without flashing back.
In the related art, the P3 picture detection method specifically includes: the picture compression package generated after the picture of imageasset is packed in the iOS engineering, namely an asset. Car compression package, depends on an advanced system authority management command sudo of the system (the command allows a system administrator to execute some or all root commands by an ordinary user), uses a assetutil tool provided for a developer to decompress the picture after packing to decompress the asset. Car to obtain an asset. Json (picture information abstract generated by picture compression), searches the asset. Json file, namely scans the file, searches DisPlayGamut whether P3 words are contained, throws out the picture if the P3 words are contained, and ends the search if the P3 words are not contained. In the related art, since the P3 picture detection method uses assetutil tools, each investigation needs packaging, no good solution exists in the industry, the method depends on the acquisition of the advanced authority of the computer system, even if the investigation is performed by using scripts, the full automation cannot be realized, and the coverage rate is low. The traditional process can start to scan the P3 word only by decompressing the Assets. Car to obtain the Assets. Json, the decompression process also depends on the support of the advanced authority of the computer, the compiling and packaging process is long, unpredictable and the detection process is complex.
In the related art, a technical scheme for detecting the P3 picture by using a color characteristic file is not provided, but the detection mode of the P3 picture provided by the related art can be thoroughly abandoned, and the problems can be timely found and thoroughly solved.
Further, the picture detection method provided by the disclosure is separated from the traditional detection flow after compiling, and the whole detection process is placed at a stage before compiling. And on the premise that compiling and packaging processing operation is not carried out on each picture in the initial picture set, detecting color characteristic file information of all picture information in the iOS engineering, and searching whether a target picture containing P3 information exists or not. Because the whole process does not generate the frames. Car, the subsequent decompression by using assetutil tools to obtain the frames. Json can be avoided, and then a series of processing operations of searching the target pictures containing the P3 information from the frames. Json can successfully acquire all the P3 pictures from the initial picture set, thereby avoiding the possibility of incomplete searching range and easy omission of the related technical process.
As an alternative embodiment, for each picture, detecting whether a color profile object is present comprises: reading picture abstract information for each picture; based on the picture summary information, it is detected whether a color profile object exists.
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 an embodiment of the present disclosure, the picture summary information includes explicit information of the picture, and also includes hidden information of the picture. Summary information is a variety of 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. The further information may include, but is not limited to, size, color space, color description file, and Alpha channel.
It can be detected whether the color profile object is contained or not by the digest information. Specifically, the picture summary information may be read by an image processing library object.
Alternatively, the image processing library object may be an image object of a Python image library (Python Image Library, PIL). As an alternative embodiment, retrieving the target picture existing in the initial picture set based on the detected color profile object includes: detecting whether the picture summary 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 taking the picture containing the appointed display type information in the picture summary information as the searched target picture existing in the initial picture set.
As an alternative embodiment, after retrieving the target picture existing in the initial picture set, the method further comprises: and saving the picture abstract information of the target picture.
According to embodiments of the present disclosure, for detecting a picture containing a color profile object, it may be further detected whether a display type (DIAPLAYTYPE) is contained, and the value of the display type is P3. If the target picture is included, the picture is indicated to be a P3 picture, and the picture abstract information of the target picture is stored. If not, the picture is not the P3 picture, and the picture does not need to be stored.
Fig. 3 schematically shows a flowchart 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, the P3 picture is detected.
In operation S330, it is detected whether a P3 picture is included. If yes, 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 utilizing the assetutil tool in the related technology is thoroughly abandoned, so that the whole picture detection process does not need to acquire the high-level authority of the system, the method 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 at any time.
Fig. 4 schematically shows a flowchart 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, folders under the engineering directory are scanned.
In operation S420, a subfolder iterator object is created.
In operation S430, each of the jpg and png pictures 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 yes, operation S4100 is executed. If not, operation S460 is performed.
In operation S4100, the detection process ends.
According to the embodiment of the disclosure, all the picture files are read from the engineering catalog before compiling and packaging the pictures, and the P3 information hidden in the icc_profile is retrieved from the engineering catalog, so that the information of the P3 picture is determined, and various technical problems of a picture detection method provided by the related technology are successfully avoided.
Through actual measurement, for the application engineering of a shopping website with hundreds of thousands of daily activities, the scanning time length of the picture detection method provided by the present disclosure is only 10 seconds, compared with the traditional picture detection method which is approximately time-consuming at the minute level, the detection time is greatly reduced, and through multiple test comparison, the picture detection method provided by the present disclosure is completely consistent with the scanning assembly.json in accuracy, but the whole detection process of the picture detection method provided by the present disclosure can thoroughly cover all engineering pictures, and has good practicability.
As an alternative embodiment, the embodiment of the disclosure may implement the picture detection method through a script. For example, p3check4py2.py may be used as a detection script, and in combination with a path to be detected as a parameter, the P3 map detected under the path and its sub-path may be output finally through the embodiments of the present disclosure. The scheme is applied to the daily packing flow of the master station application program of a shopping website, and in the continuous 10-version iteration process, the problem that 2 cases possibly cause on-line due to P3 picture import is successfully avoided.
The picture detection method provides a complete solution when researching hidden information of pictures, and detects icc_profile information of all picture information in engineering on the premise of not compiling and packing, and searches for the inclusion condition of P3 information. Because the process does not generate the Assembles. Car yet, all the pictures can be successfully acquired, thereby avoiding the possibility of missing the traditional process. In addition, the method and the device can be completely separated from the traditional detection flow, and the detection process is carried out at a stage before compiling, so that the pictures used in all iOS projects can be comprehensively examined one by one without depending on compiling and packing, and manual detection is thoroughly liberated.
Fig. 5 schematically illustrates a block diagram of a picture detection system according to an embodiment of the 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 the compiling and packaging processing operation.
The detecting module 520 is configured to detect, for each picture, whether a color profile object exists.
The retrieving module 530 is configured to retrieve a target picture existing in the initial picture set based on the detected color profile object, where the color gamut of the target picture is greater than the preset range.
And the processing module 540 is used for performing 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, aiming at the P3 target picture in the iOS engineering, before compiling and packing processing operation is carried out on each picture in the initial picture set, the color characteristic file object of each picture is detected to search out the target picture existing in the initial picture set, and finally compiling and packing processing operation is carried out on the target picture set except the target picture in the initial picture set, so that the detection of the target picture is fully automatic, and the pictures used in all the iOS engineering can be thoroughly and individually examined without depending on compiling and packing, thereby thoroughly freeing up manual detection, effectively improving the picture detection efficiency and reducing the potential safety hazard of a system.
As an alternative embodiment, the detection module comprises: the reading submodule is used for reading the picture abstract information aiming at each picture; and the first detection sub-module is used for detecting whether the color characteristic file object exists or not based on the picture abstract information.
As an alternative embodiment, the reading submodule comprises: a creation 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 retrieving module comprises: the second detection sub-module is used for detecting whether the picture summary 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 sub-module is used for taking the picture containing the appointed display type information in the picture abstract information as the retrieved target picture existing in the initial picture set.
As an alternative embodiment, after retrieving the target picture existing in the initial picture set, the system further comprises: and the storage module is used for storing the picture abstract information of the target picture.
The method for detecting the picture by utilizing the assetutil tool in the related technology is thoroughly abandoned, so that the whole picture detection process does not need to acquire the high-level authority of the system, the method 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 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 in one module to be implemented, or any one of the modules may be split into a plurality of modules. Or at least some of the functionality of one or more of the modules may be combined with, and implemented in, at least some of the functionality of other modules. According to embodiments of the invention, at least one of the acquisition module 510, the detection module 520, the retrieval module 530, the processing module 540, the reading sub-module, the first detection sub-module, the creation unit, the reading unit, the second detection sub-module, the processing sub-module, and the saving module may be implemented at least in part as hardware circuitry, 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 any other reasonable manner of integrating or packaging a circuit, or in any other suitable combination of three implementations of software, hardware, and firmware. Or at least one of the acquisition module 510, the detection module 520, the retrieval module 530, the processing module 540, the reading sub-module, the first detection sub-module, the creation unit, the reading unit, the second detection sub-module, the processing sub-module, and the saving module may be at least partially implemented as a computer program module, which when executed by a computer, may perform the functions of the respective module.
Fig. 6 schematically illustrates a block diagram of a computer system suitable for implementing a picture detection method and a system thereof, in accordance with an embodiment of the present disclosure. The computer system illustrated in fig. 6 is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present disclosure.
As shown in fig. 6, a computer system 600 according to an embodiment of the present disclosure includes a processor 601 that 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. The processor 601 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or an associated chipset and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. Processor 601 may also include on-board 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 disclosure as described above.
In the RAM 603, various programs and data required for the operation of the system 600 are stored. The processor 601, the ROM 602, and the RAM 603 are connected to each other through 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. Note that the program may 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, the system 600 may further include an input/output (I/O) interface 605, the input/output (I/O) interface 605 also being connected to the bus 604. The system 600 may also include one or more of the following components connected to the I/O interface 605: an input section 601 including a keyboard, a mouse, and the like; an output portion 607 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; 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 drive 610 is also connected to the I/O interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.
According to embodiments of the present disclosure, the method described above with reference to the flowcharts 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 shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 609, and/or installed from the removable medium 611. The above-described functions defined in the system of the embodiments of the present disclosure are performed when the computer program is executed by the processor 601. The systems, devices, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the disclosure.
It should be noted that the computer readable medium shown in the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any 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 context of this 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 the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. 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, the computer-readable medium may include the ROM 602 and/or the RAM 603 described above and/or one or more memories other than the ROM 602 and the RAM 603.
The flowcharts 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 that may be contained in the apparatus described in the above embodiments; or may be present alone without being fitted into the device. The computer-readable medium carries one or more programs which, when executed by one of the apparatuses, cause the apparatus to perform a picture detection method.
The embodiments of the present disclosure are described above. These examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the embodiments cannot be used advantageously in combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be made by those skilled in the art without departing from the scope of the disclosure, and such alternatives and modifications are intended to fall within the scope of the disclosure.
Claims (8)
1. A picture detection method, comprising:
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 for each picture;
Searching out 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;
performing compiling and packaging processing operation on a target picture set except the target picture in the initial picture set;
wherein, for each picture, the detecting whether the color profile object exists includes:
Reading picture abstract information aiming at each picture;
Detecting whether the color characteristic file object exists or not based on the picture abstract information;
The retrieving, based on the detected color profile object, a target picture that exists in the initial picture set includes:
Detecting whether the picture summary 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 a picture is larger than the preset range;
And taking the picture containing the appointed display type information in the picture abstract information as the retrieved target picture existing in the initial picture set.
2. The method of claim 1, wherein the reading of the picture summary information comprises:
Creating an image processing library object;
and reading the picture abstract information by using the image processing library object.
3. The method of claim 1, wherein after retrieving the target picture present in the initial picture set, the method further comprises:
And saving the picture abstract information of the target picture.
4. A picture detection system, comprising:
the system comprises an acquisition module, a compiling and packaging module and a packaging module, wherein the acquisition module is used for acquiring an initial picture set, wherein 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 for each picture;
the searching module is used for searching out a target picture existing in the initial picture set based on the detected color characteristic file object, and the color gamut of the target picture is larger than a preset range;
The processing module is used for executing compiling and packaging processing operation on the target picture set except the target picture in the initial picture set;
the detection module comprises:
The reading submodule is used for reading the picture abstract information aiming at each picture;
the first detection sub-module is used for detecting whether the color characteristic file object exists or not based on the picture abstract information;
the retrieval module comprises:
The second detection sub-module is used for detecting whether the picture summary 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 the preset range;
And the processing sub-module is used for taking the picture containing the appointed display type information in the picture abstract information as the retrieved target picture existing in the initial picture set.
5. The system of claim 4, wherein the read sub-module comprises:
A creation 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.
6. The system of claim 4, wherein after retrieving the target picture present in the initial picture set, the system further comprises:
and the storage module is used for storing the picture abstract information of the target picture.
7. A computer system, comprising:
One or more processors; and
Storage means 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 1-3.
8. A computer readable medium having stored thereon executable instructions which, when executed by a processor, cause the processor to implement the method of any of claims 1 to 3.
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