CN115423878A - Image test system, image test method, electronic device, and storage medium - Google Patents
Image test system, image test method, electronic device, and storage medium Download PDFInfo
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- CN115423878A CN115423878A CN202211026875.XA CN202211026875A CN115423878A CN 115423878 A CN115423878 A CN 115423878A CN 202211026875 A CN202211026875 A CN 202211026875A CN 115423878 A CN115423878 A CN 115423878A
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Abstract
An image testing system, an image testing method, an electronic device, and a computer-readable storage medium are disclosed. The image testing system comprises an application program module, a hardware abstraction module and a hardware driving module. And the application program module is used for generating control parameters according to a preset control algorithm and transmitting the control parameters to the hardware driving module through the hardware abstraction module. And the hardware driving module is used for working according to the control parameters to obtain a test image and transmitting the test image to the application program module. The application program module is used for generating a test result according to the test image. According to the technical scheme, the control parameters are generated by the application program module according to the preset control algorithm, so that a platform algorithm of the hardware abstraction module is not needed, and under the condition that software effect testing of the hardware abstraction module is not completed, whether the hardware problem exists in the camera or not can be determined through image testing, and therefore the problem of the camera is determined in advance to be improved.
Description
Technical Field
The present application relates to a camera test technology, and more particularly, to an image test system, an image test method, an electronic device, and a computer-readable storage medium.
Background
In the related art, the related test of the camera hardware of the mobile phone production line depends on the software effect debugging of the hardware abstraction module, the software effect debugging is coupled too deeply with the software, when the software effect debugging lags behind the whole machine production, the image software problem can cover the camera hardware problem, and the camera hardware problem cannot be exposed in advance, so that the best improvement time is missed.
Disclosure of Invention
The embodiment of the application provides an image testing system, an image testing method, electronic equipment and a computer readable storage medium.
The image testing system comprises an application program module, a hardware abstraction module and a hardware driving module. And the application program module is used for generating control parameters according to a preset control algorithm and transmitting the control parameters to the hardware driving module through the hardware abstraction module. And the hardware driving module is used for working according to the control parameters to obtain a test image and transmitting the test image to the application program module. The application program module is used for generating a test result according to the test image
The image testing method of the embodiment of the application comprises the following steps: the application program module generates control parameters according to a preset control algorithm and transmits the control parameters to the hardware driving module through the hardware abstraction module; the hardware driving module works according to the control parameters to obtain a test image and transmits the test image to the application program module; and the application program module generates a test result according to the test image.
The electronic device of the embodiments of the present application comprises one or more processors and a memory, wherein the memory stores a computer program, and the steps of the image testing method are realized when the computer program is executed by the processors.
The computer readable storage medium of the present application embodiment has stored thereon a computer program which, when executed by a processor, implements the steps of the image testing method described above.
In the image testing system, the image testing method, the electronic device and the computer readable storage medium, the application program module generates the control parameters according to the preset control algorithm, so that a platform algorithm of the hardware abstraction module is not needed, and whether the camera has a hardware problem or not can be determined through image testing under the condition that the software effect testing of the hardware abstraction module is not completed, so that the camera problem is determined in advance to be improved.
Additional aspects and advantages of embodiments of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of embodiments of the present application.
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The above and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic diagram of an image testing system according to some embodiments of the present application;
FIGS. 2-8 are schematic flow charts of image testing methods according to certain embodiments of the present disclosure;
FIG. 9 is a schematic view of an electronic device of some embodiments of the present application.
Detailed Description
Reference will now be made in detail to the embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are illustrative and are only for the purpose of explaining the present application and are not to be construed as limiting the present application.
The following disclosure provides many different embodiments or examples for implementing different configurations of embodiments of the application. In order to simplify the disclosure of the embodiments of the present application, the components and arrangements of specific examples are described below. Of course, they are merely examples and are not intended to limit the present application.
In the related art, the process of testing the definition of the camera of the mobile phone production line and the cleanliness of the imaging system is as follows: a Hardware abstraction module (HAL) utilizes a 3A algorithm of a platform (the platform and a mobile phone usually belong to different manufacturers, and therefore the algorithm of the platform needs to be debugged) to transmit a picture stream to an SFR (Spatial Frequency Response) after 3A convergence is completed, wherein the SFR is mainly used for measuring the influence of line increase of Spatial Frequency on a single image and obtaining definition) and a white board (cleanliness) algorithm to perform image processing, so as to judge whether the definition of the camera meets the requirement, and synchronously check the problems of black clusters/bright lines and the like of the camera.
The SFR test method can be as follows: HAL completes focusing by using an AE (automatic exposure) algorithm and an AF (automatic focusing) algorithm of a platform, and carries out definition calculation on a collected pure RAW (light source signals captured by a CMOS or CCD image sensor are converted into original data of digital signals) image, so that SFR test depends on the debugging progress and accuracy of the AE algorithm/AF algorithm.
The whiteboard testing method can be as follows: HAL completes convergence by using an AE algorithm/AWB (automatic white balance) algorithm of a platform, converts an acquired RAW Image into a JPG (joint photographic experts group) Image after being processed by an Image Signal Processor (ISP) and then performs Image processing to judge the cleanliness of the Image, and is deeply coupled with an AE algorithm and an AWB algorithm of effect debugging.
The related test of the camera hardware of the mobile phone production line depends on the software effect debugging of the hardware abstraction module, the software effect debugging is too deep, when the software effect debugging lags behind the whole machine production, the problem of the camera hardware can be covered by the image software problem, the problem of the camera hardware can be exposed only after the camera hardware problem is delayed to the half section after the test, the optimization progress of the camera hardware problem is delayed, and the camera hardware problem cannot be exposed in advance and the best improvement time is missed.
Referring to fig. 1, an Image Test System (ITS) 100 according to an embodiment of the present disclosure includes an application module 10, a hardware abstraction module 20, and a hardware driver module 30. The application module 10 is configured to generate control parameters according to a preset control algorithm, and transmit the control parameters to the hardware driver module 30 through the hardware abstraction module 20. The hardware driver module 30 is configured to operate according to the control parameters to obtain a test image and transmit the test image to the application module 10. The application module 10 is used to generate a test result from the test image.
In the image testing system 100 according to the embodiment of the present application, the application module 10 generates the control parameters according to the preset control algorithm, so that it is not necessary to use the platform algorithm of the hardware abstraction module 20, and in the case that the software effect test of the hardware abstraction module 20 is not completed, it is possible to determine whether the camera has a hardware problem through the image test, so as to determine the camera problem in advance to improve the camera problem.
In particular, the image testing system 100 may be used for a camera. The application program module 10 may be a Camera engineering Mode (Camera engineering Mode) APP, a preset control algorithm that has already been debugged may be stored in the application program module 10, and an algorithm of a platform may not be used in an image test process, so that a software debugging progress of the platform algorithm does not need to be relied on. In addition, different projects and different platforms can use the same application program module 10, and the decoupling from the software effect debugging is really realized.
The camera includes hardware structures such as a lens, an image sensor, a motor, and an aperture, and the hardware driving module 30 may be configured to drive the hardware structures of the camera, for example, the hardware driving module 30 may be configured to drive the motor to drive the lens and/or the image sensor to move, and the hardware driving module 30 may be configured to drive an aperture switch and control the size of the aperture. The test image may be transmitted directly (without passing through the hardware abstraction module 20) by the hardware driver module 30 to the application module 10. The application program module 10 is configured to generate a test result according to the test image, and determine whether the hardware structure of the camera is abnormal according to the test result, for example, the camera may be checked to have problems such as black clusters/bright lines. Wherein the test image may be a RAW image.
For production line image problem testing, production line camera hardware testing does not depend on the debugging effect and progress of software AF and AWB of a hardware abstraction module, hardware problem testing can be performed in advance, and image testing smoothness is improved. For hardware research and development engineers, software analysis is not needed when a production line tests problems, and the hardware engineers can analyze abnormal points of hardware through locally stored data. To image effect engineer, need not pay close attention to the hardware problem test again, can liberate manpower and energy in solving and producing the line problem, attentively overcome the image effect problem.
According to the embodiment of the application, the plotting process of the test image is optimized, so that the decoupling of the camera hardware test process and the effect debugging of the image software is realized, and the whole test process does not depend on the progress and the accuracy of the software effect debugging.
In some embodiments, the predetermined control algorithm comprises a 3A algorithm, the control parameters comprise a 3A parameter, and the application module 10 is configured to determine the sharpness of the test image as the test result.
Therefore, the definition test can be carried out on the test image, so that the definition test does not need to depend on the software debugging progress of a platform algorithm, and the decoupling is realized.
Specifically, the 3A algorithm includes an AE algorithm, an AF algorithm, and an AWB algorithm, and the 3A parameters include AE parameters, AF parameters, and AWB parameters. The definition test may be performed by using an SFR test method, and specifically, the application module 10 may generate AE parameters and AF parameters according to an AE algorithm and an AF algorithm, and the AE parameters and the AF parameters are transmitted to the hardware driver module 30 through the hardware abstraction module 20. The hardware driving module 30 is used for completing focusing according to the AE parameters and AF parameters to acquire a test image and transmitting the test image to the application module 10. The application module 10 is used to determine the sharpness of the test image as a test result.
In some embodiments, the application module 10 is configured to determine the sharpness of the test image, generate a new 3A parameter according to the sharpness of the test image, transmit the new 3A parameter to the hardware driver module 30 via the hardware abstraction module 20 to obtain a new test image, determine the sharpness of the new test image, and obtain the highest sharpness as the test result.
In this manner, accurate sharpness may be determined as a test result.
Specifically, the method of SFR test may be adopted for the sharpness test, and the application module 10 may generate the AE parameters and the AF parameters according to the AE algorithm and the AF algorithm, wherein the AF parameters may include a motor stroke value (code value). The AE parameters and AF parameters are transmitted to the hardware driver module 30 via the hardware abstraction module 20. The hardware driving module 30 is used for pushing the motor to reach the corresponding position according to the motor stroke value and acquiring the test image to return to the application program module 10. The application program module 10 processes the test image, for example, the test image is a RAW image, the application program module 10 may perform operations such as downsampling, RAW to YUV conversion, and the like on the RAW image, then calculates the definition, calculates the direction of the next motor movement and the motor stroke value according to the definition of the test image, thereby generating a new 3A parameter, transmits the new 3A parameter to the hardware driving module 30 through the hardware abstraction module 20 to obtain a new test image, and then determines the definition of the new test image, repeats the above operations to find the clearest test image, the definition of the clearest test image is used as the highest definition, and the clearest test image and the highest definition may be used as the test result. The test result can be used for representing the current hardware structure of the camera, so that the most clear test image can be shot, and the highest definition can be achieved.
In some embodiments, the predetermined control algorithm comprises a 3A algorithm, the control parameters comprise a 3A parameter, and the application module 10 is configured to determine the cleanliness of the test image as the test result.
Therefore, the cleanliness test of the test image can be carried out, so that the cleanliness test does not need to depend on the software debugging progress of a platform algorithm, and decoupling is realized.
Specifically, the 3A algorithm includes an AE algorithm, an AF algorithm, and an AWB algorithm, and the 3A parameters include AE parameters, AF parameters, and AWB parameters. The whiteboard test method may be used to perform the cleanliness test, and specifically, the application module 10 may generate the AE parameter and the AWB parameter according to the AE algorithm and the AWB algorithm, and the AE parameter and the AWB parameter are transmitted to the hardware driver module 30 through the hardware abstraction module 20. The hardware driver module 30 is used for acquiring a test image according to the AE parameters and the AWB parameters and transmitting the test image to the application module 10. The application module 10 is used to determine the cleanliness of the test image as a test result.
In some embodiments, the 3A parameter includes a preset stroke value, and the hardware driver module 30 is configured to push the horse to a preset position according to the preset stroke value to obtain a test image and transmit the test image to the application module 10.
In this manner, an accurate degree of cleanliness may be determined as a test result.
Specifically, the method of whiteboard testing may be adopted to perform the cleanliness testing, and the application module 10 may generate an AE parameter and an AWB parameter according to an AE algorithm and an AWB algorithm, where the AWB parameter may include a preset stroke value, and the preset stroke value may be a stroke value corresponding to a telephoto position of the motor. The AE parameters and AWB parameters are transmitted to the hardware driver module 30 via the hardware abstraction module 20. The hardware driving module 30 is configured to push the motor to a corresponding position according to a preset trip value and obtain a test image, where the test image may be a RAW image, and return the test image to the application program module 10. The application module 10 processes the test image, for example, down-sampling, RAW-to-YUV conversion, and the like can be performed, and the processed test image can be converted into a JPG image, and the JPG image can be output after being rendered and previewed. And judging the cleanliness of the picture according to the JPG image to be used as a test result. The test result can represent whether the problems of dead spots, lens dirtiness, frosting and the like exist.
In some embodiments, the preset control algorithm comprises an optical anti-shake algorithm, the control parameters comprise anti-shake compensation parameters, and the application module 10 is configured to determine an anti-shake effect as a test result according to the test image.
Therefore, the anti-shake effect test can be performed on the test image, so that the anti-shake effect test does not need to depend on the software debugging progress of the platform algorithm, and decoupling is realized.
Specifically, the anti-shake compensation parameters may include a compensation stroke value, the hardware driving module 30 is configured to push the motor to perform anti-shake compensation according to the compensation stroke value, and then obtain a test image and return the test image to the application module 10, and the application module 10 is configured to determine an anti-shake effect according to the test image as a test result, for example, determine whether the test image has problems such as double images, water ripples, and the like.
In some embodiments, the application module 10 is further configured to generate control parameters according to a bi-camera calibration test algorithm, and transmit the control parameters to the hardware driver module 30 via the hardware abstraction module 20. The hardware driver module 30 is configured to operate according to the control parameters to obtain a test image and transmit the test image to the application module 10. The application program module 10 is used for generating a test result according to the test image to realize the double shot calibration. Therefore, the double-shooting calibration test does not need to depend on the software debugging progress of a platform algorithm, and decoupling is realized.
In some embodiments, the hardware abstraction module 20 is configured to transmit the motor stroke information stored by the hardware driver module 30 to the application module 10, and the application module 10 is configured to generate the control parameters according to a preset control algorithm and the motor stroke information.
In this way, the application module 10 can obtain the motor stroke information stored in the hardware driving module 30, and can obtain the allowable working range of the corresponding motor, thereby facilitating the implementation of the subsequent control.
Specifically, the motor stroke information may be burned in the hardware driving module 30, and the motor stroke information may include a motor allowable stroke range, where the motor allowable stroke range includes a stroke value corresponding to the near-focus position and a stroke value corresponding to the far-focus position. The application module 10 is configured to generate control parameters according to a preset control algorithm and the motor stroke information, and may be, for example: the application program module 10 is used for determining an AF parameter according to an AF algorithm, wherein the AF parameter is a motor stroke value, and the motor stroke value is within a motor allowed stroke range; for another example, the application module 10 is configured to determine a stroke value corresponding to the far focus position as a preset stroke value.
Referring to fig. 1 and 2, an image testing method according to an embodiment of the present disclosure includes:
01: the application program module 10 generates control parameters according to a preset control algorithm, and transmits the control parameters to the hardware driving module 30 through the hardware abstraction module 20;
02: the hardware driving module 30 works according to the control parameters to obtain a test image and transmits the test image to the application program module 10;
03: the application module 10 generates a test result from the test image.
The image testing method according to the embodiment of the present application can be implemented by the image testing system 100 according to the embodiment of the present application, wherein the steps 01 and 03 can be implemented by the application module 10, and the step 02 can be implemented by the hardware driver module 30.
In the image testing method according to the embodiment of the application, the application program module 10 generates the control parameters according to the preset control algorithm, so that the platform algorithm of the hardware abstraction module 20 is not needed, and under the condition that the software effect test of the hardware abstraction module 20 is not completed, whether the hardware problem exists in the camera can be determined through the image test, so that the problem of the camera is determined in advance to be improved.
Referring to fig. 3, in some embodiments, the preset control algorithm includes a 3A algorithm, the control parameters include 3A parameters, and step 03 (the application module 10 generates the test result according to the test image) includes:
032: the application module 10 determines the sharpness of the test image as a test result.
Step 032 may be implemented by application module 10, among other things.
Referring to fig. 4, in some embodiments, the image testing method further includes:
04: the application program module 10 determines the definition of the test image, generates a new 3A parameter according to the definition of the test image, transmits the new 3A parameter to the hardware driving module 30 through the hardware abstraction module 20 to obtain a new test image, and determines the definition of the new test image;
step 03 (the application module 10 generates a test result from the test image) includes:
034: the highest resolution was obtained as the test result.
Wherein, step 04 and step 034 may be implemented by the application module 10.
Referring to fig. 5, in some embodiments, the preset control algorithm includes a 3A algorithm, the control parameters include 3A parameters, and step 03 (the application module 10 generates the test result according to the test image) includes:
036: the application module 10 determines the cleanliness of the test image as a test result.
Wherein step 036 may be implemented by application module 10.
Referring to fig. 6, in some embodiments, the 3A parameter includes a preset run length value, and step 02 (the hardware driver module 30 works according to the control parameter to obtain a test image and transmit the test image to the application module 10) includes:
022: the hardware driving module 30 pushes the horse to a preset position according to a preset stroke value to acquire a test image and transmits the test image to the application module 10.
Step 022 may be implemented by the hardware driver module 30.
Referring to fig. 7, in some embodiments, the preset control algorithm includes an optical anti-shake algorithm, the control parameter includes an anti-shake compensation parameter, and step 03 (the application module 10 generates the test result according to the test image) includes:
038: the application module 10 determines the anti-shake effect as a test result from the test image.
Wherein step 038 may be implemented by application module 10.
Referring to fig. 8, in some embodiments, the image testing method further includes:
05: the hardware abstraction module 20 transmits the motor stroke information stored in the hardware driving module 30 to the application program module 10;
step 01 (the application module 10 generates control parameters according to a preset control algorithm), which includes:
012: the application module 10 generates control parameters based on a preset control algorithm and motor travel information.
The explanation of the image testing system 100 in the above embodiment is also applicable to the image testing method in the embodiment of the present application, and is not repeated herein.
Referring to fig. 9, the image testing method according to the embodiment of the present application can be implemented by the electronic device 1000 according to the embodiment of the present application. In particular, the electronic device 1000 includes one or more processors 400 and memory 500. The memory 500 stores a computer program. The steps of the image testing method of any of the above embodiments are implemented when the computer program is executed by the processor 400.
For example, the computer program, when executed by the processor 400, implements the steps of the following image testing method:
01: the application program module 10 generates control parameters according to a preset control algorithm, and transmits the control parameters to the hardware driving module 30 through the hardware abstraction module 20;
02: the hardware driving module 30 works according to the control parameters to obtain a test image and transmits the test image to the application program module 10;
03: the application module 10 generates a test result from the test image.
In the electronic device 1000 according to the embodiment of the present application, the application module 10 generates the control parameter according to the preset control algorithm, so that it is not necessary to use the platform algorithm of the hardware abstraction module 20, and under the condition that the software effect test of the hardware abstraction module 20 is not completed, it is possible to determine whether the camera has a hardware problem through the image test, so as to determine the camera problem in advance to improve.
The electronic device 1000 may include a smart phone, a tablet computer, a smart watch, a smart bracelet, and the like, which are not specifically limited herein. The electronic device 1000 according to the embodiment of the present application is illustrated by taking a smart phone as an example, and should not be construed as limiting the present application.
The computer readable storage medium of the embodiments of the present application stores thereon a computer program, which when executed by a processor, implements the steps of the image testing method of any one of the embodiments described above.
For example, in the case where the program is executed by a processor, the steps of the following image test method are implemented:
01: the application program module 10 generates control parameters according to a preset control algorithm, and transmits the control parameters to the hardware driving module 30 through the hardware abstraction module 20;
02: the hardware driving module 30 works according to the control parameters to obtain a test image and transmits the test image to the application program module 10;
03: the application module 10 generates a test result from the test image.
In the computer-readable storage medium according to the embodiment of the present application, the application module 10 generates the control parameters according to the preset control algorithm, so that a platform algorithm of the hardware abstraction module 20 is not needed, and in a case that the software effect test of the hardware abstraction module 20 is not completed, it can be determined through an image test whether the camera has a hardware problem, so as to determine the camera problem in advance to improve the camera problem.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, such as an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processing module-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection having one or more wires (control method), a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Further, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the embodiments of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, references to the description of "certain embodiments" or the like are intended to mean that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment of the present application. In the present specification, schematic representations of the terms used above do not necessarily refer to the same embodiment. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application and that variations, modifications, substitutions and alterations in the above embodiments may be made by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. An image testing system is characterized by comprising an application program module, a hardware abstraction module and a hardware driving module, wherein the application program module is used for generating control parameters according to a preset control algorithm and transmitting the control parameters to the hardware driving module through the hardware abstraction module, the hardware driving module is used for working according to the control parameters to obtain a test image and transmitting the test image to the application program module, and the application program module is used for generating a test result according to the test image.
2. The image testing system of claim 1, wherein the predetermined control algorithm comprises a 3A algorithm, the control parameters comprise a 3A parameter, and the application module is configured to determine a sharpness of the test image as the test result.
3. The image testing system of claim 2, wherein the application module is configured to determine a sharpness of the test image, generate a new 3A parameter according to the sharpness of the test image, transmit the new 3A parameter to the hardware driver module via the hardware abstraction module to obtain a new test image, determine the sharpness of the new test image, and obtain a highest sharpness as the test result.
4. The image testing system of claim 1, wherein the predetermined control algorithm comprises a 3A algorithm, the control parameters comprise a 3A parameter, and the application module is configured to determine a cleanliness level of the test image as the test result.
5. The image testing system of claim 4, wherein the 3A parameters include a preset stroke value, and the hardware driving module is configured to push the motor to a preset position according to the preset stroke value to obtain the test image and transmit the test image to the application program module.
6. The image testing system of claim 1, wherein the predetermined control algorithm comprises an optical anti-shake algorithm, the control parameters comprise anti-shake compensation parameters, and the application module is configured to determine an anti-shake effect from the test image as the test result.
7. The image testing system of claim 1, wherein the hardware abstraction module is configured to transmit the motor stroke information stored by the hardware driver module to an application module, and the application module is configured to generate the control parameter according to the preset control algorithm and the motor stroke information.
8. An image testing method, characterized in that the image testing method comprises:
the application program module generates control parameters according to a preset control algorithm and transmits the control parameters to the hardware driving module through the hardware abstraction module;
the hardware driving module works according to the control parameters to obtain a test image and transmits the test image to the application program module;
and the application program module generates a test result according to the test image.
9. An electronic device, characterized in that the electronic device comprises one or more processors and a memory, the memory storing a computer program which, when executed by the processors, carries out the steps of the image testing method of claim 8.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the image testing method of claim 8.
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