Test picture classification method and system and storage medium

Abstract

The invention discloses a test picture classification method and system and a storage medium, and the classification method provided by the invention comprises the steps: creating an information pre-definition table through adding a plurality of flag bits, and analyzing IME information, camera information and a shooting mode related to a test picture according to the information pre-definition table; creating a folder according to the analyzed camera information and the shooting mode; and modifying the file name of the test picture and then storing the test picture into the folder. According to the method provided by the invention, more metadata about the picture is stored by using the newly added flag bit in the picture information, and the picture files are automatically classified and managed through the data. According to the invention, the efficiency of picture classification and management is improved, especially in a scene in which a large number of test pictures need to be organized according to information such as shooting equipment, camera types or shooting modes.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply control and management, and in particular to a test picture classification method, system and storage medium. Background Art

[0002] With the development of technology, mobile phone cameras are more and more widely used in daily life, which poses a challenge to the shooting function of mobile phones. There are more and more mobile phone shooting modes, such as basic mode, portrait mode, professional mode, super night scene, document, ultra-clear mode, zoom mode, HDR mode, third-party apk, etc. These modes bring users a better mobile phone experience.

[0003] The addition of these modes brings a better experience to users. During the research and development stage, evaluators need to test the jpg photos taken by different modes of the shooting equipment, and need to compare the image quality performance of multiple comparison machines and debugging machines with the same camera in the same scene. The comparison machine is a currently launched machine defined according to product characteristics, which is used for image quality comparison. The acceptance image quality of the debugging machine needs to exceed that of the comparison machine, or be equivalent to it. The performance of the comparison machine and the debugging machine needs to be debugged or scored, and then a large number of pictures need to be taken and the test pictures need to be classified and compared.

[0004] Usually testers need to go out for testing. After the test is completed, they can export the test pictures of each mobile phone to the computer, and then classify and organize them according to different test cameras and different modes. Finally, they output numbered scene pictures of different test machines in different modes for evaluation and debugging personnel to view.

[0005] When testing different modes, the debugging personnel need to record the scene modes shot. When the same scene is shot multiple times, it is easy to be confused. A small number of modes can be classified according to the size of the picture or the effect of the picture display, but such modes are relatively rare (such as blur mode and watermark mode will be displayed on the jpg picture). The final imaging jpg of most modes is not much different, so it is difficult to classify the modes in batches, and confusion is easy to occur when there are too many pictures.

[0006] Therefore, there is an urgent need to propose a test image classification method that can achieve rapid classification and accurate management of images in scenarios where a large number of test images need to be organized according to information such as shooting equipment, camera type or shooting mode. Summary of the invention

[0007] The purpose of the present invention is to provide a test image classification method to solve the problem that images cannot be classified quickly and accurately.

[0008] In order to solve the above technical problems, the present invention provides a test picture classification method, comprising:

[0009] Add multiple flags to the image information to store: hardware ID information, camera information, and shooting mode information;

[0010] Create predefined tables of information;

[0011] Parse the IME information, camera information and shooting mode of the test picture according to the information predefined table;

[0012] Creating a folder according to the parsed camera information and the shooting mode;

[0013] Modify the file name of the test image according to the parsed IME information and the corresponding file number already existing in the folder; and

[0014] Store the renamed test image in the folder.

[0015] Optionally, the picture information includes jpg exif data.

[0016] Optionally, the information predefined table includes address bits where relevant information of the camera information and the shooting mode information is stored in the jpg exif reserved bits, and a correspondence between the hardware ID information and the shooting device.

[0017] Optionally, the process of parsing the hardware ID information, camera information and shooting mode information of the test image according to the information predefined table includes: reading the camera information, the hardware ID information and the shooting mode information according to the jpg exif reserved address information, the read value is a predefined code value, and reversely parsing the camera information, shooting mode and IME information corresponding to the test image according to the information predefined table.

[0018] Optionally, the process of modifying the file name of the test picture according to the parsed IME information and the corresponding file serial number already existing in the folder includes: adding IME information and picture serial number to the name of the test picture, the picture serial number is n+1, and n is the maximum serial number already existing in the folder.

[0019] Optionally, the folder includes a folder with the camera information as the first layer and the shooting mode information as the second layer.

[0020] Optionally, the camera information includes at least one of front, rear, wide-angle, depth of field and macro.

[0021] Optionally, the shooting modes include at least one of professional mode, portrait beauty, super night, document, ultra-clear mode, basic photography, zoom photography, HDR photography and app software.

[0022] The present invention also provides a test picture classification system, which is used to implement the steps of the test picture classification method as described above, including:

[0023] Information extension module, used to add multiple flags to the picture information;

[0024] An information predefined table module, used to create a predefined table of correspondence between the flag bit and the actual hardware and shooting mode;

[0025] An information parsing module, used to parse the picture information data according to the information predefined table, and extract IME information, camera information and shooting mode;

[0026] A folder management module, used to create a folder with at least two layers of structure according to the parsed camera information and shooting mode;

[0027] The file naming module is used to modify the file name of the test image according to the IME information and the maximum sequence number of the existing files in the folder;

[0028] The picture storage module is used to store the test picture with the modified name in the corresponding folder.

[0029] Optionally, the information predefined table module includes:

[0030] An address bit mapping module is used to determine the storage location of the camera information and the shooting mode information in the picture information;

[0031] The hardware ID mapping module is used to establish a corresponding relationship between the hardware ID information and the shooting device.

[0032] Optionally, the information parsing module includes:

[0033] A predefined code value reading module, used for reading the predefined code values ​​of camera information, hardware ID information and shooting mode information from the reserved address bits;

[0034] The reverse parsing module is used to convert the predefined code value into specific picture information according to the information predefined table.

[0035] The present invention also provides a storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described above are executed.

[0036] Compared with the prior art, the present invention has at least the following technical effects:

[0037] The present invention provides a test picture classification method, system and electronic device, which realizes efficient picture management by embedding specific meta information in picture information. When a picture is shot, the three flag information of the picture information is parsed, and the picture is classified into a designated folder, and the pictures are automatically numbered and named according to the number of test pictures, so as to realize real-time viewing of the shot pictures, and facilitate the R&D personnel to debug the pictures. For the problem that picture classification is difficult, the newly added flag in the picture information is used to store more metadata about the pictures, and the picture files are automatically classified and managed through this information. The efficiency of picture retrieval and management is improved, especially when a large number of pictures need to be organized according to information such as shooting equipment, camera type or shooting mode. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A block diagram of a test picture classification method in an embodiment of the present invention;

[0039] Figure 2 This is a functional block diagram of a test image classification system in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The following is a description of a test picture classification method, system and storage medium of the present invention in conjunction with a schematic diagram, wherein a preferred embodiment of the present invention is shown. It should be understood that those skilled in the art can modify the present invention described herein while still achieving the advantageous effects of the present invention. Therefore, the following description should be understood as being widely known to those skilled in the art, and not as a limitation of the present invention.

[0041] The present invention is described in more detail in the following paragraphs by way of example with reference to the accompanying drawings. The advantages and features of the present invention will become more apparent from the following description. It should be noted that the accompanying drawings are in very simplified form and are not in exact proportions, and are only used to facilitate and clearly assist in illustrating the purpose of the embodiments of the present invention.

[0042] This example provides a test image classification method. Figure 1 ,include:

[0043] S1. Add multiple flags to the image information to store: hardware ID information, camera information, and shooting mode information;

[0044] S2. Create a predefined information table;

[0045] S3, parsing the IME information, camera information and shooting mode of the test picture according to the information predefined table;

[0046] S4, creating a folder according to the parsed camera information and the shooting mode;

[0047] S5, modifying the file name of the test image according to the parsed IME information and the corresponding file number already existing in the folder; and

[0048] S6. Storing the renamed test image in the folder.

[0049] It should be noted that image file formats include JPEG, PNG, GIF, BMP, etc., and metadata include EXIF, IPTC, XMP, etc. In this embodiment, preferably, the picture information includes jpg exif data.

[0050] In this embodiment, efficient picture management is achieved by adding the jpg shooting mode, the device hardware ID and the flag of the shooting camera information to the original exif (Exchangeable Image File Format) information of jpg.

[0051] Specifically, by adding a custom flag bit to the exif data of the jpg file, key information such as the hardware ID, camera type and shooting mode is recorded. An information predefined table is created to map the custom information in the exif data to ensure the accuracy and consistency of information parsing. A double-layer folder structure is adopted, and the camera type and shooting mode are used as the classification basis, which helps to quickly locate and classify pictures. The pictures are renamed in combination with the IME information and the serial number to ensure the uniqueness of the file name, which is easy to manage and identify. This method supports a variety of camera types and shooting modes to adapt to different shooting needs and scenes. Automatic classification and naming of pictures can be achieved, which greatly reduces the need for manual operation and improves efficiency. This embodiment provides an efficient and reliable solution, which is very suitable for test and evaluation environments that require a large amount of image processing.

[0052] Furthermore, in this embodiment, after the current picture is taken, the test picture is transmitted back to the base server via the network for classification and management, thus solving the problem of delayed transmission of the test picture and slow picture transmission.

[0053] Furthermore, in step S2, the information predefined table includes the address bits where the camera information and the shooting mode information are stored in the jpg exif reserved bits, and the corresponding relationship between the hardware ID information and the shooting device.

[0054] In this embodiment, the information predefined table contains the address bit information of the EXIF ​​reserved bits, and these address bits point to the exact location where the camera information and shooting mode information are stored. Through these address bits, the system can directly locate the corresponding fields in the EXIF ​​data to read or write relevant information. The table also records the correspondence between the hardware ID and the shooting device. Each hardware ID is uniquely associated with a specific hardware device, such as test machine 1. This mapping relationship is crucial to ensure that the device that takes the picture can be correctly identified when parsing the EXIF ​​data.

[0055] Since the definition of reserved bits in the EXIF ​​standard may vary, the information predefined table provides a unified parsing rule to ensure that no matter which device the image comes from, the camera information and shooting mode can be correctly parsed according to the predefined rules. Through the predefined table, the system can quickly access and parse EXIF ​​data without having to redetermine the information position during each image processing process, thereby improving the overall processing efficiency. When a new camera type or shooting mode needs to be added, only the information predefined table needs to be updated without modifying the underlying data processing logic, simplifying the maintenance and update of the system.

[0056] Further, in step S3, the process of parsing the hardware ID information, camera information and shooting mode information of the test image according to the information predefined table includes: reading the camera information, the hardware ID information and the shooting mode information according to the jpg exif reserved address information, the read value is a predefined code value, and reversely parsing the camera information, shooting mode and IME information corresponding to the test image according to the information predefined table.

[0057] In this embodiment, to read the exif reserved address information, the system first locates the reserved address of the exif data in the jpg file, which has been clearly marked in the information predefined table. The reserved address corresponds to the specific location where the hardware ID information, camera information and shooting mode information are stored. After locating the reserved address, the system reads the data in these addresses, which exist in the form of predefined code values. The predefined code value is a set of coding standards set within the system to simplify data storage and processing. The read predefined code value will then be compared with the information predefined table. By searching the predefined table, the system converts the code value back to specific hardware ID information, camera information and shooting mode information. This process is called reverse parsing because it converts the encoded data back to the original information.

[0058] Detailed steps of the parsing process:

[0059] Hardware ID information analysis: The system reads the predefined code value of the hardware ID according to the reserved address, and searches for the corresponding hardware device information in the predefined information table.

[0060] Camera information parsing: Similarly, the system reads the predefined code value of the camera information and uses a predefined table to determine the specific camera type, such as front, rear, wide-angle, etc.

[0061] Shooting mode information analysis: For shooting modes, the system also reads predefined code values ​​and uses a predefined table to identify which shooting mode it is, such as professional mode, portrait beauty, ultra-night mode, etc.

[0062] Further, in step S3, the camera information includes at least one of front, rear, wide angle, depth of field and macro.

[0063] The shooting modes include at least one of professional mode, portrait beauty, super night, document, ultra-clear mode, basic photography, zoom photography, HDR photography and app software.

[0064] Further, in step S4, the folder includes a folder with the camera information as the first layer and the shooting mode information as the second layer.

[0065] Further, in step S5, the process of modifying the file name of the test picture according to the parsed IME information and the corresponding file serial number already existing in the folder includes: adding IME information and picture serial number to the name of the test picture, the picture serial number is n+1, and n is the maximum serial number already existing in the folder.

[0066] Specifically, the first-level folder (camera information): Based on the parsed camera information, the system will create the first-level folder in the storage directory. For example, if the picture is taken by the front camera, the picture will be classified into a folder named "front camera".

[0067] Second-level folders (shooting mode information): Inside each first-level folder, the system will create second-level folders based on the shooting mode information. For example, if the picture is taken in the "Portrait Beauty" mode, the picture will be further classified into a subfolder called "Portrait Beauty".

[0068] This two-layer folder structure makes image management more orderly, and users can easily find the required images according to camera type and shooting mode.

[0069] In step S5, the file name of the test image is modified to ensure that each image has a unique identifier for easy retrieval and management.

[0070] Add IME information: Add the parsed IME information to the original file name of the image. IME information is usually used to identify the mobile phone or other mobile device that took the image, which helps to track the source of the image.

[0071] Increase the image number: To ensure the uniqueness of the file name, check the existing files in the target folder and find the largest file number n; then, the system sets the new image number to n + 1. For example, if the largest file number in the folder is 23, the new image number will be 24.

[0072] Finally, the file name of the test image is modified by combining the IME information and the new image serial number. Assuming the IME information is "ABC123", the new file name can be "ABC123_24.jpg". Each test image is assigned a unique file name containing device information and serial number for subsequent test image management.

[0073] Furthermore, before step S1, when taking a photo, the light-sensitive sensor collects raw data, and different ISP profiles are sent in different shooting modes to facilitate parameter distinction of each mode later.

[0074] Furthermore, 3A statistics are conducted.

[0075] Furthermore, after the 3A raw data is processed, it needs to be processed by modules such as OB, LSC, Raw De-noise, Demosica, Gamma, color matix, Tone, De-noise, and sharpness. Because different modes, output sizes, or final effect requirements are inconsistent, specific ISP parameters are required.

[0076] The raw data is processed by the ISP, and then processed into RAW, YUV, and JPG, and finally becomes the scene captured by the camera.

[0077] In the above image processing flow, after the raw data is captured from the sensor, it will go through a series of processing steps to be converted into the final image.

[0078] in:

[0079] 1.3A refers to Auto Exposure (AE), Auto White Balance (AWB) and Auto Focus (AF).

[0080] 2.OB (Optical Black): refers to the optical black level, which is used to correct the fixed pattern noise of the image sensor.

[0081] 3.LSC (Lens Shading Correction): Lens shading correction, used to correct the unevenness of image brightness and color caused by the optical characteristics of the lens.

[0082] 4.Raw De-noise: Raw data denoising, used to reduce random noise in raw image data.

[0083] 5.Demosaic: Demosaic, converting the Bayer pattern of the original data into a color image.

[0084] 6.Gamma: Gamma correction, used to adjust the brightness and contrast of the image.

[0085] 7.Color Matrix: Color matrix, used to adjust the color balance and saturation of the image.

[0086] 8.Tone: Tone mapping is used to adjust the tonal response of an image to better reflect the human eye's perception of brightness changes.

[0087] 9.De-noise: De-noise, further reduce the noise in the image and improve image quality.

[0088] 10.Sharpness: Sharpness enhancement, used to improve image clarity and edge contrast.

[0089] 11. ISP (Image Signal Processor): Image signal processor is a hardware or software component that performs all the above processing steps.

[0090] 12.RAW: Raw image format, data obtained directly from the image sensor without any processing.

[0091] 13.YUV: A color encoding system that decomposes color information into brightness (Y) and two chrominance components (U and V).

[0092] The raw data is first processed by 3A, and then processed by various modules in ISP (such as OB, LSC, denoising, demosaic, etc.), and finally converted into image data in RGB or YUV format. Further compression and format conversion are performed as needed to generate images in formats such as JPG for display or storage. In other specific examples, different shooting modes and scenes may require adjustment of ISP parameters to obtain the best image effect.

[0093] In a specific example, the photographing device is taken as an example of a smart phone.

[0094] The provided mobile phone refers to the test mobile phone for shooting test, which includes debugging machine 1, debugging machine 2, debugging machine 3, comparison machine 1, comparison machine 2, comparison machine 3, etc. Each test mobile phone is an independent device, and the test mobile phone needs to maintain a network connection with the server.

[0095] Use the test phone to take pictures. In the same scene, all test phones need to be called to take pictures of the same scene.

[0096] It should be noted that during the test, different test phones will be used to take photos of the same scene with the same camera. For example, if the rear camera is used to take photos of the grass, all test phones will use the rear camera to take photos of the grass for a continuous period of time.

[0097] Add three flags in the jpg exif to store information including the phone ID, camera information and shooting mode information.

[0098] Among them, the jpg shooting mode is added, and the ISP profile (Image Signal Processor) sent in each mode is recorded on the BSP side (Board Support Package), and keywords for each mode are sent on the BSP side for the subsequent identification and distinction of ISP parameters.

[0099] Among them, the device hardware ID is to read the IME number and record it.

[0100] Among them, different cameras have different sensor (digital image sensor) names in BSP, and different sensors can correspond to different camera information.

[0101] Furthermore, jpg exif stores hexadecimal data, so it is necessary to predefine the ISP profile and the camera information, and store the relevant information in the specified address bit of the jpg exif reserved bit.

[0102] For example: the predefined ISP profile is stored at 0x1616; the predefined camera information is stored at 0x1617; the predefined mobile phone IME information is stored at 0x1618, 0x1619, and 0x161A.

[0103] The following is a predefined table of ISP profile and camera information.

[0104] Table 1

[0105]

[0106]

[0107] Furthermore, after a single mobile phone shoots a scene, check the picture and click Send to Server to send the picture to the server. The pictures that have been sent to the server will be displayed as sent. It should be noted that the click Send to Server option is added because during the test, due to some environmental or human factors, the pictures taken are abnormal. Abnormal pictures need to be deleted and discarded. If they are not manually checked and sent directly to the server, the picture sequence will be disordered and the test resources will be uneven.

[0108] After receiving the picture sent back by the mobile phone, the server reads the camera information, mobile phone ID information, and shooting mode information of the picture to be used as the basis for classification in subsequent steps.

[0109] Read the camera information, mobile phone ID information, and shooting mode information of the picture, including the following steps:

[0110] For the reading of three key flag information added in jpg exif, the camera information, mobile phone ID information and shooting mode information are read according to the reserved address of jpg exif. The read value is a predefined code value. According to the predefined table of information, the corresponding camera information and shooting mode are reversely parsed to test the mobile phone IME information.

[0111] The parsed camera information includes front camera, rear camera, wide angle, depth of field, macro and other information. The parsed shooting mode information includes at least one of professional mode, portrait beauty, ultra night, document, ultra clear mode, basic photography, zoom photography, hdr photography and app software. The unique identification ID of the test phone is determined through the parsed IME information.

[0112] Furthermore, when the test image is transmitted back to the server, it is divided into the corresponding folder according to the judgment. At this time, if the folder already contains photos taken by the mobile phone in this mode, the number of existing pictures will be automatically read, and then the serial number of the newly transmitted picture will be automatically increased.

[0113] Specifically, a folder is created with the camera information as the first layer and the shooting mode as the second layer.

[0114] If it exists, do not create it.

[0115] According to the IME information of the mobile phone and the existing picture numbers of the current camera and current mode, the newly incoming pictures are renamed and the mobile phone information and picture numbers are added.

[0116] Place the renamed pictures into the corresponding folders.

[0117] The photos taken will be classified into corresponding folders according to each mode, such as Facebook software, QQ software, WeChat software, Snapchat software, professional mode, portrait beauty, ultra night, document, ultra clear mode, basic photography, zoom photography, HDR photography, etc. Finally, a folder with camera information as the first layer and shooting mode as the second layer is formed.

[0118] Furthermore, the debugging personnel can view the image effects in real time and conduct evaluation and debugging.

[0119] Embodiment 2

[0120] This embodiment provides a test image classification system, please refer to Figure 2 , used to implement the test picture classification method provided in Example 1, including:

[0121] The information extension module is used to add multiple flags to the image information.

[0122] The information predefined table module is used to create a predefined table of the correspondence between the flag bit and the actual hardware and shooting mode.

[0123] The information parsing module is used to parse the picture information data according to the information predefined table and extract the IME information, camera information and shooting mode.

[0124] The folder management module is used to create a folder with at least two layers of structure according to the parsed camera information and shooting mode.

[0125] The file naming module is used to modify the file name of the test image according to the IME information and the maximum sequence number of the existing files in the folder.

[0126] The picture storage module is used to store the test picture with the modified name in the corresponding folder.

[0127] Specifically, in this embodiment, the information extension module is specifically used to add multiple flag bits to the EXIF ​​information of the jpg picture.

[0128] Furthermore, in this embodiment, the information predefined table module includes:

[0129] The address bit mapping module is used to determine the storage location of the camera information and the shooting mode information in the picture information.

[0130] The hardware ID mapping module is used to establish a corresponding relationship between the hardware ID information and the shooting device.

[0131] Furthermore, in this embodiment, the information parsing module includes:

[0132] The predefined code value reading module is used to read the predefined code values ​​of camera information, hardware ID information and shooting mode information from the EXIF ​​reserved address bits.

[0133] The reverse parsing module is used to convert the predefined code value into specific picture information according to the information predefined table.

[0134] Accordingly, other embodiments of the present application may also provide a computer-readable storage medium in which computer executable instructions are stored, and when the computer executable instructions are executed by the processor, the various method embodiments of the present application are implemented. Computer-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be a computer-readable instruction, a data structure, a module of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0135] In summary, the present invention provides a test image classification method, system and storage medium, utilizes the newly added flag bits in the image information to store more metadata about the image, and automatically classifies and manages the image files through this information, thereby improving the efficiency of image retrieval and management, especially when it is necessary to organize a large number of images according to information such as shooting equipment, camera type or shooting mode.

[0136] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A test picture classification method, characterized in that: include: Add multiple flags to the image information to store: hardware ID information, camera information, and shooting mode information; Create predefined tables of information; Parse the IME information, camera information and shooting mode of the test picture according to the information predefined table; Creating a folder according to the parsed camera information and the shooting mode; Modify the file name of the test image according to the parsed IME information and the corresponding file number already existing in the folder; and Store the renamed test image in the folder.

2. The test picture classification method according to claim 1, characterized in that: The picture information includes jpg exif data.

3. The test picture classification method according to claim 2, characterized in that: The information predefined table includes the address bits where the camera information and the shooting mode information are stored in the jpg exif reserved bits, and the corresponding relationship between the hardware ID information and the shooting device.

4. The test picture classification method according to claim 2, characterized in that: The process of parsing the hardware ID information, camera information and shooting mode information of the test image according to the information predefined table includes: reading the camera information, the hardware ID information and the shooting mode information according to the jpg exif reserved address information, the read value is a predefined code value, and reverse parsing the camera information, shooting mode and IME information corresponding to the test image according to the information predefined table.

5. The test picture classification method according to claim 1, characterized in that: The process of modifying the file name of the test picture according to the parsed IME information and the corresponding file serial number already existing in the folder includes: adding IME information and a picture serial number to the name of the test picture, wherein the picture serial number is n+1, and n is the maximum serial number already existing in the folder.

6. The test picture classification method according to claim 1, characterized in that: The folder includes a folder with the camera information as a first layer and the shooting mode information as a second layer.

7. The test picture classification method according to claim 1, characterized in that: The camera information includes at least one of front, rear, wide angle, depth of field and macro.

8. The test picture classification method according to claim 1, characterized in that: The shooting modes include at least one of professional mode, portrait beauty, super night, document, ultra-clear mode, basic photography, zoom photography, HDR photography and app software.

9. A test picture classification system, characterized in that: The steps for implementing the test picture classification method according to any one of claims 1 to 8 include: Information extension module, used to add multiple flags to the picture information; An information predefined table module, used to create a predefined table of correspondence between the flag bit and the actual hardware and shooting mode; An information parsing module, used to parse the picture information data according to the information predefined table, and extract IME information, camera information and shooting mode; A folder management module, used to create a folder with at least two layers of structure according to the parsed camera information and shooting mode; The file naming module is used to modify the file name of the test image according to the IME information and the maximum sequence number of the existing files in the folder; The picture storage module is used to store the test picture with the modified name in the corresponding folder.

10. The test picture classification system according to claim 9, characterized in that: The information predefined table module includes: An address bit mapping module is used to determine the storage location of the camera information and the shooting mode information in the picture information; The hardware ID mapping module is used to establish a corresponding relationship between the hardware ID information and the shooting device.

11. The test picture classification system according to claim 9, characterized in that: The information parsing module includes: A predefined code value reading module, used for reading the predefined code values ​​of camera information, hardware ID information and shooting mode information from the reserved address bits; The reverse parsing module is used to convert the predefined code value into specific picture information according to the information predefined table.

12. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are executed.

Images