An image processing system based on large models and agents

Abstract

The application discloses an image processing system based on a large model and an agent, determines first target data information based on to-be-processed image information and first data information, and performs image parameter adjustment processing on the to-be-processed image information based on the first target data information to obtain first target image information.

Description

Technical Field

[0001] This application relates to the field of computer technology, and more specifically to an image processing system based on a large model and intelligent agents. Background Technology

[0002] With the rapid development of display technology, consumers have increasingly higher demands for the image quality of display devices. Color mapping tables, in particular, are widely used in film, television, advertising, and game production because they ensure the color accuracy and consistency of output images. However, current image processing technologies using color mapping tables require users to manually select the appropriate color, which is cumbersome. Summary of the Invention

[0003] This application provides an image processing system based on a large model and an intelligent agent.

[0004] In a first aspect, this application provides a method comprising:

[0005] Acquire the image information to be processed and the first data information;

[0006] Based on the image information to be processed and the first data information, the first target data information is determined;

[0007] Based on the first target data information, the image parameters of the image information to be processed are adjusted to obtain the first target image information.

[0008] Secondly, this application provides a system comprising:

[0009] The information acquisition module is used to acquire the image information to be processed and the first data information;

[0010] The information determination module is used to determine the first target data information based on the image information to be processed and the first data information;

[0011] The image processing module is used to adjust the image parameters of the image to be processed based on the first target data information to obtain the first target image information.

[0012] Thirdly, this application also provides a computer device, which includes:

[0013] One or more processors;

[0014] Memory; and

[0015] One or more applications, wherein the applications are stored in memory and configured to be executed by a processor to implement the methods of any of the first aspects.

[0016] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, the computer program being loaded by a processor to perform the steps of the method in any of the first aspects. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a scene diagram of the image processing system provided in an embodiment of the present invention;

[0019] Figure 2 This is a flowchart of one embodiment of the image processing method provided by the present invention;

[0020] Figure 3 This is a flowchart illustrating a specific embodiment of determining first target data information provided in this invention.

[0021] Figure 4 This is a flowchart illustrating a specific embodiment of image parameter adjustment processing for image information to be processed, provided by an embodiment of the present invention.

[0022] Figure 5 This is a schematic block diagram of the image processing system provided in the embodiments of the present invention;

[0023] Figure 6 This is a schematic diagram of an embodiment of the computer device provided in this invention. Detailed Implementation

[0024] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] In the description of this application, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this application. Furthermore, the terms "first," "second," and "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first," "second," "third," etc., may explicitly or implicitly include one or more features. In the description of this application, "several" means one or more, unless otherwise explicitly specified.

[0026] In this application, the term "exemplary" is used to mean "used as an example, illustration, or description." Any embodiment described as "exemplary" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use this application. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that this application can be made without using these specific details. In other instances, well-known structures and processes are not described in detail to avoid obscuring the description of this application with unnecessary detail. Therefore, this application is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0027] It should be noted that since the method in this application embodiment is executed in a computer device, the processing objects of each computer device exist in the form of data or information, such as time, which is essentially time information. It is understood that if size, quantity, position, etc. are mentioned in subsequent embodiments, they are all corresponding data that exist so that the computer device can process them. Specific details will not be elaborated here.

[0028] This application provides an image processing method, system, computer device, and computer-readable storage medium based on a large model and intelligent agents, which will be described in detail below.

[0029] Please see Figure 1 , Figure 1 This is a schematic diagram of a scene of the image processing system provided in an embodiment of this application. The image processing system may include a computer device 100, such as... Figure 1 Computer equipment in the country.

[0030] In this embodiment, the computer device 100 is mainly used to acquire image information to be processed and first data information; determine first target data information based on the image information to be processed and the first data information; and perform image parameter adjustment processing on the image information to be processed based on the first target data information to obtain the first target image information. During the image processing, the user does not need to manually select a color mapping table, which can improve the efficiency and accuracy of image processing.

[0031] In this embodiment, the computer device 100 can be a standalone server, a server network, or a server cluster. For example, the computer device 100 described in this embodiment includes, but is not limited to, a computer, a network host, a single network server, a set of multiple network servers, or a cloud server composed of multiple servers. The cloud server is composed of a large number of computers or network servers based on cloud computing.

[0032] It is understood that the computer device 100 used in the embodiments of this application can be a device that includes both receiving and transmitting hardware, that is, a device having receiving and transmitting hardware capable of performing bidirectional communication on a bidirectional communication link. Such a device may include: cellular or other communication devices having a single-line display, a multi-line display, or a cellular or other communication device without a multi-line display. Specifically, the computer device 100 may be a desktop terminal or a mobile terminal, and may also be one of the following: an augmented reality (AR) device, a mobile phone, a tablet computer, a laptop computer, etc.

[0033] Those skilled in the art will understand that Figure 1 The application environment shown is merely one application scenario of the solution in this application and does not constitute a limitation on the application scenario of the solution in this application. Other application environments may include those that are more specific to this application. Figure 1 The number of computer devices shown is more or less, for example Figure 1 Only one computer device is shown in the image. It is understood that the image processing system may also include one or more other services, which are not limited here.

[0034] In addition, such as Figure 1 As shown, the image processing system may also include a memory 200 for storing data, such as color data information, such as first color data information, second color data information, etc., and image information, such as image information to be processed, first target image information, etc.

[0035] It should be noted that, Figure 1The schematic diagram of the image processing system shown is merely an example. The image processing system and scenario described in this application are for the purpose of more clearly illustrating the technical solutions of this application and do not constitute a limitation on the technical solutions provided in this application. As those skilled in the art will know, with the evolution of image processing systems and the emergence of new business scenarios, the technical solutions provided in this application are also applicable to similar technical problems.

[0036] First, this application provides an image processing method applied to a computer device. The image processing method includes: acquiring image information to be processed and first data information; determining first target data information based on the image information to be processed and the first data information; and performing image parameter adjustment processing on the image information to be processed based on the first target data information to obtain the first target image information.

[0037] like Figure 2 The diagram shown is a flowchart of an embodiment of the image processing method in this application. The image processing method may include the following steps S201 to S203, as detailed below:

[0038] S201. Obtain the image information to be processed and the first data information.

[0039] In this embodiment, the image information to be processed is information acquired by a computer device that requires image processing. Optionally, the image information to be processed can be image information acquired by the imaging module configured on the computer device itself, image information captured by a high-definition camera, or image information acquired by the imaging module of other computer devices through means such as network, Bluetooth, and infrared. This embodiment does not limit the scope of the application. For example, when the image processing method of this application is applied to a smartphone, the smartphone can directly acquire the image information to be processed through its own imaging module. When the image processing method of this application is applied to a server, the server can acquire the image information to be processed through the imaging module of the smartphone and obtain the image information to be processed from the smartphone through means such as network, Bluetooth, and infrared.

[0040] Furthermore, the image information to be processed can be static image data or dynamic video data. For example, the image information to be processed can be the video frame data currently being viewed by the user, or the image data currently being browsed by the user. This embodiment does not limit this.

[0041] Optionally, the first data information is prompt data used to guide the target processing model to output the second target data information. The first data information can be text data input by the user through a mouse, keyboard, touch screen, etc., or it can be voice data input by the user through a microphone. This embodiment does not limit this. For example, the first data information can be "Sunset scene, warm twilight light, color temperature about 2000K, used for a 4K UHD display, sRGB color gamut, target LUT format is 17-level CUBE." The first data information can also be "Indoor scene, cool white light source, color temperature about 6500K, used for professional photography, target color gamut Adobe RGB, LUT format is 9-level, device is a professional photography camera." The first data information can also be "Outdoor natural light, midday direct sunlight, color temperature about 5500K, used for television playback, target color gamut Rec.709, LUT format is 17-level, device is a smart TV."

[0042] S202. Based on the image information to be processed and the first data information, determine the first target data information.

[0043] In this embodiment, the first target data information is color mapping information that matches the image information to be processed and the first data information, determined based on the image information to be processed and the first data information. The original color data information of the image information to be processed can be non-linearly mapped to the target color data information through the first target data information, thereby improving the image quality display effect of the image information to be processed.

[0044] Optionally, the first target data information can be in tabular form or in curve form; this embodiment is not limited to either. For example, the first target data information can be a 3D Look-Up Table (3DLUT). 3DLUT is a mapping table that implements direct color mapping. When a color is input, 3DLUT will look up and output the corresponding color based on the position of the color in the RGB space. This non-linear color correction and adjustment method makes 3DLUT highly flexible and accurate in color processing.

[0045] In a specific implementation method, refer to Figure 3 As shown, the step S202 above, which determines the first target data information based on the image information to be processed and the first data information, may include the following steps S301 to S302, as follows:

[0046] S301. The target processing model is used to generate data from the image information to be processed and the first data information to obtain the second target data information.

[0047] In this embodiment, the target processing model is an artificial intelligence model used to generate data from the image information to be processed and the first data information. The target processing model can be built based on a large model and an intelligent agent. A large model refers to an artificial neural network model with a very large number of parameters. In the field of artificial intelligence, a large model typically refers to a model with hundreds of millions to trillions of parameters. Such models usually need to be trained on large-scale datasets and require significant computational resources for optimization and tuning. Large models are commonly used to solve complex tasks such as natural language processing, computer vision, and speech recognition.

[0048] Optionally, the large model can be a language model of the scale of ChatGPT, BERT, XLNet, Zhipu model, Claude, Moonshot AI model, ChatGLM model, Qianyitongwen model, MiniMax model, Xinghuo model, Llama model, 360GPT model, Qwen model, Baichuan model, Yunque model, vivoLM model, and Wenxin Yiyan, etc., and the embodiments of this application are not limited thereto.

[0049] Furthermore, the second target data information includes second data information and / or, third data information. The image information to be processed is displayed through the target display module. The second data information is data information related to the target display module, and the third data information represents the format information corresponding to the first target data information. For example, the second target data information is "color temperature: 2000K; color gamut: sRGB; device: 4K UHD display; LUT format: 17 levels .cube". The second target data information includes the second data information "color temperature: 2000K; color gamut: sRGB; device: 4K UHD display" and the third data information "LUT format: 17 levels .cube".

[0050] In one specific embodiment, the second data information includes first color temperature information, and / or, first color gamut information, and / or, first type information. The first color temperature information represents the ambient light color temperature value of the target display module, which indicates the color temperature of the illumination light surrounding the target display module. The first color gamut information represents the range of colors that the target display module can display; for example, the color gamut information can be sRGB, Adobe RGB, Rec.709, etc. The first type information represents the device type corresponding to the target display module; for example, the type information can be a 4K UHD monitor, a professional camera, a smart TV, etc.

[0051] S302. Based on the second target data information, determine the first target data information.

[0052] In one specific embodiment, the second target data information includes second data information and / or, third data information. The step of determining the first target data information based on the second target data information specifically includes: determining the third target data information based on the second data information; and performing data format conversion processing on the third target data information based on the third data information to obtain the first target data information. For example, if the third target data information is a 17th-order 3DLUT and the third data information is "LUT format: 9th order .cube", then the 17th-order 3DLUT is converted to a 9th-order 3DLUT to obtain the first target data information.

[0053] This application embodiment determines the third target data information based on the second data information, and performs data format conversion processing on the third target data information based on the third data information, so that the determined first target data information can be better adapted to the target display module, thereby improving the image quality display effect of the image information to be processed.

[0054] In one specific embodiment, the step of determining the third target data information based on the second data information specifically includes: matching the second data information with the fourth data information in the fourth target data information; if any fourth data information in the fourth target data information matches the second data information, determining the fourth data information that matches the second data information as the third target data information; and / or, if none of the fourth data information in the fourth target data information matches the second data information, determining the third target data information based on the second data information and the first color data information.

[0055] In this embodiment, the fourth target data information is color mapping information generated by a computer device. The fourth target data information includes several fourth data informations. The fourth data information that matches the second data information refers to the color mapping information corresponding to the second data information in the fourth target data information. For example, the fourth target data information includes fourth data information A, fourth data information B, and fourth data information C. Fourth data information A, fourth data information B, and fourth data information C correspond to data information A, data information B, and data information C, respectively. If the second data information is data information A, then the fourth data information that matches the second data information is fourth data information A.

[0056] In this embodiment of the application, when determining the third target data information based on the second data information, it first determines whether there is a matching fourth data information in the fourth target data information based on the second data information, that is, whether the computer device has generated color mapping information corresponding to the second data information. When it is determined that the computer device has generated the fourth data information corresponding to the second data information, the fourth data information is directly determined as the third target data information, which can improve the determination efficiency of the third target data information and thus improve the image processing efficiency.

[0057] In one specific embodiment, if the fourth data information in the fourth target data information does not match the second data information, that is, it is determined that the computer device has not generated color mapping information corresponding to the second data information, then the third target data information is determined based on the second data information and the first color data information, and the third target data information is updated in the fourth target data information, so that the third target data information can be directly obtained from the fourth target data information when image processing is performed on the image information to be processed next time, thereby improving the image processing efficiency.

[0058] In this embodiment, the first color data information is the color data information corresponding to a standard color chart. For example, the first color data information is the RGB data corresponding to a standard 17-level color chart. The format of the third target data information determined based on the second data information and the first color data information varies depending on the first color data information. For example, when the first color data information is the RGB data corresponding to a standard 17-level color chart, the format of the third target data information is 17-level.cube; when the first color data information is the RGB data corresponding to a standard 9-level color chart, the format of the third target data information is 9-level.cube.

[0059] In one specific embodiment, the second data information includes first color temperature information, and / or, first color gamut information, and / or, first type information. The step of determining the third target data information based on the second data information and the first color data information specifically includes: performing color conversion processing on the first color data information based on the first color gamut information to obtain the second color data information; determining the third color data information based on the first type information and the first association information; and determining the third target data information based on the second color data information, the third color data information, and the first color temperature information.

[0060] In this embodiment, color conversion processing of the first color data information refers to converting the first color data information from one color space to another. For example, if the first color data information is data information in the RGB color space, color conversion processing of the first color data information refers to converting the first color data information from the RGB color space to the XYZ color space. Different color gamut information corresponds to different color conversion operations. For example, when the color gamut information is sRGB, the color conversion operation is sRGBtoXYZ; when the color gamut information is P3, the color conversion operation is P3toXYZ. In a specific embodiment, the above-mentioned step of performing color conversion processing on the first color data information based on the first color gamut information to obtain the second color data information specifically includes: determining the target color conversion operation based on the first color gamut information; the target color conversion operation being the color conversion operation corresponding to the first color gamut information; and performing color conversion processing on the first color data information based on the target color conversion operation to obtain the second color data information. This embodiment performs color conversion processing on the first color data information based on the first color gamut information, which can generate the first target data information corresponding to the first color gamut information. This allows the image information to be processed after processing based on the first target data information to meet the color gamut requirements of the target display module, thereby improving the image quality display effect of the image information to be processed.

[0061] Furthermore, the third color data information is the calibrated color data information corresponding to the first color data information determined based on the first type information and the first association information. The first association information represents the one-to-one correspondence between the type information and the color data information. For example, the first association information includes color data information A, color data information B, and color data information C corresponding to 4K UHD displays, professional photography cameras, and smart TVs, respectively. If the first type information is 4K UHD displays, then the third color data information can be determined to be color data information A based on the first type information and the first association information.

[0062] In one specific embodiment, the first association information is obtained through the following steps: acquiring multiple first image information; displaying the multiple first image information through several display modules of different types, and collecting color data of the first image information displayed on each display module through a color measurement module to obtain candidate color data information corresponding to each display module; determining the first association information based on the type information of several display modules and the candidate color data information corresponding to each display module. The multiple first image information corresponds to the first color data information. For example, if the first color data information is 4913 RGB values ​​corresponding to a 17-level color chart, then the first image information is the color chart corresponding to each of the 4913 RGB values. The color measurement module can be a CA410 display color analyzer, or it can be a CS2000 luminance meter; this embodiment does not limit the specific color measurement module.

[0063] In one specific embodiment, the third target data information represents the one-to-one correspondence between the first color data information and the fifth color data information. The step of determining the third target data information based on the second color data information, the third color data information, and the first color temperature information specifically includes: performing color restoration processing on the second color data information based on the first color temperature information to obtain the fourth color data information; performing color correction processing on the fourth color data information based on the third color data information to obtain the fifth color data information; and determining the third target data information based on the first color data information and the fifth color data information. In this embodiment, performing color correction processing on the fourth color data information based on the third color data information to obtain the fifth color data information, and then determining the third target data information based on the fifth color data information, can improve the accuracy of the obtained third target data information.

[0064] Optionally, the steps described above for performing color restoration processing on the second color data information based on the first color temperature information to obtain the fourth color data information specifically include: determining the first parameter information based on the first color temperature information; and calculating and processing the second color data information and the first parameter information using a color appearance model to obtain the fourth color data information. The color appearance model can be constructed based on the CAM16 color appearance model, the CIECAM02 color appearance model, or the CIECAM97s color appearance model; this embodiment does not impose any limitations.

[0065] In one specific embodiment, the color appearance model includes a first color appearance module and a second color appearance module. The input terminal of the first color appearance module is configured to receive second color data information and second parameter information, and the output terminal of the first color appearance module is connected to the input terminal of the second color appearance module. The steps described above for calculating and processing the second color data information and the first parameter information using the color appearance model to obtain fourth color data information specifically include: inputting the second color data information and the second parameter information into the first color appearance module, and performing calculation and processing on the second color data information and the second parameter information through the first color appearance module to obtain eighth color data information; inputting the eighth color data information and the first parameter information into the second color appearance module, and performing calculation and processing on the eighth color data information and the second parameter information through the second color appearance module to obtain fourth color data information.

[0066] In this embodiment, the first parameter information is the parameter information on which the second color appearance module depends, determined based on the first color temperature information. The first parameter information is obtained through the following steps: obtaining the spectral power distribution information corresponding to the first color temperature information; determining the color space coordinate information corresponding to the first color temperature information based on the spectral power distribution information and the scaling factor; performing a transformation process on the color space coordinate information to obtain the first information; and fusing the first information and the second information to obtain the first parameter information. The second information is the parameter information on which the second color appearance module depends, such as background information, screen brightness information, and test condition information. The process of determining the color space coordinate information based on the spectral power distribution information and the scaling factor, and converting the color space coordinate information into XYZ color information, can refer to existing technologies and will not be elaborated here.

[0067] Furthermore, the second parameter information is the parameter information on which the first color appearance module depends, determined based on the second color temperature information. The second color temperature information is a pre-set reference color temperature information, which can be set based on the user's color temperature preference; for example, the second color temperature information can be 6500K. In this embodiment, the first target data information is determined based on the second color temperature information, which can be combined with the user's color temperature preference to make the obtained target image information more in line with the user's color preference.

[0068] It should be noted that the step of determining the second parameter information based on the second color temperature information is the same as the step of determining the first parameter information based on the first color temperature information described above. For details, please refer to the step of determining the first parameter information based on the first color temperature information. This embodiment will not repeat the details here.

[0069] In one specific embodiment, the fourth color data information includes a plurality of first pixel values, and the third color data information includes a plurality of second pixel values. The step of performing color correction processing on the fourth color data information based on the third color data information to obtain the fifth color data information specifically includes: for any first pixel value in the fourth color data information, determining a first color difference value based on the first pixel value and each second pixel value; filtering a plurality of second pixel values ​​based on the first color difference value to obtain a first target pixel value; performing data generation processing on the third pixel value corresponding to the first target pixel value to obtain a sixth color data information; and determining the fifth color data information based on the first pixel value and the sixth color data information.

[0070] In this embodiment, the first color difference value can characterize the color difference between the first pixel value and each second pixel value. This embodiment can use the CIEDE2000 algorithm to calculate the first color difference value, or the CIELAB algorithm to calculate the first color difference value, or the CIELUV algorithm to calculate the first color difference value. This embodiment does not limit the calculation.

[0071] Optionally, the first color difference value is obtained through the following steps: performing color conversion processing on the first pixel value to obtain the fifth pixel value; performing color conversion processing on each second pixel value to obtain the sixth pixel value; and performing calculation processing on the fifth pixel value and the sixth pixel value to obtain the first color difference value.

[0072] In this embodiment, color conversion processing of the first pixel value refers to converting the first pixel value from one color space to another, for example, converting the first pixel value from the XYZ color space to the LAB color space. Color conversion processing of each second pixel value refers to converting each second pixel value from one color space to another, for example, converting each second pixel value from the XYZ color space to the LAB color space.

[0073] Furthermore, the first target pixel value is the second pixel value among a plurality of second pixel values ​​whose first color difference value satisfies the first condition. The second pixel value whose first color difference value satisfies the first condition can be the second pixel value with the smallest corresponding first color difference value among a plurality of second pixel values. The second pixel value whose first color difference value satisfies the first condition can also be the second pixel value among a plurality of second pixel values ​​whose corresponding first color difference value is within a first range. This embodiment does not limit the specific value.

[0074] In one specific embodiment, the first color data information includes a plurality of seventh pixel values, each of which corresponds one-to-one with a plurality of second pixel values. The third pixel value corresponding to the first target pixel value is the pixel value corresponding to the first target pixel value among the plurality of seventh pixel values. The step of generating the sixth color data information by processing the third pixel value corresponding to the first target pixel value specifically includes: performing data filling processing on the third pixel value corresponding to the first target pixel value to obtain the ninth color data information; and performing segmentation processing on the color space corresponding to the ninth color data information to obtain the sixth color data information. For example, by adding 17 values ​​in the three dimensions of the third pixel value corresponding to the first target pixel value (top, bottom, left, right, front, and back), the third pixel value corresponding to the first target pixel value and the 17 values ​​added in the three dimensions can form a color space of a cube with a side length of 35. Dividing the color space of this cube into 17th order cubes yields 4913 RGB values, which are the sixth color data information.

[0075] In one specific embodiment, the sixth color data information includes a plurality of fourth pixel values. The step of determining the fifth color data information based on the first pixel value and the sixth color data information specifically includes: performing calculation processing on the first pixel value and the plurality of fourth pixel values ​​to obtain a second color difference value; performing filtering processing on the plurality of fourth pixel values ​​based on the second color difference value to obtain the second target pixel information corresponding to the first pixel value; and performing fusion processing on the second target pixel information corresponding to the plurality of first pixel values ​​to obtain the fifth color data information.

[0076] In this embodiment, the second color difference value can characterize the color difference between the first pixel value and the fourth pixel value. This embodiment can use the CIEDE2000 algorithm to calculate and process the first pixel value and several fourth pixel values, or the CIELAB algorithm to calculate and process the first pixel value and several fourth pixel values, or the CIELUV algorithm to calculate and process the first pixel value and several fourth pixel values. This embodiment does not limit the calculation.

[0077] Optionally, the step of calculating and processing the first pixel value and several fourth pixel values ​​to obtain the second color difference value between the first pixel value and each fourth pixel value specifically includes: performing color conversion processing on the first pixel value to obtain a fifth pixel value; performing color conversion processing on each fourth pixel value to obtain an eighth pixel value; and performing calculation and processing on the fifth pixel value and the eighth pixel value to obtain the second color difference value.

[0078] In this embodiment, color conversion processing of the first pixel value refers to converting the first pixel value from one color space to another, for example, converting the first pixel value from the XYZ color space to the LAB color space. Color conversion processing of each fourth pixel value refers to converting each fourth pixel value from one color space to another, for example, converting each fourth pixel value from the RGB color space to the LAB color space.

[0079] Furthermore, the second target pixel information is the pixel value that satisfies the second condition among a plurality of fourth pixel values. The pixel value that satisfies the second condition among a plurality of fourth pixel values ​​can be the pixel value with the smallest corresponding second color difference value among a plurality of fourth pixel values. The pixel value that satisfies the second condition among a plurality of fourth pixel values ​​can also be the pixel value with the corresponding second color difference value within the second range among a plurality of fourth pixel values. This embodiment does not limit the specific pixel value.

[0080] S203. Based on the first target data information, perform image parameter adjustment processing on the image information to be processed to obtain the first target image information.

[0081] In this embodiment, the first target image information is the adjusted image information obtained by adjusting the image parameters of the image information to be processed based on the first target data information. This embodiment determines the first target data information based on the image information to be processed and the first data information, and then adjusts the image parameters of the image information to be processed based on the first target data information to obtain the first target image information. Users only need to input the first data information to adjust the image information to be processed, without needing to manually select a color mapping table, which improves the efficiency and accuracy of image processing. For example, if a user inputs the first data information "Sunset scene, warm twilight light, color temperature approximately 2000K, for a 4K UHD display, sRGB color gamut, target LUT format 17-level CUBE" into a computer device, the computer device can then select the appropriate first target data information to adjust the image parameters of the image information to be processed based on the first data information and the image information to be processed.

[0082] In a specific implementation method, refer to Figure 4 As shown, step S203 above, which involves adjusting image parameters based on the first target data information to obtain the first target image information, may include steps S401 to S402, as follows:

[0083] S401. Based on the first target data information, the seventh color data information of the image information to be processed is mapped to obtain the target color data information.

[0084] In this embodiment, the seventh color data information is the color data information of the image information to be processed before processing, and the target color data information is the mapped color data information corresponding to the seventh color data information in the first target data information. For example, the first target data information includes RGB1 corresponding to RGB2, RGB3 corresponding to RGB4, and if the seventh color data information is RGB1, then the target color data information is RGB2.

[0085] S402. Based on the target color data information, perform image parameter adjustment processing on the image information to be processed to obtain the first target image information.

[0086] In this embodiment, image parameter adjustment processing based on target color data information refers to adjusting the seventh color data information of the image information to be processed to the target color data information. By adjusting the seventh color data information of the image information to be processed to the target color data information, non-linear mapping of the color of the image information to be processed can be achieved, ensuring that the color of the image information to be processed can be displayed correctly.

[0087] In one specific embodiment, the second target data information obtained in step S301 by using the target processing model to generate data from the image information to be processed and the first data information also includes fifth data information. This fifth data information is used to characterize the color adjustment focus of the image information to be processed. For example, the fifth data information could be "enhance orange and red, reduce blue to simulate a warm twilight atmosphere," or "improve image clarity and contrast while maintaining color fidelity," or "balance colors, enhance green and blue to ensure accurate color reproduction under natural light." After adjusting the image parameters of the image information to be processed based on the first target data information to obtain the first target image information, the process includes: performing color adjustment processing on the first target image information based on the fifth data information to obtain the second target image information. In this embodiment, performing color adjustment processing on the first target image information based on the fifth data information can further improve the image quality display effect of the image information to be processed.

[0088] In summary, the image processing method based on a large model and intelligent agent provided in this implementation scheme obtains the image information to be processed and the first data information, determines the first target data information based on the image information to be processed and the first data information, and performs image parameter adjustment processing on the image information to be processed based on the first target data information to obtain the first target image information. In this solution, first target data information is determined based on the image information to be processed and first data information. Then, image parameter adjustment processing is performed on the image information to be processed based on the first target data information to obtain the first target image information. Users only need to input the first data information to adjust the image information to be processed, without the need to manually select a color mapping table, which can improve the efficiency and accuracy of image processing. Furthermore, the target processing model is used to generate data from the image information to be processed and the first data information to obtain second target data information. Based on the second target data information, the first target data information is determined, which can make the determined first target data information better adapt to the target display module, thereby improving the image quality display effect of the image information to be processed. Furthermore, if any fourth data information in the fourth target data information matches the second data information, the fourth data information that matches the second data information is determined as the third target data information, which can improve the efficiency of determining the third target data information, thereby improving the efficiency of image processing.

[0089] To better implement the image processing method in the embodiments of this application, an image processing system is also provided in the embodiments of this application, such as... Figure 5 As shown, the image processing system 600 includes:

[0090] Information acquisition module 610 is used to acquire image information to be processed and first data information;

[0091] The information determination module 620 is used to determine the first target data information based on the image information to be processed and the first data information;

[0092] The image processing module 630 is used to perform image parameter adjustment processing on the image information to be processed based on the first target data information to obtain the first target image information.

[0093] In this embodiment, first target data information is determined based on the image information to be processed and first data information. Then, image parameter adjustment processing is performed on the image information to be processed based on the first target data information to obtain the first target image information. Users only need to input the first data information to adjust the image information to be processed, without having to manually select a color mapping table, which can improve the efficiency and accuracy of image processing.

[0094] In some embodiments of this application, the information determination module 620 determines first target data information based on the image information to be processed and the first data information, including:

[0095] The target processing model is used to generate data from the image information to be processed and the first data information to obtain the second target data information.

[0096] Based on the second target data information, the first target data information is determined.

[0097] In some embodiments of this application, the second target data information includes second data information and / or, third data information. The information determination module 620 determines the first target data information based on the second target data information, including:

[0098] Based on the second data information, the third target data information is determined;

[0099] Based on the third data information, the third target data information is converted into a data format to obtain the first target data information.

[0100] In some embodiments of this application, the information determination module 620 determines third target data information based on second data information, including:

[0101] Match the second data information with the fourth data information in the fourth target data information;

[0102] If any fourth data information in the fourth target data information matches the second data information, the fourth data information that matches the second data information is determined as the third target data information; and / or,

[0103] If none of the fourth data information in the fourth target data information matches the second data information, the third target data information is determined based on the second data information and the first color data information.

[0104] In some embodiments of this application, the second data information includes first color temperature information, and / or, first color gamut information, and / or, first type information. The information determination module 620 determines third target data information based on the second data information and the first color data information, including:

[0105] The first color data information is processed by color conversion based on the first color gamut information to obtain the second color data information;

[0106] Based on the first type of information and the first association information, the third color data information is determined;

[0107] Based on the second color data information, the third color data information, and the first color temperature information, the third target data information is determined.

[0108] In some embodiments of this application, the information determination module 620 determines third target data information based on second color data information, third color data information, and first color temperature information, including:

[0109] Based on the first color temperature information, the second color data information is processed to restore the color, resulting in the fourth color data information;

[0110] The fourth color data information is color-corrected based on the third color data information to obtain the fifth color data information.

[0111] Based on the first color data information and the fifth color data information, the third target data information is determined.

[0112] In some embodiments of this application, the fourth color data information includes a plurality of first pixel values, the third color data information includes a plurality of second pixel values, and the information determination module 620 performs color correction processing on the fourth color data information based on the third color data information to obtain fifth color data information, including:

[0113] For any first pixel value in the fourth color data information, a first color difference value is determined based on the first pixel value and each second pixel value;

[0114] Based on the first color difference value, several second pixel values ​​are filtered to obtain the first target pixel value;

[0115] Data generation processing is performed on the third pixel value corresponding to the first target pixel value to obtain the sixth color data information; the third pixel value is the pixel value corresponding to the first target pixel value in the first color data information.

[0116] Based on the first pixel value and the sixth color data information, the fifth color data information is determined.

[0117] In some embodiments of this application, the sixth color data information includes several fourth pixel values. The information determination module 620 determines the fifth color data information based on the first pixel values ​​and the sixth color data information, including:

[0118] The second color difference value is obtained by calculating and processing the first pixel value and several fourth pixel values;

[0119] Based on the second color difference value, several fourth pixel values ​​are filtered to obtain the second target pixel information corresponding to the first pixel value;

[0120] The second target pixel information corresponding to several first pixel values ​​is fused to obtain the fifth color data information.

[0121] In some embodiments of this application, the image processing module 630 performs image parameter adjustment processing on the image information to be processed based on the first target data information to obtain the first target image information, including:

[0122] Based on the first target data information, the seventh color data information of the image information to be processed is mapped to obtain the target color data information;

[0123] Based on the target color data, the image parameters of the image to be processed are adjusted to obtain the first target image information.

[0124] In some embodiments of this application, after the image processing module 630 performs image parameter adjustment processing on the image information to be processed based on the first target data information to obtain the first target image information, the image processing module 630 is further configured to:

[0125] The first target image information is color-adjusted based on the fifth data information to obtain the second target image information; the fifth data information is obtained by data generation processing of the image information to be processed and the first data information through the target processing model.

[0126] This application embodiment also provides a computer device, the computer device including:

[0127] One or more processors;

[0128] Memory; and

[0129] One or more applications, wherein the applications are stored in memory and configured to be executed by a processor from the steps of the image processing method in any of the above-described image processing method embodiments.

[0130] This application also provides a computer device, such as... Figure 6 As shown, it illustrates a structural schematic diagram of the computer device involved in the embodiments of this application, specifically:

[0131] The computer device may include components such as a processor 801 with one or more processing cores, a memory 802 with one or more computer-readable storage media, a power supply 803, and an input unit 804. Those skilled in the art will understand that... Figure 6 The computer device structure shown does not constitute a limitation on the computer device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein:

[0132] The processor 801 is the control center of the computer device. It connects various parts of the computer device via various interfaces and lines, and performs various functions and processes data by running or executing software programs and / or modules stored in the memory 802, and by calling data stored in the memory 802, thereby providing overall monitoring of the computer device. Optionally, the processor 801 may include one or more processing cores; optionally, the processor 801 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into the processor 801.

[0133] The memory 802 can be used to store software programs and modules. The processor 801 executes various functional applications and data processing by running the software programs and modules stored in the memory 802. The memory 802 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 802 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 802 may also include a memory controller to provide the processor 801 with access to the memory 802.

[0134] The computer device also includes a power supply 803 that supplies power to the various components. Optionally, the power supply 803 can be logically connected to the processor 801 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 803 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0135] The computer device may also include an input unit 804, which can be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0136] Although not shown, the computer device may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 801 in the computer device loads the executable files corresponding to the processes of one or more application programs into the memory 802 according to the following instructions, and the processor 801 runs the application programs stored in the memory 802 to realize various functions, as follows:

[0137] Acquire the image information to be processed and the first data information;

[0138] Based on the image information to be processed and the first data information, the first target data information is determined;

[0139] Based on the first target data information, the image parameters of the image information to be processed are adjusted to obtain the first target image information.

[0140] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0141] Therefore, embodiments of this application provide a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), a magnetic disk, or an optical disk, etc. A computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in any of the image processing methods provided in embodiments of this application. For example, the computer program loaded by the processor can execute the following steps:

[0142] Acquire the image information to be processed and the first data information;

[0143] Based on the image information to be processed and the first data information, the first target data information is determined;

[0144] Based on the first target data information, the image parameters of the image information to be processed are adjusted to obtain the first target image information.

[0145] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the detailed descriptions of other embodiments above, which will not be repeated here.

[0146] In practice, each of the above units or structures can be implemented as an independent entity or can be arbitrarily combined to be implemented as the same or several entities. For the specific implementation of each of the above units or structures, please refer to the previous method embodiments, which will not be repeated here.

[0147] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0148] The foregoing has provided a detailed description of an image processing method, system, computer device, and computer-readable storage medium based on a large model and intelligent agent, as provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method, characterized in that, include: Acquire the image information to be processed and the first data information; Based on the image information to be processed and the first data information, the first target data information is determined; Based on the first target data information, the image parameters of the image to be processed are adjusted to obtain the first target image information.

2. The method according to claim 1, characterized in that, The step of determining the first target data information based on the image information to be processed and the first data information includes: The image information to be processed and the first data information are processed using a target processing model to generate second target data information. Based on the second target data information, the first target data shooting information is determined.

3. The method according to claim 2, characterized in that, The second target data information includes second data information and / or, third data information; The step of determining the first target data information based on the second target data information includes: Based on the second data information, the third target data information is determined; Based on the third data information, the third target data information is converted into a data format to obtain the first target data information.

4. The method according to claim 3, characterized in that, The step of determining the third target data information based on the second data information includes: Match the second data information with the fourth data information in the fourth target data information; If any of the fourth data information matches the second data information, the fourth data information that matches the second data information is determined as the third target data information; and / or, If none of the fourth data information in the fourth target data information matches the second data information, the third target data information is determined based on the second data information and the first color data information.

5. The method according to claim 4, characterized in that, The second data information includes first color temperature information, and / or, first color gamut information, and / or, first type information; The step of determining the third target data information based on the second data information and the first color data information includes: Based on the first color gamut information, the first color data information is subjected to color conversion processing to obtain the second color data information; Based on the first type of information and the first association information, the third color data information is determined; Based on the second color data information, the third color data information, and the first color temperature information, the third target data information is determined.

6. The method according to claim 5, characterized in that, The step of determining the third target data information based on the second color data information, the third color data information, and the first color temperature information includes: Based on the first color temperature information, the second color data information is processed to restore the color, resulting in the fourth color data information. Based on the third color data information, the fourth color data information is subjected to color correction processing to obtain the fifth color data information; Based on the first color data information and the fifth color data information, the third target data information is determined.

7. The method according to claim 6, characterized in that, The fourth color data information includes several first pixel values, and the third color data information includes several second pixel values; The step of performing color correction processing on the fourth color data information based on the third color data information to obtain the fifth color data information includes: For any first pixel value in the fourth color data information, a first color difference value is determined based on the first pixel value and each second pixel value; Based on the first color difference value, a number of second pixel values ​​are filtered to obtain the first target pixel value; Data generation processing is performed on the third pixel value corresponding to the first target pixel value to obtain sixth color data information; the third pixel value is the pixel value corresponding to the first target pixel value in the first color data information. Based on the first pixel value and the sixth color data information, the fifth color data information is determined.

8. The method according to claim 7, characterized in that, The sixth color data information includes several fourth pixel values; The determination of the fifth color data information based on the first pixel value and the sixth color data information includes: The first pixel value and several fourth pixel values ​​are calculated and processed to obtain the second color difference value; Based on the second color difference value, several fourth pixel values ​​are filtered to obtain the second target pixel information corresponding to the first pixel value; The second target pixel information corresponding to several first pixel values ​​is fused to obtain fifth color data information.

9. The method according to claim 1, characterized in that, The step of adjusting the image parameters of the image to be processed based on the first target data information to obtain the first target image information includes: Based on the first target data information, the seventh color data information of the image information to be processed is mapped to obtain the target color data information; Based on the target color data information, the image parameters of the image to be processed are adjusted to obtain the first target image information.

10. The method according to any one of claims 1 to 9, characterized in that, After adjusting the image parameters of the image to be processed based on the first target data information to obtain the first target image information, the process includes: The first target image information is color-adjusted based on the fifth data information to obtain the second target image information; the fifth data information is obtained by performing data generation processing on the image information to be processed and the first data information through a target processing model.

11. A system, characterized in that, include: The information acquisition module is used to acquire the image information to be processed and the first data information; The information determination module is used to determine first target data information based on the image information to be processed and the first data information; The image processing module is used to perform image parameter adjustment processing on the image information to be processed based on the first target data information to obtain the first target image information; Optionally, the information determining module determines first target data information based on the image information to be processed and the first data information, including: The image information to be processed and the first data information are processed using a target processing model to generate second target data information. Based on the second target data information, the first target data information is determined; Optionally, the second target data information includes second data information and / or third data information, and the information determining module determines the first target data information based on the second target data information, including: Based on the second data information, the third target data information is determined; Based on the third data information, the third target data information is converted into a data format to obtain the first target data information; Optionally, the information determining module determines third target data information based on the second data information, including: Match the second data information with the fourth data information in the fourth target data information; If any of the fourth data information matches the second data information, the fourth data information that matches the second data information is determined as the third target data information; and / or, If none of the fourth data information in the fourth target data information matches the second data information, the third target data information is determined based on the second data information and the first color data information; Optionally, the second data information includes first color temperature information, and / or, first color gamut information, and / or, first type information. The information determination module determines third target data information based on the second data information and the first color data information, including: Based on the first color gamut information, the first color data information is subjected to color conversion processing to obtain the second color data information; Based on the first type of information and the first association information, the third color data information is determined; Based on the second color data information, the third color data information, and the first color temperature information, the third target data information is determined; Optionally, the information determining module determines third target data information based on the second color data information, the third color data information, and the first color temperature information, including: Based on the first color temperature information, the second color data information is processed to restore the color, resulting in the fourth color data information. Based on the third color data information, the fourth color data information is subjected to color correction processing to obtain the fifth color data information; Based on the first color data information and the fifth color data information, the third target data information is determined; Optionally, the fourth color data information includes a plurality of first pixel values, the third color data information includes a plurality of second pixel values, and the information determining module performs color correction processing on the fourth color data information based on the third color data information to obtain fifth color data information, including: For any first pixel value in the fourth color data information, a first color difference value is determined based on the first pixel value and each second pixel value; Based on the first color difference value, a number of second pixel values ​​are filtered to obtain the first target pixel value; Data generation processing is performed on the third pixel value corresponding to the first target pixel value to obtain sixth color data information; the third pixel value is the pixel value corresponding to the first target pixel value in the first color data information. Based on the first pixel value and the sixth color data information, the fifth color data information is determined; Optionally, the sixth color data information includes several fourth pixel values, and the information determining module determines the fifth color data information based on the first pixel value and the sixth color data information, including: The first pixel value and several fourth pixel values ​​are calculated and processed to obtain the second color difference value; Based on the second color difference value, several fourth pixel values ​​are filtered to obtain the second target pixel information corresponding to the first pixel value; The second target pixel information corresponding to several first pixel values ​​is fused to obtain fifth color data information; Optionally, the image processing module adjusts the image parameters of the image to be processed based on the first target data information to obtain the first target image information, including: Based on the first target data information, the seventh color data information of the image information to be processed is mapped to obtain the target color data information; Based on the target color data information, the image parameters of the image to be processed are adjusted to obtain the first target image information; Optionally, after the image processing module performs image parameter adjustment processing on the image information to be processed based on the first target data information to obtain the first target image information, the image processing module is further configured to: The first target image information is color-adjusted based on the fifth data information to obtain the second target image information; the fifth data information is obtained by performing data generation processing on the image information to be processed and the first data information through a target processing model.

12. A computer device, characterized in that, The computer device includes: One or more processors; Memory; and One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the method of any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that, It contains a computer program that is loaded by a processor to perform the steps of the method according to any one of claims 1 to 10.

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