Lens effect evaluation method and device based on image vision, equipment and medium

Abstract

The application relates to the technical field of lenses and provides a lens effect evaluation method and device based on image vision, equipment and a medium. Images respectively photographed by multiple lenses in a camera device are acquired; the images are spliced to generate a panoramic image; exposure parameters are generated by detecting the synchronization degree of the exposure states between the lenses based on image parameters corresponding to the images and the panoramic image; panoramic parameters are generated by detecting whether the coverage range corresponding to the panoramic image is complete; color parameters between the lenses are generated based on the color distribution in the images; and a lens effect evaluation report is generated according to the exposure parameters, the panoramic parameters and the color parameters. The exposure synchronization degree, the panoramic integrity and the color consistency of the lenses can be accurately and comprehensively evaluated in the application scene of multiple lenses, comprehensive quantitative indexes are provided for the multiple-lens effect evaluation, the comprehensiveness and accuracy of the generated image information under the multiple lenses are ensured, and the visual effect and the user experience of the product are improved.

Description

Technical Field

[0001] This application relates to the field of lens technology, and more specifically, to a method, apparatus, device, and medium for evaluating lens effects based on image vision. Background Technology

[0002] With the rapid development of digital media technology, images and videos have become an indispensable part of people's daily lives. Whether it's sharing photos on social media, creating short videos, or in professional fields like film and television production and security monitoring, high-quality images and videos are essential. Therefore, evaluating the imaging effect of lenses has become particularly important, as it directly relates to the visual quality and information transmission effectiveness of images and videos.

[0003] Current methods for evaluating camera lenses involve taking a single image with the lens and assessing the image's display quality to reflect the lens's performance. However, this method cannot be applied to situations with multiple camera lenses, making its evaluation somewhat one-sided and unable to comprehensively assess the overall effect of images taken by multiple camera lenses. Summary of the Invention

[0004] The embodiments of this application provide a method, apparatus, device, and medium for evaluating lens effects based on image vision, which can at least partially solve the problem of insufficient comprehensive evaluation of the shooting effects of multiple camera lenses.

[0005] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0006] According to one aspect of this application, a lens effect evaluation method based on image vision is provided, comprising: synchronously sending a shooting command to multiple lenses in a camera device to acquire images captured by the lenses respectively of a target object; stitching the images together to generate a panoramic image; detecting the degree of synchronization of the exposure states between the lenses based on the image parameters corresponding to the images and the panoramic image, and generating exposure parameters; detecting whether the coverage area corresponding to the panoramic image is complete, and generating panoramic parameters; generating color parameters between the lenses based on the color distribution in the image; and generating a lens effect evaluation report based on the exposure parameters, the panoramic parameters, and the color parameters.

[0007] In this application, based on the aforementioned scheme, the step of detecting the synchronization degree of exposure states between lenses based on the image parameters corresponding to the image and the panoramic image, and generating exposure parameters, includes: generating histograms corresponding to the image and the panoramic image; determining a first exposure parameter between the images based on the histogram corresponding to the image; determining a second exposure parameter corresponding to the panoramic image based on the probability of brightness levels appearing simultaneously in each region set in the histogram corresponding to the panoramic image; and representing the synchronization degree of exposure states between lenses based on the first exposure parameter and the second exposure parameter.

[0008] In this application, based on the aforementioned scheme, the step of detecting whether the coverage area corresponding to the panoramic image is complete and generating panoramic parameters includes: identifying target objects in the panoramic image; segmenting the panoramic image according to the region corresponding to the target object to generate a segmented image; performing geometric transformation on the segmented image; comparing the generated transformed image with a preset object region; and generating panoramic parameters based on the comparison result.

[0009] In this application, based on the aforementioned scheme, generating color parameters between lenses based on the color distribution in the image includes: determining the color distribution function of the image based on the pixels of the image captured by each lens; and determining the color parameters between lenses according to the color distribution function of the image.

[0010] In this application, based on the aforementioned scheme, the step of stitching the images to generate a panoramic image includes: detecting feature points in the images and performing feature point matching; generating a transformation matrix based on the matched feature points, so as to perform coordinate transformation on the images through the transformation matrix and stitch them together to generate a panoramic image.

[0011] In this application, based on the aforementioned scheme, generating a lens effect evaluation report according to the exposure parameters, the panoramic parameters, and the color parameters includes: obtaining a template for the evaluation report; inputting the exposure parameters, the panoramic parameters, and the color parameters into the template to generate the lens effect evaluation report.

[0012] In this application, based on the aforementioned scheme, after generating a lens effect evaluation report according to the exposure parameters, the panoramic parameters, and the color parameters, the method further includes: adjusting the angle of each lens.

[0013] According to one aspect of this application, a lens effect evaluation device based on image vision is provided, comprising:

[0014] The image unit is used to simultaneously send shooting commands to multiple lenses in the camera device, acquire images captured by the lenses respectively of the target object, and stitch the images together to generate a panoramic image;

[0015] An exposure unit is used to detect the degree of synchronization of the exposure states between each lens based on the image parameters corresponding to the image and the panoramic image, and to generate exposure parameters.

[0016] A panoramic unit is used to detect whether the coverage area corresponding to the panoramic image is complete and to generate panoramic parameters.

[0017] A color unit is used to generate color parameters between lenses based on the color distribution in the image.

[0018] The reporting unit is used to generate a lens effect evaluation report based on the exposure parameters, the panoramic parameters, and the color parameters.

[0019] In this application, based on the aforementioned scheme, the step of detecting the synchronization degree of exposure states between lenses based on the image parameters corresponding to the image and the panoramic image, and generating exposure parameters, includes: generating histograms corresponding to the image and the panoramic image; determining a first exposure parameter between the images based on the histogram corresponding to the image; determining a second exposure parameter corresponding to the panoramic image based on the probability of brightness levels appearing simultaneously in each region set in the histogram corresponding to the panoramic image; and representing the synchronization degree of exposure states between lenses based on the first exposure parameter and the second exposure parameter.

[0020] In this application, based on the aforementioned scheme, the step of detecting whether the coverage area corresponding to the panoramic image is complete and generating panoramic parameters includes: identifying target objects in the panoramic image; segmenting the panoramic image according to the region corresponding to the target object to generate a segmented image; performing geometric transformation on the segmented image; comparing the generated transformed image with a preset object region; and generating panoramic parameters based on the comparison result.

[0021] In this application, based on the aforementioned scheme, generating color parameters between lenses based on the color distribution in the image includes: determining the color distribution function of the image based on the pixels of the image captured by each lens; and determining the color parameters between lenses according to the color distribution function of the image.

[0022] In this application, based on the aforementioned scheme, the step of stitching the images to generate a panoramic image includes: detecting feature points in the images and performing feature point matching; generating a transformation matrix based on the matched feature points, so as to perform coordinate transformation on the images through the transformation matrix and stitch them together to generate a panoramic image.

[0023] In this application, based on the aforementioned scheme, generating a lens effect evaluation report according to the exposure parameters, the panoramic parameters, and the color parameters includes: obtaining a template for the evaluation report; inputting the exposure parameters, the panoramic parameters, and the color parameters into the template to generate the lens effect evaluation report.

[0024] In this application, based on the aforementioned scheme, after generating a lens effect evaluation report according to the exposure parameters, the panoramic parameters, and the color parameters, the method further includes: adjusting the angle of each lens.

[0025] According to one aspect of this application, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the image vision-based lens effect evaluation method as described in the above embodiments.

[0026] According to one aspect of this application, an electronic device is provided, comprising: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the image vision-based lens effect evaluation method as described in the above embodiments.

[0027] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the image vision-based lens effect evaluation method provided in the various alternative implementations described above.

[0028] In the technical solution of this application, a shooting command is simultaneously sent to multiple lenses in a camera device to acquire images captured by each lens targeting a target object; the images are then stitched together to generate a panoramic image; based on the image parameters corresponding to the images and the panoramic image, the synchronization degree of the exposure states between the lenses is detected, and exposure parameters are generated; the completeness of the coverage area corresponding to the panoramic image is detected, and panoramic parameters are generated; based on the color distribution in the images, color parameters between the lenses are generated; and a lens effect evaluation report is generated based on the exposure parameters, the panoramic parameters, and the color parameters. Through multi-lens synchronous shooting and image stitching, and based on a comprehensive analysis of image parameters, panoramic coverage area, and color distribution, the exposure synchronization, panoramic integrity, and color consistency of each lens can be accurately and comprehensively evaluated in multi-lens application scenarios. This provides comprehensive quantitative indicators for multi-lens effect evaluation, helps optimize shooting strategies, improves shooting quality, ensures the comprehensiveness and accuracy of image information, and enhances the visual effect and user experience of the final product.

[0029] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0030] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0031] Figure 1 The flowchart illustrating a lens effect evaluation method based on image vision in one embodiment of this application is shown schematically.

[0032] Figure 2 The flowchart illustrating the generation of exposure parameters is shown in one embodiment of this application.

[0033] Figure 3 The illustration shows a schematic diagram of a lens effect evaluation device based on image vision in one embodiment of this application.

[0034] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

[0035] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0036] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0037] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0038] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0039] The implementation details of the technical solution of this application are described below:

[0040] Figure 1 A flowchart illustrating a lens effect evaluation method based on image vision according to an embodiment of this application is shown. (Refer to...) Figure 1 As shown, this image-based vision-based lens effect evaluation method includes at least steps S110 to S150, which are described in detail below:

[0041] In step S110, a photo-taking command is simultaneously sent to multiple lenses in the camera device to acquire images captured by the lenses respectively of the target object, and the images are stitched together to generate a panoramic image.

[0042] In one embodiment of this application, the camera device is equipped with multiple lenses to simultaneously acquire high-definition images or videos from multiple directions in a single shot, and uses the high-definition images as the images to be stitched in step S110, and uses the image frames in the video as the images to be stitched in step S110.

[0043] First, connect the camera device via a network or other communication interface. Using the device driver interface, identify and initialize each lens in the camera device, including setting parameters such as resolution, frame rate, and exposure. Upon receiving the shooting command, the synchronization control module generates a global synchronization signal. This signal is simultaneously sent to each lens in the camera device via a high-speed communication channel. Each lens, upon receiving the synchronization signal, immediately activates its shutter mechanism to take a picture.

[0044] After each lens takes a picture, it transmits the captured image to the computer via a communication interface. The computer receives and stores these images, ensuring the integrity and accuracy of the data.

[0045] In one embodiment of this application, stitching the images together to generate a panoramic image includes:

[0046] Detect feature points in the image and perform feature point matching;

[0047] A transformation matrix is ​​generated based on the matched feature points, and the images are then transformed and stitched together to generate a panoramic image.

[0048] In one embodiment of this application, feature points are extracted from each image through feature point detection. Then, corresponding feature points between different images are found through feature point matching. These matched feature points will serve as reference points for image stitching.

[0049] Based on the coordinates of the matched feature points in the images, a transformation matrix is ​​generated between the images. The transformation matrix describes how to transform one image into the coordinate system of another image to achieve seamless stitching.

[0050] After obtaining the transformation matrix, each image is transformed to align them in the same coordinate system. Then, image fusion is used to merge the transformed images into a single panoramic image.

[0051] In step S120, based on the image parameters corresponding to the image and the panoramic image, the degree of synchronization of the exposure states between each lens is detected, and exposure parameters are generated.

[0052] like Figure 2 As shown, in one embodiment of this application, based on the image parameters corresponding to the image and the panoramic image, the synchronization degree of the exposure states between each lens is detected, and exposure parameters are generated, including:

[0053] S210, Generate histograms corresponding to the image and the panoramic image;

[0054] S220, determine the first exposure parameters between the images based on the histogram corresponding to the images;

[0055] S230, based on the histogram corresponding to the panoramic image, set the probability of brightness levels appearing simultaneously in each region, and determine the second exposure parameter corresponding to the panoramic image.

[0056] S240, based on the first exposure parameter and the second exposure parameter, indicates the degree of synchronization of the exposure states between the lenses.

[0057] In one embodiment of this application, histograms of the images captured by each lens and a histogram corresponding to the stitched panoramic image are generated. Based on the number of pixels in the histograms, a first exposure parameter between the images captured by the two lenses is first evaluated. for:

[0058]

[0059] in, These represent the brightness levels in the two images respectively.i The number of pixels below N This represents the total number of pixels in the image. In this embodiment, the larger the calculated first exposure parameter, the more consistent the exposure of the two images.

[0060] Then, based on the histogram of the panoramic image, the second exposure parameters between all shots are determined. for:

[0061]

[0062] in, It is the brightness level in the histogram of the panoramic image. i and j The probability of them occurring simultaneously; These are the brightness levels in the histograms corresponding to the two images. i and j The probability of occurrence. Calculated in this embodiment. The higher the value, the more similar the exposure of the two images, because they are more interdependent.

[0063] The above process uses a first exposure parameter to measure the exposure synchronization between two lenses individually, and then uses a second exposure parameter to measure the exposure synchronization of the panoramic image corresponding to all lenses. This allows us to understand the exposure synchronization between individual lenses, as well as to comprehensively and globally evaluate the exposure of all lenses, thus improving the accuracy and comprehensiveness of exposure synchronization detection and evaluation.

[0064] In step S130, it is detected whether the coverage area corresponding to the panoramic image is complete, and panoramic parameters are generated.

[0065] In one embodiment of this application, detecting whether the coverage area corresponding to the panoramic image is complete and generating panoramic parameters includes:

[0066] Identify target objects in the panoramic image;

[0067] The panoramic image is segmented based on the region corresponding to the target object to generate a segmented image;

[0068] The segmented image is subjected to geometric transformation, and the generated transformed image is compared with a preset object region. Based on the comparison result, panoramic parameters are generated.

[0069] In one embodiment of this application, an input panoramic image is analyzed to identify specific target objects within the image. The target object can be any predefined object, such as a precision device, a control panel, etc.

[0070] Furthermore, deep convolutional neural networks can be used to extract features from panoramic images. Through multi-layer convolution and pooling operations, rich feature information can be extracted from the image to form a feature map. After the target objects are identified, the panoramic image is segmented according to the position and boundaries of these objects. A high-precision semantic segmentation network can be used to divide the image into different regions, each region corresponding to one or more target objects. The segmented image will more clearly show the position and shape of each target object.

[0071] Next, geometric transformations are performed on the segmented image, specifically rotation, scaling, translation, or more complex transformations, to change its shape, size, or orientation, so as to align or match the target object in the segmented image with a preset object region, making comparison and analysis easier.

[0072] After geometric transformation, the transformed image is compared with a preset object region. The preset object region can be defined based on prior knowledge or standards, representing the position and shape of the target object under ideal or standard conditions. The purpose of the comparison is to evaluate the similarity or difference between the transformed image and the preset region. Based on the comparison results, panoramic parameters are generated. In this embodiment, the panoramic parameters are used to represent the differences in image content between the segmented image and the preset object region.

[0073] In step S140, color parameters between each lens are generated based on the color distribution in the image.

[0074] In one embodiment of this application, color parameters between lenses are generated based on the color distribution in the image, including:

[0075] Based on the pixels of the images captured by each lens, the color distribution function of the image is determined;

[0076] Based on the color distribution function of the image, determine the color parameters between lenses.

[0077] In one embodiment of this application, the pixel set of the image is assumed to be... Each pixel In space, it can be represented as a three-dimensional vector. In this embodiment, the color distribution function of the image... for:

[0078]

[0079] in, For indicator functions, c Indicates color value, N Indicates the number of pixels. i This represents a pixel identifier. In this embodiment, a color distribution function is defined. It can accurately describe the frequency of each color in an image. It not only considers the existence of color, but also quantifies the distribution of color in the image by discretizing the color space and calculating the frequency.

[0080] Let the images captured by the two lenses be respectively and Their color distributions are respectively and Then the color parameters between the two lenses for:

[0081]

[0082] log is a logarithmic function.

[0083] The above process measures the information loss from one color distribution to another; when the two distributions are identical, the color parameter is 0. This process effectively assesses the color consistency differences between images captured by different lenses, providing an intuitive numerical metric to quantify the quality of color consistency. It allows for the rapid identification of which lenses produce color differences, guiding subsequent adjustments and optimizations.

[0084] In step S150, a lens effect evaluation report is generated based on the exposure parameters, the panoramic parameters, and the color parameters.

[0085] In one embodiment of this application, a lens effect evaluation report is generated based on the exposure parameters, the panoramic parameters, and the color parameters, including:

[0086] Get the evaluation report template;

[0087] Input the exposure parameters, the panoramic parameters, and the color parameters into the template to generate a lens effect evaluation report.

[0088] In one embodiment of this application, a flexible template is pre-designed, capable of receiving and processing various types of shot effect evaluation parameters. The template employs an extensible markup language (such as XML or JSON) to allow for easy addition of new parameter types in the future. The extensible template structure facilitates the future addition of new parameter types and evaluation metrics. XML is an extensible markup language. JSON is JavaScript Object Notation.

[0089] The collected parameters are mapped to corresponding fields in the template. Specifically, exposure parameters are mapped to the "Exposure Settings" section of the template. Panorama parameters are mapped to the "Panorama Shooting Configuration" section. Color parameters are mapped to the "Color Management" section. Based on the output of the evaluation algorithm, a pre-designed report template is populated. The report template includes a detailed analysis of the lens effect, a score, and improvement suggestions.

[0090] It can also generate intuitive visualizations, such as line graphs and color balance comparison charts, to help users understand the shot effects more clearly. The generated reports can be output in PDF (Portable Document Format), HTML (Hyper Text Markup Language), or other formats for users to view and save. Intuitive visualizations help users better understand shot effects.

[0091] Through the above steps, the system can efficiently generate lens effect evaluation reports, which not only improves the accuracy and efficiency of the evaluation, but also automates the entire process from data collection to report generation, reduces human intervention and errors, and provides users with intuitive and easy-to-understand analysis results.

[0092] After generating a lens effect evaluation report based on the exposure parameters, the panoramic parameters, and the color parameters, the report further includes: adjusting the angles of each lens to adjust the overlapping area between images, thereby improving the shooting effect of the camera lens.

[0093] In the technical solution of this application, a shooting command is simultaneously sent to multiple lenses in a camera device to acquire images captured by each lens targeting a target object; the images are then stitched together to generate a panoramic image; based on the image parameters corresponding to the images and the panoramic image, the synchronization degree of the exposure states between the lenses is detected, and exposure parameters are generated; the completeness of the coverage area corresponding to the panoramic image is detected, and panoramic parameters are generated; based on the color distribution in the images, color parameters between the lenses are generated; and a lens effect evaluation report is generated based on the exposure parameters, the panoramic parameters, and the color parameters. Through multi-lens synchronous shooting and image stitching, and based on a comprehensive analysis of image parameters, panoramic coverage area, and color distribution, the exposure synchronization, panoramic integrity, and color consistency of each lens can be accurately and comprehensively evaluated in multi-lens application scenarios. This provides comprehensive quantitative indicators for multi-lens effect evaluation, helps optimize shooting strategies, improves shooting quality, ensures the comprehensiveness and accuracy of image information, and enhances the visual effect and user experience of the final product.

[0094] The following describes an apparatus embodiment of this application, which can be used to execute the image vision-based lens effect evaluation method in the above embodiments of this application. It is understood that the apparatus can be a computer program (including program code) running on a computer device, for example, the apparatus is application software; the apparatus can be used to execute the corresponding steps in the method provided in the embodiments of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the above embodiments of the image vision-based lens effect evaluation method of this application.

[0095] Figure 3 A block diagram of an image-based lens effect evaluation apparatus according to an embodiment of this application is shown.

[0096] Reference Figure 3 As shown, a lens effect evaluation apparatus based on image vision according to an embodiment of this application includes:

[0097] Image unit 310 is used to simultaneously send shooting commands to multiple lenses in the camera device, acquire images captured by the lenses respectively of the target object, and stitch the images together to generate a panoramic image;

[0098] Exposure unit 320 is used to detect the degree of synchronization of exposure states between lenses based on the image parameters corresponding to the image and the panoramic image, and generate exposure parameters.

[0099] Panoramic unit 330 is used to detect whether the coverage area corresponding to the panoramic image is complete and generate panoramic parameters.

[0100] Color unit 340 is used to generate color parameters between lenses based on the color distribution in the image;

[0101] Reporting unit 350 is used to generate a lens effect evaluation report based on the exposure parameters, the panoramic parameters, and the color parameters.

[0102] In this application, based on the aforementioned scheme, the step of detecting the synchronization degree of exposure states between lenses based on the image parameters corresponding to the image and the panoramic image, and generating exposure parameters, includes: generating histograms corresponding to the image and the panoramic image; determining a first exposure parameter between the images based on the histogram corresponding to the image; determining a second exposure parameter corresponding to the panoramic image based on the probability of brightness levels appearing simultaneously in each region set in the histogram corresponding to the panoramic image; and representing the synchronization degree of exposure states between lenses based on the first exposure parameter and the second exposure parameter.

[0103] In this application, based on the aforementioned scheme, the step of detecting whether the coverage area corresponding to the panoramic image is complete and generating panoramic parameters includes: identifying target objects in the panoramic image; segmenting the panoramic image according to the region corresponding to the target object to generate a segmented image; performing geometric transformation on the segmented image; comparing the generated transformed image with a preset object region; and generating panoramic parameters based on the comparison result.

[0104] In this application, based on the aforementioned scheme, generating color parameters between lenses based on the color distribution in the image includes: determining the color distribution function of the image based on the pixels of the image captured by each lens; and determining the color parameters between lenses according to the color distribution function of the image.

[0105] In this application, based on the aforementioned scheme, the step of stitching the images to generate a panoramic image includes: detecting feature points in the images and performing feature point matching; generating a transformation matrix based on the matched feature points, so as to perform coordinate transformation on the images through the transformation matrix and stitch them together to generate a panoramic image.

[0106] In this application, based on the aforementioned scheme, generating a lens effect evaluation report according to the exposure parameters, the panoramic parameters, and the color parameters includes: obtaining a template for the evaluation report; inputting the exposure parameters, the panoramic parameters, and the color parameters into the template to generate the lens effect evaluation report.

[0107] In this application, based on the aforementioned scheme, after generating a lens effect evaluation report according to the exposure parameters, the panoramic parameters, and the color parameters, the method further includes: adjusting the angle of each lens.

[0108] In the technical solution of this application, a shooting command is simultaneously sent to multiple lenses in a camera device to acquire images captured by each lens targeting a target object; the images are then stitched together to generate a panoramic image; based on the image parameters corresponding to the images and the panoramic image, the synchronization degree of the exposure states between the lenses is detected, and exposure parameters are generated; the completeness of the coverage area corresponding to the panoramic image is detected, and panoramic parameters are generated; based on the color distribution in the images, color parameters between the lenses are generated; and a lens effect evaluation report is generated based on the exposure parameters, the panoramic parameters, and the color parameters. Through multi-lens synchronous shooting and image stitching, and based on a comprehensive analysis of image parameters, panoramic coverage area, and color distribution, the exposure synchronization, panoramic integrity, and color consistency of each lens can be accurately and comprehensively evaluated in multi-lens application scenarios. This provides comprehensive quantitative indicators for multi-lens effect evaluation, helps optimize shooting strategies, improves shooting quality, ensures the comprehensiveness and accuracy of image information, and enhances the visual effect and user experience of the final product.

[0109] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown.

[0110] It should be noted that the computer system of the electronic device in this embodiment is only an example and should not impose any limitations on the function and scope of use of the embodiments of this application.

[0111] In this embodiment, the computer system includes a central processing unit 401, which can perform various appropriate actions and processes based on a program stored in a read-only memory 402 or a program loaded from a storage section 408 into a random access memory 403, such as executing the methods described in the above embodiments. The random access memory 403 also stores various programs and data required for system operation. The central processing unit 401, the read-only memory 402, and the random access memory 403 are interconnected via a bus 404. An input / output interface 405 is also connected to the bus 404.

[0112] The following components are connected to the input / output interface 405: an input section 406 including a keyboard, mouse, etc.; an output section 407 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the input / output interface 405 as needed. A removable medium 411, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 410 as needed so that computer programs read from it can be installed into the storage section 408 as needed.

[0113] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409, and / or installed from removable medium 411. When the computer program is executed by central processing unit 401, it performs various functions defined in the system of this application.

[0114] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. The transmitted data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0115] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0116] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0117] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various alternative implementations described above.

[0118] In another aspect, this application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the methods described in the above embodiments.

[0119] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0120] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the methods according to the embodiments of this application.

[0121] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0122] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for evaluating lens effects based on image vision, characterized in that, include: Simultaneously send photo-taking commands to multiple lenses in the camera device to acquire images captured by each lens of the target object, and stitch the images captured by the multiple lenses to generate a panoramic image; Based on the images captured by the multiple lenses and the image parameters corresponding to the panoramic image, the degree of synchronization of the exposure states between the lenses is detected, and exposure parameters are generated. Detect whether the coverage area corresponding to the panoramic image is complete, and generate panoramic parameters; Based on the color distribution in the images captured by the multiple lenses, color parameters between the lenses are generated. Based on the exposure parameters, the panoramic parameters, and the color parameters, a lens effect evaluation report is generated; The step of detecting the synchronization of exposure states between the lenses and generating exposure parameters based on the image parameters corresponding to the images captured by the multiple lenses and the panoramic image includes: Generate histograms of the images captured by the multiple lenses and the corresponding panoramic images; Based on the histograms corresponding to the images captured by the multiple lenses, the first exposure parameters between each image are determined. for: in, These represent the brightness levels in the two images respectively. i The number of pixels below N This represents the total number of pixels in the image; Based on the probability of a preset brightness level occurring simultaneously in each region within the histogram corresponding to the panoramic image, the second exposure parameter corresponding to the panoramic image is determined. for: in, It is the brightness level in the histogram of the panoramic image. i and j The probability of them occurring simultaneously; These are the brightness levels in the histogram of the panoramic image. i and j The probability of occurrence; The degree of synchronization of exposure states between lenses is represented by the first exposure parameter and the second exposure parameter. Specifically, the exposure synchronization between two lenses is measured separately by the first exposure parameter, and then the exposure synchronization of the panoramic image corresponding to all lenses is measured by the second exposure parameter. The step of detecting whether the coverage area corresponding to the panoramic image is complete and generating panoramic parameters includes: Identify target objects in the panoramic image; The panoramic image is segmented based on the region corresponding to the target object to generate a segmented image; The segmented image is subjected to geometric transformation, the generated transformed image is compared with a preset object region, and panoramic parameters are generated based on the comparison result. Specifically, based on the color distribution in the images captured by the multiple lenses, color parameters are generated between each lens, including: Based on the pixels of the images captured by the multiple lenses, determine the color distribution function of the images captured by the multiple lenses. for: in, For indicator functions, c Indicates color value, N This represents the total number of pixels in the image. k Indicates pixel identifier, A set of pixels representing an image; Based on the color distribution function of the images captured by the multiple lenses, the color parameters between the lenses are determined. for: in, and These represent images taken by two lenses respectively. and The color distribution.

2. The image vision-based lens effect evaluation method according to claim 1, characterized in that, The step of stitching together the images captured by the multiple lenses to generate a panoramic image includes: Detect feature points in the image and perform feature point matching; A transformation matrix is ​​generated based on the matched feature points. The images captured by the multiple lenses are then transformed and stitched together to generate a panoramic image.

3. The image-based vision-based lens effect evaluation method according to claim 1, characterized in that, The step of generating a lens effect evaluation report based on the exposure parameters, the panoramic parameters, and the color parameters includes: Get the evaluation report template; Input the exposure parameters, the panoramic parameters, and the color parameters into the template to generate a lens effect evaluation report.

4. The image vision-based lens effect evaluation method according to claim 1, characterized in that, After generating a lens effect evaluation report based on the exposure parameters, the panoramic parameters, and the color parameters, the process further includes: Adjust the angles of each camera lens.

5. A lens effect evaluation device based on image vision, characterized in that, include: The image unit is used to simultaneously send shooting commands to multiple lenses in the camera device, acquire images captured by the lenses respectively of the target object, and stitch the images captured by the multiple lenses to generate a panoramic image; An exposure unit is used to detect the degree of synchronization of the exposure states between the lenses based on the images captured by the multiple lenses and the image parameters corresponding to the panoramic image, and to generate exposure parameters. A panoramic unit is used to detect whether the coverage area corresponding to the panoramic image is complete and to generate panoramic parameters. A color unit is used to generate color parameters between lenses based on the color distribution in the images captured by the multiple lenses respectively. The reporting unit is used to generate a lens effect evaluation report based on the exposure parameters, the panoramic parameters, and the color parameters. The step of detecting the synchronization of exposure states between the lenses and generating exposure parameters based on the image parameters corresponding to the images captured by the multiple lenses and the panoramic image includes: Generate histograms of the images captured by the multiple lenses and the corresponding panoramic images; Based on the histograms corresponding to the images captured by the multiple lenses, the first exposure parameters between each image are determined. for: in, These represent the brightness levels in the two images respectively. i The number of pixels below N This represents the total number of pixels in the image; Based on the probability of a preset brightness level occurring simultaneously in each region within the histogram corresponding to the panoramic image, the second exposure parameter corresponding to the panoramic image is determined. for: in, It is the brightness level in the histogram of the panoramic image. i and j The probability of them occurring simultaneously; These are the brightness levels in the histogram of the panoramic image. i and j The probability of occurrence; The degree of synchronization of exposure states between lenses is represented by the first exposure parameter and the second exposure parameter. Specifically, the exposure synchronization between two lenses is measured separately by the first exposure parameter, and then the exposure synchronization of the panoramic image corresponding to all lenses is measured by the second exposure parameter. The step of detecting whether the coverage area corresponding to the panoramic image is complete and generating panoramic parameters includes: Identify target objects in the panoramic image; The panoramic image is segmented based on the region corresponding to the target object to generate a segmented image; The segmented image is subjected to geometric transformation, the generated transformed image is compared with a preset object region, and panoramic parameters are generated based on the comparison result. Specifically, based on the color distribution in the images captured by the multiple lenses, color parameters are generated between each lens, including: Based on the pixels of the images captured by the multiple lenses, determine the color distribution function of the images captured by the multiple lenses. for: in, For indicator functions, c Indicates color value, N This represents the total number of pixels in the image. k Indicates pixel identifier, A set of pixels representing an image; Based on the color distribution function of the images captured by the multiple lenses, the color parameters between the lenses are determined. for: in, and These represent images taken by two lenses respectively. and The color distribution.

6. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the image vision-based lens effect evaluation method as described in any one of claims 1 to 4.

7. An electronic device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the image vision-based lens effect evaluation method as described in any one of claims 1 to 4.

Images