Sunscreen application detection method, device, and storage medium

Abstract

The application discloses a sunscreen application detection method and device and a storage medium, and relates to the technical field of image processing. The method comprises the following steps: collecting UV images of a user's face at at least two preset angles by an ultraviolet imaging device; inputting each UV image into a pre-trained image segmentation model to generate a target image containing a reflection interference mark and a sunscreen substance mark; determining an effective sunscreen area according to the reflection interference mark and the sunscreen substance mark in the target image; mapping the effective sunscreen area to a face reference coordinate system; calculating the area ratio of the effective sunscreen area relative to the total face area; and finally generating a sunscreen application detection result based on the area ratio. The method generates a target image by using UV images and a pre-trained image segmentation model, determines an effective sunscreen area by combining a reflection interference mark and a sunscreen substance mark, and evaluates the sunscreen application effect, thereby improving the sunscreen application detection effect.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and in particular to a method, device and storage medium for detecting sunscreen application. Background Technology

[0002] Currently, traditional sunscreen application testing typically uses the Sun Protection Factor (SPF) test to assess its effectiveness. The SPF test uses an ultraviolet spectrometer to irradiate skin with and without sunscreen, measuring the dose of erythema produced under specific wavelengths of ultraviolet light. The ratio of the two doses is used to calculate the SPF value, which is then used to determine the sunscreen's effectiveness; a higher SPF indicates better application. However, in practical applications, individual skin differences can affect the final test results, leading to relatively poor accuracy in detecting sunscreen application using traditional methods.

[0003] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] This application provides a method, device, and storage medium for detecting sunscreen application, aiming to solve the problem that traditional methods have poor detection effects on sunscreen application.

[0005] To achieve the above objectives, this application provides a method for detecting sunscreen application, the method comprising the following steps:

[0006] The ultraviolet imaging device acquires UV images of the user's face at at least two preset angles.

[0007] Each of the UV images is input into a pre-trained image segmentation model to generate a target image containing reflective interference markers and sunscreen substance markers;

[0008] The effective sun protection area is determined based on the reflective interference markers and sunscreen substance markers in the target image;

[0009] The effective sun protection area is mapped to the facial reference coordinate system, and the area ratio of the effective sun protection area relative to the total facial area is calculated.

[0010] The detection results for sunscreen application are generated based on the area ratio.

[0011] In one embodiment, the step of determining the effective sun protection area based on the reflective interference markers and the sunscreen substance markers in the target image includes:

[0012] Based on the reflectivity and area information of the reflective interference mark, a matching weight value is determined, and the reflective interference mark in the target image is associated with the corresponding weight value.

[0013] In the target image from different angles, determine the weighted sum of the weight values ​​corresponding to the reflective interference markers in the same physical region;

[0014] When the weighted sum is less than a preset threshold, the physical area is determined as the effective sun protection area.

[0015] In one embodiment, after the step of generating the detection result of sunscreen application based on the area ratio, the method further includes:

[0016] The application effect of the product is determined based on the comparison between the test results and historical test data;

[0017] When the application effect is that the area ratio of the effective sun protection area decreases, application improvement information is generated based on the historical detection data;

[0018] Based on the user's skin type information, a matching sunscreen product and corresponding sunscreen product usage recommendations are determined;

[0019] The application improvement information and sunscreen product usage suggestions are fed back to the corresponding user interface.

[0020] In one embodiment, after the step of generating the detection result of sunscreen application based on the area ratio, the method further includes:

[0021] Obtain a sun protection coverage distribution map that includes the detection results;

[0022] In the sun protection coverage distribution map, the effective sun protection coverage area and the uncovered area are rendered with a first visual color and a second visual color, respectively;

[0023] The updated sun protection coverage distribution map will be rendered and displayed on the corresponding interface.

[0024] In one embodiment, after the step of obtaining the sun protection coverage distribution map including the detection results, the method further includes:

[0025] The coverage rate of key areas is determined based on the size of the uncovered area, wherein the coverage rate is the ratio of the area of ​​the uncovered area to the total area of ​​the face;

[0026] When the uncovering rate of the area corresponding to the key area is detected to be lower than the threshold, a key repainting reminder is triggered;

[0027] The key touch-up reminder is fed back to the user interface.

[0028] In one embodiment, after the step of acquiring UV images of the user's face at at least two preset angles using an ultraviolet imaging device, the method further includes:

[0029] Real-time detection of current facial pose information;

[0030] Based on the facial posture information, the deviation value between the user's face and the ultraviolet imaging device is determined;

[0031] Adjust the acquisition parameters of the ultraviolet imaging device according to the deviation value;

[0032] According to the adjusted ultraviolet acquisition device, the step of acquiring UV images of the user's face at at least two preset angles through the ultraviolet imaging device is performed.

[0033] In one embodiment, after the step of acquiring UV images of the user's face at at least two preset angles using an ultraviolet imaging device, the method further includes:

[0034] The system simultaneously captures color images of the user's face from at least two preset angles using a color camera.

[0035] The UV image and color image are spatially registered based on the feature point matching algorithm to generate the corrected UV image and color image.

[0036] The violet spectrum of the corrected UV image is mapped to the color spectrum range to generate a color-corrected UV image;

[0037] The color-corrected UV image and the corrected color image are pixel-by-pixel superimposed and fused to generate a composite image, which is then output through a display interface.

[0038] In one embodiment, the step of spatially registering the UV image and color image based on the feature point matching algorithm to generate the corrected UV image and color image includes:

[0039] Extract the feature point set from the UV image and the color image, and generate a feature descriptor for the feature point set;

[0040] The target feature points in the feature point set are determined based on the feature descriptor;

[0041] The UV image and the color image are aligned in spatial coordinate system based on the target feature points to generate a corrected UV image and a color image.

[0042] In addition, to achieve the above objectives, this application also provides a sunscreen application detection device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the sunscreen application detection method as described above.

[0043] In addition, to achieve the above objectives, this application also provides a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the sunscreen application detection method as described above.

[0044] This application provides a method, device, and storage medium for detecting sunscreen application. It involves acquiring UV images of a user's face at at least two preset angles using an ultraviolet imaging device. These UV images are then input into a pre-trained image segmentation model to generate a target image containing reflective interference markers and sunscreen substance markers. Based on these markers, an effective sunscreen area is determined. This effective sunscreen area is then mapped to a facial reference coordinate system, and the area ratio of the effective sunscreen area relative to the total facial area is calculated. Finally, a detection result for sunscreen application is generated based on this area ratio. This embodiment acquires UV images using an ultraviolet imaging device, generates target images using a pre-trained image segmentation model, determines the effective sunscreen area using reflective interference markers and sunscreen substance markers, and finally evaluates the sunscreen application effect based on the area ratio. This method can accurately and quickly detect the coverage of a user's sunscreen application, thereby improving the detection effect. Attached Figure Description

[0045] 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.

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a flowchart illustrating the first embodiment of the sunscreen application detection method of this application;

[0048] Figure 2 This is a flowchart illustrating the second embodiment of the sunscreen application detection method of this application;

[0049] Figure 3This is a flowchart illustrating the third embodiment of the sunscreen application detection method of this application;

[0050] Figure 4 This is a schematic diagram of the hardware operating environment of the sunscreen application detection device involved in the embodiments of this application.

[0051] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0052] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0053] To better understand the above technical solutions, exemplary embodiments of this application will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of this application are shown in the drawings, it should be understood that this application can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of this application and to fully convey the scope of this application to those skilled in the art.

[0054] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0055] The main solution of this application is as follows: A UV image of the user's face at at least two preset angles is acquired using an ultraviolet imaging device; each UV image is input into a pre-trained image segmentation model to generate a target image containing reflective interference markers and sunscreen substance markers; an effective sun protection area is determined based on the reflective interference markers and sunscreen substance markers in the target image; the effective sun protection area is mapped to a facial reference coordinate system, and the area ratio of the effective sun protection area relative to the total facial area is calculated; a detection result of sunscreen application is generated based on the area ratio.

[0056] Currently, most sunscreen application detection methods on the market rely on simple color comparison techniques. These methods involve users applying sunscreen themselves and then observing changes in skin color under a specific light source to determine if the sunscreen is applied evenly. However, in practical applications, this method relies on subjective user feedback and cannot comprehensively reflect the sunscreen application status on the user's face. This results in traditional solutions having poor detection effectiveness for sunscreen application.

[0057] This method acquires UV images of a user's face at at least two preset angles using an ultraviolet imaging device. These UV images are then input into a pre-trained image segmentation model to generate target images containing reflective interference markers and sunscreen substance markers. Based on these markers, an effective sun protection area is determined. This effective sun protection area is then mapped to a facial reference coordinate system, and the area ratio of the effective sun protection area relative to the total facial area is calculated. Finally, a detection result for sunscreen application is generated based on this area ratio. This embodiment acquires UV images using an ultraviolet imaging device, generates target images using a pre-trained image segmentation model, determines effective sun protection areas using reflective interference markers and sunscreen substance markers, and finally evaluates the sunscreen application effect based on the area ratio. This method can accurately and quickly detect the coverage of a user's sunscreen application, thereby improving the detection effect of sunscreen application.

[0058] It should be noted that the executing entity in this embodiment can be an application detection system, or a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or a sunscreen application detection device capable of performing the above functions. This embodiment does not specifically limit it in this way. The following uses an application detection system as the executing entity to describe this embodiment and the following embodiments.

[0059] Example 1

[0060] Based on this, embodiments of this application provide a method for detecting sunscreen application, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the sunscreen application detection method of this application, which includes steps S10 to S50:

[0061] Step S10: Acquire UV images of the user's face at at least two preset angles using an ultraviolet imaging device.

[0062] In this embodiment, the application detection system performs the processing action. The ultraviolet imaging device is communicatively connected to the application detection system. The application detection system can be installed in a smart makeup mirror or in other smart terminals. The ultraviolet imaging device is a device capable of capturing ultraviolet reflection and absorption, converting invisible ultraviolet information into a visible image. It can also be a dedicated imaging device equipped with a UV filter and a high-sensitivity sensor, operating in the 315-400nm (UVA band) wavelength range. UV images reflect the reflective characteristics of an object's surface under ultraviolet irradiation and can be used to distinguish sunscreens from other substances.

[0063] Specifically, the ultraviolet imaging device is placed at two or more preset angles, which may include a combination of a frontal view and a 30° side view, to cover the three-dimensional curved features of the face and ensure full coverage of the user's face. For example, one angle can be a frontal view and another angle can be a side view, and the ultraviolet imaging device captures UV images of the user's face at these angles respectively.

[0064] Optionally, in this embodiment, after step S10, steps S11 to S13 are further included:

[0065] Step S11: Real-time detection of current facial pose information.

[0066] Step S12: Determine the deviation value between the user's face and the ultraviolet imaging device based on the facial posture information.

[0067] Step S13: Adjust the acquisition parameters of the ultraviolet imaging device according to the deviation value.

[0068] Step S14: Based on the adjusted ultraviolet acquisition device, perform the step of acquiring UV images of the user's face at at least two preset angles using the ultraviolet imaging device.

[0069] Specifically, facial pose information refers to various parameters describing the user's current facial pose, such as pitch, yaw, and roll angles. These parameters reflect changes in the user's head posture relative to the ultraviolet imaging device. The preset pose angle range refers to the ideal range of the user's facial pose set in advance when the ultraviolet imaging device acquires UV images. When the actual facial pose information deviates from this range, the acquisition parameters of the imaging device need to be adjusted. Acquisition parameters, including exposure time and focal length, are key parameters affecting image quality. Changing these parameters can optimize the UV image acquisition effect under different facial poses.

[0070] In this embodiment, a camera connected to the smear detection system acquires the user's facial posture information in real time. For example, the camera can capture continuous changes in facial images, and the displacement of facial feature points in the images can be analyzed to infer posture changes. Alternatively, an inertial sensor in a smart device can be used to detect head movement. The smear detection system then uses pre-set adjustment rules to determine the degree of deviation between the user's face and the ultraviolet imaging device based on the facial posture information to calculate new acquisition parameter values. For example, if the user's pitch angle deviates from the preset range of the ultraviolet imaging device, the system will adjust the exposure time accordingly based on the magnitude of the deviation to adapt to the current lighting and human posture conditions.

[0071] Simultaneously, the focal length is dynamically adjusted based on changes in distance and posture to ensure facial image clarity. Using a UV imaging device with adjusted parameters, a UV image of the user's face is acquired again at a preset angle. This acquisition yields high-quality UV images that better match the current facial posture, providing a better data foundation for subsequent image processing and analysis. By detecting facial posture information in real time and adjusting the acquisition parameters of the UV imaging device accordingly, the acquired UV images maintain good quality and accuracy under different user postures, further improving the overall effectiveness of sunscreen application detection.

[0072] Step S20: Input each of the UV images into the pre-trained image segmentation model to generate a target image containing reflective interference markers and sunscreen substance markers.

[0073] In this embodiment, the image segmentation model is a deep learning-based algorithm that can segment an image into multiple regions and label each region. The pre-trained image segmentation model refers to a model that has been trained with a large amount of data and is capable of identifying and labeling reflective interference regions and sunscreen material regions in UV images.

[0074] Specifically, the UV image acquired in step S10 is input into a pre-trained image segmentation model. The model analyzes the pixel features in the image to identify areas covered by sunscreen and marks them as "sunscreen material markers," while also identifying reflective areas caused by skin oil or other factors and marking them as "reflective interference markers."

[0075] Optionally, in this embodiment, the step of determining the effective sun protection area based on the reflective interference mark and the sunscreen substance mark in the target image includes steps S21 to S22:

[0076] Step S21: Determine a matching weight value based on the reflectivity and area information of the reflective interference mark, and associate the reflective interference mark in the target image with the corresponding weight value.

[0077] Step S22: In the target image at different angles, determine the weighted sum of the weight values ​​corresponding to the reflective interference markers in the same physical region.

[0078] Step S23: When the weighted sum is less than a preset threshold, the physical area is determined as the effective sun protection area.

[0079] Specifically, reflective interference markers refer to markers identified as reflective areas in a target image. Weight values ​​are numerical values ​​assigned to these markers based on their influence at different angles, used to quantify the impact of reflective interference. Weighted summation involves summing the weight values ​​of reflective interference markers from different angles within the same physical area to comprehensively assess the degree of reflective interference in that area. The preset threshold is a value pre-set based on the actual application scenario and sun protection detection requirements, used to determine whether a physical area is affected by reflective interference. The effective sun protection area refers to the area in the target image where reflective interference is minimal, accurately reflecting the coverage of sun protection materials.

[0080] In this embodiment, the smear detection system first assigns weight values ​​to reflective interference marks in the target image. The weight values ​​can be determined based on factors such as reflectivity and area size. For example, areas with higher reflectivity can be assigned larger weight values. Then, the smear detection system identifies the same physical region in the target image from different angles and calculates a weighted sum of the reflective interference marks in that region. Specifically, the calculation method can be to add the weight values ​​of the reflective interference marks in that region at each angle. Next, the calculated weighted sum is compared with a preset threshold. If the weighted sum is less than the preset threshold, it indicates that the reflective interference in that physical region is relatively small, and it can be identified as an effective sun protection area. The preset threshold can be adjusted based on experimental data and actual needs. For example, if the preset threshold is 1.5, and the weighted sum of a certain physical region is 1.0, then that region is identified as an effective sun protection area. By adding weight values ​​to reflective interference marks and calculating the weighted sum of the same physical region at different angles, effective sun protection areas can be determined more accurately, thereby improving the accuracy and reliability of sunscreen smear detection.

[0081] Step S30: Determine the effective sun protection area based on the reflective interference markers and sunscreen substance markers in the target image.

[0082] In this embodiment, the effective sun protection area refers to the actual sun protection area in the target image that is marked as being covered by sun protection material and is not affected by reflective interference.

[0083] Specifically, the application detection system analyzes the marking information in the target image, eliminates the areas corresponding to reflective interference markings, and retains only the areas corresponding to sunscreen material markings, thereby determining the effective sun protection area.

[0084] Step S40: Map the effective sun protection area to the facial reference coordinate system, and calculate the area ratio of the effective sun protection area relative to the total facial area.

[0085] In this embodiment, the facial reference coordinate system is a preset coordinate system used to locate and quantify the position and area of ​​various facial regions. Area ratio refers to the ratio of the area of ​​the effective sun protection zone to the total facial area, used to quantify the coverage rate of sunscreen application.

[0086] Specifically, the application detection system maps the identified effective sun protection area onto the facial reference coordinate system. Through coordinate positioning and area calculation algorithms, it calculates the area of ​​the effective sun protection area and compares it with the total area of ​​the face to obtain the area ratio.

[0087] As an optional implementation, a pre-stored standard facial model is first invoked. This model contains detailed facial structure data, such as the length, width, and depth of the face, as well as the positional information of key feature points. Then, a computer vision algorithm is used to register the standard facial model with the user's current facial image, ensuring that the standard facial coordinate system is accurately mapped onto the user's facial image. Next, a mapping algorithm in computer vision is used to match the determined effective sun protection area with the acquired facial reference coordinate system.

[0088] After matching, the outline of the effective sun protection area is extracted. Then, based on the facial structural features and coordinate system orientation, each pixel or feature point in this area is converted into a corresponding 3D coordinate value in the facial reference coordinate system. This can be achieved by constructing a transformation matrix from image space to coordinate system space. Next, the coordinate information of the effective sun protection area in the facial reference coordinate system is projected to obtain its projected outline on a 2D plane. The area enclosed by this projected outline is calculated using polygon area calculation formulas or integration methods, thus obtaining the total area of ​​the entire effective sun protection area. The total area of ​​the facial region can be obtained through a standard facial model or pre-stored facial area data. Finally, the area of ​​the effective sun protection area calculated in the previous step is divided by the obtained total facial region area to obtain the area percentage.

[0089] Step S50: Generate the detection result of sunscreen application based on the area ratio.

[0090] In this embodiment, the sunscreen application test result refers to the final evaluation report generated based on the area ratio, used to inform the user whether the sunscreen application effect has met the standard. The test result is not limited to forms such as scores, stars, comments, percentage of application completeness, or representation of the application area on the face.

[0091] Specifically, the application detection system generates a detection result based on the area ratio. If the area ratio reaches a preset threshold (e.g., 80%), the sunscreen application is considered effective; if it is below the threshold, the user is prompted to reapply sunscreen.

[0092] Optionally, in this embodiment, after the step of generating the detection result of sunscreen application based on the area ratio, steps S51 to S52 are further included:

[0093] Step S51: Determine the user's application effect based on the comparison results of the detection results and historical detection data.

[0094] Step S52: When the application effect is that the area ratio of the effective sun protection area decreases, application improvement information is generated based on the historical detection data.

[0095] Step S53: Feedback the application improvement information and the sunscreen product usage suggestions to the corresponding user interface.

[0096] Specifically, the test results refer to the assessment information about the user's sunscreen application based on the area ratio, while historical test data refers to the relevant data records obtained from the user's previous sunscreen application tests. Application improvement information refers to suggestions provided to the user on how to improve their sunscreen application method based on the differences between the current test results and historical data. Sunscreen product usage suggestions refer to recommending suitable sunscreen products and their application methods to the user based on their sun protection needs and test results. The user interface refers to the interface through which the user interacts with the application detection system, used to display the test results and related information. By comparing the test results with historical data, generating application improvement information and sunscreen product usage suggestions, and feeding them back to the user interface, personalized sun protection guidance can be provided to users, helping them to better protect themselves from the sun and improve its effectiveness.

[0097] The application detection system first compares and analyzes the current test results with the user's historical test data. By comparing changes in the area coverage at different time points, it determines whether the user's sunscreen application effectiveness has improved or decreased. If the test results indicate that the current sunscreen application effectiveness is poor, the application detection system will generate targeted application improvement information based on the user's skin type, environmental factors (such as UV intensity, duration of outdoor activities, etc.), and the distribution of effective sun-protected areas in historical data. For example, it may suggest areas where sunscreen application needs to be strengthened, or recommend adjusting the thickness and evenness of the application. Simultaneously, the application detection system will link to recommended sunscreen products, selecting suitable sunscreens from its database based on the user's skin type (such as dry, oily, sensitive, etc.) and sun protection needs, and providing detailed usage instructions, such as application amount and application intervals.

[0098] The application detection system integrates the updated sunscreen distribution map and application improvement information into the user interface. The sunscreen distribution map uses different colors or markers to visually display effective sunscreen areas and areas without sunscreen, allowing users to easily understand their sunscreen application status. Application improvement information is presented in text or graphic form on the user interface, clearly conveying how to improve sunscreen application. For example, on the sunscreen distribution map, green can represent effective sunscreen areas and red can represent areas without sunscreen, while application improvement information is displayed at the bottom of the screen, such as "We recommend that you apply more sunscreen to your forehead and bridge of your nose to improve sun protection." Users can view detailed information through interactive devices such as touchscreens and follow the system's recommended sunscreen product usage suggestions.

[0099] For example, assuming the user is facing the UV imaging device during detection, the device first acquires a UV image from the front, then rotates to the side and acquires another UV image. These two images record the UV reflection of the user's face at different angles. In the UV image, some areas show lower UV reflectivity due to the user applying sunscreen; the model marks these as sunscreen areas. Other areas reflect UV rays due to skin oils; the model marks these as reflective interference areas. In the final target image, the sunscreen areas and reflective interference areas are clearly distinguished. A portion of the target image is marked as sunscreen, but a small portion is also marked as reflective interference. The application detection system uses logical operations to remove reflective interference areas from the sunscreen areas. The final effective sunscreen area is the area covered by the sunscreen after removing interference. Assuming the total facial area is 100 square centimeters and the effective sunscreen area is 70 square centimeters, the area ratio is 70%. This ratio reflects the coverage rate of sunscreen application on the user's face. If the preset threshold is 80% and the calculated area ratio is 70%, the detection result indicates that the user needs to apply sunscreen to the areas where no sunscreen has been applied.

[0100] In the technical solution provided in this embodiment, UV images of the user's face at at least two preset angles are acquired using an ultraviolet imaging device. These UV images are then input into a pre-trained image segmentation model to generate a target image containing reflective interference markers and sunscreen substance markers. Based on these markers, an effective sun protection area is determined. This effective sun protection area is then mapped to a facial reference coordinate system, and the area ratio of the effective sun protection area relative to the total facial area is calculated. Finally, a detection result for sunscreen application is generated based on this area ratio. This embodiment acquires UV images using an ultraviolet imaging device, generates target images using a pre-trained image segmentation model, determines effective sun protection areas using reflective interference markers and sunscreen substance markers, and finally evaluates the sunscreen application effect based on the area ratio. This method can accurately and quickly detect the coverage of the user's sunscreen application, thereby improving the detection effect of sunscreen application.

[0101] Example 2

[0102] Based on the same inventive concept, this application also provides a second embodiment, referring to... Figure 2 , Figure 2 This is a schematic flowchart of the second embodiment of the sunscreen application detection method of this application. In this embodiment, after the step of generating the detection result of sunscreen application based on the area ratio, steps S60 to S70 are further included:

[0103] Step S60: Obtain a sun protection coverage distribution map containing the detection results.

[0104] Step S70: In the sun protection coverage distribution map, the effective sun protection coverage area and the uncovered area are rendered with a first visualization color and a second visualization color, respectively.

[0105] Step S80: Render the updated sun protection coverage distribution map onto the corresponding interface for display.

[0106] In this embodiment, the sunscreen distribution map refers to an image showing the distribution of sunscreen on the user's face. The updated sunscreen distribution map refers to an image that has been re-labeled and displayed after current detection and analysis, illustrating the sunscreen coverage on the user's face in graphic form. It includes sunscreen application detection results generated based on area proportions, intuitively reflecting the distribution of effective sunscreen areas and uncovered areas. The first and second visualization colors are two different colors used to distinguish between effective sunscreen coverage areas and uncovered areas in the sunscreen coverage distribution map. Through color differentiation, users can more intuitively understand the coverage of sunscreen on their face.

[0107] Specifically, the application detection system uses computer vision algorithms to convert the coordinates of the effective sun protection area in the facial reference coordinate system into image pixels, generating a sun protection coverage distribution map. Then, based on the area percentage data from the detection results, the sun protection coverage distribution map is optimized using the first and second visualization colors. Finally, the sun protection coverage distribution map, labeled with the first and second visualization colors, is rendered into the application detection system and displayed on the corresponding interface, allowing users to more intuitively view the sun protection application effect.

[0108] As an optional implementation, the smear detection system uses graphics processing software to draw a sun protection coverage distribution map based on the coordinates and area information of the effective sun protection area. During the drawing process, different colors (i.e., a first visual color and a second visual color) can be used to distinguish between effective sun protection areas and uncovered areas so that users can clearly identify them.

[0109] Finally, the application detection system renders the effective sun protection coverage area and the uncovered area in the sun protection coverage distribution map as the first visual color and the second visual color, respectively, according to the pre-set color rules.

[0110] Optionally, in this embodiment, after the step of obtaining the sun protection coverage distribution map including the detection results, steps S61 to S63 are further included:

[0111] Step S61: Determine the coverage rate of key areas based on the size of the uncovered area, wherein the coverage rate is the ratio of the area of ​​the uncovered area to the total facial area.

[0112] Step S62: When the coverage rate of the area corresponding to the key part is detected to be lower than the threshold, a key repainting reminder is triggered.

[0113] Step S63: Feedback the key touch-up reminder to the user interface.

[0114] Specifically, uncovered areas refer to facial areas on the sun protection coverage distribution map where no sunscreen has been applied. Key areas refer to areas of the face with higher sun protection needs, such as the forehead, bridge of the nose, and cheekbones, as these areas are typically more susceptible to direct UV radiation. Coverage rate refers to the proportion of uncovered areas within key areas to the total area of ​​that area, used to assess the sun protection status of these areas. The threshold value is a threshold set based on sun protection standards or experience, used to determine whether the coverage rate of key areas has reached a level requiring a reminder to reapply sunscreen. Key area reapplication reminders are reminders sent to users when the coverage rate of key areas falls below the threshold value, prompting them to reapply sunscreen to these areas.

[0115] In this embodiment, the application detection system first extracts the area information of uncovered areas from the sunscreen coverage distribution map using an image processing algorithm. Then, by combining the key area information in the facial reference coordinate system, it determines the area of ​​uncovered areas for each key area. Finally, based on the area of ​​uncovered areas and the total area of ​​key areas, it calculates the coverage rate of the key areas. The specific calculation formula is: Coverage rate = (Area of ​​uncovered areas ÷ Total area of ​​key areas) × 100%.

[0116] Next, the calculated coverage rate of each key area is compared with a preset threshold. If the coverage rate of a key area is lower than the threshold, the system triggers a reminder to reapply sunscreen. The threshold can be set according to different sun protection needs and standards. For example, for daily sun protection, the threshold can be set to 10%, while for sun protection during prolonged outdoor activities, the threshold can be set to 5%. Finally, the triggered reminder information is displayed through the user interface. The reminder information can be presented in various forms such as text, sound, and images to ensure that the user can clearly receive the reminder. For example, a text reminder such as "Your forehead and bridge of the nose are not covered with sunscreen, please reapply it in time" can be displayed on the user interface screen, accompanied by an audio prompt to attract the user's attention. The above scheme determines the coverage rate of key areas based on the size of the uncovered area, and triggers a reminder to reapply sunscreen when the coverage rate is lower than the threshold, feeding the reminder back to the user interface. This timely reminder can prompt users to reapply sunscreen to key areas, improve sun protection effectiveness, and effectively protect the skin from UV damage.

[0117] In the technical solution provided in this embodiment, by generating a sun protection coverage distribution map and rendering the effective sun protection coverage area and the uncovered area with different visual colors, the coverage of sun protection substances on the user's face can be intuitively displayed, helping the user to better understand their sun protection effect and thus reapply in time to improve the sun protection effect.

[0118] Example 3

[0119] Based on the same inventive concept, this application also provides a third embodiment, referring to... Figure 3 , Figure 3 This is a flowchart illustrating the third embodiment of the sunscreen application detection method of this application. In this embodiment, after the step of acquiring UV images of the user's face at at least two preset angles using an ultraviolet imaging device, steps S90 to S120 are further included:

[0120] Step S90: Simultaneously capture color images of the user's face at at least two preset angles using a color camera.

[0121] In this embodiment, the color images of the user's face captured by a color camera (such as a regular RGB camera) at different angles, reflecting details such as color and texture, can present the natural appearance of the user's face, including information such as skin tone and feature points that are different from UV images.

[0122] Specifically, while acquiring UV images using an ultraviolet imaging device, a color camera simultaneously captures multi-angle color images of the user's face. It is crucial to ensure that the acquisition time, location, and other parameters of the two sets of images (i.e., UV images and color images) are consistent to enable effective registration and fusion later. For example, the ultraviolet imaging device and the color camera are integrated into the same device and synchronously triggered through precise timing control, ensuring that both cameras capture images simultaneously the instant the user makes the same facial pose.

[0123] Step S100: Spatial registration is performed on the UV image and color image based on the feature point matching algorithm to generate the corrected UV image and color image.

[0124] In this embodiment, the feature point matching algorithm is a computer vision technique that establishes correspondences between images by identifying and matching feature points (such as key points and corner points) in the image. Spatial registration refers to the process of aligning images with different imaging methods or different perspectives to the same coordinate system, so that objects in the image correspond in spatial position.

[0125] Specifically, feature points are first extracted from both the UV and color images. For example, for the UV image, algorithms such as SURF (Speed-Up Robust Features) or SIFT (Scale-Invariant Feature Transform) can be used to detect and describe feature points; for the color image, the same algorithms or other feature extraction algorithms suitable for color images (such as the ORB algorithm) are used. After the feature points are extracted, their matching relationship between the two images is calculated to find corresponding point pairs. Then, based on these matching feature point pairs, the transformation matrix is ​​estimated. On this basis, geometric correction is performed on the UV and color images, such as rotation, scaling, and translation, to align the spatial coordinate systems of the two images, generating the corrected UV and color images.

[0126] As an optional implementation, the step of spatially registering the UV image and color image based on the feature point matching algorithm to generate the corrected UV image and color image includes:

[0127] Extract feature point sets from the UV image and the color image, and generate feature descriptors for the feature point sets; determine target feature points that match in the feature point sets based on the feature descriptors; align the spatial coordinate systems of the UV image and the color image based on the target feature points to generate corrected UV and color images.

[0128] Specifically, feature points refer to points in an image that have obvious characteristics and are easily identifiable and distinguishable, such as corner points, edge points, and texture points. A feature point set refers to the set of all feature points detected in an image. A feature descriptor is a vector that quantifies and describes the local image information surrounding a feature point, used to characterize the unique properties of the feature point. Feature point matching refers to finding corresponding feature point pairs, i.e., target feature points, in the feature point sets of two images based on the similarity of their feature descriptors. Target feature points are feature points representing the same physical location in different images; matching establishes a correspondence between images. Spatial coordinate system alignment refers to using geometric transformations to make the pixels of two images correspond in spatial location, i.e., establishing a pixel coordinate mapping relationship for the same physical scene in different images. A corrected image refers to an image that has undergone geometric transformations to eliminate the influence of factors such as differences in imaging equipment and shooting angle deviations.

[0129] The smear detection system performs feature point detection on both UV and color images. Various feature point detection algorithms, such as the Harris corner detection algorithm and the FAST feature point detection algorithm, can be used to extract a set of feature points from the image. Then, for each feature point, its feature descriptor is calculated. Based on the image grayscale, texture, and other information surrounding the feature point, a unique and discriminative feature descriptor vector is generated.

[0130] Next, the feature descriptors of the UV image and the color image are compared to calculate their similarity. Various similarity metrics can be used, such as Euclidean distance, Hamming distance, and cosine similarity. Generally, the smaller the distance or the higher the similarity, the more closely the feature points match. Based on a set matching threshold, feature point pairs with similarity higher than the threshold are selected as the target feature points for matching. For example, the nearest neighbor distance ratio method can be used: for each feature point, the ratio of its distance to its nearest neighbor and second nearest neighbor feature points is calculated; if the ratio is less than a certain threshold (e.g., 0.7), the feature point is considered a successful match.

[0131] Finally, based on the matched target feature points, the geometric transformation parameters between the UV image and the color image are determined. Various methods can be used, such as homography matrix estimation and affine transformation matrix estimation. Taking homography matrix estimation as an example, a 3×3 homography matrix is ​​solved using a preset algorithm with at least four pairs of target feature points. Then, based on the obtained homography matrix, a perspective transformation is performed on the UV image to align it with the spatial coordinate system of the color image. The transformed UV image and color image are the corrected images.

[0132] By extracting feature point sets and feature descriptors from UV and color images, the target feature points for matching are accurately determined. Based on these target feature points, the spatial coordinate systems of the UV and color images are aligned to generate a corrected image. This effectively corrects the image, thereby improving the reliability and accuracy of sunscreen application detection methods.

[0133] Step S110: Map the violet spectrum of the corrected UV image to the color spectrum range to generate a color-corrected UV image.

[0134] In this embodiment, the violet spectral mapping in the UV image refers to converting image information that is originally in the ultraviolet spectral range (usually invisible) into a color spectral range in the visible spectrum through color conversion technology. This allows information that is originally invisible or difficult to identify in the UV image (such as details of sunscreen substances, skin texture, etc.) to be displayed in color tones.

[0135] Specifically, the smear detection system performs color processing on the corrected UV image. First, it analyzes the corresponding spectral response in the UV image to determine the pixel values ​​associated with the violet spectrum. Then, using a color gamut mapping algorithm, these violet spectrum pixel values ​​are converted to pixel values ​​within the color spectrum range; for example, violet (RGB value approximately 128,0,128) is converted to red (RGB value 255,0,0) or a warm red family. This process can be achieved using the color space conversion function in image processing software or through a dedicated spectral mapping algorithm library.

[0136] Step S120: Perform pixel overlay and fusion of the color-corrected UV image and the corrected color image to generate a composite image and output the composite image through the display interface.

[0137] In this embodiment, pixel overlay fusion refers to the superposition and merging of two images with the same spatial dimensions and coordinates at the pixel level to generate a new composite image. Pixel overlay fusion of color-corrected UV images and color images can achieve an organic combination of two different types of information, allowing users to simultaneously observe the distribution of sunscreen substances and the natural color structure of the face.

[0138] Specifically, first, ensure that the color-corrected UV image and the corrected color image have been spatially registered and have the same resolution and size. Then, process each pair of corresponding pixels according to certain fusion rules. For example, a weighted average of the pixel values ​​of the two images can be used. In terms of weighting, appropriate weights might be assigned to the color image (such as the normal color of skin, hair, and other external features), while higher weights might be assigned to the color-corrected UV image (such as the prominent red areas of sunscreen), so that the information of interest can be highlighted in the composite image. Alternatively, a region-based fusion method can be used, identifying different regions in the image (such as skin regions, eye regions, etc.) through a segmentation algorithm, and then setting different fusion strategies for each region. After calculating the superposition value of each pair of pixels, a composite image can be obtained. Once the two images are effectively fused, the composite image can be transmitted to a corresponding display interface, such as a computer screen or mobile phone display, for users to view.

[0139] In the technical solution provided in this embodiment, through a series of steps such as synchronous acquisition of color images, spatial registration, spectral mapping, and pixel overlay fusion, the intuitive and accurate detection and display of the user's facial sunscreen application is achieved, providing users with a more convenient and efficient way to evaluate the sunscreen effect, and helping users to better manage sunscreen and protect their skin.

[0140] Since the system described in the embodiments of this application is a system used to implement the methods of the embodiments of this application, those skilled in the art can understand the specific structure and variations of the system based on the methods described in the embodiments of this application, and therefore will not be described in detail here. All systems used in the methods of the embodiments of this application fall within the scope of protection of this application.

[0141] This application provides a sunscreen application detection device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the sunscreen application detection method in the first embodiment described above.

[0142] The following is for reference. Figure 4The diagram illustrates a structural schematic of a sunscreen application detection device suitable for implementing embodiments of this application. The sunscreen application detection device in this application may include, but is not limited to, mobile terminals such as smart makeup mirrors, mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 4 The sunscreen application detection device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of this application.

[0143] like Figure 4 As shown, the sunscreen application detection device may include a processing unit 1001 (e.g., a core processor, graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the sunscreen application detection device. The processing unit 1001, the ROM 1002, and the RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the sunscreen application detection device to communicate wirelessly or wiredly with other devices to exchange data. Although a sunscreen application detection device with various systems is shown in the figure, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems may be implemented alternatively.

[0144] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from read-only memory 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0145] The sunscreen application detection device provided in this application, employing the sunscreen application detection method described in the above embodiments, can solve the technical problem of poor detection effect of traditional solutions for sunscreen application. Compared with the prior art, the beneficial effects of the sunscreen application detection device provided in this application are the same as those of the sunscreen application detection method provided in the above embodiments, and other technical features of the sunscreen application detection device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0146] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0147] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0148] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to perform the sunscreen application detection method in the above embodiments.

[0149] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, radio frequency (RF), etc., or any suitable combination thereof.

[0150] The aforementioned computer-readable storage medium may be included in the sunscreen application detection device; or it may exist independently and not assembled into the sunscreen application detection device.

[0151] The aforementioned computer-readable storage medium carries one or more programs that, when executed by the sunscreen application detection device, cause the sunscreen application detection device to: acquire UV images of a user's face at at least two preset angles using an ultraviolet imaging device; input each of the UV images into a pre-trained image segmentation model to generate a target image containing reflective interference markers and sunscreen substance markers; determine an effective sunscreen area based on the reflective interference markers and sunscreen substance markers in the target image; map the effective sunscreen area to a facial reference coordinate system and calculate the area ratio of the effective sunscreen area relative to the total facial area; and generate a sunscreen application detection result based on the area ratio.

[0152] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0153] 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. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing 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 the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may 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.

[0154] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0155] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described sunscreen application detection method, which can solve the technical problem of poor detection effect of traditional solutions for sunscreen application. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the sunscreen application detection method provided in the above embodiments, and will not be repeated here.

[0156] This application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the sunscreen application detection method described above.

[0157] The computer program product provided in this application can solve the technical problem of poor detection effect of traditional solutions for sunscreen application. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the sunscreen application detection method provided in the above embodiments, and will not be repeated here.

[0158] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent scope of this application.

Claims

1. A method for detecting sunscreen application, characterized in that, The sunscreen application detection method includes the following steps: The ultraviolet imaging device acquires UV images of the user's face at at least two preset angles. Real-time detection of current facial posture information; Based on the facial posture information, the deviation value between the user's face and the ultraviolet imaging device is determined; The acquisition parameters of the ultraviolet imaging device are adjusted according to the deviation value to adapt to the current lighting and human posture conditions. The acquisition parameters include the exposure time. Using the adjusted ultraviolet imaging device, the step of acquiring UV images of the user's face at at least two preset angles via the ultraviolet imaging device is performed again; Each of the UV images is input into a pre-trained image segmentation model to generate a target image containing reflective interference markers and sunscreen substance markers. The pre-trained image segmentation model is used to segment the UV image into multiple regions, identify and mark reflective interference regions and sunscreen substance regions in the UV image, and output a target image containing reflective interference markers and sunscreen substance markers. The reflective interference markers represent reflective regions caused by skin oil or other factors, and the sunscreen substance markers represent regions covered by sunscreen substances. The effective sun protection area is determined based on the reflective interference markers and sunscreen substance markers in the target image; The effective sun protection area is mapped to the facial reference coordinate system, and the area ratio of the effective sun protection area relative to the total facial area is calculated. The detection results of sunscreen application are generated based on the area ratio. The step of determining the effective sun protection area based on the reflective interference markers and the sunscreen substance markers in the target image includes: A matching weight value is determined based on the reflectivity and area information of the reflective interference mark, and the reflective interference mark in the target image is associated with the corresponding weight value. The weight value is used to quantify the influence of reflective interference. The weight value corresponding to the reflective interference mark with higher reflectivity is greater than the weight value corresponding to the reflective interference mark with lower reflectivity. In the target image from different angles, a weighted sum of the weight values ​​corresponding to the reflective interference markers in the same physical region is determined, and the weighted sum is used to evaluate the degree of reflective interference in the region; When the weighted sum is less than a preset threshold, the physical area is determined as the effective sun protection area. The effective sun protection area is the actual sun protection area in the target image that is marked as being covered by sun protection material and is not affected by reflective interference.

2. The method as described in claim 1, characterized in that, Following the step of generating the sunscreen application detection result based on the area ratio, the method further includes: The application effect of the product is determined based on the comparison between the test results and historical test data; When the application effect indicates that the area of ​​the effective sun protection zone has decreased, application improvement information is generated based on the historical detection data. Based on the user's skin type information, a matching sunscreen product and corresponding sunscreen product usage recommendations are determined; The application improvement information and sunscreen product usage suggestions are fed back to the corresponding user interface.

3. The method as described in claim 1, characterized in that, Following the step of generating the sunscreen application detection result based on the area ratio, the method further includes: Obtain a sun protection coverage distribution map that includes the detection results; In the sun protection coverage distribution map, the effective sun protection coverage area and the uncovered area are rendered with the first visualization color and the second visualization color, respectively; The updated sun protection coverage distribution map will be rendered and displayed on the corresponding interface.

4. The method as described in claim 3, characterized in that, After the step of obtaining the sun protection coverage distribution map containing the detection results, the method further includes: The coverage rate of key areas is determined based on the area of ​​the effective sun protection coverage area, wherein the coverage rate is the ratio of the area of ​​the effective sun protection coverage area in the key areas to the total area of ​​the key areas; When the coverage rate of the area corresponding to the key area is detected to be lower than the threshold, a key repainting reminder is triggered; The reminder to repaint key areas is displayed on the user interface.

5. The method as described in claim 1, characterized in that, Following the step of acquiring UV images of the user's face at at least two preset angles using an ultraviolet imaging device, the method further includes: The system simultaneously captures color images of the user's face from at least two preset angles using a color camera. The UV image and color image are spatially registered based on the feature point matching algorithm to generate the corrected UV image and color image. The violet spectrum of the corrected UV image is mapped to the color spectrum range to generate a color-corrected UV image; The color-corrected UV image and the corrected color image are pixel-by-pixel superimposed and fused to generate a composite image, which is then output through a display interface.

6. The method as described in claim 5, characterized in that, The step of spatially registering the UV image and color image based on the feature point matching algorithm to generate the corrected UV image and color image includes: Extract the feature point set from the UV image and the color image, and generate a feature descriptor for the feature point set; The target feature points in the feature point set are determined based on the feature descriptor; The UV image and the color image are aligned in spatial coordinate system based on the target feature points to generate a corrected UV image and a color image.

7. A sunscreen application detection device, characterized in that, The sunscreen application detection device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the sunscreen application detection method as described in any one of claims 1 to 6.

8. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, it implements the steps of the sunscreen application detection method as described in any one of claims 1 to 6.

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