Vehicle, data processing method and device thereof, terminal equipment and storage medium

Abstract

The invention discloses a vehicle, a data processing method and device thereof, terminal equipment and a storage medium, and relates to the technical field of vehicles. The method comprises the following steps: in response to a voice instruction, generating an original picture and a draft picture of the original picture according to the voice instruction and a preset picture generation model; determining a target color of each region of the line draft picture according to the original picture and the line draft picture; determining a target color set according to the target color of each region of the line draft picture; displaying the original picture, the line draft picture and the target color set, responding to the color filling instruction of each region of the line draft picture, and performing color filling on each region of the line draft picture according to the color filling instruction of each region of the line draft picture and colors in the target color set to obtain a color filled picture; and scoring the color-filled picture based on the target color of each region of the line draft picture to determine a target score value of the color-filled picture. Therefore, entertainment contents are provided for children, the distraction risk of a driver is reduced, and the driving safety is improved.

Description

Technical Field

[0001] This application relates to the technical field of vehicles, and in particular, to a data processing method for a vehicle, a data processing device for a vehicle, a computer-readable storage medium, a terminal device, and a vehicle. Background Art

[0002] When a vehicle travels for a long time, young children in the vehicle will interfere with the driver's driving and increase the driving risk. Summary of the Invention

[0003] This application aims to at least solve one of the technical problems in the related art to some extent. For this purpose, the first object of this application is to propose a data processing method for a vehicle, the method including: responding to a voice command, generating an original picture and a line drawing picture of the original picture according to the voice command and a preset picture generation model; determining the target color of each area of the line drawing picture according to the original picture and the line drawing picture; determining a target color set according to the target color of each area of the line drawing picture; displaying the original picture, the line drawing picture, and the target color set, and responding to a coloring command for each area of the line drawing picture, and coloring each area of the line drawing picture according to the coloring command for each area of the line drawing picture and the colors in the target color set to obtain a colored picture; scoring the colored picture based on the target color of each area of the line drawing picture to determine the target score value of the colored picture. In this way, young children in the vehicle can control the in-vehicle computer to generate the original picture, the line drawing picture, and the target color set and perform coloring by issuing a voice command, providing rich entertainment content for children, reducing the driving burden and distraction risk of the driver, so as to improve driving safety; it can also enhance the user's satisfaction and loyalty to the in-vehicle computer system, while enriching the system functions and realizing a diversified and personalized riding experience.

[0004] The second object of this application is to propose a data processing device for a vehicle.

[0005] The third object of this application is to propose a computer-readable storage medium.

[0006] The fourth object of this application is to propose a terminal device.

[0007] The fifth object of this application is to propose a terminal device.

[0008] To achieve the above object, an embodiment of the first aspect of the present application provides a method for processing vehicle data, the method including: responding to a voice instruction, generating an original picture and a line drawing picture of the original picture according to the voice instruction and a preset picture generation model; determining the target color of each area of the line drawing picture according to the original picture and the line drawing picture; determining a target color set according to the target color of each area of the line drawing picture; displaying the original picture, the line drawing picture and the target color set, and responding to a coloring instruction for each area of the line drawing picture, coloring each area of the line drawing picture according to the coloring instruction for each area of the line drawing picture and the colors in the target color set to obtain a colored picture; scoring the colored picture based on the target color of each area of the line drawing picture to determine a target score value of the colored picture.

[0009] According to an embodiment of the present application, scoring the colored picture based on the target color of each area of the line drawing picture to determine a target score value of the colored picture includes: calculating a similarity value between the target color of each area of the line drawing picture and the coloring color of the corresponding area; determining a score value of each area of the colored picture according to a preset similarity interval where the similarity value is located; determining the target score value of the colored picture based on the sum value of the score values of each area of the colored picture.

[0010] According to an embodiment of the present application, determining the target color of each area of the line drawing picture according to the original picture and the line drawing picture includes: extracting each area of the line drawing picture by using a preset contour extraction algorithm; assigning a corresponding mask to each area of the line drawing picture; performing a per-pixel multiplication operation on the mask of each area of the line drawing picture and the original picture to determine the pixel value of each area of the line drawing picture; performing color analysis on the pixel value of each area of the line drawing picture to determine the target color of each area of the line drawing picture.

[0011] According to an embodiment of the present application, determining the target color set according to the target color of each area of the line drawing picture includes: calculating a similarity value between each preset color in a preset color set and the target color of each area of the line drawing picture; determining a first color set and a second color set based on the similarity value; taking the union of the first color set and the second color set as the target color set.

[0012] According to an embodiment of the present application, determining the first color set and the second color set based on the similarity value includes: taking the preset colors corresponding to the similarity values greater than a first preset similarity value threshold as the first color set; taking the preset colors corresponding to the similarity values less than a second preset similarity value threshold as the second color set; wherein, the first preset similarity value threshold is greater than the second preset similarity value threshold, and the number of colors in the first color set is greater than the number of colors in the second color set.

[0013] According to an embodiment of the present application, generating an original image and a line drawing image of the original image according to a voice command and a preset image generation model includes: converting the voice command into a text command; performing a matching process on the text command and a preset word set to obtain a matching result; in the case where the matching result is inconsistent, using the text command as an input to the preset image generation model to output the original image and the line drawing image of the original image.

[0014] To achieve the above object, an embodiment of the second aspect of the present application provides a data processing device for a vehicle. The device includes: a generation module, configured to respond to a voice command and generate an original image and a line drawing image of the original image according to the voice command and a preset image generation model; a first determination module, configured to determine a target color for each area of the line drawing image according to the original image and the line drawing image; a second determination module, configured to determine a target color set according to the target color of each area of the line drawing image; a coloring module, configured to display the original image, the line drawing image, and the target color set, and respond to a coloring command for each area of the line drawing image, and color each area of the line drawing image according to the coloring command for each area of the line drawing image and the color in the target color set to obtain a colored image; a third determination module, configured to score the colored image based on the target color of each area of the line drawing image to determine a target score value of the colored image.

[0015] To achieve the above object, an embodiment of the third aspect of the present application provides a computer-readable storage medium, on which a data processing program for a vehicle is stored. When the data processing program for the vehicle is executed by a processor, the foregoing data processing method for the vehicle is implemented.

[0016] To achieve the above object, an embodiment of the fourth aspect of the present application provides a terminal device, including a memory, a processor, and a data processing program for a vehicle stored on the memory and executable on the processor. When the processor executes the data processing program for the vehicle, the foregoing data processing method for the vehicle is implemented.

[0017] To achieve the above object, an embodiment of the fourth aspect of the present application provides a vehicle, including the foregoing terminal device.

[0018] A vehicle, a data processing method, apparatus, terminal device, and storage medium according to embodiments of the present application respond to a voice command, generate an original image and a line drawing image of the original image according to the voice command and a preset image generation model; determine the target color of each region of the line drawing image according to the original image and the line drawing image; determine a target color set according to the target color of each region of the line drawing image; display the original image, the line drawing image, and the target color set, and respond to a coloring command for each region of the line drawing image, and color each region of the line drawing image according to the coloring command for each region of the line drawing image and the colors in the target color set to obtain a colored image; score the colored image based on the target color of each region of the line drawing image to determine the target score value of the colored image. In this way, low-age children in the vehicle can control the vehicle-mounted computer to generate the original image, the line drawing image, and the target color set and perform coloring by issuing a voice command, providing rich entertainment content for children, reducing the driving burden and distraction risk of the driver, and improving driving safety; it can also enhance the user's satisfaction and loyalty to the vehicle-mounted computer system, while enriching the system functions and realizing a diversified and personalized riding experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a flowchart of a data processing method for a vehicle according to some embodiments of the present application;

[0020] Figure 2 is a block diagram of a data processing apparatus for a vehicle according to some embodiments of the present application;

[0021] Figure 3 is a block diagram of a terminal device according to some embodiments of the present application;

[0022] Figure 4 is a block diagram of a vehicle according to some embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] Embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application and should not be construed as limiting the present application.

[0024] The vehicle, its data processing method, apparatus, terminal device, and storage medium according to embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0025] Figure 1 is a flowchart of a data processing method for a vehicle according to some embodiments of the present application. Referring to Figure 1 , the data processing method for a vehicle according to embodiments of the present application may include the following steps:

[0026] S110, in response to a voice command, generate an original image and a line drawing image of the original image according to the voice command and a preset image generation model.

[0027] Specifically, the voice command issued by the user can be "generate a picture to play the coloring game". After the vehicle-mounted computer receives the voice command, it inputs the voice into the preset image generation model to output the original image and the line drawing image of the original image. Among them, the original image is a color image, and the line drawing image of the original image is a black-and-white image. The line drawing image only uses simple lines to outline the outline, shape and structure of the object.

[0028] It should be noted that the preset image generation model can directly generate the original image and the line drawing image of the original image based on the voice command, or only generate the original image, and determine the corresponding line drawing image by performing image processing on the original image. For example, first preprocess the original image (such as grayscale and denoising, etc.); then, use a preset edge detection algorithm (such as the Canny algorithm) to extract the outline and lines of the object in the original image; finally, create a pure white background image with the same size as the original image, and overlay the detected outline and lines on the white background image to generate the final line drawing image.

[0029] S120, determine the target color of each area of the line drawing image according to the original image and the line drawing image.

[0030] Specifically, after generating the original image and the corresponding line drawing image, a preset contour extraction algorithm can be used to extract each area of the line drawing image, and generate a corresponding mask for each area. Apply the mask corresponding to each area to extract the target color from the corresponding area of the original image; or the original image and the line drawing image can be input into a preset color determination model to output the target color of each area of the line drawing image.

[0031] It should be noted that the method for determining the target color of each area of the line drawing image can be determined according to the actual situation, and no specific restrictions are made here.

[0032] S130, determine a target color set according to the target color of each area of the line drawing image.

[0033] Specifically, a target color set needs to be formed according to the target color of each area of the line drawing image for coloring each area of the line drawing image. For example, integrate the target colors of each area of the line drawing image into a target color set; another example is to generate some colors with a small difference from the target color, and integrate the colors with a small difference and the target color into a target color set; another example is to generate some colors with a large difference from the target color, and integrate the colors with a small difference, the colors with a large difference and the target color into a target color set.

[0034] S140 displays the original image, the line drawing image, and the target color set, and responds to the coloring instruction for each area of the line drawing image, and colors each area of the line drawing image according to the coloring instruction for each area of the line drawing image and the colors in the target color set to obtain a colored image.

[0035] Specifically, after generating the original image, the line drawing image, and the target color set, the in-vehicle computer will control the in-vehicle terminal device to display the original image, the line drawing image, and the target color set. The user refers to the colors of each area of the original image and issues a coloring instruction based on the colors in the target color set. For example, the user can click on a color in the target color set and then click on an area in the line drawing image to color that area. After coloring each area of the line drawing image, a colored image is obtained.

[0036] S150 scores the colored image based on the target color of each area of the line drawing image to determine the target score value of the colored image.

[0037] Specifically, the score value of each area of the colored image can be determined by calculating the similarity value between the target color of each area of the line drawing image and the coloring color of the corresponding area. For example, if the similarity value between the target color of each area of the line drawing image and the coloring color of the corresponding area is relatively high, it is determined that the score value of the corresponding area of the colored image is relatively high; if the similarity value between the target color of each area of the line drawing image and the coloring color of the corresponding area is relatively low, it is determined that the score value of the corresponding area of the colored image is relatively low. The sum of the score values of each area of the colored image is the target score value of the colored image.

[0038] After determining the target score value of the colored image, a personified summary feedback can also be generated and sent to the vehicle terminal, and the target score value and evaluation are announced to the user through TTS (Text to Speech).

[0039] In this way, low-age children in the vehicle can control the in-vehicle computer to generate the original image, the line drawing image, and the target color set and perform coloring by issuing voice commands, providing rich entertainment content for children, reducing the driving burden and distraction risk of the driver, so as to improve driving safety; it can also enhance the user's satisfaction and loyalty to the in-vehicle computer system, and at the same time enrich the system functions to achieve a diversified and personalized riding experience.

[0040] It should be noted that after the vehicle-mounted device receives a voice command, it can also upload the voice command to the cloud. The cloud generates an original picture and a line drawing picture of the original picture based on the voice command, determines the target color and the set of target colors for each area of the line drawing picture according to the original picture and the line drawing picture, and then the cloud sends the original picture, the line drawing picture, and the set of target colors to the vehicle-mounted device. The vehicle-mounted device controls the in-vehicle terminal device to display the original picture, the line drawing picture, and the set of target colors. After the user finishes coloring, the colored picture is uploaded back to the cloud for scoring.

[0041] In some embodiments, the colored picture is scored based on the target color of each area of the line drawing picture to determine the target score value of the colored picture, including: calculating the similarity value between the target color of each area of the line drawing picture and the coloring color of the corresponding area; determining the score value of each area of the colored picture according to the preset similarity interval where the similarity value is located; and determining the target score value of the colored picture based on the sum value of the score values of each area of the colored picture.

[0042] Specifically, the target color of each area of the line drawing picture and the coloring color of each area of the colored picture can be converted to a preset color space (such as the CIELAB color space) to determine the corresponding color vectors, and the Euclidean distance between the target color vector and the corresponding coloring color vector is calculated. The similarity value between the target color of the area of the line drawing picture and the coloring color of the corresponding area is determined according to the Euclidean distance. For example, the similarity value can be determined by looking up the two-dimensional relationship mapping table between the Euclidean distance and the similarity value, where the two-dimensional relationship mapping table includes multiple Euclidean distances and the corresponding similarity values. Alternatively, a preset color similarity calculation model can also be used to calculate the similarity value between the target color of each area of the line drawing picture and the coloring color of the corresponding area. The specific calculation method is not specifically limited here.

[0043] After determining the similarity value between the target color of the area of the line drawing picture and the coloring color of the corresponding area, it is judged which preset similarity interval the similarity value is in, and the score value corresponding to the preset similarity interval is used as the score value of this area of the colored picture. In this way, the score value of each area of the colored picture can be determined, and at the same time, the sum value of the score values of each area of the colored picture is calculated, and this sum value is the target score value of the colored picture.

[0044] Exemplarily, the preset similarity interval can be calibrated according to the actual situation. For example, the preset similarity interval can include (100%, 80%], (80%, 50%], (50%, 30%] and (30%, 0%). Among them, the corresponding scoring value for (100%, 80%] is 4 points, the corresponding scoring value for (80%, 50%] is 3 points, the corresponding scoring value for (50%, 30%] is 2 points, the corresponding scoring value for (30%, 0%] is 1 point, the scoring value corresponding to the similarity value of 100% is 5 points, and the scoring value corresponding to the similarity value of 0% is 0 points.

[0045] Assume that the line drawing image includes Region 1 and Region 2. The target color of Region 1 of the line drawing image is positive red, and the target color of Region 2 of the line drawing image is positive blue. Correspondingly, the coloring image also includes Region 1 and Region 2.

[0046] When the filling color in Region 1 of the coloring image is light red and the filling color in Region 2 of the coloring image is orange, the calculated similarity value between positive red and light red is 75%, and the similarity value between positive blue and orange is 10%.

[0047] Since the similarity value of 75% is within (100%, 80%], it is determined that the scoring value of Region 1 of the coloring image is 4 points. Since the similarity value of 10% is within (30%, 0%], it is determined that the scoring value of Region 2 of the coloring image is 1 point. Then the target scoring value of the coloring image is 5 points.

[0048] In some embodiments, the target scoring value of the coloring image can also be determined by judging whether the color number of each region of the coloring image matches the color number of each region of the line drawing image.

[0049] Specifically, each color in the target color set is pre-numbered to determine the color number of each color in the target color set. Based on the color number of each color in the target color set and the color of each region of the line drawing image, the corresponding color number is assigned to each region of the line drawing image. After filling each region of the line drawing image with the color in the target color set, a coloring image is obtained. When the color number of the region in the coloring image matches the color number of the corresponding region in the line drawing image, it is determined that the scoring value of this region in the coloring image is the first preset value; when the color number of the region in the coloring image does not match the color number of the corresponding region in the line drawing image, it is determined that the scoring value of this region in the coloring image is the second preset value. An addition operation is performed on the scoring values of each region of the coloring image to obtain a sum value, and this sum value is the target scoring value of the coloring image. Among them, both the first preset value and the second preset value can be calibrated according to the actual situation, and no specific limitation is made here.

[0050] Exemplarily, assume that the target color set includes red, yellow, blue, and purple, the color number of red is 1, the color number of yellow is 2, the color number of blue is 3, and the color number of purple is 4. Assume that the line drawing image includes region 1 and region 2, the color of region 1 of the line drawing image is red, and the color of region 2 of the line drawing image is blue. Then, the color number of region 1 of the line drawing image is 1, and the color number of region 2 of the line drawing image is 3.

[0051] In the case where the filling color of region 1 of the colored image is red and the filling color of region 2 of the colored image is yellow, it can be determined that the filling color number of region 1 of the colored image is 1, and the filling color number of region 2 of the colored image is 2.

[0052] From this, it can be seen that the color number of region 1 of the line drawing image matches the filling color number of region 1 of the colored image, and it is determined that the scoring value of region 1 of the colored image is the first preset value (for example, 5 points). The color number of region 2 of the line drawing image does not match the filling color number of region 2 of the colored image, and it is determined that the scoring value of region 2 of the colored image is the second preset value (for example, 0 points). Then, the target scoring value of the colored image is 5 points.

[0053] In some embodiments, determining the target color of each region of the line drawing image according to the original image and the line drawing image includes: extracting each region of the line drawing image by using a preset contour extraction algorithm; assigning corresponding masks to each region of the line drawing image; performing a per-pixel multiplication operation on the masks of each region of the line drawing image and the original image to determine the pixel values of each region of the line drawing image; and performing color analysis on the pixel values of each region of the line drawing image to determine the target color of each region of the line drawing image.

[0054] Specifically, each region of the line drawing image can be extracted by using a preset contour extraction algorithm (such as the Sobel algorithm), and a corresponding mask is assigned to each region. The mask refers to a binary image with the same size as the original image, the pixel value of the target region is 1, and the pixel values of other regions are 0. Then, a per-pixel multiplication operation is performed on the mask of each region and the original image to extract the pixel values of the corresponding region. Finally, color analysis, such as K-Means clustering or color histogram, is performed on the extracted pixel values of the regions respectively to determine the color of each region.

[0055] In some embodiments, determining the target color set according to the target color of each region of the line drawing image includes: calculating the similarity value between each preset color in the preset color set and the target color of each region of the line drawing image; determining the first color set and the second color set based on the similarity value; and taking the union of the first color set and the second color set as the target color set.

[0056] Specifically, the preset color set includes all colors that can be perceived by the human vision. The calculation method of the similarity value between each preset color in the preset color set and the target color of each area of the line drawing image is the same as that between the target color of each area of the line drawing image and the filling color of the corresponding area, which will not be elaborated here. The preset color with a larger similarity to the target color is used as the first color set, the preset color with a larger difference from the target color is used as the second color set, and the union of the first color set and the second color set is used as the target color set.

[0057] In some embodiments, determining the first color set and the second color set based on the similarity value includes: using the preset color corresponding to the similarity value greater than the first preset similarity value threshold as the first color set; using the preset color corresponding to the similarity value less than the second preset similarity value threshold as the second color set; wherein, the first preset similarity value threshold is greater than the second preset similarity value threshold, and the number of colors in the first color set is greater than the number of colors in the second color set. The first preset similarity value threshold and the second preset similarity value threshold can be determined according to the actual situation and are not specifically limited here.

[0058] Specifically, the preset color with a larger similarity to the target color can be determined by comparing the similarity value with the first preset similarity value threshold. For example, the preset color corresponding to the similarity value greater than the first preset similarity value threshold is used as the preset color with a larger similarity to the target color. The preset color with a larger difference from the target color is determined by comparing the similarity value with the second preset similarity value threshold. For example, the preset color corresponding to the similarity value less than the second preset similarity value threshold is used as the preset color with a larger difference from the target color. To enhance the color recognition ability of young users, it is necessary to have more colors in the target color set that are similar to the target color, for example, accounting for 70% of the target color set, and fewer colors in the target color set that are different from the target color, for example, accounting for 30% of the target color set, that is, the number of colors in the first color set is greater than the number of colors in the second color set.

[0059] In this way, by setting colors similar to the target color in the target color set, it can promote the learning of basic concepts such as colors and shapes by young children and improve their cognitive ability.

[0060] In some embodiments, generating the original image and the line drawing image of the original image according to the voice command and the preset image generation model includes: converting the voice command into a text command; performing a matching process on the text command and the preset word set to obtain a matching result; in the case where the matching result is inconsistent, using the text command as the input of the preset image generation model to output the original image and the line drawing image of the original image.

[0061] Specifically, after the voice command issued by the user, the voice command is converted into a text command, and the text command is matched with a preset word set to determine whether the voice command issued by the user involves harmful content. When it is determined that the voice command issued by the user does not involve harmful content, an original picture and a line drawing picture of the original picture are generated.

[0062] Exemplarily, if the matching result between the text command and the preset word set is inconsistent, it indicates that the voice command issued by the user does not involve harmful content. Then, the text command can be used as the input of the preset picture generation model to output the original picture and the line drawing picture of the original picture. If the matching result between the text command and the preset word set is consistent, it indicates that the voice command issued by the user involves harmful content. Then, the text command cannot be input into the preset picture generation model, and a corresponding response is issued to prompt the user to issue a voice command again.

[0063] In this way, refusing to generate pictures containing harmful content can, to a certain extent, prevent young children from being affected by negative content, and further improve the reliability and user experience of the vehicle.

[0064] In summary, young children in the vehicle can issue voice commands to control the vehicle computer to generate original pictures, line drawing pictures and a target color set and perform coloring, providing rich entertainment content for children, reducing the driving burden and distraction risk of the driver, so as to improve driving safety; it can also enhance the user's satisfaction and loyalty to the vehicle computer system, while enriching the system functions and realizing a diverse and personalized riding experience.

[0065] Corresponding to the above embodiments, the present application also proposes a data processing device for a vehicle.

[0066] Referring to Figure 2 , the data processing device 200 of the vehicle includes: a generation module 210, a first determination module 220, a second determination module 230, a coloring module 240, and a third determination module 250.

[0067] Among them, the generation module 210 is used to respond to the voice command and generate an original picture and a line drawing picture of the original picture according to the voice command and the preset picture generation model. The first determination module 220 is used to determine the target color of each area of the line drawing picture according to the original picture and the line drawing picture. The second determination module 230 is used to determine the target color set according to the target color of each area of the line drawing picture. The coloring module 240 is used to display the original picture, the line drawing picture and the target color set, and respond to the coloring instruction of each area of the line drawing picture, and color each area of the line drawing picture according to the coloring instruction of each area of the line drawing picture and the color in the target color set to obtain a colored picture. The third determination module 250 is used to score the colored picture based on the target color of each area of the line drawing picture to determine the target score value of the colored picture.

[0068] According to an embodiment of the present application, the third determination module 250 is specifically configured to calculate a similarity value between the target color of each region of the line drawing image and the coloring color of the corresponding region; determine a score value for each region of the coloring image according to the preset similarity interval where the similarity value is located; and determine the target score value of the coloring image based on the sum value of the score values of each region of the coloring image.

[0069] According to an embodiment of the present application, the first determination module 220 is specifically configured to extract each region of the line drawing image by using a preset contour extraction algorithm; assign a corresponding mask to each region of the line drawing image; perform a pixel-by-pixel multiplication operation on the mask of each region of the line drawing image and the original image to determine the pixel value of each region of the line drawing image; and perform color analysis on the pixel value of each region of the line drawing image to determine the target color of each region of the line drawing image.

[0070] According to an embodiment of the present application, the second determination module 230 is specifically configured to calculate a similarity value between each preset color in the preset color set and the target color of each region of the line drawing image; determine a first color set and a second color set based on the similarity value; and use the union of the first color set and the second color set as the target color set.

[0071] According to an embodiment of the present application, the second determination module 230 is specifically configured to use the preset color corresponding to the similarity value greater than the first preset similarity value threshold as the first color set; use the preset color corresponding to the similarity value less than the second preset similarity value threshold as the second color set; wherein, the first preset similarity value threshold is greater than the second preset similarity value threshold, and the number of colors in the first color set is greater than the number of colors in the second color set.

[0072] According to an embodiment of the present application, the generation module 210 is specifically configured to convert a voice command into a text command; perform a matching process on the text command and a preset word set to obtain a matching result; and in the case where the matching result is inconsistent, use the text command as the input of a preset image generation model to output an original image and a line drawing image of the original image.

[0073] It should be noted that the above explanations of the embodiments and beneficial effects of the vehicle data processing method are also applicable to the vehicle data processing device of the embodiments of the present application. To avoid redundancy, no detailed expansion will be made here.

[0074] Corresponding to the above embodiments, the present application also proposes a computer-readable storage medium.

[0075] The computer-readable storage medium of the present application stores a data processing program for a vehicle. When the data processing program for the vehicle is executed by a processor, the foregoing data processing method for the vehicle is implemented.

[0076] It should be noted that the above explanations of the embodiments and beneficial effects of the data processing method for the vehicle are also applicable to the computer-readable storage medium of the embodiments of the present application. To avoid redundancy, no detailed elaboration will be made here.

[0077] Corresponding to the above embodiments, the present application also proposes a terminal device.

[0078] See Figure 3 As shown, the terminal device 300 of the present application includes a memory 310, a processor 320, and a data processing program for a vehicle stored on the memory 310 and executable on the processor 320. When the processor executes the data processing program for the vehicle, the foregoing data processing method for the vehicle is implemented.

[0079] It should be noted that the above explanations of the embodiments and beneficial effects of the data processing method for the vehicle are also applicable to the terminal device of the embodiments of the present application. To avoid redundancy, no detailed elaboration will be made here.

[0080] Corresponding to the above embodiments, the present application also proposes a vehicle.

[0081] See Figure 4 As shown, the vehicle of the present application includes the foregoing terminal device.

[0082] It should be noted that the logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in combination with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in combination with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection portion having one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then stored in a computer memory.

[0083] It should be understood that various parts of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0084] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0085] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0086] In the present application, unless otherwise clearly specified and defined, terms such as "mounted", "connected", "coupled", "fixed", etc. shall be construed in a broad sense. For example, it may be a fixed connection, a detachable connection, or integrated; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the internal communication of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances.

[0087] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A data processing method for a vehicle, characterized in that, The method includes: In response to a voice command, generating an original image and a line drawing image of the original image according to the voice command and a preset image generation model; Determining a target color for each region of the line drawing image according to the original image and the line drawing image; Determining a target color set according to the target color of each region of the line drawing image; Displaying the original image, the line drawing image, and the target color set, and in response to a coloring instruction for each region of the line drawing image, coloring each region of the line drawing image according to the coloring instruction for each region of the line drawing image and the colors in the target color set to obtain a colored image; Scoring the colored image based on the target color of each region of the line drawing image to determine a target score value of the colored image.

2. The vehicle data processing method according to claim 1, characterized in that, Scoring the colored image based on the target color of each region of the line drawing image to determine a target score value of the colored image, including: Calculating a similarity value between the target color of each region of the line drawing image and the coloring color of the corresponding region; Determining a score value for each region of the colored image according to a preset similarity interval in which the similarity value is located; Determining a target score value of the colored image based on the sum value of the score values of each region of the colored image.

3. The vehicle data processing method according to claim 1, characterized in that, Determining a target color for each region of the line drawing image according to the original image and the line drawing image, including: Extracting each region of the line drawing image by using a preset contour extraction algorithm; Assigning a corresponding mask to each region of the line drawing image; Performing a per-pixel multiplication operation on the mask of each region of the line drawing image and the original image to determine the pixel value of each region of the line drawing image; Performing color analysis on the pixel value of each region of the line drawing image to determine the target color of each region of the line drawing image.

4. The vehicle data processing method according to claim 1, characterized in that, Determining a target color set according to the target color of each region of the line drawing image, including: Calculating a similarity value between each preset color in a preset color set and the target color of each region of the line drawing image; Determining a first color set and a second color set based on the similarity value; Taking the union of the first color set and the second color set as the target color set.

5. The vehicle data processing method according to claim 4, characterized in that, Determining a first color set and a second color set based on the similarity value, including: Taking the preset colors corresponding to the similarity values greater than a first preset similarity value threshold as the first color set; Taking the preset colors corresponding to the similarity values less than a second preset similarity value threshold as the second color set; Wherein, the first preset similarity value threshold is greater than the second preset similarity value threshold, and the number of colors in the first color set is greater than the number of colors in the second color set.

6. The vehicle data processing method according to claim 1, characterized in that Generating an original image and a line drawing image of the original image according to the voice command and a preset image generation model, including: Converting the voice command into a text command; Performing a matching process on the text command and a preset word set to obtain a matching result; In the case where the matching result is inconsistent, the text instruction is used as the input of the preset picture generation model to output the original picture and the line drawing picture of the original picture.

7. A data processing device for a vehicle, characterized in that, The device includes: a generation module, configured to respond to a voice instruction, and generate an original picture and a line drawing picture of the original picture according to the voice instruction and a preset picture generation model; a first determination module, configured to determine the target color of each area of the line drawing picture according to the original picture and the line drawing picture; a second determination module, configured to determine a target color set according to the target color of each area of the line drawing picture; a coloring module, configured to display the original picture, the line drawing picture, and the target color set, and respond to the coloring instruction of each area of the line drawing picture, and color each area of the line drawing picture according to the coloring instruction of each area of the line drawing picture and the color in the target color set to obtain a colored picture; a third determination module, configured to score the colored picture based on the target color of each area of the line drawing picture to determine the target score value of the colored picture.

8. A computer-readable storage medium, characterized in that, A vehicle data processing program is stored thereon, and when the vehicle data processing program is executed by a processor, the vehicle data processing method according to any one of claims 1-6 is implemented.

9. A terminal device, characterized in that, It includes a memory, a processor, and a vehicle data processing program stored on the memory and executable on the processor. When the processor executes the vehicle data processing program, the vehicle data processing method according to any one of claims 1-6 is implemented.

10. A vehicle, characterized in that, It includes the terminal device according to claim 9.

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