Resource recall method, device and network side equipment

Abstract

The present application discloses a resource recall method, device and network-side equipment, belonging to the field of communication technology. The method is applied to the network-side equipment, and the method includes: when the recall data requested by the user equipment UE includes picture data, obtaining at least part of the color value in the picture data; determining the target color value according to the distribution of at least part of the color value in the preset color model, the target color value is the color value of the main color in the picture corresponding to the picture data; sending target information to the UE so that the UE displays the target interface; wherein the target information includes the recall data and the target color value, the target color value is used to indicate the background color of the target interface, and the target interface is the interface for the UE to display the recall data.

Description

Technical Field

[0001] The present application belongs to the field of communication technology, and specifically relates to a resource recall method, device and network side equipment. Background Art

[0002] With the continuous development of communication technology, the functions of electronic devices are becoming more and more abundant. For example, electronic devices can perform online searches through the network.

[0003] Currently, when a user triggers an electronic device to perform an online search, the electronic device may display a search result interface with a pure white background, or the electronic device may display a search result interface with a picture set by the user as the background, which results in poor display flexibility of the electronic device. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a resource recall method, apparatus and network-side equipment, which can solve the problem of poor display flexibility of electronic devices.

[0005] In a first aspect, an embodiment of the present application provides a resource recall method, which is applied to a network side device, and the method includes: when the recall data requested by a user equipment UE (User Equipment, UE) includes picture data, obtaining at least part of the color values ​​in the picture data; determining a target color value according to the distribution of at least part of the color values ​​in a preset color model, the target color value being the color value of the main color in the picture corresponding to the picture data; sending target information to the UE so that the UE displays a target interface; wherein the target information includes the recall data and the target color value, the target color value is used to indicate the background color of the target interface, and the target interface is an interface for the UE to display the recall data.

[0006] In the second aspect, an embodiment of the present application provides a resource recall device, which includes an acquisition module, a determination module and a sending module; the acquisition module is used to acquire at least part of the color value in the picture data when the recall data requested by the user equipment UE includes picture data; the determination module is used to determine the target color value according to the distribution of at least part of the color value in a preset color model, and the target color value is the color value of the main color in the picture corresponding to the picture data; the sending module is used to send target information to the UE so that the UE displays a target interface; wherein the target information includes the recall data and the target color value, the target color value is used to indicate the background color of the target interface, and the target interface is the interface for the UE to display the recall data.

[0007] In a third aspect, an embodiment of the present application provides a network side device, which includes a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the program or instructions are executed by the processor, the steps of the method described in the first aspect are implemented.

[0008] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0009] In a fifth aspect, an embodiment of the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the method described in the first aspect.

[0010] In a sixth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and is executed by at least one processor to implement the method described in the first aspect.

[0011] In an embodiment of the present application, when the recall data requested by the user equipment UE includes picture data, at least part of the color values ​​in the picture data can be obtained; and based on the distribution of at least part of the color values ​​in a preset color model, the target color value is determined, and the target color value is the color value of the main color in the picture corresponding to the picture data; and target information is sent to the UE so that the UE displays a target interface; wherein the target information includes the recall data and the target color value, the target color value is used to indicate the background color of the target interface, and the target interface is the interface for the UE to display the recall data. Through this scheme, since the network side device can determine the color value of the main color in the picture corresponding to the picture data based on the distribution of at least part of the color values ​​in the acquired picture data in a preset color model when the recall data requested by the UE includes picture data, and send information including the color value and the recall data to the UE, so that the UE displays the interface of the recall data, and the background color of the interface is the color indicated by the target color value; that is, the color value of the background color of the interface of the recall data displayed by the UE indicated by the network side device can be the color value of the main color in the picture corresponding to the picture data included in the recall data. Therefore, compared with the background color scheme of the interface corresponding to the recall data displayed by the UE in the traditional technology, the resource recall method provided in the embodiment of the present application can improve the flexibility of UE display. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 is a block diagram of a wireless communication system to which the embodiments of the present application can be applied;

[0013] Figure 2It is a flowchart of a resource recall method provided in an embodiment of the present application;

[0014] Figure 3 is a schematic diagram of a method for obtaining at least part of a color value in a resource recall method provided in an embodiment of the present application;

[0015] Figure 4 It is a schematic diagram of the distribution of the RGB model and at least part of the color values ​​in the RGB model in the resource recall method provided in an embodiment of the present application;

[0016] Figure 5 is a schematic diagram of the distribution of at least part of the color values ​​on the X-axis in the RGB model in the resource recall method provided in an embodiment of the present application;

[0017] Figure 6 is a schematic diagram of a resource recall device provided in an embodiment of the present application;

[0018] Figure 7 is a schematic diagram of a network side device provided in an embodiment of the present application;

[0019] Figure 8 It is a hardware schematic diagram of the network side device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0021] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0022] It is worth noting that the technology described in the embodiments of the present application is not limited to the Long Term Evolution (LTE) / LTE-Advanced (LTE-A) system, but can also be used in other wireless communication systems, such as Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Frequency Division Multiple Access (FDMA), Orthogonal Frequency Division Multiple Access (OFDMA), Single-carrier Frequency-Division Multiple Access (SC-FDMA) and other systems. The terms "system" and "network" in the embodiments of the present application are often used interchangeably, and the described technology can be used for the systems and radio technologies mentioned above as well as for other systems and radio technologies. However, the following description describes a New Radio (NR) system for illustrative purposes, and the NR terminology is used in most of the following descriptions, although these technologies can also be applied to applications other than NR system applications, such as the 6th generation (6 th Generation, 6G) communication system.

[0023] Figure 1A block diagram of a wireless communication system applicable to an embodiment of the present application is shown. The wireless communication system includes UE11 and a network side device 12. Among them, UE can also be called an electronic device, and UE can be a mobile phone, a tablet computer (Tablet Personal Computer), a laptop computer (Laptop Computer) or a notebook computer, a personal digital assistant (Personal Digital Assistant, PDA), a handheld computer, a netbook, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a mobile Internet device (Mobile Internet Device, MID), a wearable device (Wearable Device) or a vehicle-mounted device (VUE), a pedestrian terminal (PUE) and other terminal side devices, and wearable devices include: bracelets, headphones, glasses, etc. It should be noted that the specific type of UE is not limited in the embodiment of the present application. The network side device 12 can be a base station or a core network, wherein the base station can be referred to as a node B, an evolved node B, an access point, a base transceiver station (Base Transceiver Station, BTS), a radio base station, a radio transceiver, a basic service set (Basic Service Set, BSS), an extended service set (Extended Service Set, ESS), a B node, an evolved B node (eNB), a home B node, a home evolved B node, a WLAN access point, a WiFi node, a transmitting and receiving point (Transmitting Receiving Point, TRP) or some other suitable term in the field. As long as the same technical effect is achieved, the base station is not limited to a specific technical vocabulary. It should be noted that in the embodiment of the present application, only the base station in the NR system is taken as an example, but the specific type of the base station is not limited.

[0024] The resource recall method, apparatus, and network-side equipment provided in the embodiments of the present application are described in detail below with reference to the accompanying drawings through specific embodiments and their application scenarios.

[0025] The resource recall method provided in the embodiment of the present application can be applied to the scenario where the UE requests resources from the network side device.

[0026] Exemplarily, taking the UE searching through the network as an example, the server corresponding to the UE (e.g., the network side device in the embodiment of the present application) can determine the color value of the main color in the picture corresponding to the picture data (e.g., the target color value in the embodiment of the present application) according to the distribution of at least part of the color values ​​in the picture data obtained in the preset color model when the search result data requested by the UE (e.g., the recall data in the embodiment of the present application) includes picture data, and send information including the color value and the search result data (e.g., the target information in the embodiment of the present application) to the UE, so that the UE displays the interface of the search result data (e.g., the target interface in the embodiment of the present application), so that the UE can display the interface of the search result data with the background color indicated by the color value after receiving the information. In this way, since the color value of the background color of the interface of the recall data indicated by the network side device to be displayed by the UE can be the color value of the main color in the picture corresponding to the picture data included in the recall data, compared with the background color scheme of the interface corresponding to the recall data displayed by the UE in the traditional technology, the resource recall method provided in the embodiment of the present application can improve the flexibility of UE display.

[0027] Combination Figure 2 , an embodiment of the present application provides a network switching method, which may include the following steps 101 to 103.

[0028] Step 101: When the recalled data requested by the UE includes picture data, the network side device obtains at least part of the color values ​​in the picture data.

[0029] Optionally, in an embodiment of the present application, the recall data may be corresponding result data returned by the network side device in response to any data recall request of the UE, for example, the recall data may be search result data returned by the network side device in response to an image search request of the UE.

[0030] It can be understood that in an embodiment of the present application, the network side device can determine the data corresponding to the data recall request after receiving the data recall request from the UE, and use the address information of the acquired data or the acquired data as the recall data, and send the recall data to the UE.

[0031] Optionally, in an embodiment of the present application, the network side device can read the image data in the form of a data stream into a computer programming language Java image core class through the address information of the above-mentioned image data, and obtain at least part of the color value in the image data through the image core class.

[0032] Optionally, in an embodiment of the present application, when the above-mentioned image data includes image data of images in different image formats, the network side device can convert the image data corresponding to the images in different formats into binary data corresponding to images in conventional formats (such as JPG, jpg, bmp, BMP, gif, GIF, WBMP, png, PNG, JPEG, webp, WebP, wbmp, jpeg) according to the image format to ensure that the above-mentioned image data can be read into the computer programming language java image core class.

[0033] For example, the network side device can convert the data corresponding to the webp image processed by Google image compression technology into binary data corresponding to the jpg image.

[0034] Optionally, in an embodiment of the present application, at least part of the color values ​​in the above-mentioned image data may be all the color values ​​in the image data, or at least part of the color values ​​in the above-mentioned image data may be part of the color values ​​in the image data.

[0035] Optionally, in an embodiment of the present application, when at least part of the color values ​​in the above-mentioned image data can be part of the color values ​​in the image data, the network side device can adopt a sampling strategy to obtain the partial color values, thereby reducing the complexity and time consumption of further processing by the network side device.

[0036] Optionally, in the embodiment of the present application, the sampling ratio in the above sampling strategy may be a system default, or may be set by the user according to actual usage requirements (user-defined).

[0037] Optionally, in the embodiment of the present application, if the types of colors corresponding to all color values ​​in the above picture data are relatively small and the distribution of the same color is relatively concentrated, the network side device can appropriately increase the above sampling ratio. However, under normal circumstances, the above sampling ratio does not exceed 10% of the number of all color values, thereby ensuring the accuracy of subsequent processing by the network side device while further reducing the complexity and time consumption of the processing.

[0038] The resource recall method provided in the embodiment of the present application is exemplarily described below with reference to the accompanying drawings.

[0039] For example, the network side device can use the Java image core class to traverse each pixel in the image corresponding to the image data and obtain the color value of each pixel. If the color value includes an alpha value, that is, an A value, then Figure 3 As shown in (a) in the figure, the offset traversed by the network side device is 4 bytes (i.e. A, blue B, green G, red R). At this time, a color value can be expressed as (A value, R value, G value, B value); if the color value does not include the A value, then Figure 3As shown in (b), the offset traversed by the network side device is 3 bytes (i.e. B, G, R), and a color value can be represented as (R value, G value, B value). It can be understood that since a byte is 8 bits, the range of values ​​that can be represented in binary is 256 values ​​from 0 to 255, that is, the range of A value, R value, G value and B value is 0 to 255.

[0040] It should be noted that the above A value indicates the transparency of the image. The smaller the A value, the higher the transparency of the image. The larger the above R value, G value and B value, the darker the color of the image.

[0041] It can be understood that in the embodiment of the present application, each color value corresponds to a pixel, and the R value, G value and B value in the color value can also be referred to as the value of the R sub-pixel, the value of the G sub-pixel and the value of the B sub-pixel, respectively.

[0042] Optionally, in the embodiment of the present application, the above step 101 can be specifically implemented by the following step 101a.

[0043] Step 101a: When the recalled data requested by the UE includes picture data, the network-side device obtains at least part of the color value from the picture data according to a preset filtering rule.

[0044] Optionally, in an embodiment of the present application, the above-mentioned preset filtering rule may be a system default, or the above-mentioned preset filtering rule may be set by a user according to actual usage requirements. It can be understood that when the preset filtering rule is set by a user according to actual usage requirements, the data recall request sent by the UE to the network side device may include the filtering rule, so that the network side device obtains at least part of the color value from the picture data according to the filtering rule.

[0045] For example, taking the preset filtering rules set by the user according to actual usage needs as an example, if the user needs to filter the red color value in the color value, the network side device can delete the color values ​​with R value greater than 200, G value less than 50 and B value less than 50 from the acquired colors, thereby filtering out the color values ​​in the red range.

[0046] For other descriptions in step 101a, please refer to the relevant descriptions in the above step 101. In order to avoid repetition, they will not be repeated here.

[0047] In the embodiment of the present application, since the network side device can obtain at least part of the color value from the image data according to the preset filtering rules to meet the different usage requirements of users, the flexibility of the network side device in obtaining the color value can be improved.

[0048] Step 102: The network-side device determines a target color value according to the distribution of at least part of the color values ​​in a preset color model.

[0049] In the embodiment of the present application, the target color value may be the color value of the main color in the image corresponding to the above-mentioned image data.

[0050] Optionally, in an embodiment of the present application, the number of pictures corresponding to the above-mentioned picture data may be one or more, which may be specifically determined according to the request of the UE.

[0051] Optionally, in the embodiment of the present application, the main color in the image may be the color corresponding to the pixel value with the largest number in the image.

[0052] Optionally, in an embodiment of the present application, the above-mentioned preset color model can be any model such as an RGB model, a CMY model (a model established with cyan, magenta and yellow as the three primary colors) or an HSV model (a model established with hue, saturation and brightness).

[0053] Optionally, in an embodiment of the present application, when the above-mentioned preset color model is an RGB model, since the numerical range for representing color in the RGB model is 0 to 255, this numerical range is completely consistent with the binary numerical value processed by the above-mentioned java image core class. Therefore, the network side device uses the RGB model to process the color value, and bit operations can be used to achieve the best performance and complete the operation in the shortest time.

[0054] It should be noted that, for the convenience of description, unless otherwise specified, the above-mentioned preset color model is used as an RGB model for example in the embodiments of the present application, and the type of the above-mentioned preset color model is not limited in actual use.

[0055] The resource recall method provided in the embodiment of the present application is exemplarily described below with reference to the accompanying drawings.

[0056] For example, after obtaining at least part of the color values ​​in the image data, the network side device can establish a mathematical three-dimensional space rectangular coordinate system (i.e., RGB model) based on the R value, B value, and G value in the color value, such as Figure 4 As shown in (a), the X-axis of the three-dimensional rectangular coordinate system corresponds to the R value, the Y-axis of the three-dimensional rectangular coordinate system corresponds to the B value, and the Z-axis of the three-dimensional rectangular coordinate system corresponds to the G value. Figure 4 As shown in (b), the network side device obtains the distribution of the color value in the RGB model, and the network side device can determine the above target color value according to the distribution.

[0057] Optionally, in the embodiment of the present application, since the range of each coordinate axis in the RGB model is 0 to 255, the network side device can quantize 256×256×256=16777216 coordinate points. However, the amount of calculation will be too large if the coordinate points reach tens of millions. In order to reduce the time consumption of calculation, the network side device can simplify 256×256×256 to 32×32×32=32768 coordinate intervals, and each new coordinate interval contains 8×8×8=512 original coordinate points.

[0058] Optionally, in an embodiment of the present application, the network-side device may create a mapping relationship between each of the above-mentioned coordinate intervals and the number of color values ​​distributed within the coordinate interval to facilitate further determination of the above-mentioned target color value.

[0059] Optionally, in the embodiment of the present application, the above step 102 can be specifically implemented by the following steps 102a, 102b and 102c.

[0060] Step 102a: The network-side device divides the preset color model based on the R value, the G value, and the B value in at least part of the color values ​​to obtain a plurality of color sub-models.

[0061] Optionally, in an embodiment of the present application, the network side device may determine the coordinate axis having the largest difference between the maximum value and the minimum value distributed on each coordinate axis in the above-mentioned preset color model as the coordinate axis to be segmented first.

[0062] For example, if the maximum and minimum values ​​of the X-axis, Y-axis, and Z-axis are (x2, x1), (y2, y1), and (z2, z1), respectively, the network side device can calculate the values ​​of x2-x1=a, y2-y1=b, and z2-z1=c. If a>b>c, the network side device can determine that the X-axis is the coordinate axis to be divided first.

[0063] It should be noted that x2 is the coordinate interval (or coordinate value) corresponding to the maximum R value in the above-mentioned at least part of the color values ​​on the X-axis, and x1 is the coordinate interval (or coordinate value) corresponding to the minimum R value in the above-mentioned at least part of the color values ​​on the X-axis; y2 is the coordinate interval (or coordinate value) corresponding to the maximum G value in the above-mentioned at least part of the color values ​​on the Y-axis, and y1 is the coordinate interval (or coordinate value) corresponding to the minimum G value in the above-mentioned at least part of the color values ​​on the Y-axis, and so on.

[0064] Optionally, in an embodiment of the present application, the network side device may divide the above preset color model by the following method 1 or method 2.

[0065] The following is an illustrative description of the first and second methods respectively with reference to the accompanying drawings.

[0066] Method 1

[0067] Optionally, in an embodiment of the present application, the network side device may adopt a unilateral median segmentation method to divide the preset color model into at least one color sub-model, and the division granularity may be adjusted / determined according to the scenario.

[0068] For example, assuming that the network side device simplifies the above preset color model into 32×32×32=32768 coordinate intervals, if the division order determined by the network side device is: X axis (ie, R value), Y axis (ie, G value), Z axis (ie, B value), then: Figure 5 As shown, it is a schematic diagram of the distribution of at least part of the color values ​​obtained by the network side device on the X-axis in the above preset color model; the network side device can sort the R values ​​of all the color values ​​in the at least part of the color values ​​from large to small, and calculate the median (that is, the R value in the middle position of the R value sequence). Figure 5 As shown, if the coordinate interval to which the median calculated by the network side device belongs is coordinate interval 13, the network side device can sort all the R values ​​distributed in coordinate interval 14 to coordinate interval 31 in order from large to small, and calculate the median again. If the coordinate interval to which the median calculated by the network side device this time belongs is coordinate interval 19, the network side device can determine the plane perpendicular to the X-axis where the spatial coordinate point (19×8,0,0) is located as the dividing surface, and divide the above-mentioned preset color model into model V1 (i.e., a model composed of all coordinates of the X-axis coordinates between the coordinate interval 0 and 19) and model V (i.e., a model composed of all coordinates of the X-axis coordinates between the coordinate interval 20 and 31), and mark the spatial coordinate ranges of model V1 and model V, and the representation format of the spatial coordinate range is (x2, x1, y2, y1, z2, z1). Furthermore, the network side device can continue to execute the above steps on model V, dividing model V into model V2 and model V′, and so on, until the network side device divides the above preset color model n-1 times, and obtains n models V1, V2...Vn-1, Vn, that is, obtains n color sub-models corresponding to the R value, so that the division of the preset color model based on the R value in at least part of the color value can be completed.

[0069] It should be noted that the value range of n is between 1 and 256. The larger the value of n is, the finer the separation granularity is and the higher the calculation complexity is.

[0070] Then, the network side device can divide the preset color model in the same way based on the G value in at least part of the color value to obtain g models; and divide the preset color model based on the B value in at least part of the color value to obtain q models; g, q and n can be the same or different.

[0071] It can be understood that in the embodiment of the present application, the above-mentioned multiple color sub-models include the above-mentioned n models, q models and g models.

[0072] Method 2

[0073] For example, assuming that the network side device simplifies the above preset color model into 32×32×32=32768 coordinate intervals, if the separation order determined by the network side device is: X axis (ie, R value), Y axis (ie, G value), Z axis (ie, B value), then: Figure 5 As shown, it is a schematic diagram of the distribution of at least part of the color values ​​obtained by the network side device on the X-axis in the above-mentioned preset color model. The network side device can first determine the space corresponding to each coordinate interval in the coordinate interval 0 to the coordinate interval 31 as a model; and determine the space corresponding to every at least two consecutive coordinate intervals in the coordinate interval 0 to the coordinate interval 31 as a model. In this way, the division of the preset color model based on the R value in at least part of the color value can be completed.

[0074] Then, the network side device can divide the preset color model based on the G value in at least part of the color values ​​in the same way; and divide the preset color model based on the B value in at least part of the color values. After the network side divides the preset model based on the R value, G value and B value in at least part of the color values, the above-mentioned multiple color sub-models can be obtained.

[0075] Step 102b: The network-side device determines a target color sub-model from a preset color model according to the number of color values ​​distributed in the color sub-model.

[0076] Optionally, in the embodiment of the present application, the above step 102b can be specifically implemented by one of the following possible implementation methods or another possible implementation method.

[0077] A possible implementation

[0078] Optionally, in an embodiment of the present application, the above-mentioned multiple color sub-models may include: at least one first color sub-model corresponding to the above-mentioned R value, at least one second color sub-model corresponding to the above-mentioned G value, and at least one third color sub-model corresponding to the above-mentioned B value, then the above-mentioned step 102b can be specifically implemented through the following steps 102b1 to 102b4.

[0079] It can be understood that in the embodiment of the present application, at least one first color sub-model corresponding to the R value is all the color sub-models obtained by the network side device by dividing the preset color model based on the R value in at least part of the color values; at least one first color sub-model corresponding to the G value is all the color sub-models obtained by the network side device by dividing the preset color model based on the G value in at least part of the color values; at least one first color sub-model corresponding to the B value is all the color sub-models obtained by the network side device by dividing the preset color model based on the B value in at least part of the color values.

[0080] Step 102b1: The network-side device determines a fourth color sub-model in the at least one first color sub-model that satisfies the first condition and the second condition.

[0081] Step 102b2: The network-side device determines a fifth color sub-model in the at least one second color sub-model that satisfies the first condition and the third condition.

[0082] Step 102b3: The network-side device determines a sixth color sub-model in the at least one third color sub-model that satisfies the first condition and the fourth condition.

[0083] Among them, the first condition is that the number of color values ​​distributed in the color sub-model reaches a preset threshold, the second condition is that the width of the color sub-model on the R axis is the smallest, the third condition is that the width of the color sub-model on the G axis is the smallest, and the fourth condition is that the width of the color sub-model on the B axis is the smallest.

[0084] It can be understood that in the embodiment of the present application, the above-mentioned fourth color sub-model is a color sub-model in which the number of distributed color values ​​reaches a preset threshold and the width on the R axis is the smallest in at least one first color sub-model corresponding to the above-mentioned R value; the above-mentioned fifth color sub-model is a color sub-model in which the number of distributed color values ​​reaches a preset threshold and the width on the G axis is the smallest in at least one second color sub-model corresponding to the above-mentioned G value; the above-mentioned fifth color sub-model is a color sub-model in which the number of distributed color values ​​reaches a preset threshold and the width on the B axis is the smallest in at least one third color sub-model corresponding to the above-mentioned B value.

[0085] In the embodiment of the present application, the R axis is the X axis, the G axis is the Z axis, and the B axis is the Y axis.

[0086] Optionally, in an embodiment of the present application, the above-mentioned preset threshold value may be a system default, or the above-mentioned preset threshold value may be set by the user according to actual usage requirements.

[0087] It can be understood that in the embodiment of the present application, the minimum width may be the minimum difference between the maximum value and the minimum value distributed on one coordinate axis in the color sub-model.

[0088] The resource recall method provided in the embodiment of the present application is exemplarily described below.

[0089] Exemplarily, taking the determination of the fourth color sub-model by the network side device as an example, assuming that the network side device divides the preset color model by the second method, the multiple color sub-models include color sub-model 1, color sub-model 2 and color sub-model 3 (i.e., at least one first color sub-model) corresponding to the R value, and the preset threshold is 0.7×P, where P is the total number of at least some of the color values. If the number of color values ​​in color sub-model 1 is a, the number of color values ​​in color sub-model 2 is b, and the number of color values ​​in color sub-model 3 is c, and a>c>0.7×P>b; the width of color sub-model 3 on the R axis>the width of color sub-model 1 on the R axis>the width of color sub-model 2 on the R axis, then the network side device can determine that color sub-model 1 is the fourth color sub-model, that is, color sub-model 1 is a color sub-model whose number of distributed color values ​​reaches the preset threshold and whose width on the R axis is the smallest.

[0090] For the method for the network side device to determine the fifth color sub-model and the sixth color sub-model, please refer to the method for the network side device to determine the fourth color sub-model in the above example. In order to avoid repetition, it will not be repeated here.

[0091] Step 102b4: The network side device determines a target color submodel from the preset color models according to the coordinate information of the fourth color submodel on the R axis, the coordinate information of the fifth color submodel on the G axis, and the coordinate information of the sixth color submodel on the B axis.

[0092] Optionally, in an embodiment of the present application, the network side device may determine that a model where the fourth color sub-model, the fifth color sub-model, and the sixth color sub-model intersect in the preset color model is the target color sub-model.

[0093] For example, assuming that the coordinate range of the fourth color sub-model on the R axis is [x3, x4], the coordinate range of the fifth color sub-model on the G axis is [z3, z4], and the coordinate range of the sixth color sub-model on the B axis is [y3, y4], then the network side device can determine the model with a spatial coordinate range of (x4, x3, y4, y3, z4, z3) as the target color sub-model, that is, the model where the fourth color sub-model, the fifth color sub-model and the sixth color sub-model intersect in the above-mentioned preset color model.

[0094] In the embodiment of the present application, since the network side device can determine the color sub-model whose number of color values ​​distributed on each coordinate axis reaches a preset threshold and whose width is the smallest, and can determine a target color sub-model based on the coordinate information of each determined color sub-model on the corresponding coordinate axis, it is possible to ensure that the above-mentioned target color values ​​are distributed in the target color sub-model, thereby improving the accuracy of the network side device in determining the target color value.

[0095] Another possible implementation

[0096] Optionally, in the embodiment of the present application, the above step 102b can be specifically implemented through the following steps 102b5 and 102b6.

[0097] Step 102b5: The network-side device determines, for each color sub-model in the multiple color sub-models, a product of the number of color values ​​distributed in the color sub-model and the volume of the color sub-model.

[0098] It can be understood that in the embodiment of the present application, each color sub-model in the above-mentioned multiple color sub-models corresponds to a product.

[0099] Step 102b6: The network-side device determines the color sub-model with the largest product among the multiple color sub-models as the target color sub-model.

[0100] Optionally, in the embodiment of the present application, the volume of a color sub-model may be determined by the network-side device according to the spatial coordinate range of the color sub-model.

[0101] For example, assuming that the spatial coordinate range of a color sub-model is (x6, x5, y6, y5, z6, z5), the network side device can determine that the volume of the color sub-model is (|x6-x5|)×(|y6-y5|)×(|z6-z5|).

[0102] For a specific description of the network-side device determining the number of color values ​​distributed in a color sub-model, reference may be made to the relevant description in the above embodiments, which will not be described again here to avoid repetition.

[0103] In an embodiment of the present application, after determining the number of color values ​​distributed in each color sub-model and the volume of the color sub-model, the network side device can further determine the product of the number of color values ​​distributed in each color sub-model and the volume of the color sub-model, and determine the color sub-model with the largest product as the target color sub-model.

[0104] In an embodiment of the present application, since the electronic device can determine the product of the number of color values ​​distributed in each color sub-model and the volume of the color sub-model, and determine the color sub-model with the largest product as the target sub-model, it can ensure that the above-mentioned target color value is distributed in the target color sub-model, thereby further improving the accuracy of the network side device in determining the target color value.

[0105] Step 102c: The network-side device determines the average value of the color values ​​distributed in the target color sub-model as the target color value.

[0106] Optionally, in the embodiment of the present application, if the color value includes an alpha value (i.e., an A value), the network side device may take the average values ​​of the A value, R value, G value, and B value of all color values ​​distributed in the target color sub-model, and determine the color value formed by combining the average values ​​of the A value, R value, G value, and B value as the target color value. If the color value does not include an alpha value, the network side device may take the average values ​​of the R value, G value, and B value of all color values ​​distributed in the target color sub-model, and determine the color value formed by combining the average values ​​of the R value, G value, and B value as the target color value.

[0107] For example, if the A values ​​of all color values ​​distributed in the target color submodel are A1, A2 and R3, the R values ​​of all color values ​​distributed in the target color submodel are R1, R2 and R3, the G values ​​of all color values ​​distributed in the target color submodel are G1, G2 and G3, and the B values ​​of all color values ​​distributed in the target color submodel are B1, B2 and B3, then the network side device can calculate the average value of A1, A2 and A3 to be a1, the average value of R1, R2 and R3 to be r1, the average value of G1, G2 and G3 to be g1, the average value of B1, B2 and B3 to be b1, and determine the color value (a1, r1, g1, b1) as the target color value.

[0108] In an embodiment of the present application, since the network side device can divide the preset color model into multiple color sub-models based on the R value, G value and B value in at least part of the acquired color values, and determine a target color sub-model from the preset color model according to the number of color values ​​distributed in each color sub-model, and determine the average value of the color values ​​distributed in the target color sub-model as the above-mentioned target color value, the accuracy of the network side device in determining the target color value can be further improved.

[0109] Step 103: The network side device sends target information to the UE.

[0110] In an embodiment of the present application, the network side device sends target information to the UE so that the UE displays the target interface.

[0111] In an embodiment of the present application, the target information may include the above-mentioned recall data and a target color value. The target color value may be used to indicate the background color of the target interface. The target interface may be an interface for the UE to display the recall data.

[0112] Optionally, in an embodiment of the present application, after the network side device determines the target color value from the above-mentioned recall data, it can return the target information including the above-mentioned recall data and the target color value online to the UE. After receiving the above-mentioned target information, the UE can display the interface of the above-mentioned recall data, and determine the above-mentioned target color value as the color value of the background color of the interface, that is, the color value of the background color of the interface of the above-mentioned recall data displayed by the UE is the color value of the main color in the picture corresponding to the picture data included in the above-mentioned recall data, thereby improving the flexibility of display.

[0113] In the resource recall method provided in the embodiment of the present application, since the network side device can determine the color value of the main color in the picture corresponding to the picture data based on the distribution of at least part of the color values ​​in the acquired picture data in a preset color model when the recall data requested by the UE includes picture data, and send information including the color value and the recall data to the UE, so that the UE displays the interface of the recall data, and the background color of the interface is the color indicated by the target color value; that is, the color value of the background color of the interface of the recall data displayed by the UE indicated by the network side device can be the color value of the main color in the picture corresponding to the picture data included in the recall data. Therefore, compared with the background color scheme of the interface corresponding to the recall data displayed by the UE in the traditional technology, the resource recall method provided in the embodiment of the present application can improve the flexibility of UE display.

[0114] The resource recall method provided in the embodiment of the present application can be executed by a resource recall device. In the embodiment of the present application, a method for executing resource recall by a resource recall device is taken as an example to illustrate the resource recall device provided in the embodiment of the present application.

[0115] Combination Figure 6 , an embodiment of the present application provides a resource recall device 60, and the resource recall device 60 may include: an acquisition module 61, a determination module 62 and a sending module 63. The acquisition module 61 can be used to acquire at least part of the color value in the picture data when the recall data requested by the user equipment UE includes picture data. The determination module 62 can be used to determine the target color value according to the distribution of at least part of the color values ​​in the preset color model, and the target color value is the color value of the main color in the picture corresponding to the picture data. The sending module 63 can be used to send target information to the UE so that the UE displays a target interface; wherein the target information includes the recall data and the target color value, the target color value is used to indicate the background color of the target interface, and the target interface is the interface for the UE to display the recall data.

[0116] In a possible implementation, the resource recall device 60 may further include a division module. The division module may be used to divide the preset color model based on the R value, G value, and B value in at least part of the color values ​​to obtain multiple color sub-models. The determination module 62 may be used to determine the target color sub-model from the preset color model according to the number of color values ​​distributed in the color sub-model. The determination module 62 may be used to determine the average value of the color values ​​distributed in the target color sub-model as the target color value.

[0117] In a possible implementation, the multiple color sub-models may include: at least one first color sub-model corresponding to the R value, at least one second color sub-model corresponding to the G value, and at least one third color sub-model corresponding to the B value. The determination module 62 may be specifically used to determine a fourth color sub-model that satisfies the first condition and the second condition in at least one first color sub-model. The determination module 62 may be specifically used to determine a fifth color sub-model that satisfies the first condition and the third condition in at least one second color sub-model. The determination module 62 may be specifically used to determine a sixth color sub-model that satisfies the first condition and the fourth condition in at least one third color sub-model. The determination module 62 may be specifically used to determine a target color sub-model from a preset color model according to coordinate information of the fourth color sub-model on the R axis, coordinate information of the fifth color sub-model on the G axis, and coordinate information of the sixth color sub-model on the B axis; wherein the first condition is that the number of color values ​​distributed in the color sub-model reaches a preset threshold, the second condition is that the width of the color sub-model on the R axis is the smallest, the third condition is that the width of the color sub-model on the G axis is the smallest, and the fourth condition is that the width of the color sub-model on the B axis is the smallest.

[0118] In a possible implementation, the determination module 62 may be used to determine, for each color sub-model in the plurality of color sub-models, the product of the number of color values ​​distributed in the color sub-model and the volume of the color sub-model. The determination module 62 may be used to determine, among the plurality of color sub-models, the color sub-model with the largest product as the target color sub-model.

[0119] In a possible implementation, the acquisition module 61 may be specifically configured to acquire at least part of the color value from the image data according to a preset filtering rule.

[0120] In the data recall device provided in the embodiment of the present application, since the data recall device can determine the color value of the main color in the picture corresponding to the picture data based on the distribution of at least part of the color values ​​in the picture data obtained in a preset color model when the recall data requested by the UE includes picture data, and send information including the color value and the recall data to the UE, so that the UE displays the interface of the recall data, and the background color of the interface is the color indicated by the target color value; that is, the color value of the background color of the interface of the recall data displayed by the UE indicated by the data recall device can be the color value of the main color in the picture corresponding to the picture data included in the recall data. Therefore, compared with the background color scheme of the interface corresponding to the recall data displayed by the UE in the traditional technology, the resource recall method provided in the embodiment of the present application can improve the flexibility of UE display.

[0121] The beneficial effects of various implementations in this embodiment can be specifically referred to the beneficial effects of the corresponding implementations in the above method embodiment. To avoid repetition, they will not be described again here.

[0122] The data recall device in the embodiment of the present application may be a server, a network attached storage (NAS), a base station or a core network, and the embodiment of the present application is not specifically limited. Among them, the base station may be referred to as a node B, an evolved node B, an access point, a base transceiver station (BTS), a radio base station, a radio transceiver, a basic service set (BSS), an extended service set (ESS), a B node, an evolved B node (eNB), a home B node, a home evolved B node, a WLAN access point, a WiFi node, a transmitting and receiving point (TRP) or some other suitable term in the field, as long as the same technical effect is achieved, the base station is not limited to a specific technical vocabulary, it should be noted that in the embodiment of the present application, only the base station in the NR system is taken as an example, but the specific type of the base station is not limited.

[0123] The data recall device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0124] The data recall device provided in the embodiment of the present application can achieve Figures 1 to 5 To avoid repetition, the various processes implemented by the method embodiment are not described here.

[0125] Alternatively, if Figure 7 As shown, an embodiment of the present application also provides a network side device 700, including a processor 701 and a memory 702, and the memory 702 stores a program or instruction that can be executed on the processor 701. When the program or instruction is executed by the processor 701, the various steps of the above-mentioned resource recall method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0126] It should be noted that the network side devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0127] Figure 8 A schematic diagram of the hardware structure of a network-side device for implementing an embodiment of the present application.

[0128] The network side device 1000 includes but is not limited to: a radio frequency unit 1001, a network module 1002, an audio output unit 1003, an input unit 1004, a sensor 1005, a display unit 1006, a user input unit 1007, an interface unit 1008, a memory 1009, and a processor 1010 and other components.

[0129] Those skilled in the art will appreciate that the network side device 1000 may also include a power source (such as a battery) for supplying power to each component, and the power source may be logically connected to the processor 1010 through a power management system, thereby implementing functions such as managing charging, discharging, and power consumption management through the power management system. Figure 8 The network side device structure shown in the figure does not constitute a limitation on the network side device. The network side device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be repeated here.

[0130] Wherein, the processor 1010 can be used to obtain at least part of the color value in the picture data when the recall data requested by the user equipment UE includes picture data. The processor 1010 is also used to determine the target color value according to the distribution of at least part of the color value in the preset color model, and the target color value is the color value of the main color in the picture corresponding to the picture data. The radio frequency unit 1001 can be used to send target information to the UE so that the UE displays the target interface; wherein the target information includes the recall data and the target color value, and the target color value is used to indicate the background color of the target interface, and the target interface is the interface for the UE to display the recall data.

[0131] In a possible implementation, the processor 1010 is further configured to divide the preset color model based on the R value, the G value, and the B value in at least part of the color values ​​to obtain a plurality of color sub-models. The processor 1010 can be specifically configured to determine the target color sub-model from the preset color model according to the number of color values ​​distributed in the color sub-model. The processor 1010 can be specifically configured to determine the average value of the color values ​​distributed in the target color sub-model as the target color value.

[0132] In a possible implementation, the multiple color sub-models may include: at least one first color sub-model corresponding to the R value, at least one second color sub-model corresponding to the G value, and at least one third color sub-model corresponding to the B value. The processor 1010 may be specifically configured to determine a fourth color sub-model that satisfies the first condition and the second condition in the at least one first color sub-model. The processor 1010 may be specifically configured to determine a fifth color sub-model that satisfies the first condition and the third condition in the at least one second color sub-model. The processor 1010 may be specifically configured to determine a sixth color sub-model that satisfies the first condition and the fourth condition in the at least one third color sub-model. The processor 1010 may be specifically configured to determine a target color sub-model from a preset color model according to coordinate information of the fourth color sub-model on the R axis, coordinate information of the fifth color sub-model on the G axis, and coordinate information of the sixth color sub-model on the B axis; wherein the first condition is that the number of color values ​​distributed in the color sub-model reaches a preset threshold, the second condition is that the width of the color sub-model on the R axis is the smallest, the third condition is that the width of the color sub-model on the G axis is the smallest, and the fourth condition is that the width of the color sub-model on the B axis is the smallest.

[0133] In a possible implementation, the processor 1010 may be used to determine, for each color sub-model in the plurality of color sub-models, a product of the number of color values ​​distributed in the color sub-model and the volume of the color sub-model. The processor 1010 may be used to determine, among the plurality of color sub-models, a color sub-model with the largest product as a target color sub-model.

[0134] In a possible implementation, the processor 1010 may be specifically configured to obtain at least a portion of color values ​​from the image data according to a preset filtering rule.

[0135] In the network side device provided in the embodiment of the present application, since the network side device can determine the color value of the main color in the picture corresponding to the picture data based on the distribution of at least part of the color values ​​in the acquired picture data in a preset color model when the recall data requested by the UE includes picture data, and send information including the color value and the recall data to the UE, so that the UE displays the interface of the recall data, and the background color of the interface is the color indicated by the target color value; that is, the color value of the background color of the interface of the recall data displayed by the UE indicated by the network side device can be the color value of the main color in the picture corresponding to the picture data included in the recall data. Therefore, compared with the background color scheme of the interface corresponding to the recall data displayed by the UE in the traditional technology, the resource recall method provided in the embodiment of the present application can improve the flexibility of UE display.

[0136] The beneficial effects of various implementations in this embodiment can be specifically referred to the beneficial effects of the corresponding implementations in the above method embodiment. To avoid repetition, they will not be described again here.

[0137] It should be understood that in the embodiment of the present application, the input unit 1004 may include a graphics processor (Graphics Processing Unit, GPU) 10041 and a microphone 10042, and the graphics processor 10041 processes the image data of the static picture or video obtained by the image capture device (such as a camera) in the video capture mode or the image capture mode. The display unit 1006 may include a display panel 10061, and the display panel 10061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 1007 includes a touch panel 10071 and at least one of other input devices 10072. The touch panel 10071 is also called a touch screen. The touch panel 10071 may include two parts: a touch detection device and a touch controller. Other input devices 10072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which will not be repeated here.

[0138] The memory 1009 can be used to store software programs and various data. The memory 1009 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, an application program or instructions required for at least one function (such as a sound playback function, an image playback function, etc.), etc. In addition, the memory 1009 may include a volatile memory or a non-volatile memory, or the memory 1009 may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM) and a direct memory bus random access memory (DRRAM). The memory 1009 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0139] The processor 1010 may include one or more processing units; optionally, the processor 1010 integrates an application processor and a modem processor, wherein the application processor mainly processes operations related to an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communication signals, such as a baseband processor. It is understandable that the modem processor may not be integrated into the processor 1010.

[0140] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of the above-mentioned resource recall method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0141] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0142] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned resource recall method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0143] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0144] An embodiment of the present application provides a computer program product, which is stored in a storage medium. The program product is executed by at least one processor to implement the various processes of the resource recall method embodiment described above, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0145] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0146] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0147] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A resource recall method, characterized in that: The method comprises: In a case where the recalled data requested by the user equipment UE includes picture data, obtaining at least part of color values ​​in the picture data; Determine a target color value according to the distribution of at least part of the color values ​​in a preset color model, wherein the target color value is a color value of a main color in the picture corresponding to the picture data; Sending target information to the UE so that the UE displays a target interface; The target information includes the recall data and the target color value, the target color value is used to indicate the background color of the target interface, and the target interface is an interface for the UE to display the recall data; The determining the target color value according to the distribution of at least part of the color values ​​in the preset color model includes: Based on the R value, the G value and the B value in the at least part of the color values, respectively, a unilateral median segmentation method is used to divide the preset color model to obtain a plurality of color sub-models; Determine, according to each color sub-model in the plurality of color sub-models, a product of the number of color values ​​distributed in each color sub-model and a volume, and determine, among the plurality of color sub-models, a color sub-model with a maximum product as a target color sub-model; An average value of color values ​​distributed in the target color sub-model is determined as the target color value.

2. The method according to claim 1, characterized in that The multiple color sub-models include: at least one first color sub-model corresponding to the R value, at least one second color sub-model corresponding to the G value, and at least one third color sub-model corresponding to the B value; The step of determining a target color sub-model from the preset color model according to the number of color values ​​distributed in the color sub-model includes: Determine a fourth color sub-model in the at least one first color sub-model that satisfies the first condition and the second condition; Determine a fifth color sub-model in the at least one second color sub-model that satisfies the first condition and the third condition; Determine a sixth color sub-model in the at least one third color sub-model that satisfies the first condition and the fourth condition; Determine the target color sub-model from the preset color model according to the coordinate information of the fourth color sub-model on the R axis, the coordinate information of the fifth color sub-model on the G axis, and the coordinate information of the sixth color sub-model on the B axis; Among them, the first condition is that the number of color values ​​distributed in the color sub-model reaches a preset threshold, the second condition is that the width of the color sub-model on the R axis is the smallest, the third condition is that the width of the color sub-model on the G axis is the smallest, and the fourth condition is that the width of the color sub-model on the B axis is the smallest.

3. The method according to claim 1, characterized in that The step of determining a target color sub-model from the preset color model according to the number of color values ​​distributed in the color sub-model includes: For each color submodel in the plurality of color submodels, determining a product of a number of color values ​​distributed in the one color submodel and a volume of the one color submodel; The color sub-model with the largest product among the multiple color sub-models is determined as the target color sub-model.

4. The method according to claim 1, characterized in that: The obtaining at least part of the color values ​​in the image data comprises: According to a preset filtering rule, at least part of the color value is obtained from the image data.

5. A resource recall device, characterized in that: The device comprises an acquisition module, a determination module and a sending module; The acquisition module is configured to acquire at least part of the color values ​​in the picture data when the recalled data requested by the user equipment UE includes the picture data; The determination module is used to determine a target color value according to the distribution of at least part of the color values ​​in a preset color model, wherein the target color value is a color value of a main color in the picture corresponding to the picture data; The sending module is used to send target information to the UE so that the UE displays a target interface; The target information includes the recall data and the target color value, the target color value is used to indicate the background color of the target interface, and the target interface is an interface for the UE to display the recall data; The device also includes a partitioning module; The division module is used to divide the preset color model by using a unilateral median segmentation method based on the R value, the G value and the B value in the at least part of the color values ​​to obtain a plurality of color sub-models; The determination module is specifically configured to determine, according to each color sub-model in the multiple color sub-models, the product of the number of color values ​​distributed in each color sub-model and the volume, and determine the color sub-model with the largest product among the multiple color sub-models as the target color sub-model; The determination module is specifically configured to determine an average value of color values ​​distributed in the target color sub-model as the target color value.

6. The device according to claim 5, characterized in that The multiple color sub-models include: at least one first color sub-model corresponding to the R value, at least one second color sub-model corresponding to the G value, and at least one third color sub-model corresponding to the B value; The determining module is specifically configured to determine a fourth color sub-model in the at least one first color sub-model that satisfies the first condition and the second condition; The determining module is specifically configured to determine a fifth color sub-model in the at least one second color sub-model that satisfies the first condition and the third condition; The determining module is specifically configured to determine a sixth color sub-model in the at least one third color sub-model that satisfies the first condition and the fourth condition; The determination module is specifically configured to determine the target color sub-model from the preset color model according to the coordinate information of the fourth color sub-model on the R axis, the coordinate information of the fifth color sub-model on the G axis, and the coordinate information of the sixth color sub-model on the B axis; Among them, the first condition is that the number of color values ​​distributed in the color sub-model reaches a preset threshold, the second condition is that the width of the color sub-model on the R axis is the smallest, the third condition is that the width of the color sub-model on the G axis is the smallest, and the fourth condition is that the width of the color sub-model on the B axis is the smallest.

7. The device according to claim 5, characterized in that The determination module is specifically configured to determine, for each color sub-model in the plurality of color sub-models, a product of the number of color values ​​distributed in the color sub-model and the volume of the color sub-model; The determination module is specifically configured to determine the color sub-model with the largest product among the multiple color sub-models as the target color sub-model.

8. The device according to claim 5, characterized in that The acquisition module is specifically configured to acquire at least part of the color value from the image data according to a preset filtering rule.

9. A network side device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the steps of the resource recall method according to any one of claims 1 to 4 are implemented.

Images