Wearing and lapping method and electronic equipment

Abstract

The invention discloses a wearing and fitting method and electronic equipment, relates to the field of artificial intelligence, and can intelligently manage clothes and recommend daily wearing and fitting, improve the accuracy of wearing and fitting recommendation, save the time and energy of a user, and improve the user experience. The method comprises the following steps: displaying a wearing and building combination on a first window according to a wearing and building score sequence; the wearing score is determined according to the temperature information and the activity information; the temperature information is used for indicating the applicable temperature of the wearing and lapping combination; the activity information is used for indicating style attributes of the wearing and building combination.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence, and more particularly to a dressing method and electronic equipment. Background Art

[0002] In daily life, the following situations often occur: 1) Users have too many clothes to wear, which causes them to have trouble dressing before going out; 2) Users need to go to a different place and are worried about what clothes to bring; 3) Users go out after dressing up, but the weather changes suddenly, causing the current outfit to be inappropriate, such as overheating or not keeping warm. This will consume a lot of users' time and energy, affecting the user experience. Summary of the invention

[0003] The embodiments of the present application provide a dressing method and an electronic device that can intelligently manage clothing and recommend daily outfits, improve the accuracy of outfit recommendations, save users' time and energy, and thus improve user experience.

[0004] To achieve the purpose, the embodiments of the present application adopt the following technical solutions: In a first aspect, a dressing method is provided, the method comprising: displaying dressing combinations in a first window in order of dressing scores; the dressing scores are determined based on temperature information and activity information; the temperature information is used to indicate the applicable temperature of the dressing combination; and the activity information is used to indicate the style attributes of the dressing combination.

[0005] The above dressing method determines the dressing score through temperature information and activity information, and displays the dressing combination on the first window in the order of dressing score. It can intelligently recommend daily dressing, improve the accuracy of dressing recommendation, save users' time and energy, and thus improve user experience.

[0006] In an implementation manner of the first aspect, the activity information is obtained online or through user input.

[0007] In this implementation, activity information obtained online indicates that the local outfit combinations for the day are displayed, and activity information obtained through user input indicates that the outfit combinations for the future or other places are displayed. Outfits can be recommended based on actual conditions, improving the accuracy of outfit recommendations, saving users' time and energy, and thus improving user experience.

[0008] In an implementable manner of the first aspect, in response to a user clicking on a target outfit combination, the first N outfit combinations are displayed in order of outfit scores or an enlarged picture of the target outfit combination is displayed on a first window; N is a positive integer; and the outfit combinations include the target outfit combination.

[0009] In this implementation, by clicking on the target outfit combination, the first N outfit combinations or an enlarged picture of the target outfit combination are displayed, which is based on the user's online or input two different options to display the results.

[0010] In an implementation manner of the first aspect, the activity information includes at least one of the following: target time, target region, indoor and outdoor, and target activity.

[0011] In this implementation method, the user's dressing style can be clearly known through the target time, target region, indoor and outdoor, and target activity in the activity information, so as to accurately recommend dressing combinations.

[0012] In an implementable manner of the first aspect, the dressing score is confirmed based on temperature information and activity information, including: based on the temperature information and activity information, the clothes in the database are screened to obtain target clothes; the target clothes include a first clothing set, a second clothing set and a third clothing set; the first clothing set includes outer upper body clothes, the second clothing set includes outer lower body clothes, and the third clothing set includes inner upper body clothes, general upper body clothes, inner jumpsuit clothes or general jumpsuit clothes; the first clothing, the second clothing and the third clothing are matched to obtain a dressing combination; the first clothing is any piece of clothing in the first clothing set, the second clothing is any piece of clothing in the second clothing set, and the third clothing is any piece of clothing in the third clothing set; the dressing combination is encoded to obtain a first dressing combination feature vector; the first dressing combination feature vector is input into a clustering neural network model to obtain a dressing score of the dressing combination.

[0013] In this implementation, the clothing in the database is screened according to the temperature information and activity information to obtain target clothing of suitable temperature and style, and the screened clothing is input into the clustering neural network model for automatic matching, and the matching score is output. In this way, clothing can be matched precisely and matching combinations can be accurately recommended.

[0014] In an implementation method of the first aspect, the training process of the clustering neural network model includes: obtaining the attribute vector of the first clothing, the attribute vector of the second clothing, and the attribute vector of the third clothing from a database; each dimension of the attribute vector is used to characterize the value of an attribute of the clothing; the clustering neural network model is trained based on the second dressing combination feature vector and the corresponding dressing score; the second dressing combination feature vector includes the attribute vector of the first clothing, the attribute vector of the second clothing, and the attribute vector of the third clothing.

[0015] In this implementation, the clustering neural network model is trained based on the second outfit combination feature vector and the corresponding outfit score in the database, including the attribute vector of the first clothing, the attribute vector of the second clothing, and the attribute vector of the third clothing, so as to improve the accuracy of the clustering neural network model.

[0016] In one possible implementation of the first aspect, the dressing score is also determined based on historical dressing combinations.

[0017] In this implementation, the outfit score is also determined by historical outfit combinations, which can avoid duplication of the recommended current local outfit combinations with outfit combinations from previous days, thereby improving the user experience.

[0018] In an implementation manner of the first aspect, the method further includes: displaying an add button on the first window; and displaying a fourth clothing item and attributes of the fourth clothing item on the first window in response to a user clicking the add button.

[0019] In this implementation, the user can import the photographed clothing images or downloaded clothing images through the add button, thereby intelligently archiving the imported clothing.

[0020] In an implementation manner of the first aspect, the method further includes: displaying a delete button on the first window; and in response to the user clicking the delete button, not displaying the fourth clothing item and the attributes of the fourth clothing item on the first window.

[0021] In this implementation, after the user imports the image, if the user is not satisfied with the imported image or the imported image is incorrect, the user can delete it by clicking the delete button, which is simple to operate.

[0022] In an implementation manner of the first aspect, the method further includes: displaying an edit button on the first window; and in response to the user clicking the edit button, displaying the attributes of the fourth clothing item in an editable state on the first window.

[0023] In this implementation, the user can change the attributes of the clothing through the edit button, avoiding the situation where the automatically identified attributes are wrong and cannot be changed, making the attributes of the clothing more accurate and simple to operate.

[0024] In a second aspect, an electronic device is provided, comprising a memory and one or more processors, wherein the memory stores computer program code, and the computer program code comprises computer instructions, which, when executed by the processor, enable the electronic device to execute the dressing method of the first aspect and any one of its embodiments.

[0025] In a third aspect, a computer-readable storage medium is provided, comprising computer instructions, which, when executed on an electronic device, enables the electronic device to execute the dressing method of the first aspect and any of its embodiments.

[0026] In a fourth aspect, a computer program product is provided. When the computer program product is run on an electronic device, the electronic device executes the dressing method of the first aspect and any embodiment thereof.

[0027] Among them, the technical effects brought about by the design methods of the second, third and fourth aspects can refer to the technical effects brought about by the different design methods in the first aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A schematic diagram of a possible hardware structure of an electronic device provided in an embodiment of the present application; Figure 2 A schematic diagram of a possible software structure of an electronic device provided in an embodiment of the present application; Figure 3 A flowchart of a dressing method provided for related technologies; Figure 4 A flowchart of a dressing method provided in an embodiment of the present application; Figure 5 A flowchart of a method for displaying outfits with card suggestions provided in an embodiment of the present application; Figure 6 A flowchart of a method for displaying outfits in an outfit app provided in an embodiment of the present application; Figure 7 A smart recommendation flow chart of a dressing method provided in an embodiment of the present application; Figure 8 A flowchart of clothing filing provided in an embodiment of the present application; Fig. 9 A flowchart of adding clothes provided in an embodiment of the present application; Fig.10 A flowchart of deleting clothing provided in an embodiment of the present application; Fig.11 A flowchart of editing clothing attributes provided in an embodiment of the present application; Fig.12 A flow chart of an attribute recognition model provided in an embodiment of the present application; Fig.13 A flowchart for confirming a dressing score provided in an embodiment of the present application; Fig.14 A training flowchart of a clustering neural network model provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] The technical solution in the embodiment of the present application will be described below in conjunction with the drawings in the embodiment of the present application. Among them, in the description of the present application, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship, for example, A / B can represent A or B; "and / or" in the present application is only a description of the association relationship of the associated objects, indicating that there can be three relationships, for example, A and / or B, which can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. And, in the description of the present application, unless otherwise specified, "multiple" refers to two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple. In addition, in order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, the words "first", "second" and the like are used to distinguish the same items or similar items with substantially the same functions and effects. It can be understood by those skilled in the art that the words "first", "second" and the like do not limit the quantity and execution order, and the words "first", "second" and the like do not necessarily limit the difference. At the same time, in the embodiments of the present application, the words "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or design. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way for easy understanding. The terms "coupling" and "connection" involved in the embodiments of the present application should be understood in a broad sense, for example, it can refer to a physical direct connection, or it can refer to an indirect connection achieved by an electronic device, such as a connection achieved by a resistor, an inductor, a capacitor or other electronic devices.

[0030] Artificial intelligence (AI) is a branch of computer science that seeks to create machines and software that can perform tasks that normally require human intelligence. A machine exhibits intelligent behaviors that are usually associated with the intelligent behaviors of humans or other animals, such as learning, reasoning, problem solving, perception, language understanding, etc.

[0031] A dressing combination (also known as clothing matching) mainly refers to upper body clothing, outer lower body clothing, hats, accessories and shoes, which should be coordinated in style and color to achieve a decent and generous effect as a whole.

[0032] The embodiment of the present application provides an electronic device, which is an electronic device with a display function. The electronic device can be mobile or fixed. The electronic device can be deployed on land (for example, indoors or outdoors, handheld or vehicle-mounted, etc.), on the water (for example, ships, etc.), or in the air (for example, airplanes, balloons, and satellites, etc.). The electronic device can be called user equipment (UE), access terminal, terminal unit, subscriber unit, terminal station, mobile station (MS), mobile station, terminal agent or terminal device, etc. For example, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a smart bracelet, a smart screen, a smart watch, a virtual reality (VR) device, an augmented reality (AR) device, a terminal in industrial control, a terminal in self-driving, a terminal in remote medical care, a terminal in smart grid, a terminal in transportation safety, a terminal in smart city, a terminal in smart home, etc. The embodiments of the present application do not limit the specific type and structure of the electronic device. A possible structure of the electronic device is described below.

[0033] Take the mobile phone as an example, Figure 1 A possible structure of the electronic device 100 is shown. The electronic device 100 may include a processor 210, an external memory interface 220, an internal memory 221, a universal serial bus (USB) interface 230, a power management module 240, a battery 241, a wireless charging coil 242, a mobile communication module 250, a wireless communication module 260, an antenna 251, an antenna 261, an audio module 270, a speaker 270A, a receiver 270B, a microphone 270C, an earphone interface 270D, a sensor module 280, a button 290, a motor 291, an indicator 292, a camera 293, a display screen 294, and a subscriber identification module (SIM) card interface 295. Optionally, in some embodiments, an audio digital signal processor (ADSP) 243 is also included.

[0034] It is to be understood that the structure illustrated in the embodiment of the present application does not constitute a specific limitation on the electronic device 100. In other embodiments of the present application, the electronic device 100 may include more or fewer components than shown in the figure, or combine some components, or split some components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0035] The processor 210 may include one or more processing units, for example, the processor 210 may be a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on chip (SoC), a central processing unit (CPU), an application processor (AP), a network processor (NP), a digital signal processor (DSP), a microcontroller unit (MCU), a programmable logic device (PLD), a modem processor, a graphics processor (GPU), an image signal processor (ISP), a controller, a video codec, and a neural-network processing unit (NPU). Among them, different processing units may be independent devices or integrated into one or more processors. For example, the processor 210 may be an application processor AP. Alternatively, the processor 210 may be integrated in a system on chip (SoC). Alternatively, the processor 210 may be integrated in an integrated circuit (IC) chip. The processor 210 may include an analog front end (AFE) and a micro-controller unit (MCU) in an IC chip.

[0036] The processor 210 may also be provided with a memory for storing computer instructions and data. In some embodiments, the memory in the processor 210 is a cache memory. The memory may store computer instructions or data that the processor 210 has just used or circulated. If the processor 210 needs to use the computer instructions or data again, it may be directly called from the memory. This avoids repeated access, reduces the waiting time of the processor 210, and thus improves the efficiency of the system.

[0037] In some embodiments, the processor 210 may include one or more interfaces. The interface may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a USB interface, etc.

[0038] In some embodiments, the processor may be a processor or a controller, such as a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the present disclosure. The above-mentioned processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0039] ADSP 243 can be coupled with audio module 270 and sensor module 280, and can be used to process audio signals and sensor data. When processor 210 is in sleep mode, ADSP 243 can still keep working, thereby reducing power consumption of electronic device 100.

[0040] It is understandable that the interface connection relationship between the modules illustrated in the embodiment of the present application is only a schematic illustration and does not constitute a structural limitation on the electronic device 100. In other embodiments of the present application, the electronic device 100 may also adopt different interface connection methods in the embodiment, or a combination of multiple interface connection methods.

[0041] The external memory interface 220 can be used to connect an external memory card to expand the storage capacity of the electronic device 100. The external memory card communicates with the processor 210 through the external memory interface 220 to implement a data storage function, such as storing music, video and other files in the external memory card.

[0042] The internal memory 221 may be used to store computer executable program codes, which include computer instructions. The processor 210 executes various functional applications and data processing of the electronic device 100 by running the computer instructions stored in the internal memory 221. In addition, the internal memory 221 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, a universal flash storage (UFS), etc.

[0043] In the embodiment of the present application, when the computer instructions are executed by the processor 210, the electronic device 100 executes the dressing method in the embodiment of the present application.

[0044] The memory involved in the embodiments of the present application may be a volatile memory or a non-volatile memory, or 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), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0045] In the embodiment of the present application, the clothes in the database can be stored in a memory, and can also be stored in a processor 210 provided with a memory.

[0046] The electronic device 100 can implement audio functions such as music playing and recording through the audio module 270, the speaker 270A, the receiver 270B, the microphone 270C, the headphone interface 270D and the application processor.

[0047] The button 290 includes a power button, a volume button, etc. The button 290 may be a mechanical button. It may also be a touch button. The electronic device 100 may receive a button input and generate a key signal input related to the user settings and function control of the electronic device 100. The motor 291 may generate a vibration prompt. The motor 291 may be used for an incoming call vibration prompt or for touch vibration feedback. The indicator 292 may be an indicator light, which may be used to indicate the charging status, the change in power, or may be used to indicate messages, missed calls, notifications, etc. The SIM card interface 295 is used to connect a SIM card. The SIM card may be inserted into or removed from the SIM card interface 295 to achieve contact and separation with the electronic device 100. The electronic device 100 may support 1 or N SIM card interfaces, where N is a positive integer greater than 1. The SIM card interface 295 may support a Nano SIM card, a Micro SIM card, a SIM card, etc. In some embodiments, the electronic device 100 uses an embedded SIM (eSIM) card. The eSIM card can be embedded in the electronic device 100 and cannot be separated from the electronic device 100 .

[0048] The electronic device 100 can realize the shooting function through the ISP, the camera 293, the video codec, the GPU, the display screen 294, and the application processor. The ISP is used to process the data fed back by the camera 293. In some embodiments, the ISP can be set in the camera 293. The camera 293 is used to capture a static image or a video. In some embodiments, the electronic device 100 may include 1 or N cameras 293, where N is a positive integer greater than 1.

[0049] In the embodiment of the present application, the camera 293 can collect the user's clothing and store it in the database.

[0050] The electronic device 100 can realize the display function through a GPU, a display screen 294, and an application processor. The GPU is a microprocessor for image processing, which connects the display screen 294 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 210 may include one or more GPUs, which execute computer instructions to generate or change display information.

[0051] In an embodiment of the present application, the dressing function can be executed by the GPU or by the processor 210, and the dressing effect can be displayed on the display screen 294.

[0052] The power management module 240 is used to receive charging input from a charger. The charger may be a wireless charger, such as a wireless charging base, other electronic devices 100 with reverse wireless charging function, etc. The power management module 240 may receive wireless charging input through a wireless charging coil 242 of the electronic device. The charger may also be a wired charger, for example, the power management module 240 may receive charging input from a wired charger through the USB interface 230. The power management module 240 is also called a charging chip.

[0053] The power management module 240 is used to connect to the battery 241. The power management module 240 receives input from the battery 241 and supplies power to the processor 210, the internal memory 221, the display screen 294, the camera 293, and the wireless communication module 260. The power management module 240 can also be used to monitor parameters such as the capacity of the battery 241, the number of cycles of the battery 241, and the health status (leakage, impedance) of the battery 241. In some other embodiments, the power management module 240 can also be set in the processor 210.

[0054] The wireless communication function of the electronic device 100 can be implemented through the antenna 251, the antenna 261, the mobile communication module 250, the wireless communication module 260, the modem processor, etc.

[0055] The mobile communication module 250 can provide solutions for wireless communications including 2G / 3G / 4G / 5G, etc., applied to the electronic device 100. The wireless communication module 260 can provide solutions for wireless communications including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared technology (IR), etc., applied to the electronic device 100.

[0056] As attached Figure 2 As shown, taking the electronic device 100 running the Android operating system as an example, the software architecture run by the processor 210 includes an application layer, a framework layer, a system runtime layer, a hardware abstract layer (HAL) layer, and a kernel layer.

[0057] The kernel layer is a layer between hardware and software. Exemplarily, the kernel layer includes display drivers, camera drivers, etc. The display driver is used to drive the display screen to display images or receive user touch operations, and the camera driver is used to drive the camera to collect image data.

[0058] In the embodiment of the present application, the camera driver can drive the camera 293 to collect the user's clothing image. The display driver can receive the user's input touch operation, drive the user's input activity information, and can also receive the user's wear touch operation, and drive the display screen 294 to display the image of the wear combination.

[0059] The HAL layer is used to abstract the hardware. The HAL layer hides the hardware interface details of a specific platform and provides a virtual hardware platform for the operating system, which is hardware-independent. For example, the HAL layer includes a display module, a camera module, etc. The display module is used for a virtual display screen, and the camera module is used for a virtual camera.

[0060] The system runtime layer includes C / C++ program libraries and runtime libraries. Many core components and services of the Android operating system are built from native code and need to be written in C and C++ as C / C++ program libraries. When an application is installed for the first time, it will be pre-compiled into a runtime library in the form of machine code. This process is called pre-compilation. In this way, when the application is started and executed, it can be accelerated by running the machine code.

[0061] The framework layer provides application programming interfaces (APIs) and programming frameworks for applications in the application layer. The framework layer includes some predefined implementation methods. For example, the framework layer includes window managers, content providers, view systems, notification managers, etc.

[0062] The application layer can include a series of application packages, such as gallery, music, browser, fashion and other applications (application, app).

[0063] In the related art, in daily life, the following situations often occur: 1) Users have trouble dressing before going out because they have too many clothes; 2) Users need to go to a different place and are entangled in the clothes to bring; 3) After dressing up and going out, the weather changes suddenly, resulting in the current outfit being inappropriate, such as overheating or not keeping warm. This will consume a lot of time and energy of users and affect the user experience.

[0064] In addition, in the related art, although some electronic devices provide a clothing recommendation function, users are required to manually input information, which makes the operation cumbersome and time-consuming, affecting the user experience. Figure 3Some dressing apps (such as the first app, the second app, the third app, and the fourth app) require users to manually input desired clothing information or personalized needs, such as main pictures, categories, colors, labels, seasons, brands, merchants, prices, names, uniform resource locators (URLs), and notes, etc., in the electronic device 100 such as mobile phones. After receiving the information input by the user, the electronic device 100 can obtain corresponding dressing recommendations based on the information, for example, the attached Figure 3 In (a), the user enters the main picture (i.e., top picture), category (i.e., top / suit), season (i.e., summer) and other information in the outfit app. Figure 3 In (b), today's outfit recommendations are displayed on the window of the outfit app, such as skirt suits, high heels, accessories and bags, etc. However, it may be cumbersome and time-consuming for users to manually input clothing information or personalized needs, which affects the user experience.

[0065] To this end, an embodiment of the present application provides a dressing method, which determines the dressing score through temperature information and activity information, or determines the dressing score through temperature information, activity information and historical dressing combinations, and displays the dressing combinations in the first window in the order of dressing scores. Based on the dressing method provided in the embodiment of the present application, it is possible to intelligently manage clothing and recommend daily outfits, improve the accuracy of dressing recommendations, save users' time and energy, and thus improve user experience.

[0066] The dressing method provided in the embodiment of the present application can be implemented on the electronic device 100 and can be displayed on the display screen 294 in the electronic device 100. The embodiment of the present application takes the electronic device 100 including the dressing recommendation function as an example to specifically illustrate the dressing method of the present application.

[0067] For example, as shown in the attached Figure 4 As shown, a dressing method provided in an embodiment of the present application may include steps S401-S402: Step S401, displaying the outfit combinations in the first window in the order of outfit scores; the outfit scores are determined based on temperature information and activity information, or the outfit scores are determined based on temperature information, activity information and historical outfit combinations; the temperature information is used to indicate the applicable temperature of the outfit combination; the activity information is used to indicate the style attributes of the outfit combination.

[0068] In a possible implementation, the first window may be displayed in full screen or in split screen. The embodiment of the present application does not limit the display form of the first window.

[0069] In a possible implementation, the first window may be the first window of a dressing app or a window of a suggestion card. The embodiment of the present application does not limit the type of the first window.

[0070] Among them, both temperature information and activity information can be obtained by calling weather services. Weather services include online weather, global positioning system (GPS) and calendar. GPS is used to obtain the current region information of the electronic device 100. The calendar is used to obtain the current time information of the electronic device 100 and the current activity information of the user. Online weather is used to obtain the weather information of the current region and the current time based on the current region information obtained by GPS and the current time information obtained by the calendar. Weather information includes temperature information, humidity information, wind speed and weather, etc.

[0071] In the embodiment of the present application, the weather service accesses the remote server to obtain the corresponding weather information. In one possible implementation, the dressing score can be determined based on temperature information and activity information, or based on a combination of temperature information, activity information, and historical dressing. In this way, the factors of temperature and activity information are taken into account, and the user can be prevented from wearing the same style of clothing in the last few days, which leads to aesthetic fatigue and affects the user experience.

[0072] In a possible implementation, the historical dressing combination may be a dressing combination of the previous two days, or a dressing combination of the previous three days. The embodiment of the present application does not limit the time of the historical dressing combination.

[0073] The activity information includes at least one of the following: target time, target region, and target activity. In order to indicate the style attributes of the outfit combination based on the user's target activity, the activity information refers to the target activity that the user needs to participate in at the target time and target region, and what style of clothing is required for the target activity. Therefore, the activity information is used to indicate the style attributes of the outfit combination.

[0074] The attributes of clothing include multiple attributes, and multiple attributes form an attribute vector. Each dimension of the attribute vector represents an attribute, and each dimension includes multiple values, and each value represents a value of the attribute. For example, see Table 1 below: Table 1 Clothing properties

[0075] From Table 1 above, we can see that the attributes include clothing, category, style, purpose, applicable temperature, sleeve length, collar type, style, color, etc. The attribute vector includes each of the above attributes. Each dimension of the attribute vector corresponds to an attribute, for example, the first dimension corresponds to the clothing attribute, the second dimension corresponds to the category attribute, the third dimension corresponds to the style attribute, and so on. Each dimension attribute includes multiple values, and each value represents a value of the attribute. Each dimension attribute is different, and the number of values ​​of each dimension attribute is also different, and the corresponding values ​​are also different. For example, the style attribute includes 9 values, namely sports, leisure, cowboy, non-mainstream, business casual, business formal, ethnic, hip-hop, etc., and the corresponding values ​​are 0, 1, 2, 3, 4, 5, 6, 7, 8. The applicable temperature attribute includes 5 values, namely <10°, 10°-15°, 15°-20°, 20°-25° and >25°, etc., and the corresponding values ​​are 0, 1, 2, 3, 4.

[0076] After obtaining the activity information and temperature information, we can not only understand the applicable temperature of the user's clothing combination, but also understand the style attributes of the user's clothing combination. Therefore, we can accurately recommend clothing combinations to users.

[0077] In a possible implementation, the target time and the target region may be the current time and the current region, or a future time or a different location. The embodiment of the present application does not limit the method of the target time and the target region.

[0078] When the target time and the target region are the current time and the current region, the electronic device 100 can automatically obtain the current local temperature information and the current local user activity information on the online weather service, and automatically display the outfit combinations in the first window in order of outfit scores.

[0079] In the following embodiments of the present application, the dressing method of the present application is specifically described by taking the electronic device 100 automatically obtaining the current local temperature information and the current local user activity information on the online weather service as an example.

[0080] In the case where the first window is a suggestion card, displaying the outfit combinations in the first window in order of outfit scores includes displaying the outfit combinations with the highest outfit scores in the first window. Figure 5 As shown in (a) in the figure, the first window 502 of the suggestion card displays the suggested outfits for the current local area (i.e., the location of the electronic device 100 on June 14), i.e., the outfit combination with the highest outfit score, for example, a long-sleeved dress with an outfit score of 98.

[0081] In the case where the first window is a dressing app, in response to an operation for clicking the dressing app icon, displaying the dressing combinations in the first window in order of dressing scores includes displaying the first N dressing combinations in the first window in order of dressing scores; N is a positive integer. Figure 6 As shown in (a) of FIG. 1 , when a user wants to open a dressing app, the electronic device 100 displays windows 501 of various apps, such as icons of a gallery app, a music app, a browser app, and a dressing app, and clicks on the icon of the dressing app, as shown in FIG. Figure 6 As shown in (b) in the figure, the first window 502 of the dressing app displays the first N outfit combinations in the order of outfit scores. For example, the first outfit: a long-sleeved dress, with a score of 98; the second outfit: a long-sleeved suit, with a score of 94; the third outfit: a long-sleeved top and jeans, with a score of 92. The text “Today’s outfit recommendation” is also displayed on the first window 502 of the dressing app.

[0082] When the target time and target region are in the future or in a different place, the electronic device 100 can obtain user activity information in the future or in a different place through activity information input by the user and temperature information in the future or in a different place through an online weather service, and display the outfit combinations for the future time or in a different place in the first window in order of outfit scores.

[0083] In the following embodiments of the present application, the dressing method of the present application is specifically described by taking the example of the electronic device 100 obtaining future or remote user activity information through activity information input by the user and obtaining future or remote temperature information through an online weather service.

[0084] An input button is also displayed on the first window 502 , and in response to the user clicking the input button, configuration options of the activity information are displayed on the first window 502 .

[0085] The configuration options of the activity information include at least one of the following: target time, target region, indoor and outdoor, and target activity. Similarly, the configuration options of the activity information are to indicate the style attributes of the outfit combination based on the user's target activity, which refers to the target activity that the user needs to participate in at the target time and target region, and what style attributes of clothing are required for the target activity. Figure 5 As shown in (b) of FIG. 1 , when the user wants to input activity information, an input button is displayed on the first window 502 of the suggestion card, and the user clicks the input button, as shown in FIG. Figure 5 As shown in (d) in FIG. 5 , configuration options of activity information are displayed on the first window 502 of the suggestion card, such as target time, target region, indoor and outdoor, and target activity, etc. For example, as shown in FIG. Figure 6As shown in (b) of FIG. 1 , when the user wants to input activity information, an input button is displayed on the first window 502 of the dressing app, and the user clicks the input button, as shown in FIG. Figure 6 As shown in (d) in the figure, configuration options of activity information are displayed on the first window 502 of the dressing app, such as target time, target area, indoor and outdoor, and target activity.

[0086] The outfit combinations are displayed in the first window in the order of outfit scores, indicating that the outfit app calculates the score of each outfit combination based on the temperature information and activity information, or based on the temperature information, activity information and historical outfit combinations, and then displays the outfit combinations in the first window in the order of outfit scores. Figure 5 As shown in (d) in FIG. 1 , when the user wants to view the outfit combinations that can be selected for an event in the future or in a different place, the user enters the event information in the first window 502 of the suggestion card. For example, the user wants to go to Beijing to attend a class reunion on August 12, 2024, that is, the target time is 2024.08.12, the target region is Beijing, and the target event is a class reunion, etc., as shown in FIG. Figure 5 As shown in (e) in FIG. 1 , the first window 502 of the suggestion card in the notification of the electronic device 100 displays the outfit combinations in the order of outfit scores, for example, the skirt suit with the highest score is 95, and the date August 12 is also displayed. Figure 6 As shown in (d) in FIG. 1 , when the user wants to view the outfit combinations that can be selected for the event, the user enters the event information in the first window 502 of the outfit app. For example, the user goes to Beijing to attend a class reunion on August 12, 2024, that is, the target time is 2024.08.12, the target region is Beijing, and the target event is a class reunion, etc., as shown in FIG. Figure 6 As shown in (e) in the figure, the first window 502 of the outfit app displays outfit combinations in the order of outfit scores. For example, the first set: skirt suit, score 95; the second set: T-shirt on the upper body and jeans on the lower body, score 93; the third set: dress, score 90, and the text "August 12 outfit recommendation" is also displayed.

[0087] In one possible implementation, the display of the outfit combination can directly display the outfit, or it can display the outfit through virtual fitting. The embodiment of the present application does not limit the display of the outfit combination.

[0088] In the embodiments of the present application, for example, as shown in the attached Figure 7As shown, after obtaining temperature information (including current local temperature information, future or remote temperature information) and activity information (current local activity information) through weather services including online weather, global positioning system (GPS) and calendar, the applicable temperature attributes of clothing (including current local applicable temperature attributes, future or remote applicable temperature attributes) and style attributes (including current local style attributes) can be obtained, and, after the activity information including target time, target region and target activity input by the user, the style attributes of clothing (including future or remote style attributes) can be obtained. Based on the applicable temperature attributes and style attributes of the clothing obtained above, as well as the historical dressing combinations, the clothing in the database is input into the attribute recognition model to perform attribute screening on the clothing, and the target clothing that meets the above applicable temperature attributes and style attributes is screened out. The target clothing is input into the clothing matching model to calculate the score, and the dressing score of each dressing combination is obtained. Then, the dressing combinations are displayed in the order of dressing scores.

[0089] The clothes in the database are obtained by uploading clothing images taken by users or downloaded clothing images to the dressing app for electronic wardrobe archiving. Figure 8 As shown, steps S801-S804 are included: Step S801: The user imports a photographed clothing image or a downloaded clothing image.

[0090] The user imports the captured clothing image or downloaded clothing image into the dressing app by clicking the add button on the first window of the dressing app. In a possible implementation, the add button is displayed on the first window; in response to the user clicking the add button, the fourth clothing and the attributes of the fourth clothing are displayed on the first window. The fourth clothing includes the captured clothing image or downloaded clothing image imported by the user.

[0091] For example, as shown in the attached Fig. 9 As shown in (a) of FIG. 1 , when the user wants to import a photographed clothing image or a downloaded clothing image, an add button is displayed on the suggestion card or the first window 502 of the outfit app, and a text “Please import clothing images” is also displayed. The user clicks the add button, as shown in FIG. Fig. 9 As shown in (b) in the figure, an image of imported clothing and attributes of the imported clothing are displayed on the suggestion card or the first window 502 of the dressing app, for example, an image of a T-shirt and attributes of the T-shirt: upper body clothing, T-shirt, casual, outerwear, >25°, short sleeves, round neck, solid color, blue, etc.

[0092] After the user imports the photographed clothing image or the downloaded clothing image into the outfit app, if the user imports incorrectly or is not satisfied with the imported image, the imported clothing can be deleted. The user can delete the imported clothing by clicking the delete button on the outfit app window. In one possible implementation, a delete button is displayed on the first window; in response to the user clicking the delete button, the fourth clothing and the attributes of the fourth clothing are not displayed on the first window.

[0093] For example, as shown in the attached Fig.10 As shown in (a) of FIG. 1 , when the user wants to delete the imported clothing image, a delete button is displayed on the suggestion card or the first window 502 of the outfit app, and the delete button is clicked, as shown in the attached figure. Fig.10 As shown in (b) in FIG. 5 , the clothing and its attributes are not displayed on the suggestion card or the first window 502 of the dressing app. For example, the add button and the text “Please import clothing images” are displayed again.

[0094] After the user imports the photographed clothing image or the downloaded clothing image into the dressing app, if the user finds that the imported clothing attributes are displayed incorrectly, the user can also edit the attributes of the clothing. The user can edit the attributes of the clothing by clicking the edit button on the dressing app window. In a possible implementation, an edit button is also displayed on the first window; in response to the user clicking the edit button, the attributes of the fourth clothing are displayed on the first window as editable.

[0095] For example, as shown in the attached Fig.11 As shown in (a) of FIG. 1 , when the user wants to edit the attributes of the imported clothing, an edit button is displayed on the suggestion card or the first window 502 of the outfit app, and the edit button is clicked, as shown in the attached figure. Fig.11 As shown in (b), the attributes of the clothing displayed on the suggestion card or the first window 502 of the dressing app are in an editable state. For example, the user selects one of the attributes to edit through the attribute drop-down button, thereby changing the selected attribute.

[0096] In step S802, the electronic device 100 inputs the clothing into an attribute recognition model.

[0097] This step is to identify the attributes of the imported clothes.

[0098] Step S803: the electronic device 100 obtains the attributes of the clothing.

[0099] After the attributes of the imported clothing are identified, the attributes of the clothing are obtained.

[0100] Step S804: the electronic device 100 archives the electronic wardrobe according to the attributes of the clothing.

[0101] This step is to electronically archive the imported clothing according to the obtained clothing attributes.

[0102] The method for electronically archiving clothing described in the above steps S801-S804 is to import clothing images taken or downloaded by the user into a suggestion card or a dressing app, then input the clothing into an attribute recognition model for attribute recognition, obtain the attributes of the clothing, and finally, electronically archive the clothing according to the attributes of the clothing.

[0103] The attribute recognition model is used to recognize the attributes of the input clothing. Fig.12 As shown, the clothing is input into the CNN network model to obtain the attributes of the clothing, for example, attribute 1, attribute 2, attribute 3...attribute N.

[0104] The clothing matching model is used to calculate the score after matching the selected target clothing. In a possible implementation, the clothing in the database is selected according to the temperature information and activity information to obtain the target clothing; the target clothing includes a first clothing set, a second clothing set and a third clothing set; the first clothing set includes upper body clothing, the second clothing set includes outerwear lower body clothing, and the third clothing set includes inner wear or general-purpose tops or one-piece clothing; the first clothing, the second clothing and the third clothing are matched to obtain a matching combination; the first clothing is any clothing in the first clothing set, the second clothing is any clothing in the second clothing set, and the third clothing is any clothing in the third clothing set; the matching combination is encoded to obtain a first matching combination feature vector; the first matching combination feature vector is input into the clustering neural network model to obtain the matching score of the matching combination.

[0105] In a possible implementation, based on temperature information and activity information, or based on temperature information, activity information and historical dressing combinations, clothing in a database is screened to obtain target clothing; the target clothing includes a first clothing set, a second clothing set and a third clothing set; the first clothing set includes upper body clothing, the second clothing set includes outer lower body clothing, and the third clothing set includes inner wear or general-purpose tops or jumpsuits; the first clothing, the second clothing and the third clothing are matched to obtain a dressing combination; the first clothing is any piece of clothing in the first clothing set, the second clothing is any piece of clothing in the second clothing set, and the third clothing is any piece of clothing in the third clothing set; the dressing combination is encoded to obtain a first dressing combination feature vector; the first dressing combination feature vector is input into a clustering neural network model to obtain a dressing score of the dressing combination.

[0106] For example, as shown in the attached Fig.13As shown, first, the clothes in the database are conditionally screened, for example, the above-mentioned applicable temperature attribute and style attribute are used to obtain the target clothes. Secondly, the target clothes are divided into data sets according to the clothing attributes. In an embodiment of the present application, the target clothes can be divided into data sets according to attributes such as clothing, category, purpose and applicable temperature. In a possible implementation, the data set can be three or four, and the embodiment of the present application does not limit the number of data sets. The data set includes three data sets, namely, the first clothing set, the second clothing set and the third clothing set, the first clothing set includes outer upper body clothing, the second clothing set includes outer lower body clothing, and the third clothing set includes inner / general tops / jumpsuit sets, that is, inner upper body clothing, general upper body clothing, inner jumpsuit clothing or general jumpsuit clothing. Then, a piece of clothing is arbitrarily selected from the three data sets in a traversal manner to form a set of dressing combinations, which includes the first clothing, the second clothing and the third clothing. Then, the first clothing, the second clothing and the third clothing in a set of dressing combinations are encoded according to the same rule to obtain the feature vector of each set of dressing combinations, that is, the first dressing combination feature vector. Finally, all the first dressing combination feature vectors are input into the clustering neural network model to calculate the scores and obtain the dressing score of each dressing combination.

[0107] In one possible implementation, the training process of the clustering neural network model includes: obtaining the attribute vector of the first clothing, the attribute vector of the second clothing, and the attribute vector of the third clothing from the database; each dimension of the attribute vector is used to characterize the value of an attribute of the clothing; the clustering neural network model is trained based on the second dressing combination feature vector and the corresponding dressing score; the second dressing combination feature vector includes the attribute vector of the first clothing, the attribute vector of the second clothing, and the attribute vector of the third clothing.

[0108] For example, as shown in the attached Fig.14 As shown in FIG. 1 , first, the attribute vector of each piece of clothing in the database is obtained. Specifically, each piece of clothing in the database is input into the Fig.12 In the CNN network model in , the attribute vector of the corresponding clothing is obtained, for example, attribute 1, attribute 2, attribute 3, ... attribute N, N is a positive integer, N>=1. Specifically, referring to Table 1, for example, the clothing attribute is the first dimension, the category attribute is the second dimension, the style attribute is the third dimension, the use attribute is the fourth dimension, the applicable temperature attribute is the fifth dimension, the sleeve length attribute is the sixth dimension, the collar type attribute is the seventh dimension, the style attribute is the eighth dimension, the color attribute is the ninth dimension, etc.

[0109] Secondly, each dimension in each attribute vector is encoded to obtain the encoded attribute features. The encoded attribute features are actually the values ​​of each dimension of the attribute vector, i.e., the encoded values, for example, attribute 1 features, attribute 2 features, attribute 3 features, ... attribute N features, where N is a positive integer, N>=1. Specifically, referring to Table 1, for example, in the first dimension of clothing attributes, upper body clothing is encoded as 0, lower body clothing is encoded as 1, jumpsuit is encoded as 2, accessories are encoded as 3, shoes are encoded as 4, and others are encoded as 5, etc. In the second dimension of category attributes, T-shirts are encoded as 0, POLO shirts are encoded as 1, shirts are encoded as 2, long shirts are encoded as 3, cotton coats are encoded as 4, down jackets are encoded as 5, trousers are encoded as 6, overalls are encoded as 7, cropped pants are encoded as 8, short pants are encoded as 9, vests are encoded as 10, jackets are encoded as 11, dresses are encoded as 12, skirts are encoded as 13, short skirts are encoded as 14, and others are encoded as 15, etc. …In the fourth dimension of usage attributes, inner wear is coded as 0, outer wear is coded as 1, general use is coded as 2, others are coded as 3, and so on. …In the ninth dimension of color attributes, red is coded as 0, yellow is coded as 1, blue is coded as 2, green is coded as 3, gray is coded as 4, others are coded as 5, and so on.

[0110] Again, the encoded attribute vectors are spliced ​​according to attribute features such as clothing, category and purpose to obtain a combination feature vector including the attribute feature sequence of the first clothing, the attribute feature sequence of the second clothing and the attribute feature sequence of the third clothing. Specifically, refer to Table 1, and use vector representation. Exemplarily, the attribute feature sequence of the first clothing is 0 1 21 2 0 1 1 3, indicating the attribute vectors of upper body clothing, POLO shirt, jeans, outer wear, 15°-20°, long sleeves, lapel, cartoon, and green. Since the first clothing includes outer upper body clothing, the first dimension is encoded as 0 and the fifth dimension is encoded as 1. The attribute feature sequence of the second clothing is 1 6 4 1 1 3 6 2 1, indicating the attribute vectors of lower body clothing, trousers, business casual, outer wear, 10°-15°, other, round neck, stripes, and yellow. Since the second clothing includes outer lower body clothing, the first dimension is encoded as 1, the second dimension is encoded as 6-8, and the fifth dimension is encoded as 1. The attribute feature sequence of the third clothing item is 2 12 6 0 2 1 2 5 2, which represents the attribute vectors of jumpsuit, dress, ethnic, inner wear, 15°-20°, short sleeve, V-neck, pattern print, and blue. Since the third clothing item includes an inner wear / general top / jumper set, the first dimension is encoded as 2, and the fifth dimension is encoded as 0 or 2. Then, the attribute feature sequence of the first clothing item, the attribute feature sequence of the second clothing item, and the attribute feature sequence of the third clothing item are combined into a second outfit combination feature sequence. Exemplarily, the second outfit combination feature sequence formed by combining the attribute feature sequence of the first clothing item, the attribute feature sequence of the second clothing item, and the attribute feature sequence of the third clothing item described above is: 0 1 2 1 2 0 1 1 3 1 6 4 1 1 3 6 2 1 2 12 6 0 2 1 2 5 2 Next, the second outfit combination feature sequence is input into the clustering algorithm to calculate the corresponding outfit score. The parameter of the clustering algorithm satisfies the number of samples S within a certain threshold from the cluster center point.

[0111] In a possible implementation, the number of samples S may be 3000 or 2000. The embodiment of the present application does not limit the number of samples S.

[0112] The more the number of clustered samples S is, the finer the classification of outfits is, and the fewer the number of clustered samples S is, the coarser the classification of outfits is. In the embodiment of the present application, considering the fineness of the classification of outfits, the number of samples S is set to be greater than or equal to 3000.

[0113] In a possible implementation, the clustering algorithm may be a K-MEANS algorithm or a mean shift clustering algorithm. The embodiment of the present application does not limit the clustering algorithm.

[0114] In the clustering algorithm, the dressing score is related to the number of samples S and the distance value d, using the following expression (1): Dress score = Formula (1).

[0115] Finally, the clustering neural network model is trained based on the second dressing combination feature vector and the corresponding dressing score until the preset training end condition is met, thereby obtaining a trained clustering neural network model.

[0116] Step S402, in response to the user clicking on the target outfit combination, displaying the first N outfit combinations in order of outfit scores or displaying an enlarged picture of the target outfit combination on the first window; the outfit combinations include the target outfit combination.

[0117] In the case where the first window is a suggestion card, the operation in response to the user clicking on the target outfit combination includes two cases: 1) Clicking on the target outfit combination is clicking on the suggestion in the notification of the electronic device 100, and the first N outfit combinations are displayed in the first window in the order of outfit scores. Figure 5 As shown in (a) of FIG. 1 , when the user wants to view a specific outfit combination, the user clicks on the first window 502 of the suggestion card in the notification of the electronic device 100, for example, clicks on the long-sleeved dress ranked first, i.e., the outfit score is 98, as shown in FIG. Figure 5As shown in (b) in the figure, the first N outfit combinations are displayed in the first window 502 of the suggestion card in the order of outfit scores, for example, the first set: long-sleeved dress, score 98; the second set: long-sleeved suit, score 94; the third set: long-sleeved upper body, jeans lower body, score 92, and the text "Today's outfit recommendation" is also displayed; the second type, after the outfit combinations are displayed in the first window 502 of the suggestion card in the order of outfit scores, clicking on the target outfit combination is to click on any outfit combination in the first N outfit combinations displayed in the order of outfit scores, and an enlarged image of the target outfit combination is displayed in the first window. Exemplary, as shown in the attached Figure 5 As shown in (b) of FIG. 1 , when the user wants to view a specific outfit combination, he clicks on any outfit combination in the first window 502 of the suggestion card, for example, he clicks on the long-sleeved dress that ranks first, i.e., the outfit score is 98, as shown in FIG. Figure 5 As shown in (c) in FIG. 1 , an enlarged image of a long-sleeved dress having a dressing score of 98 is displayed on the first window 502 of the suggestion card, for example, an enlarged image of the long-sleeved dress.

[0118] In the case where the first window is a dressing app, after the dressing combinations are displayed in the first window in the order of dressing scores, clicking on the target dressing combination is to click on any of the first N dressing combinations displayed in the order of dressing scores, and an enlarged image of the target dressing combination is displayed in the first window. Figure 6 As shown in (b) in FIG. 1 , when the user wants to view a specific outfit combination, he clicks on any outfit combination in the first window 502 of the outfit app, for example, he clicks on the long-sleeved dress that ranks first, i.e., the outfit score is 98, as shown in FIG. Figure 6 As shown in (c) in FIG. 1 , an enlarged image of a long-sleeved dress with a dressing score of 98 is displayed on the first window 502 of the suggestion card. Figure 6 As shown in (e) in FIG. 1 , when the user wants to view a specific outfit combination, he clicks on any outfit combination in the first window 502 of the outfit app, for example, he clicks on the top T-shirt and bottom jeans which are ranked second and have an outfit score of 93, as shown in FIG. Figure 6 As shown in (f) in the figure, an enlarged picture of a T-shirt for the upper body and jeans for the lower body with a dressing score of 93 is displayed on the first window 502 of the dressing app.

[0119] In the case where clicking on a target outfit combination displays any of the first N outfit combinations in order of outfit scores, in a possible implementation, the target outfit combination can be clicked by clicking on the score or by clicking on the outfit combination image. The embodiment of the present application does not limit the method of clicking on the target outfit combination.

[0120] After the outfit combinations are displayed in the first window in order of the outfit scores, click on any outfit combination, i.e., the target outfit combination, to enter the detailed interface of the target outfit combination. At this time, an enlarged image of the target outfit combination is displayed in the first window.

[0121] In one possible implementation, after the user clicks on a target outfit combination, an enlarged view of the target outfit combination includes an outfit combination image and may also include attributes of the target outfit combination. The embodiment of the present application does not limit the content of the enlarged view of the target outfit combination.

[0122] In the embodiments of the present application, for example, as shown in the attached Figure 7 As shown, the user selects the target outfit combination, and today's outfit combination is recommended on the first window.

[0123] The dressing method described in steps S401-S402 above is to intelligently display dressing combinations in the order of dressing scores through temperature information and activity information, or temperature information, activity information and historical dressing combinations, and recommend daily dressing combinations to users. And the clothes input by the user can be intelligently archived according to the attributes of the clothes. Therefore, it is possible to intelligently manage clothes and recommend daily dressing, improve the accuracy of dressing recommendations, save users' time and energy, and thus improve user experience.

[0124] The dressing method provided in the embodiments of the present application can intelligently manage clothing and recommend daily outfits, improve the accuracy of outfit recommendations, save users' time and energy, and thus improve user experience.

[0125] It is understandable that in order to implement the above functions, the electronic device includes hardware and / or software modules corresponding to the execution of each function. In combination with the algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application in combination with the embodiments, but such implementation should not be considered to be beyond the scope of the present application.

[0126] In this embodiment, the electronic device can be divided into functional modules according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0127] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program code is stored. When the processor executes the computer program code, the electronic device executes the relevant method steps in the method embodiment.

[0128] The embodiment of the present application also provides a computer program product. When the computer program product is run on a computer, it enables the computer to execute the relevant method steps in the above method embodiment.

[0129] Among them, the electronic device, computer storage medium or computer program product provided in this application is used to execute the corresponding method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method provided above, and will not be repeated here.

[0130] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0131] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0132] The units described above as separate components may or may not be physically separated, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0133] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The functions of the above-mentioned integrated units may be implemented in the form of hardware or in the form of software functional units.

[0134] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that makes the contribution or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium, including a number of instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute all or part of the steps of the above-mentioned method of each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0135] The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application shall be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A dressing method, characterized in that: The method comprises: The dressing combinations are displayed in the first window in the order of dressing scores; the dressing scores are determined according to temperature information and activity information; the temperature information is used to indicate the applicable temperature of the dressing combination; and the activity information is used to indicate the style attributes of the dressing combination.

2. The dressing method according to claim 1, characterized in that: The activity information is obtained online or through user input.

3. The dressing method according to claim 2, characterized in that: The method further comprises: In response to a user clicking on a target outfit combination, the first N outfit combinations are displayed in the first window in the order of the outfit scores or an enlarged picture of the target outfit combination is displayed; N is a positive integer; the outfit combinations include the target outfit combination.

4. The dressing method according to claim 3, characterized in that: The activity information includes at least one of the following: target time, target region, indoor and outdoor, and target activity.

5. The dressing method according to any one of claims 1 to 4, characterized in that: The dressing score is determined according to the temperature information and the activity information, including: According to the temperature information and the activity information, clothing in the database is screened to obtain target clothing; the target clothing includes a first clothing set, a second clothing set, and a third clothing set; the first clothing set includes outer upper body clothing, the second clothing set includes outer lower body clothing, and the third clothing set includes inner upper body clothing, general upper body clothing, inner one-piece clothing, or general one-piece clothing; The first clothing, the second clothing, and the third clothing are matched to obtain the outfit combination; the first clothing is any clothing in the first clothing set, the second clothing is any clothing in the second clothing set, and the third clothing is any clothing in the third clothing set; Encoding the outfit combination to obtain a first outfit combination feature vector; The first dressing combination feature vector is input into a clustering neural network model to obtain a dressing score of the dressing combination.

6. The dressing method according to claim 5, characterized in that: The training process of the clustering neural network model includes: Acquire the attribute vector of the first clothing, the attribute vector of the second clothing, and the attribute vector of the third clothing from the database; each dimension of the attribute vector is used to represent a value of an attribute of clothing; The clustering neural network model is trained based on a second dressing combination feature vector and a corresponding dressing score; the second dressing combination feature vector includes an attribute vector of the first clothing item, an attribute vector of the second clothing item, and an attribute vector of the third clothing item.

7. The dressing method according to claim 6, characterized in that: The dressing score is also determined based on historical dressing combinations.

8. The dressing method according to claim 7, characterized in that: The method further comprises: Displaying an add button on the first window; In response to the user clicking the add button, a fourth clothing item and attributes of the fourth clothing item are displayed on the first window.

9. The dressing method according to claim 8, characterized in that: The method further comprises: Displaying a delete button on the first window; In response to the user clicking the delete button, the fourth clothing item and the attributes of the fourth clothing item are not displayed on the first window.

10. The dressing method according to claim 8, characterized in that: The method further comprises: An edit button is also displayed on the first window; in response to the user clicking the edit button, the attributes of the fourth clothing item are displayed on the first window in an editable state.

11. An electronic device, characterized in that: It includes a memory and one or more processors, wherein the memory stores computer program code, and the computer program code includes computer instructions. When the computer instructions are executed by the processor, the electronic device executes the dressing method as described in any one of claims 1 to 10.

12. A computer-readable storage medium, characterized in that: It includes computer instructions, and when the computer instructions are executed on an electronic device, the electronic device executes the dressing method as described in any one of claims 1 to 10.

13. A computer program product, characterized in that When the computer program product runs on an electronic device, the electronic device executes the dressing method as described in any one of claims 1 to 10.

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