Information processing device, method, and program

Abstract

The present invention provides an information processing device, a method, and a program capable of contributing to promotion of sales of image data. This information processing device comprises a processor. The processor acquires first information including information on evaluation of an image represented by first image data and the first image data. The processor analyzes the first image data and classifies the first image data into a plurality of categories. The processor calculates an evaluation value for each category on the basis of the first information. The processor generates second information relating to second image data on the basis of the evaluation values.

Description

Information processing device, method, and program

[0001] The present invention relates to an information processing device, method, and program, and more particularly to an information processing device, method, and program for processing information relating to the sale of image data.

[0002] Patent Document 1 describes an imaging system that provides information useful for photography, which includes a setting unit that sets a request representing the photo that the user intends to take, a transmitting unit that transmits the request set by the setting unit to a learning device, a learning device that extracts images from an image database that match the request and have received a predetermined evaluation from a third party, performs machine learning using the extracted images, and outputs an inference model, a receiving unit that receives the inference model output from the learning device, and a display unit that displays the inference results performed using the inference model.

[0003] Patent Document 2 describes a system that provides advice on photographic composition tailored to the community being evaluated, and that includes a learning means that learns evaluations of the composition of multiple images posted on a social networking service (SNS), an extraction means that analyzes images captured on a terminal operated by a user and extracts feature information, and a notification means that, when a composition is tentatively specified by the user's operation, notifies the user of information indicating the evaluation that is expected to be given on the SNS for an image captured in accordance with the composition based on the extracted feature information.

[0004] JP 2019-114222 A JP 2021-77131 A

[0005] One embodiment of the technique of the present disclosure provides an information processing device, method, and program that can contribute to promoting sales of image data.

[0006] (1) An information processing device comprising a processor, the processor acquiring first information including first image data and evaluation information for an image represented by the first image data, analyzing the first image data and classifying it into a plurality of categories, calculating an evaluation value for each category based on the first information, and generating second information for the second image data based on the evaluation values.

[0007] (2) The information processing device according to (1), wherein the second information is information that contributes to promoting sales.

[0008] (3) An information processing device according to (1) or (2), wherein the first information includes information indicating that the image represented by the first image data has been gazed at, selected, or added to a cart.

[0009] (4) The information processing device according to any one of (1) to (3), wherein the shorter the period between the start of sales of the image represented by the first image data and the purchase, the higher the evaluation is given.

[0010] (5) The information processing device according to any one of (1) to (4), wherein the first information includes sales amount information as evaluation information.

[0011] (6) The information processing device according to (5), wherein the evaluation value is an average value of sales.

[0012] (7) An information processing device described in any one of (1) to (6), wherein the first information includes information on the subject and / or photographer, and the processor weights the evaluation information based on the information on the subject and / or photographer to calculate an evaluation value.

[0013] (8) The information processing device according to any one of (1) to (7), wherein the second information is information on the priority of publication when multiple second image data are sold.

[0014] (9) An information processing device described in (8), wherein the first information includes information on the date and time of sale, and the processor generates statistical information of ratings based on the date and time of sale for each category, and generates second information based on the statistical information of ratings.

[0015] (10) An information processing device according to any one of (1) to (7), wherein the categories are classified based on composition and / or pose, and the second information is information on recommended composition and / or pose.

[0016] (11) An information processing device described in (10), in which the processor extracts compositions and / or poses whose evaluation value is above a threshold or whose ranking of the evaluation value is above a threshold, and generates information on the extracted compositions and / or poses as second information.

[0017] (12) An information processing device described in (10) or (11), in which the processor acquires information on compositions and / or poses that have been sold, and generates information on unsold compositions and / or poses from the extracted compositions and / or poses as second information.

[0018] (13) An information processing device described in any one of (10) to (12), wherein the processor extracts compositions and poses whose evaluation value is above a threshold or whose ranking of evaluation value is above a threshold, and generates information combining the extracted compositions and poses as second information.

[0019] (14) An information processing device described in any one of (10) to (13), in which the processor acquires information on the number of people to be photographed at one time, extracts compositions and / or poses whose evaluation value is above a threshold or whose evaluation value ranking is above a threshold, and generates information on compositions and / or poses corresponding to the number of people as second information based on the extracted information on compositions and / or poses.

[0020] (15) An information processing device described in any one of (1) to (14), wherein the categories are classified based on composition and / or pose, and the second information is information on the combination of composition and / or pose when generating a collage image.

[0021] (16) An information processing method that acquires first information including first image data and evaluation information for an image represented by the first image data, analyzes the first image data and classifies it into multiple categories, calculates an evaluation value for each category based on the first information, and generates second information for the second image data based on the evaluation values.

[0022] (17) An information processing program that causes a computer to perform the following functions: acquire first information including evaluation information on first image data and an image represented by the first image data; analyze the first image data and classify it into multiple categories; calculate an evaluation value for each category based on the first information; and generate second information for second image data based on the evaluation value.

[0023] Conceptual diagram of an image data sales service Block diagram showing an example of the system configuration of an image data sales system Block diagram showing an example of the hardware configuration of a sales server Block diagram showing an example of the hardware configuration of a database server Block diagram showing an example of the hardware configuration of an information processing server Block diagram showing an example of the hardware configuration of a first user terminal Block diagram showing an example of the hardware configuration of a second user terminal Block diagram showing an example of the hardware configuration of a printer Block diagram of main functions of the first user terminal Diagram showing an example of an operation screen when uploading image data to be sold Diagram showing an example of an operation screen when uploading image data to be sold Diagram showing an example of an operation screen when uploading image data to be sold Main functions of the second user terminal 1. Block diagram of various functions. 2. Diagram showing an example of a screen display when viewing image data currently on sale. 3. Diagram showing an example of a screen display when viewing image data currently on sale. 4. Diagram showing an example of a screen display when viewing image data currently on sale. 5. Diagram showing an example of a display screen during printing. 6. Diagram showing an example of a display screen after printing is completed. 7. Block diagram of main functions of the sales server. 8. Block diagram of main functions of the information processing server. 9. Conceptual diagram of generation of disclosure determination information. 10. Block diagram of main functions of the sales processing unit regarding disclosure determination processing. 11. Conceptual diagram of a method for determining the display order based on disclosure determination information. 12. Flowchart of disclosure determination operation. 13. Block diagram of main functions of the image data sales system regarding generation and provision of recommendation information. 14. Diagram showing an example of display of recommendation information on a first user terminal. 15. Diagram showing an example of a collage image.

[0024] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0025] First Embodiment Here, an example in which the present invention is applied to a system that provides the following services will be described.

[0026] FIG. 1 is a conceptual diagram of the service.

[0027] This service sells image data for printing online. The service accepts image data from users (first users) who wish to sell the image data, publishes the accepted image data online, and sells it online to users (second users) who wish to purchase it. Users (second users) who purchase the image data download the image data themselves and print it. By printing, a photograph (an image represented by the image data recorded on a recording medium such as photographic paper or film) is finally obtained.

[0028] As shown in FIG. 1, a first user U1 who wishes to sell image data uploads the image data to be sold to a sales server 10 using a first user terminal 100 such as a smartphone.

[0029] The sales server 10 records the image data uploaded by the first user U1 in the database server 20. The sales server 10 also makes the image data recorded in the database server 20 available online and sells it online.

[0030] A second user U2 who wishes to purchase image data uses a second user terminal 200 such as a smartphone to view the published image data. The second user U2 also uses the second user terminal 200 to purchase the published image data.

[0031] The image data can be downloaded by purchasing it. The second user U2 uses the second user terminal 200 to download the image data from the sales server 10 and prints it on the printer 300. By printing, a printed photograph 400 is obtained.

[0032] This service is primarily used in the entertainment, music, and other fields when singers, actors, entertainers, etc. (first user U1) sell image data for printing to their fans (second user U2). For convenience, singers, actors, entertainers, etc. will be referred to simply as entertainers below. Talents include so-called idols. Idols generally refer to young entertainers who are popular among young people.

[0033] However, with this type of service, even if the same person is selling image data, sales may vary depending on the content, how it is made public, and so on.

[0034] However, it is difficult to determine or identify the factors that caused the difference in sales, especially for users who are not familiar with sales.

[0035] The image data sales system of this embodiment is a system that accepts image data for printing from users and sells the data, and is a system that can promote the sale of image data.

[0036] [System Configuration of Image Data Sales System] FIG. 2 is a block diagram showing an example of the system configuration of an image data sales system.

[0037] The image data sales system 1 of this embodiment is configured as a system that accepts image data provided by users (first users) who wish to sell image data, publishes the accepted image data, and sells it to users (second users) who wish to purchase it. The users (second users) who purchase the image data print the image data themselves.

[0038] For example, when a celebrity sells image data for printing, the celebrity becomes the first user and the celebrity's fans become the second users.

[0039] As shown in Figure 2, the image data sales system 1 is mainly composed of a sales server 10, a database server 20, an information processing server 30, a first user terminal 100 used by a first user U1, a second user terminal 200 used by a second user U2, and a printer 300, etc.

[0040] The sales server 10 and the first user terminal 100 are communicatively connected via a network 2. Similarly, the sales server 10 and the second user terminal 200 are communicatively connected via the network 2. The network 2 is constructed by, for example, wireless communication networks such as 4G (4th Generation), 5G (5th Generation), WiMAX (Worldwide Interoperability for Microwave Access), and LTE (Long Term Evolution), base stations, the Internet, etc.

[0041] The sales server 10, the database server 20, and the information processing server 30 are connected to each other via wired or wireless communication. As an example, in this embodiment, the sales server 10, the database server 20, and the information processing server 30 are connected via a LAN (Local Area Network).

[0042] The second user terminal 200 and the printer 300 are connected to each other so as to be able to communicate with each other via a wired or wireless connection. As an example, in this embodiment, the second user terminal 200 and the printer 300 are connected to each other wirelessly via Bluetooth (registered trademark).

[0043] [Hardware Configuration of Sales Server] FIG. 3 is a block diagram showing an example of the hardware configuration of the sales server.

[0044] The sales server 10 has a configuration as a general server computer, that is, it has a processor 11, a main memory unit 12, an auxiliary memory unit 13, an operation unit 14, a display unit 15, an interface unit 16, and the like.

[0045] The processor 11 executes programs and functions as various processing units. As an example, in this embodiment, the processor 11 is configured as a CPU (Central Processing Unit). Various programs and data executed by the processor 11 are stored in the main memory unit 12 and / or the auxiliary memory unit 13. The term "program" is synonymous with "software."

[0046] The main storage unit 12 includes a RAM (Random Access Memory) and a ROM (Read Only Memory). The RAM is used as a work area for the processor 11. The ROM stores basic input / output programs and the like.

[0047] The auxiliary storage unit 13 is configured by, for example, a hard disk drive (HDD), a solid state drive (SSD), or the like.

[0048] The operation unit 14 is composed of, for example, a keyboard, a mouse, and the like.

[0049] The display unit 15 is configured by, for example, a liquid crystal display (LCD), an organic electroluminescence diode display (OLED display), or the like.

[0050] The interface unit 16 includes a communication interface for connecting the sales server 10 to the network 2, a communication interface for connecting the sales server 10 to the database server 20, and a communication interface for connecting the sales server 10 to the information processing server 30.

[0051] [Hardware Configuration of Database Server] FIG. 4 is a block diagram showing an example of the hardware configuration of a database server.

[0052] The database server 20 has the same configuration as a general server computer as the sales server 10. That is, it has a processor 21, a main memory unit 22, an auxiliary memory unit 23, an operation unit 24, a display unit 25, and an interface unit 26. The configuration of each unit is substantially the same as that of the sales server 10, so a description thereof will be omitted.

[0053] [Hardware Configuration of Information Processing Server] FIG. 5 is a block diagram showing an example of the hardware configuration of the information processing server.

[0054] The information processing server 30 has the same configuration as a general server computer as the sales server 10. That is, it has a processor 31, a main memory unit 32, an auxiliary memory unit 33, an operation unit 34, a display unit 35, and an interface unit 36. The configuration of each unit is substantially the same as that of the sales server 10, so a description thereof will be omitted.

[0055] [Hardware Configuration of First User Terminal] The first user terminal 100 is configured as a computer with a communication function. Preferably, it is configured as a mobile computer such as a smartphone or a tablet terminal. More preferably, it is configured as a mobile computer with a camera function (photographing function). As an example, in this embodiment, the first user terminal 100 is configured as a smartphone with a camera function.

[0056] Fig. 6 is a block diagram showing an example of the hardware configuration of the first user terminal 100. Fig. 6 shows an example in which the first user terminal 100 is configured as a smartphone.

[0057] As shown in FIG. 6, the first user terminal 100 includes a processor 101, a main memory unit 102, an auxiliary memory unit 103, a display unit 104, an operation unit 105, a GPS (Global Positioning Systems) receiving unit 106, a camera unit 107, an audio input unit 108, an audio output unit 109, a communication unit 110, a short-range wireless communication unit 111, and a sensor unit 112.

[0058] The processor 101 executes programs and functions as various processing units. As an example, in this embodiment, the processor 101 is configured as a CPU. Various programs and data executed by the processor 101 are stored in the main memory unit 102 and / or the auxiliary memory unit 103.

[0059] The main memory unit 102 includes a RAM and a ROM. The RAM is used as a work area for the processor 101. The ROM stores a basic input / output program and the like.

[0060] The auxiliary storage unit 103 is configured, for example, by a flash memory such as an EEPROM (Electrically Erasable and Programmable ROM).

[0061] The display unit 104 is configured, for example, by a liquid crystal display, an organic EL display, or the like.

[0062] The operation unit 105 includes a touch panel and various operation buttons. The touch panel detects touch operations on the screen of the display unit 104.

[0063] The GPS receiving unit 106 receives a GPS signal including location information of the first user terminal 100 .

[0064] The camera unit 107 includes a photographing lens and an image sensor, and electronically captures images.

[0065] The audio input unit 108 includes a microphone and receives audio input.

[0066] The audio output unit 109 includes a speaker and outputs audio.

[0067] The communication unit 110 uses an antenna to wirelessly communicate with the nearest base station or the like.

[0068] The short-range wireless communication unit 111 uses an antenna to communicate with an external device by short-range wireless communication.

[0069] The sensor unit 112 includes various sensors such as a geomagnetic sensor, a gyrocompass, and an acceleration sensor.

[0070] [Hardware Configuration of Second User Terminal] The second user terminal 200 is configured as a computer equipped with a communication function. Preferably, it is configured as a mobile computer such as a smartphone or a tablet terminal. As an example, in this embodiment, the second user terminal 200 is configured as a smartphone.

[0071] Fig. 7 is a block diagram showing an example of the hardware configuration of the second user terminal 200. Fig. 7 shows an example in which the second user terminal 200 is configured as a smartphone.

[0072] Similar to the first user terminal 100, the second user terminal 200 includes a processor 201, a main memory unit 202, an auxiliary memory unit 203, a display unit 204, an operation unit 205, a GPS receiving unit 206, a camera unit 207, an audio input unit 208, an audio output unit 209, a communication unit 210, a short-range wireless communication unit 211, and a sensor unit 212. The functions of each unit are substantially the same as those of the first user terminal 100, and therefore detailed explanations thereof will be omitted.

[0073] In this embodiment, the second user terminal 200 is connected to the printer 300 via a short-range wireless communication unit 211. The short-range wireless communication unit 211 is connected to the printer 300 by, for example, Bluetooth (registered trademark).

[0074] [Printer Hardware Configuration] The printer 300 accepts a print request from the second user terminal 200, to which it is connected, and prints an image on a recording medium. There are no particular limitations on the printing method or the type of recording medium used. As an example, in this embodiment, the printer 300 is described as a so-called instant film printer. An instant film printer is a printer that uses instant film as the recording medium. In addition, in this embodiment, the printer 300 is described as a so-called mobile printer. A mobile printer is generally a printer that is small, portable, and can be carried around.

[0075] FIG. 8 is a block diagram showing an example of the hardware configuration of a printer.

[0076] As shown in FIG. 8, the printer 300 includes a control unit 301, a print unit 302, a short-range wireless communication unit 303, an operation unit 304, and the like.

[0077] The control unit 301 controls the overall operation of the printer 300. The control unit 301 is configured, for example, by a microcomputer equipped with a processor and memory. The processor is configured, for example, by a CPU. The memory includes RAM, ROM, EEPROM, etc. The ROM and / or EEPROM store programs executed by the processor and various data required for control.

[0078] The printing unit 302 prints an image on an instant film under the control of the control unit 301. The printing unit 302 includes a film loading chamber 302a, a film feeding mechanism 302b, a film transport mechanism 302c, a print head 302d, and the like.

[0079] The film loading chamber 302a is a loading section for instant film. The instant film is loaded into the film loading chamber 302a in the form of, for example, a film pack 310. The film pack 310 is a predetermined cartridge containing instant film. The instant film is stored in a stack of multiple sheets (e.g., 10 sheets) in the cartridge. For example, a mono-sheet type (sheet film system) instant film is used. Note that this type of instant film and the structure of the film pack 310 are well known, for example, as the instant film and film pack 310 used in the instant camera (Instax (registered trademark), product name "Cheki") manufactured by Fujifilm Corporation.

[0080] The film feeding mechanism 302b feeds out the instant film one by one from the film pack 310 loaded in the film loading chamber 302a.

[0081] The film transport mechanism 302c transports the instant film sent out from the film pack 310 by the film sending mechanism 302b.

[0082] The print head 302d is, for example, a line-type exposure head, and records an image by irradiating the exposure surface of the instant film conveyed by the film conveying mechanism 302c with printing light line by line.

[0083] The instant film on which the image is recorded is developed during the transport process and then discharged from a predetermined discharge port.

[0084] The short-range wireless communication unit 303 uses an antenna to communicate with an external device (the second user terminal 200 in this embodiment) by short-range wireless communication. In this embodiment, the printer 300 and the second user terminal 200 are connected to each other so that they can communicate with each other via Bluetooth (registered trademark).

[0085] The operation unit 304 includes a power button and various other operation buttons required for operating the printer 300 .

[0086] The printer 300 may have functions other than printing. For example, it may have a photographing function (camera function) (a so-called camera-equipped printer). A camera-equipped printer functions not only as a so-called external printer but also as a digital camera, and can print captured images on the spot.

[0087] [Functions of the First User Terminal] As described above, the first user terminal 100 is a terminal used by the first user U1. The first user U1 is a person who sells image data using the image data sales system 1. The first user terminal 100 is mainly used to provide the image data to be sold.

[0088] FIG. 9 is a block diagram of the main functions of the first user terminal.

[0089] As shown in FIG. 9, with regard to providing image data for sale, the first user terminal 100 has functions such as an image data acquisition unit 100a, a sales setting information acceptance unit 100b, and an upload processing unit 100c.

[0090] The image data acquisition unit 100a performs a process of acquiring image data to be sold. The image data to be sold is acquired, for example, using the camera unit 107 provided in the first user terminal 100. That is, the image data to be sold is acquired by taking a picture with the camera unit 107. Alternatively, the image data to be sold may be acquired by importing it from an external device. The external device may include an external storage (for example, a memory card) as well as an imaging device (such as a digital camera). Therefore, for example, image data taken with an external digital camera may be used as the image data to be sold. There is no particular limitation on the method of importing image data from an external device.

[0091] The sales setting information receiving unit 100b receives input of various information required for selling image data. The sales setting information includes, for example, information on the sales period set for the image data to be sold, information on the sales price, etc. The sales setting information receiving unit 100b displays a predetermined input screen on the display unit 104 and receives input of the sales setting information from the user.

[0092] The upload processing unit 100c performs a process of uploading image data to be sold and its sales setting information to the sales server 10. The upload processing unit 100c uploads the image data to be sold and its sales setting information by associating them with user identification information. The identification information is, for example, composed of a user account. The user account is set, for example, when the user applies to use a service. When setting up a user account, various information about the user is requested to be input, and the input information is associated with the user account and recorded in the database server 20. For example, information such as ID (Identification), password, account name (name, Roman alphabet, katakana), self-introduction, profile image, birthday, hometown, website URL (Uniform Resource Locator), and SNS URL is requested to be input. A profile image is an image set in the profile. It is usually composed of an image of the user (e.g., a face image).

[0093] The upload is performed in response to an instruction from the first user U1. The upload processing unit 100c displays a predetermined operation screen on the display unit 104 and receives an instruction to upload from the first user U1.

[0094] 10 to 12 are diagrams showing examples of operation screens when uploading image data to be sold.

[0095] FIG. 10 shows an example of a selection screen for selecting a method for acquiring image data.

[0096] FIG. 10 shows an example in which three methods are available for acquiring image data. The first method is to acquire the image by taking a photograph with the first user terminal 100. The second method is to acquire the image from an external camera. The third method is to acquire the image data from captured image data (image data stored in the first user terminal 100). To acquire the image using the first method, tap button IB21. To acquire the image using the second method, tap button IB22. To acquire the image data using the third method, tap button IB23.

[0097] When the first method is selected, the camera unit 107 of the first user terminal 100 is activated, and an image can be taken.

[0098] When the second method is selected, connection settings with an external camera are made, and image data is acquired from the connected camera.

[0099] If the third method is selected, the captured image data (image data stored in the first user terminal 100) is displayed as a list on the screen of the display unit 104, allowing the user to select an image.

[0100] When the image data to be sold is acquired, the screen transitions to the screen shown in FIG.

[0101] FIG. 11 shows an example of a screen for inputting sales setting information.

[0102] FIG. 11 shows an example of inputting color information, comments, sales period information, and sales price information as sales setting information.

[0103] Here, "color information" refers to information that expresses the user's feelings at the time of uploading (posting) using color. In the example shown in FIG. 11, the color is selected from six predetermined colors (white, red, orange, yellow, blue-green, and purple). The default is white. Therefore, if no color is selected, white is automatically selected as the color information.

[0104] "Comment" is a user's comment on the image for sale.

[0105] The "sales period" is the period during which the image data is sold. The start date and time and the end date and time of the sale are specified. The sales period can also be configured to be set automatically. For example, it can be configured to be automatically set to a certain period (for example, 10 minutes) based on the time of upload. Also, for example, it is possible to specify only the start date and time of the sale and have the sales period set automatically. For example, it can be configured to be automatically set to 10 minutes from the specified start date and time.

[0106] "Sales price" refers to the price required to print the image data.

[0107] As shown in Figure 11, the screen has a display field IC11 for the image represented by the image data to be sold, an input field IC12 for color information, an input field IC13 for comments, an input field IC14 for the sales period, and an input field IC15 for the sales price.

[0108] A predetermined frame IC11f is displayed in the image display column IC11, and an image IC11i representing the image data for sale is displayed within the frame IC11f. The frame IC11f is configured as an image that resembles the frame of an instant film. Therefore, the image displayed in the display column IC11 resembles a printout.

[0109] In this example, image editing is also possible. Tapping the "Edit Image" button IB31 displayed on the screen transitions to an image editing screen, where image editing (processing) becomes possible. While a detailed description of image editing is omitted, the device has a drawing (also called painting) function in addition to general retouching functions (adjusting brightness, saturation, sharpness, cropping, etc.). Therefore, by editing an image, handwritten text such as a signature or a message can be added to the image.

[0110] A list of selectable colors is displayed in the color information input field IC12. Fig. 11 shows an example in which circles filled with selectable colors are displayed in a horizontal row. The user selects a color by tapping the circle of the desired color.

[0111] A predetermined frame is displayed in the comment input field IC13. The user uses the character input function provided in the first user terminal 100 to input a comment into the frame.

[0112] The sales period input field IC14 has input fields for the start date and time and the end date and time of the sale. The user inputs the start date and time and the end date and time of the sale in each input field. The user may input the date and time information, for example, by using a character input function provided in the first user terminal 100. Alternatively, a calendar and a clock may be displayed to allow the user to select the date and time. Alternatively, a pull-down menu may be displayed to allow the user to select the date and time.

[0113] The selling price input field IC15 displays a frame for inputting a price. The user inputs the selling price (the price required for printing) into the frame. The user inputs a numerical value into the frame using the character input function provided in the first user terminal 100. Alternatively, a pull-down menu of selectable numerical values ​​may be displayed to allow selection.

[0114] The sales setting information input screen also displays a button IB32 for confirming the input contents. The confirmation button IB32 is displayed, for example, at the end of the screen (the final position when scrolling). The confirmation button IB32 is enabled when input into all input fields is complete. Therefore, if there are input fields that are not filled in, tapping the confirmation button will not produce any response. Furthermore, the color of the confirmation button IB32 changes when input into all input fields is complete. For example, it changes from gray to black. This allows the user to visually confirm that input into all input fields is complete.

[0115] When input into all input fields is completed and the confirmation button IB32 is tapped, the screen transitions to a confirmation screen for the input contents.

[0116] FIG. 12 shows an example of the confirmation screen.

[0117] As shown in FIG. 12, the input confirmation screen displays the image represented by the image data to be sold and the information entered as sales setting information (color information, comments, sales period and sales price information).

[0118] 12, an upload button IB41 is also displayed on the input content confirmation screen. The upload button IB41 is displayed, for example, at the end of the screen.

[0119] If there are no errors in the input information, the user taps the upload button IB41. Tapping the upload button IB41 instructs the execution of uploading. As a result, the image data to be sold and its sales setting information are uploaded to the sales server 10.

[0120] If there is an error in the entered sales setting information, the user returns to the sales setting information input screen and corrects the entered information in the relevant section.

[0121] In this embodiment, the image data that the first user is selling or intends to sell is an example of second image data.

[0122] [Functions of the Second User Terminal] As described above, the second user terminal 200 is a terminal used by the second user U2. The second user U2 is the person who purchases image data. The second user terminal 200 is mainly used for viewing and purchasing image data. Furthermore, in the system of this embodiment, the purchaser prints the image data themselves. Therefore, the second user terminal 200 is used to download and print the purchased image data.

[0123] FIG. 13 is a block diagram of the main functions of the second user terminal.

[0124] The second user terminal 200 performs processes such as viewing and purchasing image data that is on sale, downloading purchased image data, and printing the downloaded image data on the printer 300. With regard to these processes, the second user terminal 200 has functions such as a viewing processing unit 200a, a purchasing processing unit 200b, a download processing unit 200c, and a print processing unit 200d.

[0125] The browsing processing unit 200a performs processing to browse image data published on the sales server 10 as image data for sale. The image data is published in the same manner as a so-called web page. Therefore, the browsing processing unit 200a has the same functions as a web browser, and causes the display unit 204 to display a page on which the images for sale are displayed in a predetermined format.

[0126] 14 to 16 are diagrams showing examples of screen displays when viewing image data for sale.

[0127] Images are viewed, for example, by seller, i.e., images are displayed by users (first users) who sell the images.

[0128] FIG. 14 shows an example of a display of a so-called home screen (home page).

[0129] The home screen is the first screen displayed after a predetermined user authentication is performed. User authentication is the act of the system identifying the user who has been registered in advance. User authentication itself is a well-known technique, so a detailed explanation will be omitted. For example, user authentication is performed by entering a pre-registered ID and password.

[0130] As shown in FIG. 14, the home screen displays a user display field FC11, a following user display field FC12, a search button FB11, and the like.

[0131] The user display field FC11 displays user information. In this example, the user's name is displayed. The "user" here is a person who uses the second user terminal 200 to view, purchase, etc., image data for sale. Therefore, the user is a second user.

[0132] The following user display field FC12 displays a list of users that the user is following. In this example, the profile images of the users that the user is following are displayed in a list.

[0133] Here, "following" refers to registering a user to be able to view posts from a user that the user likes. Following is essentially synonymous with "favorite."

[0134] The search button FB11 is a button that instructs the user to search for users who are selling image data. Tapping the search button FB11 transitions to a search screen. Since the search itself is a well-known technique, a detailed explanation of it will be omitted here. Transitioning to the search screen allows the user to search for a specific user (seller).

[0135] 14, when one of the profile images of users displayed in the display field FC12 of users being followed is tapped to select it, the screen transitions to a screen (individual user information screen) that displays information about the selected user. Similarly, when a specific user is selected from search results, the screen transitions to the same screen (individual user information screen).

[0136] FIG. 15 shows an example of the display of the individual user information screen.

[0137] As shown in Figure 15, the individual user information screen displays a display field FC21 for seller information, a display field FC22 for profile image, a display field FC23 for information on sales numbers and number of followers, a profile button FB21, a display field FC24 for messages, and a display field FC25 for information on image data currently for sale.

[0138] The seller information display field FC21 is a field where seller information is displayed. In this example, the seller's name is displayed. The seller is a user who is selling image data in this system, and is the first user.

[0139] The profile image display field FC22 is a field where a profile image registered by the seller is displayed.

[0140] The display field FC23 for information on sales and follower count displays information on the total number of image data (sales count) that the seller has sold (posted) to date, and the total number of users (followers) who are following the seller.

[0141] The profile button FB21 is a button for instructing the display of the seller's profile. By tapping the profile button FB21, the seller's profile is displayed. The profile is displayed, for example, by a pull-down or a pop-up.

[0142] A message posted by the seller is displayed in the message display field FC24.

[0143] In the display field FC25 for information on image data for sale, information FC25i on image data for sale is displayed in a list.

[0144] The information FC25i on the image data for sale includes an image FC25i1 represented by the image data for sale, information FC25i2 on the sales period of the image data for sale, information FC25i3 on the sales price of the image data for sale, and information FC25i4 on comments attached to the image data for sale. The sales period information FC25i2, the sales price information FC25i3, and the comment information FC25i4 are displayed adjacent to the image FC25i1 represented by the image data for sale. In the example shown in FIG. 15, the sales period information FC25i2, the sales price information FC25i3, and the comment information FC25i4 are displayed next to the image FC25i1 represented by the image data for sale. Furthermore, the image FC25i1 represented by the image data for sale is displayed within a predetermined frame FC25iF. The frame FC25iF is configured with an image that resembles an instant film frame.

[0145] When there are multiple pieces of image data for sale, the information FC25i of the image data for sale is displayed in a line along the scroll direction of the screen. Therefore, in this embodiment, by scrolling the screen, the information FC25i of the image data for sale is displayed in order.

[0146] The number of pieces of information FC25i of image data for sale that can be displayed at one time is determined by the screen size of the display unit 204, the display size of the image FC25i1, and the like.

[0147] When one of the pieces of information FC25i displayed in the display field FC25 for the information of the image data for sale is tapped, the screen transitions to a screen (detailed display screen) that displays details of the tapped image data. The act of transitioning to the detailed display screen is an example of selecting image data.

[0148] FIG. 16 is a diagram showing an example of the detailed display screen.

[0149] The details display screen is a screen that displays details of the image data selected on the individual user information screen. Displaying the details display screen is an example of closely watching the displayed image data.

[0150] As shown in Figure 16, the detailed display screen displays a display field FC31 for sales period information, a display field FC32 for the image represented by the image data, a display field FC33 for seller information, a display field FC34 for comments, a display field FC35 for sales price information, and a print button FB31, etc.

[0151] Sales period information is displayed in the sales period information display field FC31. In this example, information on the start date and time of the sale and the end date and time of the sale are displayed. Alternatively, information on the end date and time of the sale and the remaining time until the end of the sale may be displayed.

[0152] A predetermined frame FC32f is displayed in the image display field FC32, and an image FC32i represented by image data for printing is displayed within this frame FC32f. The frame FC32f is configured with an image that resembles the frame of an instant film.

[0153] The seller information display field FC33 is a field where seller information is displayed. In this example, the seller's name and an icon image of the seller are displayed. The icon image is, for example, an image of a reduced profile image.

[0154] The comment display field FC34 displays a comment added by the seller when uploading the image data currently displayed on the details display screen.

[0155] The price required to print the image data displayed on the details display screen is displayed in a sales price information display field FC35.

[0156] The print button FB31 is a button for requesting a print of the image data displayed on the details display screen. A print request is made by tapping the print button FB31. A print request is synonymous with expressing an intention to purchase. A print request is also essentially synonymous with adding an image to a cart. The act of requesting a print of image data is another example of looking at and / or selecting the image data.

[0157] In response to the user's expression of intent to purchase (tapping the print button FB31 on the details display screen), the purchase processing unit 200b performs a settlement process with the sales server 10. Since the online settlement process itself is a known technique, a detailed description thereof will be omitted here.

[0158] When the payment process is completed, the image data displayed on the details display screen can be downloaded and printed by the printer 300.

[0159] On the details display screen, at least a part of the background is displayed in a predetermined color, as shown in Fig. 16. The displayed color is the color selected by the seller of the image data displayed on the details display screen when uploading the image data.

[0160] The download processing unit 200c cooperates with the sales server 10 to download image data from the sales server 10 for which payment processing has been completed.

[0161] The print processing unit 200d performs processing to print the downloaded image data in cooperation with the printer 300. Note that the second user terminal 200 is required to be connected to the printer 300 as a prerequisite for the print processing.

[0162] FIG. 17 is a diagram showing an example of a display screen during printing.

[0163] When printing is started by the printer 300, the screen shown in FIG. 17 (printing screen) is displayed on the display unit 204.

[0164] The printing screen displays a message PM1 indicating that printing is in progress. It also displays an animation LA1 (a so-called loading animation) indicating that printing is in progress. In the example shown in Fig. 17, an animation is displayed in which circles (dots) arranged at regular intervals on the same circumference rotate around the circumference.

[0165] In addition, the background of the print screen is partially displayed in a predetermined color, which is the color selected by the seller of the image data being printed when they uploaded the image data.

[0166] FIG. 18 is a diagram showing an example of a display screen after printing is completed.

[0167] When printing is completed by the printer 300, the screen shown in FIG. 18 (print completion screen) is displayed.

[0168] When the printing is completed, the printer 300 outputs that information (print completion notice) to the second user terminal 200. When the second user terminal 200 receives the print completion notice from the printer 300, it causes the display unit 204 to display a print completion screen.

[0169] As shown in Figure 18, the print completion screen displays a message PM2 indicating that printing is complete, a display field FC41 for information about the sales period, a display field FC42 for the printed image, a display field FC43 for reaction buttons, a display field FC44 for information about the seller, a display field FC45 for comments, and an album button FB41.

[0170] In the sales period information display field FC41, information on the sales period for the printed image is displayed.

[0171] A predetermined frame FC42f is displayed in the display field FC42 for the printed image, and the printed image FC42i is displayed within the frame FC42f. The frame FC42f is configured with an image that resembles the frame of an instant film.

[0172] Selectable reaction buttons are displayed in the reaction button display field FC43. The reaction buttons are buttons that allow the purchaser (second user) to express their feelings as a reaction to the printed image. The purchaser taps the reaction button of the image that corresponds to the feeling they want to express.

[0173] The seller information display field FC33 is a field where seller information is displayed. In this example, the seller's name and seller icon image are displayed.

[0174] The comment display field FC45 displays the comment attached to the printed image (the comment entered by the purchaser when uploading).

[0175] The album button FB41 is a button for instructing the activation of the album. The album stores images that the second user has previously printed. The second user can view the images that he or she has previously printed in the album.

[0176] The background of the print completion screen is also displayed in a specific color, which is the color selected by the seller of the printed image data when they uploaded the image data.

[0177] [Functions of the Sales Server] FIG. 19 is a block diagram of the main functions of the sales server.

[0178] The sales server 10 mainly performs processes such as accepting, publishing, and selling image data. As shown in Fig. 19, the sales server 10 has functions such as a data accepting unit 10a, a data recording processing unit 10b, a sales processing unit 10c, a sales management unit 10d, and a recommendation information acquiring unit 10e. The functions of each unit are realized by the processor 11 executing a predetermined program.

[0179] The data accepting unit 10a performs a process of accepting image data provided from the first user terminal 100. Specifically, the data accepting unit 10a performs a process of receiving the image data uploaded from the first user terminal 100 and its sales setting information.

[0180] The data recording processing unit 10b performs processing to record the image data uploaded from the first user terminal 100 and its sales setting information in the database server 20. The uploaded image data and its sales setting information are associated with the identification information (user account) of the user who uploaded the data and recorded in the database server 20.

[0181] The sales processing unit 10c performs a process of publishing the image data recorded in the database server 20 and selling the image data as image data for printing. As described above, the published image data can be viewed and purchased through the second user terminal 200.

[0182] The image data to be printed does not necessarily have to be the image data uploaded by the first user (seller). For example, it may be image data uploaded by the first user that has been resized (with a changed resolution and / or size). It may also be image data converted into an image format that can be printed by the printer 300.

[0183] The sales management unit 10d performs a process of collecting information about the sold image data as sales information at the time the image data is sold and recording it in the database server 20. This is what is known as point of sales (POS) information management. The sales information includes information about the sold image data, the sales price, the date and time of the sale, etc. The sales information can also include information about the purchaser (second user). The purchaser information includes, for example, the purchaser's age, gender, location, number of purchases, etc. The purchaser information can be, for example, information entered by the purchaser when applying to use the system (when issuing an account). This information is recorded in the database server 20 for each user (second user).

[0184] The recommendation information acquisition unit 10e performs processing to acquire recommendation information from the information processing server 30. Here, "recommendation information" refers to information such as actions and settings recommended to promote sales of image data. Recommendation information is an example of second information, and also an example of information that contributes to promoting sales. In this embodiment, disclosure determination information is acquired as recommendation information. "Disclosure determination information" refers to information on the priority order when displaying image data that is on sale. In other words, information on the display order recommended for promoting sales of image data is considered to be disclosure determination information. The recommendation information acquisition unit 10e acquires disclosure determination information as recommendation information. When making image data public, the sales processing unit 10c makes the image data public based on the disclosure determination information acquired as recommendation information. This point will be described in detail later.

[0185] [Functions of Information Processing Server] The information processing server 30 generates recommendation information based on various information recorded in the database server 20. In this embodiment, the information processing server is an example of an information processing device.

[0186] FIG. 20 is a block diagram of the main functions of the information processing server.

[0187] 20 , the information processing server 30 has functions such as a data acquisition unit 30a, an image analysis unit 30b, an evaluation extraction unit 30c, an evaluation value calculation unit 30d, and a recommendation information generation unit 30e. The functions of each unit are realized by the processor 31 executing a predetermined program. In this embodiment, the program executed by the processor 31 is an example of an information processing program.

[0188] The data acquisition unit 30a acquires image data and sales information for the image data from the database server 20. In this embodiment, the data acquisition unit 30a performs a process of acquiring data (image data and sales information for the image data) for all image data recorded in the database server 20. In this embodiment, the image data recorded in the database server 20 is an example of first image data.

[0189] The image analysis unit 30b analyzes the image data acquired by the data acquisition unit 30a and performs a process of classifying the data into multiple categories. As an example, in this embodiment, the image data is classified into multiple categories based on the pose of the subject. That is, the pose of the subject shown in the image data is recognized, and the image data is classified according to the type of pose. More specifically, the image data is classified according to which category (type of pose) it belongs to. For example, the pose of the subject, such as a pose with a hand on the face, a pose with a hand on the head, a pose with a hand on the hip, or a pose with the back turned, is recognized, and the image data is classified according to the type of pose.

[0190] The processing (image classification processing) performed by the image analysis unit 30b can employ so-called artificial intelligence (AI). Specifically, a model (trained model) that has been machine-learned (including deep learning, etc.) using predetermined learning data can be used. In the present embodiment, a trained model that has been machine-learned to classify the type of pose of the subject appearing in the image data can be used. The image analysis unit 30b uses the trained model to recognize the pose of the subject appearing in the image data and output the classification result (the result of determining which category it belongs to). Note that image recognition or image classification using AI is itself a well-known technology. Therefore, detailed description thereof will be omitted.

[0191] The evaluation extraction unit 30c extracts information (evaluation information) evaluating the image represented by the image data from the sales information of the image data. In this embodiment, the sales amount of the image data is extracted as the evaluation information. The sales amount is calculated from the sales quantity and sales price of the image data. In other words, it is calculated as "sales amount = sales quantity x sales price". In this embodiment, the evaluation information is an example of information on the evaluation of the image represented by the first image data. Furthermore, the sales information of the image data is an example of the first information.

[0192] The evaluation value calculation unit 30d calculates an evaluation value for each category classified by the image analysis unit 30b based on the evaluation information extracted by the evaluation extraction unit 30c. As described above, in this embodiment, image data is classified by the type of pose of the subject. Therefore, an evaluation value is calculated for each type of pose. Also, as described above, in this embodiment, sales amount is used as the evaluation information for the image data. Therefore, an evaluation value is calculated based on the sales amount of the image data. In this embodiment, the average sales amount is calculated for each classified type of pose to calculate an evaluation value for each type of pose. In other words, the average sales amount of image data belonging to each category (type of pose) is used as the evaluation value for that category. For example, if there are three pieces of image data belonging to a certain category (type of pose) and the sales amounts of the image data are 10,000 yen, 20,000 yen, and 30,000 yen, respectively, the evaluation value is 20,000.

[0193] The recommendation information generation unit 30e generates recommendation information based on the information on the evaluation value for each category calculated by the evaluation value calculation unit 30d. As described above, in this embodiment, disclosure determination information is generated as recommendation information. Furthermore, in this embodiment, the evaluation value for each category is calculated based on sales, and the average sales value of image data belonging to each category is set as the evaluation value for each category. The disclosure determination information is information on the priority order when displaying image data that is on sale. This information is information on the display order recommended for promoting sales of image data. The recommendation information generation unit 30e generates information on the display priority order recommended for promoting sales of image data based on information on the average sales value of image data belonging to each category. As an example, in this embodiment, categories are ranked in descending order of evaluation value to generate information on the display priority order of categories.

[0194] FIG. 21 is a conceptual diagram of the generation of disclosure determination information.

[0195] FIG. 21 shows an example in which image data is classified into 10 categories (category A to category J) based on the pose of the subject in the image.

[0196] Assume that the evaluation value of Category A is 10,000, the evaluation value of Category B is 15,000, the evaluation value of Category C is 1,000, the evaluation value of Category D is 0, the evaluation value of Category E is 20,000, the evaluation value of Category F is 16,000, the evaluation value of Category G is 8,000, the evaluation value of Category H is 13,000, the evaluation value of Category I is 18,000, and the evaluation value of Category J is 3,000.

[0197] As described above, in this embodiment, the categories are ranked in descending order of evaluation value to generate public determination information. Therefore, in this example, the public determination information is generated with Category E in first place, Category I in second place, Category F in third place, Category B in fourth place, Category H in fifth place, Category A in sixth place, Category G in seventh place, Category J in eighth place, Category C in ninth place, and Category D in tenth place.

[0198] In this way, a plurality of categories are sorted and ranked in descending order of evaluation value, and disclosure determination information indicating the display priority is generated.

[0199] [Disclosure Determination Process] The disclosure determination information generated as described above is used when selling image data of each seller (first user) on the sales server 10. That is, it is used when displaying image data sold by each seller in the display field FC25 on each seller's page (individual user information screen).

[0200] As shown in FIG. 15, the image data sold by each seller is displayed on the individual user information screen in a line along the scroll direction of the screen.

[0201] When displaying the image data of each seller on the individual user information screen, the sales processing unit 10c determines the display order of each image data based on the disclosure determination information, and displays the image data for sale in the display field FC25. The process of determining the display order of image data is called the disclosure determination process.

[0202] FIG. 22 is a block diagram of the main functions of the sales processing unit regarding the disclosure determination process.

[0203] 22, the sales processing unit 10c mainly has functions related to the disclosure determination process, such as an image analysis unit 10c1 and a disclosure determination processing unit 10c2. The functions of each unit are realized by the processor 11 executing a predetermined program.

[0204] The image analysis unit 10c1 analyzes image data and performs processing to classify the image data into a plurality of categories, similar to the image analysis unit 30b of the information processing server 30. The categories to be classified are the same as those of the image analysis unit 30b of the information processing server 30. Therefore, in this embodiment, the image data is classified into a plurality of categories depending on the posing of the subject.

[0205] The disclosure determination processing unit 10c2 performs processing to determine the display order of image data for sale based on disclosure determination information and information on the classification results of each image data category.

[0206] FIG. 23 is a conceptual diagram of a method for determining the display order based on the disclosure determination information.

[0207] 23 shows an example where a seller is selling five image data items ID1 to ID5. Assume that the first image data item ID1 is classified into category E, the second image data item ID2 is classified into category A, the third image data item ID3 is classified into category C, the fourth image data item ID4 is classified into category J, and the fifth image data item ID5 is classified into category B.

[0208] The disclosure determination processing unit 10c2 determines the display order of the image data ID1 to ID5 according to the display priority information for each category indicated in the disclosure determination information. According to the example shown in Fig. 23, the display order of the five image data ID1 to ID5 is set in descending order of priority as follows: first image data ID1, fifth image data ID5, second image data ID2, fourth image data ID4, and third image data ID3. Therefore, when these image data ID1 to ID5 are displayed on the individual user information screen, they are displayed in the order of first image data ID1, fifth image data ID5, second image data ID2, fourth image data ID4, and third image data ID3.

[0209] As described above, in this embodiment, the disclosure determination information is generated based on the sales amount of image data belonging to each category, and is set so that the higher the sales amount, the higher the display position. Therefore, by displaying image data according to the disclosure determination information, sales promotion can be expected.

[0210] [Operation of Image Data Sales System] Here, the disclosure determination operation of the image data sales system 1 of this embodiment will be described.

[0211] FIG. 24 is a flowchart of the disclosure determination operation.

[0212] The disclosure determination process is performed by the sales server 10, but as a preprocessing step, recommendation information is generated by the information processing server 30. In this embodiment, the recommendation information is disclosure determination information.

[0213] The information processing server 30 acquires image data and sales information of the image data from the database server 20 (step S11), and generates recommendation information based on the acquired image data and sales information (step S12).

[0214] In this embodiment, the information processing server 30 analyzes the acquired image data and classifies the image data into multiple categories based on the pose of the subject. Then, an evaluation value is calculated for each category. The evaluation value is calculated based on the average sales amount of the image data belonging to each category. The information processing server 30 ranks the multiple categories in descending order of evaluation value, determines the display priority, and generates disclosure determination information (recommendation information). The generated disclosure determination information is prioritized so that categories with higher sales are displayed higher.

[0215] The sales server 10 acquires recommendation information (publication determination information) from the information processing server 30 (step S21). By acquiring the recommendation information, the information processing server 30 becomes able to perform the publicity determination process. Note that the flow of the publicity determination process shown in FIG. 24 is for a specific first user (seller). That is, the publicity determination process is performed for each first user.

[0216] First, it is determined whether image data has been acquired (step S22), that is, whether the first user who is the seller has uploaded the image data.

[0217] When the image data is acquired, it is determined whether the first user who uploaded the image data is selling multiple pieces of image data including the uploaded image data (step S23).

[0218] If multiple image data including the uploaded image data are for sale, a disclosure determination process is performed (step S24). That is, the display order of the image data is determined based on disclosure determination information, which is recommendation information.

[0219] The sales server 10 displays the information of the image data for sale in the determined display order when displaying the information on the image data for sale on the second user terminal 200. Specifically, when displaying the information on the image data for sale in the display field FC25 on the individual user information screen, the sales server 10 displays the information in the determined display order (see FIG. 15 ).

[0220] If the first user is selling only one image data (if the determination in step S23 is No), there is no need to set a priority order for display, and therefore the disclosure determination process is not performed.

[0221] The sales server 10 determines whether there is image data to be discontinued (step S25). If there is image data to be discontinued, the sales server 10 determines whether there is image data to be sold (step S26). That is, it determines whether there is remaining image data for sale. If there is image data for sale, the process returns to step S23, and it is determined whether multiple image data are for sale. On the other hand, if there is no image data for sale, the process ends.

[0222] As described above, according to the image data sales system 1 of this embodiment, disclosure determination information (recommendation information) is generated based on the information recorded in the database server 20, and the display order of image data sold by each first user is determined based on the generated disclosure determination information. The disclosure determination information is set so that categories with higher sales are displayed higher. Therefore, by displaying image data according to the disclosure determination information, sales can be expected to be promoted.

[0223] [Modifications] [Category Setting] In the above embodiment, the image data is classified into multiple categories based on the pose of the subject, but the setting of the classification categories is not limited to this. Alternatively, for example, the image data may be classified into multiple categories based on the composition, background, scene, etc. That is, the composition, background, scene, etc. of the image represented by the image data are recognized, and the image data are classified into multiple categories (composition type, background type, scene type, etc.) according to the recognized composition, background, scene, etc. Furthermore, the image data may be classified into multiple categories based on the facial expression, clothing, etc. of the subject. That is, the facial expression, clothing, etc. of the subject are recognized, and the image data are classified into multiple categories (facial expression type, clothing type, etc.) according to the recognized facial expression, clothing, etc. Furthermore, a combination of these may be used to classify the image data into multiple categories.

[0224] Furthermore, one image data may be classified into multiple categories. For example, one image data may be recognized by dividing it into pose, clothing, composition, background, etc., and classified into each category according to the recognition results. In this case, one image data is classified into multiple categories from the viewpoints of pose, clothing, composition, background, etc.

[0225] [Evaluation Value] In the above embodiment, the average sales amount of image data belonging to each category is used as the evaluation value for each category, but the evaluation value is not limited to this. Any numerical value that can evaluate each category from the perspective of sales will suffice. For example, the total sales amount of image data belonging to each category, the average or total number of sales of image data belonging to each category, the purchase amount per person of image data belonging to each category (the amount purchased by one second user), etc. can also be used as the evaluation value.

[0226] The evaluation value may also be calculated using weighting. For example, the evaluation information can be weighted using information about the subject and / or photographer. In this case, for example, the sales amount (evaluation information) of each image data item is weighted by the subject and / or photographer to calculate the evaluation value for each category. The information about the subject and / or photographer is, for example, included in the sales setting information of the image data and obtained from the first user at the time of uploading.

[0227] The evaluation value may also be calculated from the perspective of the time period from when the image data goes on sale until it is purchased. That is, the time required from when it goes on sale until it is purchased is calculated as the evaluation of the image, and the average of this time is calculated as the evaluation value for each category. In this case, the shorter the time, the higher the evaluation. That is, the shorter the time from when it goes on sale until it is purchased, the higher the demand is expected to be, and therefore the higher the evaluation will be.

[0228] Alternatively, the time required to sell a predetermined number of image data items may be calculated as the evaluation of the images.

[0229] [Publicity Determination Information] In the above embodiment, the publicity determination information is generated for all image data recorded in the database server 20, but the publicity determination information may also be generated on a per-user basis. That is, the publicity determination information may be generated for each first user. In this case, the publicity determination information is generated based on image data sold by the first user and sales information for that image data. The image data and sales data include both image data that the first user has sold in the past and image data that is currently on sale. By generating publicity determination information for each first user, it is possible to generate publicity determination information appropriate for each first user. That is, it is possible to generate publicity determination information based on the sales trends of each first user.

[0230] Alternatively, image data may be grouped based on multiple perspectives, and disclosure determination information may be generated for each group. For example, image data may be divided into multiple groups based on the attributes (age, gender, occupation, etc.) of the first user selling the image data, and disclosure determination information may be generated for each group. Furthermore, image data may be divided into multiple groups based on the attributes of the second user who purchased the image data, and disclosure determination information may be generated for each group. When multiple disclosure determination information is generated based on the attributes of the second user who purchased the image data, it is preferable that the first user be able to select the disclosure determination information to use. This allows for a display order that is more suitable for the main purchasing demographic. Furthermore, image data may be divided into multiple groups based on the date and time (month, day, time) when the image data was purchased, and disclosure determination information may be generated for each group.

[0231] Furthermore, it is also possible to generate disclosure determination information using artificial intelligence. For example, when image data is classified from multiple perspectives (posing, clothing, composition, background, etc.), it is possible to generate disclosure determination information that combines each of these perspectives using artificial intelligence. Specifically, the image data is classified from the perspectives of posing, clothing, composition, background, etc., and recommended combinations (combinations of posing, clothing, composition, background, etc.) are generated using artificial intelligence based on the classification results and evaluation values. Multiple combinations are generated, ranked, and used as disclosure determination information.

[0232] In the above embodiment, the disclosure determination information is used to determine the display order of image data so that image data is displayed in descending order of priority according to the display priority indicated in the disclosure determination information. However, the disclosure determination information may be used in a non-limiting manner.

[0233] The display order of the image data may be determined so that the image data is displayed in descending order of priority. In this way, by intentionally displaying the image data in descending order of priority (lowest sales), it is possible to equalize sales.

[0234] [Method of Selling Image Data] In the above embodiment, an example was described in which image data was sold for a limited period of time, but image data may be sold indefinitely. Furthermore, when the sales period is limited, the sales period may be limited to a very short period of time. For example, the sales period may be limited to 10 minutes.

[0235] When image data is sold for a limited period of time, the disclosure determination information generated as recommendation information can be generated from the perspective of date and time. For example, the disclosure determination information is generated from the perspective of the time period during which the image data was sold, the month of sale, the date of sale, the day of sale (weekday or holiday), etc.

[0236] When generating disclosure determination information by time period, the average sales amount of image data belonging to each category is calculated by time period. Then, the display priority of each category is determined based on the obtained average sales amount. This makes it possible to generate disclosure determination information by time period. There is no particular limitation on how time periods are divided. In this example, calculating the average sales amount of image data belonging to each category by time period is an example of generating statistical information of evaluations based on sales date and time for each category. Disclosure determination information by sales month, by sales date, and by sales day of the week can also be generated in a similar manner.

[0237] In this way, by generating disclosure determination information from the perspective of date and time, it is possible to set the optimal display depending on the date and time when the image data is sold, for example, depending on the time of sale (morning, afternoon, evening, etc.), the month (season), the day of sale (Christmas, Valentine's Day, etc.), etc.

[0238] When the disclosure determination information is generated in this way from the viewpoint of date and time, the display order can be dynamically changed depending on the date and time of sale.

[0239] Furthermore, when image data is sold for a limited period of time, the disclosure determination information may be generated from the perspective of the period from when the image data goes on sale until it is purchased. That is, the time required from when the sale begins until the image data is purchased is used as the evaluation of the image data, and the average of that time is used as the evaluation value for each category to generate the disclosure determination information. This makes it possible to display information according to the sales characteristics of the image data (such as whether it sells well immediately after going on sale, whether it sells well just before the sale ends, whether it sells gradually, or whether it sells all at once).

[0240] [Display of Image Data for Sale] In the above embodiment, an example has been described in which the second user terminal 200 is a smartphone and information on image data for sale is displayed in a row along the scroll direction of the screen. The display method for information on image data for sale is not limited to this. It is preferable to set it appropriately depending on the screen size, etc. For example, the image data information may be displayed in multiple rows along the scroll direction or vertical direction of the screen. In this case, for example, the image data are displayed in order from the top left to the right of the screen. When the edge of the screen is reached, the image data are moved down one row and displayed in order from left to right in the same way.

[0241] Second Embodiment In the above embodiment, an example has been described in which information on the priority order (publication determination information) when displaying image data for sale is generated as recommendation information.

[0242] In this embodiment, information on images recommended for sale is generated as recommendation information and provided to the first user.

[0243] Hereinafter, an example will be described in which information on recommended poses (recommended pose information) is generated as information on an image recommended for sale.

[0244] FIG. 25 is a block diagram showing the main functions of the image data sales system regarding the generation and provision of recommendation information.

[0245] 25 , in the image data sales system 1 of this embodiment, the information processing server 30 generates recommendation information (recommended posing information). The generated recommendation information is transmitted to the first user terminal 100 via the sales server 10 and presented to the first user. In other words, it is displayed on the display unit 104 of the first user terminal 100.

[0246] [Generation of Recommendation Information] As in the first embodiment, the information processing server 30 has functions such as a data acquisition unit 30a, an image analysis unit 30b, an evaluation extraction unit 30c, an evaluation value calculation unit 30d, and a recommendation information generation unit 30e.

[0247] The data acquisition unit 30a acquires image data and sales information for the image data from the database server 20.

[0248] The image analysis unit 30b analyzes the image data acquired by the data acquisition unit 30a and classifies the data into a plurality of categories. In this embodiment, the image data is classified into a plurality of categories depending on the posing of the subject.

[0249] The evaluation extraction unit 30c extracts information evaluating the image represented by the image data (evaluation information) from the sales information of the image data. In this embodiment, the sales amount of the image data is extracted as the evaluation information.

[0250] The evaluation value calculation unit 30d calculates an evaluation value for each category classified by the image analysis unit 30b based on the evaluation information extracted by the evaluation extraction unit 30c. In this embodiment, an evaluation value is calculated for each type of pose.

[0251] The recommendation information generating unit 30e generates recommendation information based on the information of the evaluation value for each category calculated by the evaluation value calculating unit 30d. In this embodiment, recommended posing information as recommendation information is generated based on the information of the evaluation value for each type of posing.

[0252] The recommended pose information is composed of information in which poses classified into a plurality of types are ranked in descending order of evaluation value. In this embodiment, the poses are ranked in descending order of average sales value.

[0253] [Providing Recommendation Information] As shown in FIG. 25, the sales server 10 has functions related to providing recommendation information, such as a recommendation information acquisition unit 10f and a recommendation information provision unit 10g.

[0254] The recommendation information acquisition unit 10 f performs a process of acquiring recommendation information (recommended posing information in this embodiment) generated by the information processing server 30 from the information processing server 30 .

[0255] The recommended information providing unit 10g performs processing to provide the recommended information acquired from the information processing server 30 to the first user terminal 100. In this embodiment, the recommended information providing unit 10g provides (transmits) the recommended information to the first user terminal 100 in response to a request for information provision from the first user terminal 100.

[0256] The recommendation information provided by the sales server 10 is displayed on the display unit 104 of the first user terminal 100 in a predetermined display format.

[0257] FIG. 26 is a diagram showing an example of display of recommendation information on the first user terminal.

[0258] As recommended poses, information on recommended poses is displayed in the order of the ranking shown in the recommendation information. The example shown in Fig. 26 shows an example in which illustrations showing the poses are displayed together with the types of poses. In this case, the recommendation information including information on the illustrations is provided to the first user terminal 100. Actual photographs may be displayed instead of illustrations.

[0259] The information on the recommended poses is displayed in order along the scrolling direction of the screen. In the example shown in Fig. 26, the information on the recommended poses is displayed in order from the first place by scrolling the screen from bottom to top.

[0260] In this way, in the image data sales system of this embodiment, information on images recommended for sale (information on poses recommended for sale in the above example) is generated as recommendation information and provided to the first user. The first user can sell image data that is likely to be purchased (image data with a high expected sales value) by taking and selling images based on the provided recommendation information.

[0261] [Modifications] [Recommendation Information] In the above embodiment, an example has been described in which information on recommended poses is generated as recommendation information, but the information generated as recommendation information is not limited to this. In addition, recommendation information can be generated from the perspective of, for example, composition, background, scene, facial expression, clothing, etc. It is also possible to generate recommendation information that combines multiple perspectives. For example, information on combinations of recommended poses and compositions can be generated as recommendation information. In this case, for example, poses and compositions whose evaluation values ​​are equal to or greater than a threshold or whose evaluation value rankings are equal to or greater than a threshold are extracted, and the extracted poses and compositions are combined to generate recommendation information.

[0262] [Generation of recommendation information using artificial intelligence] Recommendation information can also be generated using artificial intelligence. In particular, when image data is classified from multiple perspectives, information on recommended combinations can be generated as recommendation information using artificial intelligence (use of so-called generative AI). For example, when image data is classified by pose and composition, recommended combinations of poses and compositions can be generated using artificial intelligence based on the evaluation values ​​of the poses and the evaluation values ​​of the compositions. More detailed information can also be generated by adding elements such as background, facial expression, and clothing. Furthermore, information according to the time of year can also be generated by adding elements of date and time.

[0263] A plurality of pieces of recommendation information can be generated using artificial intelligence. In this case, it is preferable to generate the information in order of ranking.

[0264] Furthermore, it is preferable that the resulting information be output as image information. For example, when outputting a recommended combination of poses and compositions, an image showing examples of the poses and compositions is generated and output. Alternatively, an image with similar content is output.

[0265] Furthermore, the recommendation information can also be generated as information when selling or publishing a video. In this case, for example, information such as recommended pose changes is generated as the recommendation information.

[0266] [Recommendation Information When Multiple Subjects Are Included] For example, when capturing a photograph of multiple people within the field of view, such as in a group photo, it is preferable to generate recommendation information according to the number of people. That is, recommendation information is generated that includes information such as a recommended composition according to the number of people to be photographed and a recommended pose for each person. For example, when photographing a group of three people, information on the position (composition) of each person and their pose is generated as recommendation information. In this case, for example, information on the number of people to be photographed is obtained from the first user via the first user terminal 100.

[0267] [Providing Recommended Information] When multiple pieces of information such as recommended poses and compositions are generated as recommendation information, the information provided to the first user may be limited to a certain number. For example, if the information is ranked, the top n pieces of information are presented to the first user. The number n (threshold) to be displayed may be set arbitrarily by the first user. Alternatively, only information with an evaluation value equal to or greater than a threshold may be provided to the first user.

[0268] Furthermore, a configuration may be adopted in which information on image data that has been sold (including currently on sale) is acquired for each first user, and unsold (unphotographed) image data is provided. For example, when generating information on poses or compositions to be recommended as recommendation information, unsold image data by the first user is extracted from the generated information on multiple poses or compositions, and provided to the first user. For example, when generating information on combinations of poses and compositions to be recommended as recommendation information, unsold image data by the first user is extracted from the generated information on multiple combinations of poses and compositions, and provided to the first user. Information on sold image data is acquired, for example, from the database server 20. When extracting unsold image data, the configuration may be such that the image data is extracted from among those whose evaluation value is equal to or greater than a threshold value or whose evaluation value ranking is equal to or greater than a threshold value.

[0269] Alternatively, the first user may obtain information on image data that has already been sold, and provide the first user with unsold poses and / or compositions as recommendation information, regardless of the evaluation value.

[0270] [Others] The configurations and modifications shown in the first embodiment are also applied to this embodiment as appropriate.

[0271] Third Embodiment A technique (collage) for combining a plurality of images to generate a single image is known. The generated image is called a collage image.

[0272] Fig. 27 is a diagram showing an example of a collage image, particularly showing an example in which the collage image is printed on instant film (collage print).

[0273] 27 shows an example in which three images Im1, Im2, and Im3 are combined to generate one collage image ImC. Each of the images Im1, Im2, and Im3 is displayed within a pre-divided frame to generate one collage image ImC.

[0274] In this embodiment, when a first user sells a collage image, information about the recommended collage image is generated as recommendation information.

[0275] [Generation of Recommendation Information] Here, an example will be described in which information (recommendation information) of a collage image recommended from the viewpoint of posing is generated.

[0276] As in the second embodiment, the information processing server 30 has functions such as a data acquisition unit 30a, an image analysis unit 30b, an evaluation extraction unit 30c, an evaluation value calculation unit 30d, and a recommendation information generation unit 30e (see Figure 25).

[0277] The data acquisition unit 30a acquires image data and sales information for the image data from the database server 20.

[0278] The image analysis unit 30b analyzes the image data acquired by the data acquisition unit 30a and classifies the data into a plurality of categories. In this embodiment, the image data is classified into a plurality of categories depending on the posing of the subject.

[0279] Furthermore, the image analysis unit 30b determines whether the image data is image data for a collage image. If the image data is image data for a collage image, the image analysis unit 30b further classifies the image data into a plurality of categories from the perspective of the collage form (for example, the division form of the frame). In this embodiment, the image data for the collage image is classified into a plurality of categories from the perspective of the division form of the frame (division into two parts, one above and one below, two parts below and one below, three parts above and one below, etc.).

[0280] The evaluation extraction unit 30c extracts information evaluating the image represented by the image data (evaluation information) from the sales information of the image data. In this embodiment, the sales amount of the image data is extracted as the evaluation information.

[0281] The evaluation value calculation unit 30d calculates an evaluation value for each category classified by the image analysis unit 30b based on the evaluation information extracted by the evaluation extraction unit 30c. In this embodiment, an evaluation value is calculated for each type of pose and each division form of a frame.

[0282] The recommendation information generation unit 30e generates recommendation information based on the evaluation value information calculated by the evaluation value calculation unit 30d (information on the evaluation value for each type of pose and information on the evaluation value for each frame division form). Specifically, information on the recommended frame division form and information on the poses to be combined is generated as recommendation information. For example, the frame division form with the highest evaluation value and information on the number of poses corresponding to the number of divisions of that frame are generated as recommendation information. The posing information is selected in descending order of evaluation value. Multiple pieces of recommendation information can also be generated.

[0283] [Providing Recommendation Information] The sales server 10 has functions related to providing recommendation information, such as a recommendation information acquisition unit 10f and a recommendation information provision unit 10g (see FIG. 25).

[0284] The recommendation information acquisition unit 10 f performs a process of acquiring recommendation information (information on recommended collage images) generated by the information processing server 30 from the information processing server 30 .

[0285] The recommended information providing unit 10g performs processing to provide the recommended information acquired from the information processing server 30 to the first user terminal 100. The recommended information providing unit 10g provides (transmits) the recommended information to the first user terminal 100 in response to a request for information provision from the first user terminal 100.

[0286] The recommendation information provided by the sales server 10 is displayed on the display unit 104 of the first user terminal 100 in a predetermined display format.

[0287] In this way, according to the image data sales system of the present embodiment, when a first user sells a collage image, information on recommended collage images can be provided to the first user. The first user can create a collage image based on the provided recommendation information, thereby selling image data of a collage image that is likely to be purchased.

[0288] [Modifications] [Recommendation Information] In the above embodiment, an example has been described in which information on recommended collage images is generated from the perspective of posing, but the information generated as information on recommended collage images (recommendation information) is not limited to this. In addition, information on recommended collage images can be generated from the perspective of, for example, composition, background, scene, facial expression, clothing, etc. Furthermore, information on recommended collage images can also be generated by combining multiple perspectives.

[0289] Furthermore, the information such as poses to be combined is basically a combination of poses with high evaluation values, but it is also possible to intentionally generate information by combining poses with low evaluation values.

[0290] In addition, in the above embodiment, the recommendation information is configured to generate information on the recommended frame division form and information on poses to be combined, but it may also be configured to generate only one of the information. For example, it may be configured to generate only information on the recommended frame division form, or it may be configured to generate only information on poses to be combined.

[0291] Also, for example, information on the division form of the frame to be used may be received from the first user, and information on a combination of recommended poses and the like for the received division form of the frame may be generated as recommendation information.

[0292] Similarly, image data to be used for a collage image may be received from a first user, and information on a recommended frame division form may be generated as recommendation information for the received image data. In this case, the image data received from the first user is analyzed and information on the recommended frame division form is generated.

[0293] Alternatively, the system may be configured to accept a plurality of image data from the first user and automatically generate a recommended collage image. In this case, the recommended collage image may be generated using all of the accepted image data, or may be generated using only a portion of the image data.

[0294] [Generation of recommendation information using artificial intelligence] Information on recommended collage images can also be generated using artificial intelligence. For example, when multiple image data are input, information on recommended collage images can be generated using a model that automatically generates collage images with high expected sales value. In this case, for example, machine learning is performed using the image data of the collage images recorded in the database server 20 and their sales information (especially sales information) to generate the model.

[0295] It is also possible to configure the system to accept multiple pieces of image data and automatically generate recommended collage images using a trained model.

[0296] [Others] The configurations and modifications shown in the first or second embodiment are also applied to this embodiment as appropriate.

[0297] Other Embodiments System Configuration The first user terminal 100 and the second user terminal 200 may be any computer that can communicate with the sales server 10 via the network 2. Therefore, they do not necessarily have to be mobile computers.

[0298] In the above embodiment, the printer 300 is described as a printer that prints images on instant film, but the type of printer 300 is not limited to this. Other printers that print images on recording media using inkjet printing, thermal printing, or the like may also be used. Furthermore, the printer 300 does not necessarily have to be portable; a so-called stationary printer may also be used.

[0299] The printer 300 and the second user terminal 200 may be connected by wire or wirelessly.

[0300] [Hardware Configuration of Each Server] The functions of each server are realized by various processors. The various processors include CPUs and / or GPUs (Graphic Processing Units), which are general-purpose processors that execute programs and function as various processing units; programmable logic devices (PLDs), such as FPGAs (Field Programmable Gate Arrays), whose circuit configuration can be changed after manufacture; and dedicated electrical circuits, such as ASICs (Application Specific Integrated Circuits), which are processors with circuit configurations designed specifically to execute specific processes. The term "program" is synonymous with "software."

[0301] A single processing unit may be composed of one of these various processors, or may be composed of two or more processors of the same or different types. For example, a single processing unit may be composed of multiple FPGAs, or a combination of a CPU and an FPGA. Furthermore, multiple processing units may be composed of a single processor. Examples of multiple processing units composed of a single processor include: a first configuration, as typified by computers used as clients or servers, in which a single processor is composed of a combination of one or more CPUs and software, and this processor functions as multiple processing units; a second configuration, as typified by system-on-chip (SoC), in which a processor is used to realize the functions of an entire system including multiple processing units on a single IC (Integrated Circuit) chip; and a hardware structure, in which the various processing units are composed of one or more of the above-mentioned various processors.

[0302] In the above embodiment, each process is divided among three servers (sales server 10, database server 20, and information processing server 30), but all processes may be performed by a single server. Also, some processes may be performed by the first user terminal 100 or the second user terminal 200.

[0303] The functions of each server can also be realized by a so-called cloud computer.

[0304] [Others] The configurations and functions described in the above embodiments can be combined as appropriate.

[0305] In the above embodiment, the present invention has been described as being applied to a system for selling image data for printing online. However, the application of the present invention is not limited to this. The present invention can also be applied to a system for simply selling image data. The present invention can also be applied to a system that provides image data (including image data for printing) free of charge (including partially free of charge).

[0306] Furthermore, buying and selling of image data is not limited to using general currency, but also includes using virtual currency (including so-called points, etc.) For example, points equivalent to currency may be issued, and image data may be purchased using the points.

[0307] DESCRIPTION OF SYMBOLS 10...Sales server 10a...Data receiving unit 10b...Data recording processing unit 10c...Sales processing unit 10c1...Image analysis unit 10c2...Disclosure determination processing unit 10d...Sales management unit 10e...Recommendation information acquisition unit 10f...Recommendation information acquisition unit 10g...Recommendation information providing unit 11...Processor 12...Main memory unit 13...Auxiliary memory unit 14...Operation unit 15...Display unit 16...Interface unit 20...Database server 21...Processor 22...Main memory unit 23...Auxiliary memory unit 24...Operation unit 25...Display unit 26...Interface unit 30...Information processing server 30a...Data acquisition unit 30b...Image analysis unit 30c...Evaluation extraction unit 30d...Evaluation value calculation unit 30e...Recommendation information generation unit 31...Processor 32...Main memory unit 33...Auxiliary memory unit 34: Operation unit 35: Display unit 36: Interface unit 100: First user terminal 100a: Image data acquisition unit 100b: Sales setting information reception unit 100c: Upload processing unit 101: Processor 102: Main memory unit 103: Auxiliary memory unit 104: Display unit 105: Operation unit 106: GPS receiving unit 107: Camera unit 108: Audio input unit 109: Audio output unit 110: Communication unit 111: Short-range wireless communication unit 112: Sensor unit 200: Second user terminal 200a: Viewing processing unit 200b: Purchase processing unit 200c: Download processing unit 200d: Print processing unit 201: Processor 202: Main memory unit 203: Auxiliary memory unit 204: Display unit 205: Operation unit 206: GPS receiving unit 207: Camera unit DESCRIPTION OF SYMBOLS 208...Audio input unit 209...Audio output unit 210...Communication unit 211...Near field wireless communication unit 212...Sensor unit 300...Printer 301...Control unit 302...Print unit 302a...Film loading chamber 302b...Film feeding mechanism 302c...Film transport mechanism 302d...Print head 303...Near field wireless communication unit 304...Operation unit 310...Film pack 400...Photo (printed matter) FB11...Search button FB21...Profile button FB31...Print button FB41...Album button FC11...User display column FC12...Following user display column FC21...Seller information display column FC22...Profile image display column FC23...Sales number and follower number information display column FC24...Message display columnFC25...Display column for information on image data currently on sale FC25i...Information on image data currently on sale FC25i1...Image represented by image data currently on sale FC25i2...Information on the sales period of image data currently on sale FC25i3...Information on the selling price of image data currently on sale FC25i4...Information on comments added to image data currently on sale FC25iF...Frame FC31...Display column for information on sales period FC32...Display column for image represented by image data FC32f...Frame FC32i...Image represented by image data FC33...Display column for information on seller FC34...Display column for comments FC35...Display column for information on selling price FC41...Display column for information on sales period FC42...Display column for printed image FC42f...Frame FC42i...Printed image FC43...Display column for reaction button FC44...Display column for information on seller FC45...Display column for comments IB21...Button IB22...Button IB23...Button IB31...Button IB32...Button IB41...Button IC11...Display field for image represented by image data to be sold IC11f...Frame IC11i...Image represented by image data to be sold IC12...Input field for color information IC13...Input field for comments IC14...Input field for sales period IC15...Input field for sales price ID1...First image data ID2...Second image data ID3...Third image data ID4...Fourth image data ID5...Fifth image data Im1...Image Im2...Image Im3...Image ImC...Collage image LA1...Animation indicating that printing is in progress PM1...Message indicating that printing is in progress PM2...Message indicating that printing is complete U1...First user U2...Second user

Claims

1. An information processing device comprising a processor, the processor acquiring first information including information on an evaluation of first image data and an image represented by the first image data, analyzing the first image data and classifying it into a plurality of categories, calculating an evaluation value for each of the categories based on the first information, and generating second information of second image data based on the evaluation values.

2. The information processing device according to claim 1, wherein the second information is information that contributes to sales promotion.

3. The information processing device according to claim 2, wherein the first information includes information indicating that an image represented by the first image data has been gazed at, selected, or added to a cart.

4. The information processing device according to claim 2, wherein the evaluation is given higher the shorter the period between the sale of the image represented by the first image data and its purchase.

5. The information processing device according to claim 1, wherein the first information includes sales amount information as the evaluation information.

6. The information processing device according to claim 5, wherein the evaluation value is an average sales amount.

7. An information processing device according to any one of claims 1 to 6, wherein the first information includes information of a subject and / or a photographer, and the processor calculates the evaluation value by weighting the evaluation information based on the information of the subject and / or the photographer.

8. An information processing device according to any one of claims 1 to 6, wherein the second information is information on the priority order of disclosure when a plurality of the second image data are sold.

9. The information processing device according to claim 8, wherein the first information includes sales date and time information, and the processor generates statistical information of the ratings based on the sales date and time for each category, and generates the second information based on the statistical information of the ratings.

10. An information processing device according to any one of claims 1 to 6, wherein the categories are classified based on composition and / or pose, and the second information is information on recommended composition and / or pose.

11. The information processing device according to claim 10, wherein the processor extracts compositions and / or poses whose evaluation value is above a threshold or whose ranking of the evaluation value is above a threshold, and generates information on the extracted compositions and / or poses as the second information.

12. The information processing device according to claim 11, wherein the processor acquires information on compositions and / or poses that have been sold, and generates information on unsold compositions and / or poses from the extracted compositions and / or poses as the second information.

13. The information processing device according to claim 10, wherein the processor extracts compositions and poses for which the evaluation value is equal to or greater than a threshold value or the ranking of the evaluation value is equal to or greater than a threshold value, and generates information combining the extracted compositions and poses as the second information.

14. The information processing device of claim 10, wherein the processor acquires information on the number of people to be photographed at one time, extracts compositions and / or poses for which the evaluation value is above a threshold or the ranking of the evaluation value is above a threshold, and generates composition and / or pose information corresponding to the number of people as the second information based on the extracted composition and / or pose information.

15. An information processing device according to any one of claims 1 to 6, wherein the categories are classified based on composition and / or posing, and the second information is information on a combination of composition and / or posing when generating a collage image.

16. An information processing method comprising: acquiring first information including first image data and evaluation information for an image represented by the first image data; analyzing the first image data and classifying it into a plurality of categories; calculating an evaluation value for each of the categories based on the first information; and generating second information for second image data based on the evaluation values.

17. An information processing program that causes a computer to realize the following functions: a function of acquiring first information including information on evaluation of first image data and an image represented by the first image data; a function of analyzing the first image data and classifying it into a plurality of categories; a function of calculating an evaluation value for each of the categories based on the first information; and a function of generating second information of second image data based on the evaluation values.

18. A non-transitory computer-readable recording medium having the program according to claim 17 recorded thereon.