WO2019134502A1 - 拍照方法、装置、存储介质及电子设备 - Google Patents

拍照方法、装置、存储介质及电子设备 Download PDF

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Publication number
WO2019134502A1
WO2019134502A1 PCT/CN2018/121753 CN2018121753W WO2019134502A1 WO 2019134502 A1 WO2019134502 A1 WO 2019134502A1 CN 2018121753 W CN2018121753 W CN 2018121753W WO 2019134502 A1 WO2019134502 A1 WO 2019134502A1
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Prior art keywords
adjustment information
historical
photographing
current
scene
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PCT/CN2018/121753
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English (en)
French (fr)
Inventor
陈岩
刘耀勇
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Oppo广东移动通信有限公司
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Application filed by Oppo广东移动通信有限公司 filed Critical Oppo广东移动通信有限公司
Priority to US16/764,690 priority Critical patent/US11503205B2/en
Priority to EP18898217.7A priority patent/EP3709626A4/en
Publication of WO2019134502A1 publication Critical patent/WO2019134502A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/76—Television signal recording
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/35—Categorising the entire scene, e.g. birthday party or wedding scene
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/10—Image acquisition
    • G06V10/12—Details of acquisition arrangements; Constructional details thereof
    • G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
    • G06V10/147—Details of sensors, e.g. sensor lenses
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/30—Scenes; Scene-specific elements in albums, collections or shared content, e.g. social network photos or video
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/61—Control of cameras or camera modules based on recognised objects
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/63—Control of cameras or camera modules by using electronic viewfinders
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/63—Control of cameras or camera modules by using electronic viewfinders
    • H04N23/631—Graphical user interfaces [GUI] specially adapted for controlling image capture or setting capture parameters
    • H04N23/632—Graphical user interfaces [GUI] specially adapted for controlling image capture or setting capture parameters for displaying or modifying preview images prior to image capturing, e.g. variety of image resolutions or capturing parameters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/64—Computer-aided capture of images, e.g. transfer from script file into camera, check of taken image quality, advice or proposal for image composition or decision on when to take image
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/667—Camera operation mode switching, e.g. between still and video, sport and normal or high- and low-resolution modes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/80—Camera processing pipelines; Components thereof
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods

Definitions

  • the present application relates to the field of electronic technologies, and in particular, to a photographing method, device, storage medium, and electronic device.
  • the embodiment of the present application provides a photographing method, device, storage medium and electronic device, which can automatically adjust shooting parameters to facilitate user's use.
  • An embodiment of the present application provides a photographing method, including:
  • the embodiment of the present application further provides a photographing apparatus, including:
  • a first determining module configured to determine a current photographing scene according to the current preview image
  • a first acquiring module configured to acquire, according to the current photographing scene, historical adjustment information of a photographing parameter that is pre-stored and matched with the current photographing scene;
  • a second determining module configured to determine current adjustment information of the photographing parameter according to the historical adjustment information
  • an output module configured to adjust the current preview image based on current adjustment information of the photographing parameter, and output the adjusted current preview screen.
  • the embodiment of the present application further provides a storage medium, where the storage medium stores a plurality of instructions, and the instructions are adapted to be loaded by a processor to perform the following steps:
  • the embodiment of the present application further provides an electronic device, including a memory and a processor, where the memory is used to store instructions and data, and the instructions are adapted to be loaded by the processor to perform the following steps:
  • FIG. 1 is a schematic diagram of a scene of a photographing method provided by an embodiment of the present application.
  • FIG. 2 is a schematic flowchart diagram of a photographing method provided by an embodiment of the present application.
  • FIG. 3 is a schematic structural diagram of a photographing apparatus according to an embodiment of the present application.
  • FIG. 4 is another schematic structural diagram of a photographing apparatus according to an embodiment of the present application.
  • FIG. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
  • FIG. 6 is another schematic structural diagram of an electronic device according to an embodiment of the present application.
  • the embodiment of the present application provides a photographing method, device, storage medium, and electronic device.
  • the camera device can be integrated on electronic devices such as mobile phones, tablet computers, and unmanned aerial vehicles with camera functions.
  • the photographing apparatus may be specifically configured to determine a current photographing scene according to a current preview screen, such as a beach scene, a gourmet scene, a night scene, a flower scene, an animal scene, and the like. Then, according to the current photographing scene, the pre-stored historical adjustment information of the photographing parameter matching the current photographing scene is acquired, so that the current adjustment information of the photographing parameter is determined according to the historical adjustment information, and the current preview image is based on the current adjustment information of the photographing parameter. The adjustment is performed, and then the adjusted current preview screen is output.
  • a current preview screen such as a beach scene, a gourmet scene, a night scene, a flower scene, an animal scene, and the like.
  • the present application can automatically adjust the photographing parameters according to different photographing scenes, without manual adjustment by the user, which is very convenient for the user to use, and takes photos by using the user in each scene.
  • the historical adjustment information of the parameter is used to determine the current adjustment information of the photographing parameter, and the photographing setting habit is combined with the user to adjust the photographing parameter, so that the effect of the preview screen is more in line with the user's preference, thereby reducing the number of times the user manually adjusts the photographing parameter, so that the number of times the user manually adjusts the photographing parameter is reduced. Taking pictures is more intelligent.
  • An embodiment of the present application provides a photographing method, including:
  • determining the current adjustment information of the photographing parameter according to the historical adjustment information includes:
  • the weight of each of the historical adjustment information is set according to a preset rule
  • the method before the setting the weight of each of the historical adjustment information according to the preset rule, the method further includes:
  • Setting the weight of each of the historical adjustment information according to the preset rule includes: setting a weight of each of the selected historical adjustment information according to a preset rule;
  • the adjustment information is calculated to obtain current adjustment information of the photographing parameter.
  • the calculating, according to the weight of each selected historical adjustment information, the historical adjustment information of the selected number of reservations including:
  • the historical adjustment information of the selected number of reservations is calculated according to the following formula:
  • n is the value of the reserved quantity
  • P is the current adjustment information
  • P1, P2, ..., Pn represent the selected n historical adjustment information.
  • ⁇ 1, ⁇ 2, ..., ⁇ n are the weights of n historical adjustment information, respectively.
  • the setting according to the preset rule, the weight of each of the selected historical adjustment information, including:
  • the weight of each of the selected historical adjustment information is set according to a sequence of storage time of the historical adjustment information, wherein the closer the storage time is to the current time, the greater the weight of the corresponding historical adjustment information.
  • the selecting the subscription quantity of the historical adjustment information comprises:
  • the history adjustment information of the reserved number is sequentially selected in order of storage time from near to far.
  • determining the current adjustment information of the photographing parameter according to the historical adjustment information includes:
  • one of the historical adjustment information is used as current adjustment information of the photographing parameter.
  • the determining the current photo scene according to the current preview image comprises:
  • the picture is identified by a convolutional neural network picture recognition model to determine the current picture scene.
  • the obtaining, before the acquiring the historical adjustment information of the photographing parameter that matches the current photographing scene, according to the current photographing scene further includes:
  • the photographing method provided by the embodiment of the present application specifically includes the following steps:
  • the current preview picture is the picture currently captured by the camera, and the preview picture can be displayed on the display screen, so that the user can view the current picture content and the picture effect through the preview picture.
  • the photographing scene may include a beach scene, a gourmet scene, a night scene, a flower scene, an animal scene, and the like.
  • the image recognition algorithm may perform image recognition on the current preview image to determine a current photographing scene. For example, when it is recognized that there is a flower in the current preview image, the current photographing scene may be determined as a flower scene.
  • determining the current photo scene according to the current preview image may include: acquiring a picture corresponding to the current preview picture; and identifying the picture by using a convolutional neural network picture recognition model to determine the current photo scene. For example, by acquiring the current preview picture, the current preview picture is reduced to a picture of 122*122 pixels, and sent to the trained convolutional neural network picture recognition model to identify the current photo scene.
  • the convolutional neural network picture recognition model may be trained first, for example, multiple historical shooting pictures may be collected as training samples for convolutional neural network image recognition. The model is trained to determine the parameters of the convolutional neural network picture recognition model, and then the trained convolutional neural network picture recognition model is obtained, so that the convolutional neural network picture recognition model can be used to identify the photographing scene corresponding to the current preview picture.
  • the photographing parameter may be any kind of photographing parameter, for example, brightness, contrast, exposure or white balance, etc.
  • the adjustment information of the photographing parameter refers to a specific value of the photographing parameter. For example, taking the brightness as an example, the brightness adjustment information is Refers to the brightness value.
  • historical adjustment information of various camera parameters in various camera scenes is stored in advance, for example, before the current time, the user may be in each camera scene for a period of time before the current time.
  • the set adjustment information of each camera parameter is stored, so that the history adjustment information of various camera parameters in each camera scene is stored in advance.
  • the step of storing the historical adjustment information may also be included, as follows:
  • the history preview screen is, for example, a preview screen captured by the camera each time the user opens the camera to take a photo within a period of time before the current time, such as within one month or within one week.
  • the picture corresponding to the history preview picture is input into the trained convolutional neural network picture recognition model, thereby identifying the picture scene corresponding to the history preview picture.
  • each time a history preview screen is acquired scene recognition is performed on the history preview screen to identify a historical photographing scene corresponding to the historical preview screen, and then historical adjustment information of the photographing parameters when photographing the historical preview screen is acquired, That is, the value of the photographing parameter set by the user when the historical preview screen is taken is obtained, thereby obtaining the historical adjustment information of the photographing parameter in the photographing scene corresponding to the historical preview screen.
  • scene recognition is performed on the history preview screen to identify a historical photographing scene corresponding to the historical preview screen
  • historical adjustment information of the photographing parameters when photographing the historical preview screen is acquired, That is, the value of the photographing parameter set by the user when the historical preview screen is taken is obtained, thereby obtaining the historical adjustment information of the photographing parameter in the photographing scene corresponding to the historical preview screen.
  • the historical adjustment information of the photographing parameter such as the value of the acquired brightness, the value of the contrast, and the value of the exposure, thereby obtaining a value of the brightness under the beach scene, a value of the contrast, and a value of the exposure.
  • the historical adjustment information of each camera parameter when the two preview images are photographed are respectively acquired, so that two values of the brightness under the beach scene can be obtained. Two values of contrast and two values of exposure.
  • the history adjustment information of each historical photo scene and corresponding camera parameters can be stored in a table form, for example, as shown in the following table:
  • Table 1 Storage table of photographing scenes and historical adjustment information
  • a10 ⁇ a14, b10 ⁇ b14, c10 ⁇ c14, etc. indicate the adjustment information of the photographing parameters, that is, the value of the brightness, the value of the exposure degree, and the value of the contrast, on May 03, 05, 05, and 05.
  • the day indicates the storage time of the adjustment information.
  • each time a historical photographing scene of a historical preview screen is recognized the adjustment information of each photographing parameter set by the user under the historical preview screen and the corresponding photographing scene are stored, wherein
  • the sequence of photographing time stores the adjustment information of each group of photographing parameters, for example, a10, b10, and c10 are adjustment information of a group of photographing parameters.
  • the correspondence between the historical photo scene and the adjustment information corresponding to the photographing parameter is also established.
  • step 202 historical adjustment information of the photographing parameter that matches the current photographing scene may be acquired according to the corresponding relationship. For example, after the current photographing scene is identified, the current photographing scene is compared with the pre-stored historical photographing scene to find a historical photographing scene that is consistent with the current photographing scene, and then the stored historical photographs consistent with the current photographing scene are acquired. The historical adjustment information of the photographing parameter corresponding to the scene, thereby obtaining the historical adjustment information of the photographing parameter that matches the current photographing scene.
  • the historical adjustment information of the photographing parameters corresponding to the pre-stored flower scene is: (a30, b30, c30), (a31, b31, C31), ..., (a34, b34, c34), thereby obtaining historical adjustment information of the photographing parameters that match the current photographing scene.
  • the current adjustment information of the photographing parameter may be determined by using various methods. For example, for each photographing parameter, the average value of the historical adjustment information of the photographing parameter may be obtained as current adjustment information, or may be selected. A historical adjustment information is used as the current adjustment information, or the current adjustment information is calculated by setting the weight of the historical adjustment information, and may be selected according to actual needs.
  • determining the current adjustment information of the photographing parameter according to the historical adjustment information may include:
  • the weight of each history adjustment information is set according to a preset rule.
  • the photographing parameter is brightness
  • the weight of each history adjustment information of the brightness is set according to a preset rule, and then adjusted according to each history.
  • the weight of the information is calculated by calculating all the historical adjustment information of the brightness, thereby obtaining the current adjustment information of the brightness.
  • the method further includes: determining whether the quantity of the historical adjustment information is greater than or equal to the number of reservations, and if so, selecting the historical adjustment information of the reserved quantity.
  • the selection operation is not performed, but all the historical adjustment information is weighted, and all the historical adjustment information is calculated according to each weight to obtain current adjustment information of the photographing parameters.
  • the history adjustment information of the reservation quantity may be selected according to the order of storage time of the history adjustment information, specifically, the storage time is closest to the current time.
  • the history adjustment information starts, and the history adjustment information of the reservation quantity is sequentially selected in order of storage time from near to far.
  • the number of reservations can be set according to actual needs, such as 5, 8, or 15, and so on. Taking the camera parameter as the brightness and the number of reservations as 5, for example, the current time is 10:00 on June 01, as shown in Table 1 above, for the camera parameter of the brightness, the time before the current time is selected.
  • the five historical luminance values a15, a14, a13, a12, a11 are used to calculate the current luminance value of the luminance.
  • the history adjustment information of the reservation quantity may be selected according to the storage time from far to near, or may be the historical adjustment information of the reservation quantity according to the storage time from the farthest to the nearest. There is no limit to this.
  • the weight of each historical adjustment information is set according to the preset rule, including: setting the weight of each selected historical adjustment information according to the preset rule, and then according to each selected one.
  • the weight of the historical adjustment information is calculated, and the historical adjustment information of the selected number of reservations is calculated to obtain the current adjustment information of the photographing parameters.
  • the preset rule may set the weight according to the order of the storage time of the historical adjustment information. The closer the storage time is to the current time, the greater the weight of the corresponding historical adjustment information, or the storage time is closer to the current time.
  • the weight of the corresponding history adjustment information is smaller, or in other embodiments, the weight of the history adjustment information in which the storage time is in the middle position is set to be the maximum, and the storage time is in the front and back history adjustment information.
  • the weights are set relatively small, and specific rules can be selected according to actual needs, which is not limited. Among them, the sum of ownership is 1.
  • the preset rule is, for example, setting the weight according to the order of the storage time of the historical brightness value.
  • the five historical brightness values selected are a15, a14, a13, a12, and a11.
  • the weight of the weights of the five historical brightness values can be set according to actual needs.
  • the historical brightness value a15 whose storage time is closest to the current time can be set to 0.6, a14, a13, a12,
  • the weight of a11 can be set to 0.2, 0.1, 0.08, and 0.02, respectively.
  • the preset rule may also be that the historical brightness value in which the storage time is in the middle has the largest weight, and the other brightness values are small.
  • the storage time of a13 is in the middle position, so the weight of a13 is set to the maximum, for example, may be set to 0.5.
  • the weights of a15, a14, a12, and a11 can be set to 0.1, 0.15, 0.15, and 0.1, respectively.
  • the weight can indicate the degree of deviation of the user's adjustment information of the photographing parameter.
  • the historical adjustment information of the selected number of reservations is calculated according to the weight of each selected historical adjustment information, which may specifically include:
  • the historical adjustment information of the selected number of reservations is calculated according to the following formula:
  • n is the value of the reserved quantity
  • P is the current adjustment information
  • P1, P2, ..., Pn represent the selected n historical adjustment information.
  • ⁇ 1, ⁇ 2, ..., ⁇ n are the weights of n historical adjustment information, respectively.
  • the current preview information is adjusted by using the current adjustment information, and the adjusted current preview screen is output, so that the user can take a photo with reference to the current preview screen.
  • the camera parameters can be automatically adjusted according to different camera scenes, without manual adjustment by the user, which is very convenient for the user to use, and the current adjustment information of the camera parameters is determined by using the history adjustment information of the camera parameters in each scene.
  • the effect of the current preview screen can be more in line with the user's preference, thereby reducing the number of times the user manually adjusts the photographing parameters, making the photographing more intelligent.
  • the photographing parameter may be any kind of photographing parameter of the camera, such as brightness, contrast or exposure, etc., and various photographing parameters involved in photographing may be determined according to steps 201-204, for example, In the storage table of the above table 1, each of the photographing scenes is stored with the history adjustment information of the three photographing parameters. Therefore, in the current photographing scene, the current adjustment information of the three photographing parameters may be respectively determined according to steps 201-204.
  • the default adjustment information of the camera may be used as the adjustment information of the photographing parameter.
  • the current photographing scene and the photographing parameter when photographing the current preview screen may be further performed.
  • the current adjustment information is stored, and the storage time is recorded, and the relationship between the photographing scene and the current adjustment information of the photographing parameter is established, so that the photographing parameter is adjusted as the historical adjustment information when the user takes the next photograph.
  • the storage table for storing the photographing scene and the historical adjustment information in order to save the maintenance and update the storage table, only the latest reservation quantity history adjustment information may be recorded in the storage table, for a photographing scene, When new historical adjustment information is generated, the new historical adjustment information is updated to the storage table, and the oldest historical adjustment information is deleted.
  • An embodiment of the present application provides a photographing apparatus, including:
  • a first determining module configured to determine a current photographing scene according to the current preview image
  • a first acquiring module configured to acquire, according to the current photographing scene, historical adjustment information of a photographing parameter that is pre-stored and matched with the current photographing scene;
  • a second determining module configured to determine current adjustment information of the photographing parameter according to the historical adjustment information
  • an output module configured to adjust the current preview image based on current adjustment information of the photographing parameter, and output the adjusted current preview screen.
  • the second determining module is configured to:
  • the weight of each of the historical adjustment information is set according to a preset rule
  • the photographing apparatus further includes a judging module and a selecting module
  • the determining module is configured to determine whether the quantity of the historical adjustment information is greater than or equal to a subscription quantity
  • the selecting module is configured to: when the quantity of the historical adjustment information is greater than or equal to a predetermined quantity, select the historical adjustment information of the reserved quantity;
  • the second determining module is configured to:
  • the second determining module is configured to:
  • the historical adjustment information of the selected number of reservations is calculated according to the following formula:
  • n is the value of the reserved quantity
  • P is the current adjustment information
  • P1, P2, ..., Pn represent the selected n historical adjustment information.
  • ⁇ 1, ⁇ 2, ..., ⁇ n are the weights of n historical adjustment information, respectively.
  • the second determining module is configured to set a weight of each of the selected historical adjustment information according to a sequence of storage time of the historical adjustment information, where the storage time is closer to the current time, corresponding to The greater the weight of historical adjustment information.
  • the selection module is configured to sequentially select the predetermined number of the historical adjustment information in order from the near to the farthest according to the storage time, the history adjustment information that is closest to the current time.
  • the second determining module is configured to use one of the historical adjustment information as current adjustment information of the photographing parameter when there is only one historical adjustment information of the photographing parameter.
  • the first determining module is configured to:
  • the picture is identified by a convolutional neural network picture recognition model to determine the current picture scene.
  • the photographing apparatus further includes an acquisition module, a third determination module, a second acquisition module, and a storage module:
  • the collecting module is configured to collect multiple historical preview images
  • the third determining module is configured to identify the plurality of historical preview images by using a convolutional neural network picture recognition model to determine a plurality of historical photo scenes;
  • the second obtaining module is configured to acquire historical adjustment information of the photographing parameter when photographing each of the historical preview screens, and then obtain historical adjustment information of the photographing parameters corresponding to the historical photographing scene;
  • the storage module is configured to save historical adjustment information of the plurality of historical photographing scenes and photographing parameters in each of the historical photographing scenes, and establish photographing parameters of each of the historical photographing scenes and corresponding historical photographing scenes. Correspondence between historical adjustment information;
  • the first obtaining module is configured to acquire historical adjustment information of a photographing parameter that matches the current photographing scene according to the corresponding relationship.
  • a photographing apparatus provided by an embodiment of the present application specifically includes a first determining module 301 , a first obtaining module 302 , a second determining module 303 , and an output module 304 .
  • the first determining module 301 is configured to determine a current photographing scene according to the current preview screen.
  • the current preview screen is also the screen currently captured by the camera, and the preview screen can be displayed on the display screen, so that the user can view the current photographing content and the photographing effect through the preview screen.
  • the photographing scene may include a beach scene, a gourmet scene, a night scene, a flower scene, an animal scene, and the like.
  • the first determining module 301 is specifically configured to obtain a picture corresponding to the current preview picture, and then use the convolutional neural network picture recognition model to identify the picture, thereby determining the current photo scene.
  • the first obtaining module 302 is configured to acquire, according to the current photographing scene, historical adjustment information of the photographing parameters that are pre-stored and matched with the current photographing scene.
  • the photographing parameter may be, for example, brightness, contrast, exposure, or white balance.
  • the adjustment information of the photographing parameter refers to a specific value of the photographing parameter. For example, taking the brightness as an example, the brightness adjusting information refers to the brightness value.
  • historical adjustment information of various camera parameters in various camera scenes is stored in advance, for example, before the current time, the user may be in each camera scene for a period of time before the current time.
  • the set adjustment information of each camera parameter is stored, so that the history adjustment information of various camera parameters in each camera scene is stored in advance.
  • the second determining module 303 is configured to determine current adjustment information of the photographing parameter according to the historical adjustment information.
  • the current adjustment information of the photographing parameter may be determined by using various methods. For example, for each photographing parameter, the average value of the historical adjustment information may be taken as the current adjustment information, or one of the historical adjustment information may be selected. As the current adjustment information, or by setting the weight of the historical adjustment information, the current adjustment information is calculated, and may be selected according to actual needs.
  • the second determining module 303 is specifically configured to: when the history adjustment information of the photographing parameter has two or more, set the weight of each historical adjustment information according to the preset rule, and then adjust the information according to each history.
  • the weight is calculated by calculating all the historical adjustment information of the photographing parameter, and the current adjustment information with the photographing parameter is obtained.
  • the photographing apparatus of the embodiment of the present application may further include a judging module 305 and a selecting module 306.
  • the determining module 305 is configured to determine whether the quantity of the historical adjustment information is greater than or equal to the reserved quantity before the second determining module 303 determines the weight of the historical adjustment information.
  • the second determining module 303 is configured to perform weighting on all the historical adjustment information, and calculate all the historical adjustment information according to the weights, when the number of the historical adjustment information is less than the number of reservations, the selection module 306 does not perform the selection operation. To get the current adjustment information of the camera parameters.
  • the selecting module 306 is configured to select historical adjustment information of the reserved quantity when the quantity of the historical adjustment information is greater than or equal to the reserved quantity.
  • the historical adjustment information of the reserved quantity may be selected according to the order of storing the historical adjustment information. Specifically, starting from the historical adjustment information whose storage time is closest to the current time, the number of reservations is sequentially selected according to the storage time from near to far. Historical adjustment information.
  • the number of reservations can be set according to actual needs, such as 5, 8 or 15, and so on.
  • the second determining module 303 is configured to set the weight of each selected historical adjustment information according to the preset rule, and then according to the weight of each selected historical adjustment information, The historical adjustment information of the selected number of reservations is calculated to obtain current adjustment information of the photographing parameters.
  • the preset rule may set the weight according to the order of the storage time of the historical adjustment information. The closer the storage time is to the current time, the greater the weight of the corresponding historical adjustment information, or the storage time is closer to the current time.
  • the weight of the corresponding history adjustment information is smaller, or in other embodiments, the weight of the history adjustment information in which the storage time is in the middle position is set to be the maximum, and the storage time is in the front and back history adjustment information.
  • the weights are set relatively small, and specific rules can be selected according to actual needs, which is not limited. Among them, the sum of ownership is 1.
  • the second determining module 303 may calculate historical adjustment information of the selected number of reservations according to the following formula:
  • n is the value of the reserved quantity
  • P is the current adjustment information
  • P1, P2, ..., Pn represent the selected n historical adjustment information.
  • ⁇ 1, ⁇ 2, ..., ⁇ n are the weights of n historical adjustment information, respectively.
  • the output module 304 is configured to adjust the current preview image based on the current adjustment information of the photographing parameter, and output the adjusted current preview image. After obtaining the current adjustment information of the photographing parameter, the current preview information is adjusted by using the current adjustment information, and the adjusted current preview screen is output, so that the user can take a photo with reference to the current preview screen.
  • the camera parameters can be automatically adjusted according to different camera scenes, without manual adjustment by the user, which is very convenient for the user to use, and the current adjustment information of the camera parameters is determined by using the history adjustment information of the camera parameters in each scene.
  • the effect of the current preview screen can be more in line with the user's preference, thereby reducing the number of times the user manually adjusts the photographing parameters, making the photographing more intelligent.
  • the second determining module 303 is configured to: when there is only one historical adjustment information of the photographing parameter, for example, in the storage table of Table 1, the historical brightness value of the brightness has only one, then the one historical brightness value is taken as Current brightness value.
  • the default adjustment information of the camera may be used as the adjustment information of the photographing parameter.
  • the current photographing scene and the photographing parameter when photographing the current preview screen may be further performed.
  • the current adjustment information is stored, and the storage time is recorded, and the relationship between the photographing scene and the current adjustment information of the photographing parameter is established, so that the photographing parameter is adjusted as the historical adjustment information when the user takes the next photograph.
  • an acquisition module 307 a third determination module 308, a second acquisition module 309, and a storage module 310 are further included.
  • the collecting module 307 is configured to collect a plurality of historical preview images. For example, in a period of time before the current time, such as within one month or within one week, each time the user turns on the camera to take a picture, a preview picture captured by each camera is obtained.
  • the third determining module 308 is configured to identify the plurality of historical preview images by using the convolutional neural network picture recognition model to determine a plurality of historical photo scenes.
  • the picture corresponding to the history preview picture is input into the trained convolutional neural network picture recognition model, thereby identifying the picture scene corresponding to the history preview picture.
  • the second obtaining module 309 is configured to acquire historical adjustment information of the photographing parameter when photographing each historical preview image, and then obtain historical adjustment information of the photographing parameter corresponding to the historical photographing scene.
  • scene recognition is performed on the history preview screen to identify a historical photographing scene corresponding to the historical preview screen, and then historical adjustment information of the photographing parameters when photographing the historical preview screen is acquired, That is, the value of the photographing parameter set by the user when the historical preview screen is taken is obtained, thereby obtaining the historical adjustment information of the photographing parameter in the photographing scene corresponding to the historical preview screen.
  • the storage module 310 is configured to save a plurality of historical photo scenes and historical adjustment information of the photographing parameters in each historical photographing scene, and to reproduce the correspondence between each historical photographing scene and the historical adjustment information of the photographing parameters in the corresponding historical photographing scene. relationship.
  • the first obtaining module 302 may obtain historical adjustment information of the photographing parameter that matches the current photographing scene according to the corresponding relationship. For example, after the current photographing scene is identified, the current photographing scene is compared with the pre-stored historical photographing scene to find a historical photographing scene that is consistent with the current photographing scene, and then the stored historical photographs consistent with the current photographing scene are acquired. The historical adjustment information of the photographing parameter corresponding to the scene, thereby obtaining the historical adjustment information of the photographing parameter that matches the current photographing scene.
  • the embodiment of the present application provides a storage medium, which stores a plurality of instructions, which can be loaded by a processor to perform the steps in any of the photographing methods provided by the embodiments of the present application.
  • the instructions can be loaded by a processor to perform the following steps:
  • the program may be stored in a computer readable storage medium, and the storage medium may include: Read Only Memory (ROM), Random Access Memory (RAM), disk or optical disk.
  • ROM Read Only Memory
  • RAM Random Access Memory
  • the embodiment of the present application further provides an electronic device, including a memory and a processor, where the memory is used to store instructions and data, and the instruction is adapted to be loaded by the processor to perform any of the photographing methods provided by the embodiments of the present application. A step of.
  • the instructions are adapted to be loaded by the processor to perform the following steps:
  • the processor when determining the current adjustment information of the photographing parameter according to the historical adjustment information, performs the following steps:
  • the weight of each of the historical adjustment information is set according to a preset rule
  • the processor before setting the weight of each of the historical adjustment information according to a preset rule, the processor further performs the following steps:
  • Setting the weight of each of the historical adjustment information according to the preset rule includes: setting a weight of each of the selected historical adjustment information according to a preset rule;
  • the adjustment information is calculated to obtain current adjustment information of the photographing parameter.
  • the processor when the historical adjustment information of the selected number of reservations is calculated according to the weight of each selected historical adjustment information, the processor refers to the selected number of reservations according to the following formula. Historical adjustment information is calculated:
  • n is the value of the reserved quantity
  • P is the current adjustment information
  • P1, P2, ..., Pn represent the selected n historical adjustment information.
  • ⁇ 1, ⁇ 2, ..., ⁇ n are the weights of n historical adjustment information, respectively.
  • the processor when the weight of each of the selected historical adjustment information is set according to a preset rule, the processor performs the following steps:
  • the weight of each of the selected historical adjustment information is set according to a sequence of storage time of the historical adjustment information, wherein the closer the storage time is to the current time, the greater the weight of the corresponding historical adjustment information.
  • the processor when the subscription amount of the historical adjustment information is selected, performs the following steps:
  • the history adjustment information of the reserved number is sequentially selected in order of storage time from near to far.
  • the processor when determining the current adjustment information of the photographing parameter according to the historical adjustment information, performs the following steps:
  • one of the historical adjustment information is used as current adjustment information of the photographing parameter.
  • the processor when determining the current photographing scene according to the current preview screen, performs the following steps:
  • the picture is identified by a convolutional neural network picture recognition model to determine the current picture scene.
  • the processor before acquiring the pre-stored historical adjustment information of the photographing parameter that matches the current photographing scene according to the current photographing scene, the processor further performs the following steps:
  • the above electronic device may be, for example, a tablet or a smartphone. Please refer to FIG. 5.
  • FIG. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
  • the electronic device 500 can include components such as a display unit 501, a memory 502, a processor 503, an imaging unit 504, and the like. It will be understood by those skilled in the art that the electronic device structure illustrated in FIG. 5 does not constitute a limitation to the electronic device, and may include more or less components than those illustrated, or a combination of certain components, or different component arrangements.
  • the display unit 501 can be used to display image information or the like, such as a display screen.
  • Memory 502 can be used to store applications and data.
  • the application stored in the memory 502 contains executable code.
  • Applications can form various functional modules.
  • the processor 503 executes various functional applications and data processing by running an application stored in the memory 502.
  • the processor 503 is a control center of the electronic device, and connects various parts of the entire electronic device using various interfaces and lines, executes the electronic device by running or executing an application stored in the memory 502, and calling data stored in the memory 502. The various functions and processing of data to provide overall monitoring of the electronic device.
  • the camera unit 504 can be used to take a photo, such as a camera or the like.
  • the electronic device further includes one or more programs, wherein one or more programs are stored in the memory 502 and configured to execute one or more programs by the one or more processors 503. Instructions for doing the following:
  • Determining a current photographing scene according to the current preview image and then acquiring, according to the current photographing scene, pre-stored historical adjustment information of the photographing parameter that matches the current photographing scene, determining current adjustment information of the photographing parameter according to the historical adjustment information, and then based on the photographing parameter.
  • the current adjustment information adjusts the current preview screen and outputs the adjusted current preview screen.
  • the weight of each historical adjustment information is set according to a preset rule, and then all historical adjustment information of the photographing parameter is calculated according to the weight of each historical adjustment information, Get the current adjustment information of the camera parameters.
  • each historical adjustment information Before setting the weight of each historical adjustment information according to the preset rule, determining whether the quantity of the historical adjustment information is greater than or equal to the reserved quantity; if yes, selecting the historical adjustment information of the reserved quantity, thereby setting according to the preset rule The weight of each historical adjustment information is selected, and the historical adjustment information of the selected number of reservations is calculated according to the weight of each historical adjustment information selected to obtain current adjustment information of the photographing parameters.
  • the historical adjustment information of the selected number of reservations is calculated according to the following formula:
  • n is the value of the reserved quantity
  • P is the current adjustment information
  • P1, P2, ..., Pn represent the selected n historical adjustment information.
  • ⁇ 1, ⁇ 2, ..., ⁇ n are the weights of n historical adjustment information, respectively.
  • the weight of each historical adjustment information selected is set according to the sequence of storage time of the historical adjustment information, wherein the closer the storage time is to the current time, the greater the weight of the corresponding historical adjustment information.
  • the camera parameters can be automatically adjusted according to different camera situations, without manual adjustment by the user, which is very convenient for the user to use, and the history adjustment information of the camera parameters in each scene is utilized by using the user.
  • the effect of the current preview screen can be more in line with the user's preferences, thereby reducing the number of times the user manually adjusts the camera parameters, making the camera more intelligent. .
  • the electronic device of the embodiment of the present application may further include components such as an input unit 505, an output unit 506, a speaker 507, and a power source 508.
  • the input unit 505 can be configured to receive input numbers, character information or user characteristic information (such as fingerprints), and to generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function controls.
  • user characteristic information such as fingerprints
  • the output unit 506 can be used to display information entered by the user or information provided to the user as well as various graphical user interfaces of the mobile terminal, which can be composed of graphics, text, icons, video, and any combination thereof.
  • the output unit may include a display panel.
  • the computer program can be stored in a computer readable storage medium, such as stored in a memory, and executed by at least one processor, which can include a flow of an embodiment of a method of adjusting a picture as described.
  • the storage medium may be a magnetic disk, an optical disk, a read only memory (ROM), a random access memory (RAM), or the like.
  • each functional module may be integrated into one processing chip, or each module may exist physically separately, or two or more modules may be integrated into one module.
  • the above integrated modules can be implemented in the form of hardware or in the form of software functional modules.
  • the integrated module if implemented in the form of a software functional module and sold or used as a standalone product, may also be stored in a computer readable storage medium, such as a read only memory, a magnetic disk or an optical disk, etc. .

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Abstract

一种拍照方法、装置、存储介质及电子设备，所述方法中，根据当前预览画面确定当前拍照场景；根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息；根据所述历史调节信息确定当前调节信息；基于所述当前调节信息对所述当前预览画面进行调整，并输出调整后的所述当前预览画面。

Description

拍照方法、装置、存储介质及电子设备
本申请要求于2018年01月05日提交中国专利局、申请号为201810012466.1、发明名称为“拍照方法、装置、存储介质及电子设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及电子技术领域，尤其涉及一种拍照方法、装置、存储介质及电子设备。
背景技术
随着技术的不断发展，智能手机、平板电脑等移动终端的功能越来越丰富，在日常生活中不再是扮演着单纯的通信工具，而是成为了人们工作、休闲、娱乐的必需品，而手机拍照也越来越成为人们日常生活的一部分。
发明内容
本申请实施例提供一种拍照方法、装置、存储介质及电子设备，能够自动调节拍摄参数，方便用户的使用。
本申请实施例提供一种拍照方法，包括：
根据当前预览画面确定当前拍照场景；
根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息；
根据所述历史调节信息确定所述拍照参数的当前调节信息；
基于所述拍照参数的当前调节信息对所述当前预览画面进行调整，并输出调整后的所述当前预览画面。
本申请实施例还提供一种拍照装置，包括：
第一确定模块，用于根据当前预览画面确定当前拍照场景；
第一获取模块，用于根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息；
第二确定模块，用于根据所述历史调节信息确定所述拍照参数的当前调节信息；
输出模块，用于基于所述拍照参数的当前调节信息对所述当前预览画面进行调整，并输出调整后的所述当前预览画面。
本申请实施例还提供一种存储介质，所述存储介质存储有多条指令，所述指令适于处理器进行加载，以执行以下步骤：
根据当前预览画面确定当前拍照场景；
根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息；
根据所述历史调节信息确定所述拍照参数的当前调节信息；
基于所述拍照参数的当前调节信息对所述当前预览画面进行调整，并输出调整后的所述当前预览画面。
本申请实施例还提供一种电子设备，包括存储器和处理器，所述存储器用于存储指令和数据，所述指令适于由所述处理器进行加载以执行以下步骤：
根据当前预览画面确定当前拍照场景；
根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息；
根据所述历史调节信息确定所述拍照参数的当前调节信息；
基于所述拍照参数的当前调节信息对所述当前预览画面进行调整，并输出调整后的所述当前预览画面。
附图说明
下面结合附图，通过对本发明的具体实施方式详细描述，将使本发明的技术方案及其有益效果显而易见。
图1是本申请实施例提供的拍照方法的场景示意图。
图2是本申请实施例提供的拍照方法的流程示意图。
图3是本申请实施例提供的拍照装置的一结构示意图。
图4是本申请实施例提供的拍照装置的另一结构示意图。
图5是本申请实施例提供的电子设备的一结构示意图。
图6是本申请实施例提供的电子设备的另一结构示意图。
具体实施方式
请参照图式，其中相同的组件符号代表相同的组件，本发明的原理是以实施在一适当的运算环境中来举例说明。以下的说明是基于所例示的本发明具体实施例，其不应被视为限制本发明未在此详述的其它具体实施例。
本申请实施例提供一种拍照方法、装置、存储介质及电子设备。
其中，拍照装置可以集成在手机、平板电脑以及具有拍照功能的无人飞行器等电子设备上。
例如，如图1所示，拍照装置具体可以用于根据当前预览画面确定当前拍照场景，拍照场景比如可以是沙滩场景、美食场景、夜景场景、花朵场景以及动物场景等等。然后，根据当前拍照场景，获取预先存储的与当前拍照场景相匹配的拍照参数的历史调节信息，从而根据历史调节信息确定拍照参数的当前调节信息，并基于拍照参数的当前调节信息对当前预览画面进行调整，然后输出调整后的当前预览画面，通过上述方式，本申请可以实现根据不同的拍照场景自动调节拍照参数，不需要用户手动调节，极方便用户使用，且通过利用用户在各场景下拍照参数的历史调节信息来确定拍照参数的当前调节信息，结合了用户的拍照设置习惯来调节拍照参数，可以使得预览画面的效果更符合用户的喜好，进而可以减少用户手动调节拍照参数的次数，使得拍照更智能化。
以下将详细说明。
本申请实施例提供一种拍照方法，包括：
根据当前预览画面确定当前拍照场景；
根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息；
根据所述历史调节信息确定所述拍照参数的当前调节信息；
基于所述拍照参数的当前调节信息对所述当前预览画面进行调整，并输出调整后的所述当前预览画面。
在一些实施例中，所述根据所述历史调节信息确定所述拍照参数的当前调节信息，包括：
当所述拍照参数的历史调节信息有两个或以上时，根据预设规则设置每个所述历史调节信息的权重；
根据每个所述历史调节信息的权重，对所述拍照参数的所有历史调节信息进行计算，得到所述拍照参数的当前调节信息。
在一些实施例中，所述根据预设规则设置每个所述历史调节信息的权重之前，还包括：
判断所述历史调节信息的数量是否大于或等于预订数量；
若是，则选取预订数量的所述历史调节信息；
所述根据预设规则设置每个所述历史调节信息的权重，包括：根据预设规则，设置所选取的每个所述历史调节信息的权重；
所述根据每个所述历史调节信息的权重，对所述拍照参数的所有历史调节信息进行计算，包括：根据所选取的每个历史调节信息的权重，对所选取的预订数量的所述历史调节信息进行计算，以得到所述拍照参数的当前调节信息。
在一些实施例中，所述根据所选取的每个历史调节信息的权重，对所选取的预订数量的所述历史调节信息进行计算，包括：
根据以下公式对所选取的预订数量的所述历史调节信息进行计算：
P＝λ1*P1+λ1*P2+......+λn*Pn
其中，λ1+λ2+......+λn＝1，n为预订数量的值，P为当前调节信息，P1、P2、......、Pn表示所选取的n个历史调节信息，λ1、λ2、......、λn分别为n个历史调节信息的权重。
在一些实施例中，所述根据预设规则，设置所选取的每个所述历史调节信息的权重，包括：
根据所述历史调节信息的存储时间的先后顺序，设置所选取的每个所述历史调节信息的权重，其中存储时间越靠近当前时刻，对应的历史调节信息的权重越大。
在一些实施例中，所述选取预订数量的所述历史调节信息，包括：
从存储时间最靠近当前时刻的历史调节信息开始，按照存储时间由近到远的顺序依次选取预订数量的所述历史调节信息。
在一些实施例中，所述根据所述历史调节信息确定所述拍照参数的当前调节信息，包括：
当所述拍照参数的历史调节信息仅有一个时，则将一个所述历史调节信息作为所述拍照参数的当前调节信息。
在一些实施例中，所述根据当前预览画面确定当前拍照场景，包括：
获取当前预览画面对应的图片；
利用卷积神经网络图片识别模型对所述图片进行识别，进而确定当前拍照场景。
在一些实施例中，所述根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息之前，还包括：
采集多个历史预览画面；
利用卷积神经网络图片识别模型对所述多个历史预览画面进行识别，以确定多个历史拍照场景；
获取对每个所述历史预览画面进行拍照时拍照参数的历史调节信息，进而获取对应历史拍照场景下的拍照参数的历史调节信息；
保存所述多个历史拍照场景以及每个所述历史拍照场景下的拍照参数的历史调节信息，并建立每个所述历史拍照场景和对应历史拍照场景下的拍照参数的历史调节信息之间的对应关系；
所述根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息，包括：根据所述对应关系，获取与所述当前拍照场景相匹配的拍照参数的历史调节信息。
参阅图2，本申请实施例提供的拍照方法中，具体包括如下步骤：
201、根据当前预览画面确定当前拍照场景。
电子设备的摄像头打开时，会实时捕获画面，当前预览画面也即摄像头当前所捕获的画面，预览画面可以在显示屏上进行显示，从而用户可以通过预览画面查看当前的拍照内容和拍照效果。
拍照场景可以包括沙滩场景、美食场景、夜景场景、花朵场景以及动物场景等等。其中，可以通过图像识别算法对当前预览画面进行图像识别，以确定当前拍照场景，比如当识别出当前预览画面中有花朵，则当前拍照场景可以确定为花朵场景。
在一些实施例中，根据当前预览画面确定当前拍照场景，可以包括：获取当前预览画面对应的图片；利用卷积神经网络图片识别模型对图片进行识别，进而确定当前拍照场景。如，通过获取当前预览画面，然后将该当前预览画面缩小为122*122像素的图片，送入训练好的卷积神经网络图片识别模型中，以识别当前拍照场景。其中，在利用卷积神经网络图片识别模型对当前预览画面进行识别之前，可以先对卷积神经网络图片识别模型进行训练，比如可以采集多个历史拍摄画面作为训练样本对卷积神经网络图片识别模型进行训练，以确定卷积神经网络图片识别模型的各参数，进而得到训练好的卷积神经网络图片识别模型，从而利用卷积神经网络图片识别模型可以识别当前预览画面对应的拍照场景。
202、根据当前拍照场景，获取预先存储的与当前拍照场景相匹配的拍照参数的历史调节信息。
拍照参数可以是任意一种拍照参数，例如可以是亮度、对比度、曝光度或白平衡等，拍照参数的调节信息是指拍照参数的具体数值，例如，以亮度为例，亮度的调节信息即是指亮度值。
本实施例中，预先存储各种拍照场景下，各种拍照参数的历史调节信息，比如，在当前时刻以前，可以是在当前时刻以前的一段时间内，将用户每次在各个拍照场景下，设置的各拍照参数的调节信息进行存储，从而预先存储各拍照场景下，各种拍照参数的历史调节信息。
在一些实施例，在获取预先存储的与当前拍照场景相匹配的拍照参数的历史调节信息之前，还可以包括存储历史调节信息的步骤，具体如下：
(1)采集多个历史预览画面。
历史预览画面比如是在当前时刻之前的一段时间内，如一个月内或者一个星期之内，用户每次打开摄像头进行拍照时，每次摄像头捕获的预览画面。
(2)利用卷积神经网络图片识别模型对多个历史预览画面进行识别，以确定多个历史拍照场景。
将历史预览画面对应的图片输入训练好的卷积神经网络图片识别模型中，从而识别历史预览画面对应的拍照场景。
(3)获取对每个历史预览画面进行拍照时拍照参数的历史调节信息，进而获取对应历史拍照场景下的拍照参数的历史调节信息。
其中，可以是每获取一个历史预览画面，则对该历史预览画面进行场景识别，以识别该历史预览画面对应的历史拍照场景，然后获取对该历史预览画面进行拍照时拍照参数的历史调节信息，即获取在拍摄该历史预览画面时用户所设置的拍照参数的值，从而得到该历史预览画面对应的拍照场景下的拍照参数的历史调节信息。举例而言，当获取一个历史预览画面，经过卷积神经网络图片识别模型进行识别后，得到该历史预览画面对应的历史拍照场景为沙滩场景，然后记录下在对该历史预览画面进行拍照时各拍照参数的历史调节信息，比如获取亮度的值，对比度的值，曝光度的值，从而获取沙滩场景下的亮度的一个值、对比度的一个值以及曝光度的一个值。其中，当获取的两个历史预览画面均识别为沙滩场景时，则分别获取对这两个预览画面进行拍照时各拍照参数的历史调节信息，从而可以得到沙滩场景下的亮度的两个值、对比度的两个值以及曝光度的两个值。
(4)保存多个历史拍照场景以及每个历史拍照场景下的拍照参数的历史调节信息，并简历每个历史拍照场景和对应历史拍照场景下的拍照参数的历史调节信息之间的对应关系。
其中，以亮度、对比度以及曝光度三种拍照参数为例，各历史拍照场景和对应的各拍照参数的历史调节信息可以采用表格形式进行存储，譬如，可以如下表所示：
Figure PCTCN2018121753-appb-000001
表一拍照场景和历史调节信息的存储表
其中，a10～a14、b10～b14、c10～c14等等，表示拍照参数的调节信息，即亮度的值、曝光度的值以及对比度的值，05月03日、05月05日、05月10日等表示调节信息的存储时间。如上表所示，本实施例中，每识别出一个历史预览画面的历史拍照场景，则将在该历史预览画面下用户设置的各拍照参数的调节信息与对应的拍照场景进行存储，其中，按照拍照时间的先后顺序存储各组拍照参数的调节信息，比如a10、b10、c10为一组拍照参数的调节信息。其中，还建立历史拍照场景和对应拍照参数的调节信息的对应关系。
在步骤202中，可以根据该对应关系，获取与当前拍照场景相匹配的拍照参数的历史调节信息。例如，在识别出当前拍照场景之后，将当前拍照场景和预先存储的历史拍照场景进行比对，以寻找和当前拍照场景一致的历史拍照场景，进而获取所存储的和当前拍照场景一致的历史拍照场景所对应的拍照参数的历史调节信息，由此可以得到与当前拍照场景相匹配的拍照参数的历史调节信息。譬如，当前拍照场景为花朵场景，拍照参数包括亮度、对比度和曝光度，则获取预先存储的花朵场景所对应的拍照参数的历史调节信息为：(a30,b30,c30)、(a31,b31,c31)、......、(a34,b34,c34)，从而得到与当前拍照场景相匹配的拍照参数的历史调节信息。
203、根据历史调节信息确定拍照参数的当前调节信息。
在本申请实施例中，可以采用多种方法确定拍照参数的当前调节信息，比如，对于每一种拍照参数，可以获取该拍照参数的历史调节信息的平均值作为当前调节信息，或者可以选取其中一个历史调节信息作为当前调节信息，或者通过设置历史调节信息的权重来计算得到当前调节信息，具体可以根据实际需要来选择。
在一种实施例中，根据历史调节信息确定拍照参数的当前调节信息可以包括：
(1)当拍照参数的历史调节信息有两个或以上时，根据预设规则设置每个历史调节信息的权重。
(2)根据每个历史调节信息的权重，对拍照参数的所有历史调节信息进行计算，得带拍照参数的当前调节信息。
例如当拍照参数为亮度时，根据上述(1)和(2)，当亮度的历史调节信息有多个时，根据预设规则设置亮度的每个历史调节信息的权重，然后根据每个历史调节信息的权重，对亮度的所有历史调节信息进行计算，进而得到亮度的当前调节信息。
其中，当拍照参数历史调节信息存储有较多时，为了减少计算时间，提高效率，可以选取一部分历史调节信息进行计算以得到当前调节信息。比如，在设置一个拍照参数的每个历史调节信息的权重之前，还可以包括：判断历史调节信息的数量是否大于或等于预订数量，若是，则选取预订数量的历史调节信息。
当历史调节信息的数量小于预订数量时，则不进行选取操作，而是对所有的历史调节 信息进行权重设置，并根据各权重对所有历史调节信息进行计算，以得到拍照参数的当前调节信息。
在一种实施例中，当历史调节信息的数量大于或等于预订数量时，可以根据历史调节信息的存储时间的先后顺序选取预订数量的历史调节信息，具体地，从存储时间最靠近当前时刻的历史调节信息开始，按照存储时间由近到远的顺序依次选取预订数量的历史调节信息。其中，预订数量可以根据实际需要进行设置，如可以是5个、8个或15个，等等。以拍照参数为亮度、预订数量为5个为例，设当前时刻为6月01日10时，如上述表一所示的存储表，对于亮度的拍照参数而言，选取离当前时刻最近的前5个历史亮度值a15、a14、a13、a12、a11来计算亮度的当前亮度值。当然，在其他实施例中，也可以是按照存储时间由远到近的顺序选取预订数量的历史调节信息，或者还可以是按照存储时间由远到近的顺序间隔选取预订数量的历史调节信息，对此不做限定。
其中，在选取预订数量的历史调节信息之后，根据预设规则设置每个历史调节信息的权重，包括：根据预设规则设置所选取的每个历史调节信息的权重，然后根据所选取的每个历史调节信息的权重，对所选取的预订数量的历史调节信息进行计算，以得到拍照参数的当前调节信息。其中，预设规则比如可以是按照历史调节信息的存储时间的先后顺序设置权重，存储时间越靠近当前时刻，对应的历史调节信息的权重越大，或者，也可以是存储时间越靠近当前时刻，对应的历史调节信息的权重越小，或者在另一些实施例中，还可以是将存储时间处于中间位置的历史调节信息的权重设置得最大，而将存储时间处于前面和后面的历史调节信息的权重设置得比较小，具体的规则可以根据实际需要进行选择，对此不做限定。其中，所有权重的和为1。
举例而言，以亮度的拍照参数为例，预设规则例如是按照历史亮度值的存储时间的先后顺序设置权重，存储时间越靠近当前时刻，对应的历史亮度值的权重越大。其中选取的5个历史亮度值为a15、a14、a13、a12、a11，存储时间越靠近当前时刻的历史亮度值，其权重越大，因此5个历史亮度值a15、a14、a13、a12、a11的权重依次变小，其中5个历史亮度值的权重的具体值可以根据实际需要进行设置，例如存储时间最靠近当前时刻的历史亮度值a15，其权重可以设置0.6，a14、、a13、a12、a11的权重可以分别设置为0.2、0.1、0.08、0.02。又比如，预设规则还可以是存储时间处于中间的历史亮度值的权重最大，其他亮度值较小，比如，a13的存储时间处于中间位置，因此a13的权重设置为最大，例如可以设置为0.5，a15、a14、a12、a11的权重可以分别设置为0.1、0.15、0.15、0.1。其中，权重可以表示出用户对拍照参数的调节信息的偏向程度。
本实施例中，根据所选取的每个历史调节信息的权重，对所选取的预订数量的历史调节信息进行计算，具体可以包括：
根据以下公式对所选取的预订数量的历史调节信息进行计算：
P＝λ1*P1+λ1*P2+......+λn*Pn
其中，λ1+λ2+......+λn＝1，n为预订数量的值，P为当前调节信息，P1、P2、......、Pn表示所选取的n个历史调节信息，λ1、λ2、......、λn分别为n个历史调节信息的权重。由此，可以出计算拍照参数的当前调节信息。
204、基于拍照参数的当前调节信息对当前预览画面进行调整，并输出调整后的当前预览画面。
获取拍照参数的当前调节信息后，利用当前调节信息对当前预览画面进行调整，并输出调整后的当前预览画面，由此用户可以参考当前预览画面进行拍照。
通过本实施例，可以实现根据不同的拍照场景自动调节拍照参数，不需要用户手动调节，极方便用户使用，且通过利用用户在各场景下拍照参数的历史调节信息来确定拍照参数的当前调节信息，结合了用户的拍照设置习惯来调节拍照参数，可以使得当前预览画面 的效果更符合用户的喜好，进而可以减少用户手动调节拍照参数的次数，使得拍照更智能化。
上述步骤201～204中，拍照参数可以是摄像头的任意一种拍照参数，比如可以是亮度、对比度或者曝光度等，拍照时所涉及的各种拍照参数均可以按照步骤201～204进行确定，比如，在上述表一的存储表中每种拍照场景对应存储有三种拍照参数的历史调节信息，因此在当前拍照场景中，可以按照步骤201～204分别确定三种拍照参数的当前调节信息。
在一些实施例中，当拍照参数的历史调节信息仅有一个时，例如在表一的存储表中，亮度的历史亮度值只有一个，则将该一个历史亮度值作为当前亮度值。当然，在其他实施例中，当拍照参数的历史调节信息仅有一个时，也可以是将摄像头的默认调节信息作为拍照参数的调节信息。
在一些实施例中，输出调整后的当前预览画面之后，若用户对当前预览画面进行拍照，即检测到用户的拍照指令之后，进一步可以将当前拍照场景和对当前预览画面进行拍照时的拍照参数的当前调节信息进行存储，同时记录存储时间，并建立拍照场景和拍照参数的当前调节信息之间的关系，以在用户下一次拍照时作为历史调节信息对拍照参数进行调节。
其中，对于本申请用于存储拍照场景和历史调节信息的存储表，为了节省维护和更新存储表的开销，可以在存储表中只记录最新的预订数量个历史调节信息，对于一个拍照场景，若有新的历史调节信息产生，则将新的历史调节信息更新至存储表中，并删除最早的历史调节信息。
本申请实施例提供一种拍照装置，包括：
第一确定模块，用于根据当前预览画面确定当前拍照场景；
第一获取模块，用于根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息；
第二确定模块，用于根据所述历史调节信息确定所述拍照参数的当前调节信息；
输出模块，用于基于所述拍照参数的当前调节信息对所述当前预览画面进行调整，并输出调整后的所述当前预览画面。
在一些实施例中，所述第二确定模块用于：
当所述拍照参数的历史调节信息有两个或以上时，根据预设规则设置每个所述历史调节信息的权重；
根据每个所述历史调节信息的权重，对所述拍照参数的所有历史调节信息进行计算，得到所述拍照参数的当前调节信息。
在一些实施例中，所述拍照装置还包括判断模块和选取模块；
所述判断模块，用于判断所述历史调节信息的数量是否大于或等于预订数量；
所述选取模块，用于当所述历史调节信息的数量大于或等于预订数量时，选取预订数量的所述历史调节信息；
所述第二确定模块用于：
根据预设规则，设置所选取的每个所述历史调节信息的权重；
根据所选取的每个历史调节信息的权重，对所选取的预订数量的所述历史调节信息进行计算，以得到所述拍照参数的当前调节信息。
在一些实施例中，所述第二确定模块用于：
根据以下公式对所选取的预订数量的所述历史调节信息进行计算：
P＝λ1*P1+λ1*P2+......+λn*Pn
其中，λ1+λ2+......+λn＝1，n为预订数量的值，P为当前调节信息，P1、P2、......、Pn表示所选取的n个历史调节信息，λ1、λ2、......、λn分别为n个历史调节信息的权重。
在一些实施例中，所述第二确定模块用于根据所述历史调节信息的存储时间的先后顺 序，设置所选取的每个所述历史调节信息的权重，其中存储时间越靠近当前时刻，对应的历史调节信息的权重越大。
在一些实施例中，所述选取模块用于从存储时间最靠近当前时刻的历史调节信息开始，按照存储时间由近到远的顺序依次选取预订数量的所述历史调节信息。
在一些实施例中，所述第二确定模块用于当所述拍照参数的历史调节信息仅有一个时，则将一个所述历史调节信息作为所述拍照参数的当前调节信息。
在一些实施例中，所述第一确定模块用于：
获取当前预览画面对应的图片；
利用卷积神经网络图片识别模型对所述图片进行识别，进而确定当前拍照场景。
在一些实施例中，所述拍照装置还包括采集模块、第三确定模块、第二获取模块以及存储模块：
所述采集模块，用于采集多个历史预览画面；
所述第三确定模块，用于利用卷积神经网络图片识别模型对所述多个历史预览画面进行识别，以确定多个历史拍照场景；
所述第二获取模块，用于获取对每个所述历史预览画面进行拍照时拍照参数的历史调节信息，进而获取对应历史拍照场景下的拍照参数的历史调节信息；
所述存储模块，用于保存所述多个历史拍照场景以及每个所述历史拍照场景下的拍照参数的历史调节信息，并建立每个所述历史拍照场景和对应历史拍照场景下的拍照参数的历史调节信息之间的对应关系；
所述第一获取模块，用于根据所述对应关系，获取与所述当前拍照场景相匹配的拍照参数的历史调节信息。
参阅图3，本申请实施例提供的一种拍照装置中，具体包括第一确定模块301、第一获取模块302、第二确定模块303以及输出模块304。
其中，第一确定模块301用于根据当前预览画面确定当前拍照场景。当前预览画面也即摄像头当前所捕获的画面，预览画面可以在显示屏上进行显示，从而用户可以通过预览画面查看当前的拍照内容和拍照效果。拍照场景可以包括沙滩场景、美食场景、夜景场景、花朵场景以及动物场景等等。
在一些实施例中，第一确定模块301具体可以用于获取当前预览画面对应的图片，然后利用卷积神经网络图片识别模型对图片进行识别，进而确定当前拍照场景。
第一获取模块302用于根据当前拍照场景，获取预先存储的与当前拍照场景相匹配的拍照参数的历史调节信息。拍照参数例如可以是亮度、对比度、曝光度或白平衡等，拍照参数的调节信息是指拍照参数的具体数值，例如，以亮度为例，亮度的调节信息即是指亮度值。
本实施例中，预先存储各种拍照场景下，各种拍照参数的历史调节信息，比如，在当前时刻以前，可以是在当前时刻以前的一段时间内，将用户每次在各个拍照场景下，设置的各拍照参数的调节信息进行存储，从而预先存储各拍照场景下，各种拍照参数的历史调节信息。
第二确定模块303用于根据历史调节信息确定拍照参数的当前调节信息。在本申请实施例中，可以采用多种方法确定拍照参数的当前调节信息，比如，对于每一种拍照参数，可以取历史调节信息的平均值作为当前调节信息，或者可以选取其中一个历史调节信息作为当前调节信息，或者通过设置历史调节信息的权重来计算得到当前调节信息，具体可以根据实际需要来选择。
在一些实施例中，第二确定模块303具体可以用于当拍照参数的历史调节信息有两个或以上时，根据预设规则设置每个历史调节信息的权重，然后根据每个历史调节信息的权 重，对拍照参数的所有历史调节信息进行计算，得带拍照参数的当前调节信息。
其中，当拍照参数历史调节信息存储有较多时，为了减少计算时间，提高效率，可以选取一部分历史调节信息进行计算以得到当前调节信息。进一步地，本申请实施例的拍照装置还可以包括判断模块305和选取模块306。判断模块305用于在第二确定模块303确定历史调节信息的权重之前，判断历史调节信息的数量是否大于或等于预订数量。
其中，当历史调节信息的数量小于预订数量，则选取模块306不做选取操作，第二确定模块303用于对所有的历史调节信息进行权重设置，并根据各权重对所有历史调节信息进行计算，以得到拍照参数的当前调节信息。
其中，选取模块306用于当历史调节信息的数量大于或等于预订数量时，选取预订数量的历史调节信息。其中，可以根据历史调节信息的存储时间的先后顺序选取预订数量的历史调节信息，具体地，从存储时间最靠近当前时刻的历史调节信息开始，按照存储时间由近到远的顺序依次选取预订数量的历史调节信息。预订数量可以根据实际需要进行设置，如可以是5个、8个或15个，等等。
其中，在选取预订数量的历史调节信息之后，第二确定模块303用于根据预设规则设置所选取的每个历史调节信息的权重，然后根据所选取的每个历史调节信息的权重，对所选取的预订数量的历史调节信息进行计算，以得到拍照参数的当前调节信息。其中，预设规则比如可以是按照历史调节信息的存储时间的先后顺序设置权重，存储时间越靠近当前时刻，对应的历史调节信息的权重越大，或者，也可以是存储时间越靠近当前时刻，对应的历史调节信息的权重越小，或者在另一些实施例中，还可以是将存储时间处于中间位置的历史调节信息的权重设置得最大，而将存储时间处于前面和后面的历史调节信息的权重设置得比较小，具体的规则可以根据实际需要进行选择，对此不做限定。其中，所有权重的和为1。
本实施例中，第二确定模块303可以根据以下公式对所选取的预订数量的历史调节信息进行计算：
P＝λ1*P1+λ1*P2+......+λn*Pn
其中，λ1+λ2+......+λn＝1，n为预订数量的值，P为当前调节信息，P1、P2、......、Pn表示所选取的n个历史调节信息，λ1、λ2、......、λn分别为n个历史调节信息的权重。由此，可以计算出拍照参数的当前调节信息。
其中，输出模块304用于基于拍照参数的当前调节信息对当前预览画面进行调整，并使输出调整后的当前预览画面。获取拍照参数的当前调节信息后，利用当前调节信息对当前预览画面进行调整，并输出调整后的当前预览画面，由此用户可以参考当前预览画面进行拍照。
通过本实施例，可以实现根据不同的拍照场景自动调节拍照参数，不需要用户手动调节，极方便用户使用，且通过利用用户在各场景下拍照参数的历史调节信息来确定拍照参数的当前调节信息，结合了用户的拍照设置习惯来调节拍照参数，可以使得当前预览画面的效果更符合用户的喜好，进而可以减少用户手动调节拍照参数的次数，使得拍照更智能化。
在一些实施例中，第二确定模块303用于当拍照参数的历史调节信息仅有一个时，例如在表一的存储表中，亮度的历史亮度值只有一个，则将该一个历史亮度值作为当前亮度值。当然，在其他实施例中，当拍照参数的历史调节信息仅有一个时，也可以是将摄像头的默认调节信息作为拍照参数的调节信息。
在一些实施例中，输出调整后的当前预览画面之后，若用户对当前预览画面进行拍照，即检测到用户的拍照指令之后，进一步可以将当前拍照场景和对当前预览画面进行拍照时的拍照参数的当前调节信息进行存储，同时记录存储时间，并建立拍照场景和拍照参数的 当前调节信息之间的关系，以在用户下一次拍照时作为历史调节信息对拍照参数进行调节。
参阅图4，在本申请另一实施例提供的拍照装置中，进一步还可以包括采集模块307、第三确定模块308、第二获取模块309以及存储模块310。
在本实施例中，在第一获取模块302获取预先存储的与当前拍照场景相匹配的拍照参数的历史调节信息之前，采集模块307用于采集多个历史预览画面。比如，在当前时刻之前的一段时间内，如一个月内或者一个星期之内，用户每次打开摄像头进行拍照时，获取每次摄像头捕获的预览画面。
第三确定模块308用于利用卷积神经网络图片识别模型对多个历史预览画面进行识别，以确定多个历史拍照场景。将历史预览画面对应的图片输入训练好的卷积神经网络图片识别模型中，从而识别历史预览画面对应的拍照场景。
第二获取模块309用于获取对每个历史预览画面进行拍照时拍照参数的历史调节信息，进而获取对应历史拍照场景下的拍照参数的历史调节信息。其中，可以是每获取一个历史预览画面，则对该历史预览画面进行场景识别，以识别该历史预览画面对应的历史拍照场景，然后获取对该历史预览画面进行拍照时拍照参数的历史调节信息，即获取在拍摄该历史预览画面时用户所设置的拍照参数的值，从而得到该历史预览画面对应的拍照场景下的拍照参数的历史调节信息。
存储模块310用于保存多个历史拍照场景以及每个历史拍照场景下的拍照参数的历史调节信息，并简历每个历史拍照场景和对应历史拍照场景下的拍照参数的历史调节信息之间的对应关系。
其中，第一获取模块302可以根据该对应关系，获取与当前拍照场景相匹配的拍照参数的历史调节信息。例如，在识别出当前拍照场景之后，将当前拍照场景和预先存储的历史拍照场景进行比对，以寻找和当前拍照场景一致的历史拍照场景，进而获取所存储的和当前拍照场景一致的历史拍照场景所对应的拍照参数的历史调节信息，由此可以得到与当前拍照场景相匹配的拍照参数的历史调节信息。
本申请实施例提供一种存储介质，其存储有多条指令，该指令能够被处理器进行加载，以执行本申请实施例所提供的任一种拍照方法中的步骤。
例如，在一些实施例中，所述指令能够被处理器进行加载，以执行以下步骤：
根据当前预览画面确定当前拍照场景；
根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息；
根据所述历史调节信息确定所述拍照参数的当前调节信息；
基于所述拍照参数的当前调节信息对所述当前预览画面进行调整，并输出调整后的所述当前预览画面。
本领域普通技术人员可以理解上述实施例的各种方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序可以存储于一计算机可读存储介质中，存储介质可以包括：只读存储器(ROM，Read Only Memory)、随机存取记忆体(RAM，Random Access Memory)、磁盘或光盘等。
本申请实施例还提供一种电子设备，包括存储器和处理器，该存储器用于存储指令和数据，该指令适于处理器进行加载，以执行本申请实施例所提供的任一种拍照方法中的步骤。
在一些实施例中，所述指令适于由所述处理器进行加载以执行以下步骤：
根据当前预览画面确定当前拍照场景；
根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息；
根据所述历史调节信息确定所述拍照参数的当前调节信息；
基于所述拍照参数的当前调节信息对所述当前预览画面进行调整，并输出调整后的所述当前预览画面。
在一些实施例中，根据所述历史调节信息确定所述拍照参数的当前调节信息时，所述处理器执行以下步骤：
当所述拍照参数的历史调节信息有两个或以上时，根据预设规则设置每个所述历史调节信息的权重；
根据每个所述历史调节信息的权重，对所述拍照参数的所有历史调节信息进行计算，得到所述拍照参数的当前调节信息。
在一些实施例中，根据预设规则设置每个所述历史调节信息的权重之前，所述处理器还执行以下步骤：
判断所述历史调节信息的数量是否大于或等于预订数量；
若是，则选取预订数量的所述历史调节信息；
所述根据预设规则设置每个所述历史调节信息的权重，包括：根据预设规则，设置所选取的每个所述历史调节信息的权重；
所述根据每个所述历史调节信息的权重，对所述拍照参数的所有历史调节信息进行计算，包括：根据所选取的每个历史调节信息的权重，对所选取的预订数量的所述历史调节信息进行计算，以得到所述拍照参数的当前调节信息。
在一些实施例中，根据所选取的每个历史调节信息的权重，对所选取的预订数量的所述历史调节信息进行计算时，所述处理器根据以下公式对所选取的预订数量的所述历史调节信息进行计算：
P＝λ1*P1+λ1*P2+......+λn*Pn
其中，λ1+λ2+......+λn＝1，n为预订数量的值，P为当前调节信息，P1、P2、......、Pn表示所选取的n个历史调节信息，λ1、λ2、......、λn分别为n个历史调节信息的权重。
在一些实施例中，根据预设规则，设置所选取的每个所述历史调节信息的权重时，所述处理器执行以下步骤：
根据所述历史调节信息的存储时间的先后顺序，设置所选取的每个所述历史调节信息的权重，其中存储时间越靠近当前时刻，对应的历史调节信息的权重越大。
在一些实施例中，选取预订数量的所述历史调节信息时，所述处理器执行以下步骤：
从存储时间最靠近当前时刻的历史调节信息开始，按照存储时间由近到远的顺序依次选取预订数量的所述历史调节信息。
在一些实施例中，根据所述历史调节信息确定所述拍照参数的当前调节信息时，所述处理器执行以下步骤：
当所述拍照参数的历史调节信息仅有一个时，则将一个所述历史调节信息作为所述拍照参数的当前调节信息。
在一些实施例中，根据当前预览画面确定当前拍照场景时，所述处理器执行以下步骤：
获取当前预览画面对应的图片；
利用卷积神经网络图片识别模型对所述图片进行识别，进而确定当前拍照场景。
在一些实施例中，根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息之前，所述处理器还执行以下步骤：
采集多个历史预览画面；
利用卷积神经网络图片识别模型对所述多个历史预览画面进行识别，以确定多个历史拍照场景；
获取对每个所述历史预览画面进行拍照时拍照参数的历史调节信息，进而获取对应历 史拍照场景下的拍照参数的历史调节信息；
保存所述多个历史拍照场景以及每个所述历史拍照场景下的拍照参数的历史调节信息，并建立每个所述历史拍照场景和对应历史拍照场景下的拍照参数的历史调节信息之间的对应关系；
所述根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息，包括：根据所述对应关系，获取与所述当前拍照场景相匹配的拍照参数的历史调节信息。
例如，上述电子设备可以是诸如平板电脑或者智能手机等。请参阅5，图5为本申请实施例提供的电子设备的一结构示意图。
该电子设备500可以包括显示单元501、存储器502、处理器503、摄像单元504等部件。本领域技术人员可以理解，图5中示出的电子设备结构并不构成对电子设备的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。
显示单元501可用于显示图像信息等，例如为显示屏幕。
存储器502可用于存储应用程序和数据。存储器502存储的应用程序中包含有可执行代码。应用程序可以组成各种功能模块。处理器503通过运行存储在存储器502的应用程序，从而执行各种功能应用以及数据处理。
处理器503是电子设备的控制中心，利用各种接口和线路连接整个电子设备的各个部分，通过运行或执行存储在存储器502内的应用程序，以及调用存储在存储器502内的数据，执行电子设备的各种功能和处理数据，从而对电子设备进行整体监控。
摄像单元504可以用于拍摄照片，例如为摄像头等。
在本实施例中，电子设备还包括有一个或者一个以上的程序，其中一个或者一个以上程序存储于存储器502中，且经配置以由一个或者一个以上处理器503执行一个或者一个以上程序包含用于进行以下操作的指令：
根据当前预览画面确定当前拍照场景，然后根据当前拍照场景，获取预先存储的与当前拍照场景相匹配的拍照参数的历史调节信息，根据历史调节信息确定拍照参数的当前调节信息，之后基于拍照参数的当前调节信息对当前预览画面进行调整，并输出调整后的当前预览画面。
其中，当拍照参数的历史调节信息有两个或以上时，根据预设规则设置每个历史调节信息的权重，然后根据每个历史调节信息的权重，对拍照参数的所有历史调节信息进行计算，得到拍照参数的当前调节信息。
其中，在根据预设规则设置每个历史调节信息的权重之前，还可以判断历史调节信息的数量是否大于或等于预订数量；若是，则选取预订数量的历史调节信息，从而根据预设规则，设置所选取的每个历史调节信息的权重，并根据所选取的每个历史调节信息的权重，对所选取的预订数量的历史调节信息进行计算，以得到拍照参数的当前调节信息。
其中，根据以下公式对所选取的预订数量的历史调节信息进行计算：
P＝λ1*P1+λ1*P2+......+λn*Pn
其中，λ1+λ2+......+λn＝1，n为预订数量的值，P为当前调节信息，P1、P2、......、Pn表示所选取的n个历史调节信息，λ1、λ2、......、λn分别为n个历史调节信息的权重。
其中，根据历史调节信息的存储时间的先后顺序，设置所选取的每个历史调节信息的权重，其中存储时间越靠近当前时刻，对应的历史调节信息的权重越大。
以上各个操作的具体实施可参见前面的实施例，在此不再赘述。
由上可知，本申请实施例的电子设备中，可以实现根据不同的拍照场景自动调节拍照参数，不需要用户手动调节，极方便用户使用，且通过利用用户在各场景下拍照参数的历史调节信息来确定拍照参数的当前调节信息，结合了用户的拍照设置习惯来调节拍照参数， 可以使得当前预览画面的效果更符合用户的喜好，进而可以减少用户手动调节拍照参数的次数，使得拍照更智能化。
进一步地，如图6所示，本申请实施例的电子设备还可以包括输入单元505、输出单元506、扬声器507以及电源508等部件。
输入单元505可用于接收输入的数字、字符信息或用户特征信息(比如指纹)，以及产生与用户设置以及功能控制有关的键盘、鼠标、操作杆、光学或者轨迹球信号输入。
输出单元506可用于显示由用户输入的信息或提供给用户的信息以及移动终端的各种图形用户接口，这些图形用户接口可以由图形、文本、图标、视频和其任意组合来构成。输出单元可包括显示面板。
需要说明的是，对本申请实施例所述拍照方法而言，本领域普通技术人员可以理解实现本申请实施例所述拍照方法的全部或部分流程，是可以通过计算机程序来控制相关的硬件来完成，所述计算机程序可存储于一计算机可读取存储介质中，如存储在存储器中，并被至少一个处理器执行，在执行过程中可包括如所述调整图片的方法的实施例的流程。其中，所述的存储介质可为磁碟、光盘、只读存储器(ROM，Read Only Memory)、随机存取记忆体(RAM，Random Access Memory)等。
对本申请实施例的所述拍照装置而言，其各功能模块可以集成在一个处理芯片中，也可以是各个模块单独物理存在，也可以两个或两个以上模块集成在一个模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。所述集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中，所述存储介质譬如为只读存储器，磁盘或光盘等。
以上对本申请实施例所提供的一种拍照方法、装置、存储介质以及电子设备进行了详细介绍，本文中应用了具体个例对本发明的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本发明的方法及其核心思想；同时，对于本领域的技术人员，依据本发明的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本发明的限制。

Claims (20)

  1. 一种拍照方法，其中，包括：
    根据当前预览画面确定当前拍照场景；
    根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息；
    根据所述历史调节信息确定所述拍照参数的当前调节信息；
    基于所述拍照参数的当前调节信息对所述当前预览画面进行调整，并输出调整后的所述当前预览画面。
  2. 根据权利要求1所述的方法，其中，所述根据所述历史调节信息确定所述拍照参数的当前调节信息，包括：
    当所述拍照参数的历史调节信息有两个或以上时，根据预设规则设置每个所述历史调节信息的权重；
    根据每个所述历史调节信息的权重，对所述拍照参数的所有历史调节信息进行计算，得到所述拍照参数的当前调节信息。
  3. 根据权利要求2所述的方法，其中，所述根据预设规则设置每个所述历史调节信息的权重之前，还包括：
    判断所述历史调节信息的数量是否大于或等于预订数量；
    若是，则选取预订数量的所述历史调节信息；
    所述根据预设规则设置每个所述历史调节信息的权重，包括：根据预设规则，设置所选取的每个所述历史调节信息的权重；
    所述根据每个所述历史调节信息的权重，对所述拍照参数的所有历史调节信息进行计算，包括：根据所选取的每个历史调节信息的权重，对所选取的预订数量的所述历史调节信息进行计算，以得到所述拍照参数的当前调节信息。
  4. 根据权利要求3所述的方法，其中，所述根据所选取的每个历史调节信息的权重，对所选取的预订数量的所述历史调节信息进行计算，包括：
    根据以下公式对所选取的预订数量的所述历史调节信息进行计算：
    P＝λ1*P1+λ1*P2+......+λn*Pn
    其中，λ1+λ2+......+λn＝1，n为预订数量的值，P为当前调节信息，P1、P2、......、Pn表示所选取的n个历史调节信息，λ1、λ2、......、λn分别为n个历史调节信息的权重。
  5. 根据权利要求3所述的方法，其中，所述根据预设规则，设置所选取的每个所述历史调节信息的权重，包括：
    根据所述历史调节信息的存储时间的先后顺序，设置所选取的每个所述历史调节信息的权重，其中存储时间越靠近当前时刻，对应的历史调节信息的权重越大。
  6. 根据权利要求3所述的方法，其中，所述选取预订数量的所述历史调节信息，包括：
    从存储时间最靠近当前时刻的历史调节信息开始，按照存储时间由近到远的顺序依次选取预订数量的所述历史调节信息。
  7. 根据权利要求2所述的方法，其中，所述根据所述历史调节信息确定所述拍照参数的当前调节信息，包括：
    当所述拍照参数的历史调节信息仅有一个时，则将一个所述历史调节信息作为所述拍照参数的当前调节信息。
  8. 根据权利要求1所述的方法，其中，所述根据当前预览画面确定当前拍照场景，包括：
    获取当前预览画面对应的图片；
    利用卷积神经网络图片识别模型对所述图片进行识别，进而确定当前拍照场景。
  9. 根据权利要求1所述的方法，其中，所述根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息之前，还包括：
    采集多个历史预览画面；
    利用卷积神经网络图片识别模型对所述多个历史预览画面进行识别，以确定多个历史拍照场景；
    获取对每个所述历史预览画面进行拍照时拍照参数的历史调节信息，进而获取对应历史拍照场景下的拍照参数的历史调节信息；
    保存所述多个历史拍照场景以及每个所述历史拍照场景下的拍照参数的历史调节信息，并建立每个所述历史拍照场景和对应历史拍照场景下的拍照参数的历史调节信息之间的对应关系；
    所述根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息，包括：根据所述对应关系，获取与所述当前拍照场景相匹配的拍照参数的历史调节信息。
  10. 一种拍照装置，其中，包括：
    第一确定模块，用于根据当前预览画面确定当前拍照场景；
    第一获取模块，用于根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息；
    第二确定模块，用于根据所述历史调节信息确定所述拍照参数的当前调节信息；
    输出模块，用于基于所述拍照参数的当前调节信息对所述当前预览画面进行调整，并输出调整后的所述当前预览画面。
  11. 一种存储介质，其中，所述存储介质存储有多条指令，所述指令适于处理器进行加载，以执行以下步骤：
    根据当前预览画面确定当前拍照场景；
    根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息；
    根据所述历史调节信息确定所述拍照参数的当前调节信息；
    基于所述拍照参数的当前调节信息对所述当前预览画面进行调整，并输出调整后的所述当前预览画面。
  12. 一种电子设备，包括存储器和处理器，其中，所述存储器用于存储指令和数据，所述指令适于由所述处理器进行加载以执行以下步骤：
    根据当前预览画面确定当前拍照场景；
    根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息；
    根据所述历史调节信息确定所述拍照参数的当前调节信息；
    基于所述拍照参数的当前调节信息对所述当前预览画面进行调整，并输出调整后的所述当前预览画面。
  13. 根据权利要求12所述的电子设备，其中，根据所述历史调节信息确定所述拍照参数的当前调节信息时，所述处理器执行以下步骤：
    当所述拍照参数的历史调节信息有两个或以上时，根据预设规则设置每个所述历史调节信息的权重；
    根据每个所述历史调节信息的权重，对所述拍照参数的所有历史调节信息进行计算，得到所述拍照参数的当前调节信息。
  14. 根据权利要求13所述的电子设备，其中，根据预设规则设置每个所述历史调节 信息的权重之前，所述处理器还执行以下步骤：
    判断所述历史调节信息的数量是否大于或等于预订数量；
    若是，则选取预订数量的所述历史调节信息；
    所述根据预设规则设置每个所述历史调节信息的权重，包括：根据预设规则，设置所选取的每个所述历史调节信息的权重；
    所述根据每个所述历史调节信息的权重，对所述拍照参数的所有历史调节信息进行计算，包括：根据所选取的每个历史调节信息的权重，对所选取的预订数量的所述历史调节信息进行计算，以得到所述拍照参数的当前调节信息。
  15. 根据权利要求14所述的电子设备，其中，根据所选取的每个历史调节信息的权重，对所选取的预订数量的所述历史调节信息进行计算时，所述处理器根据以下公式对所选取的预订数量的所述历史调节信息进行计算：
    P＝λ1*P1+λ1*P2+......+λn*Pn
    其中，λ1+λ2+......+λn＝1，n为预订数量的值，P为当前调节信息，P1、P2、......、Pn表示所选取的n个历史调节信息，λ1、λ2、......、λn分别为n个历史调节信息的权重。
  16. 根据权利要求14所述的电子设备，其中，根据预设规则，设置所选取的每个所述历史调节信息的权重时，所述处理器执行以下步骤：
    根据所述历史调节信息的存储时间的先后顺序，设置所选取的每个所述历史调节信息的权重，其中存储时间越靠近当前时刻，对应的历史调节信息的权重越大。
  17. 根据权利要求14所述的电子设备，其中，选取预订数量的所述历史调节信息时，所述处理器执行以下步骤：
    从存储时间最靠近当前时刻的历史调节信息开始，按照存储时间由近到远的顺序依次选取预订数量的所述历史调节信息。
  18. 根据权利要求13所述的电子设备，其中，根据所述历史调节信息确定所述拍照参数的当前调节信息时，所述处理器执行以下步骤：
    当所述拍照参数的历史调节信息仅有一个时，则将一个所述历史调节信息作为所述拍照参数的当前调节信息。
  19. 根据权利要求12所述的电子设备，其中，根据当前预览画面确定当前拍照场景时，所述处理器执行以下步骤：
    获取当前预览画面对应的图片；
    利用卷积神经网络图片识别模型对所述图片进行识别，进而确定当前拍照场景。
  20. 根据权利要求12所述的电子设备，其中，根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息之前，所述处理器还执行以下步骤：
    采集多个历史预览画面；
    利用卷积神经网络图片识别模型对所述多个历史预览画面进行识别，以确定多个历史拍照场景；
    获取对每个所述历史预览画面进行拍照时拍照参数的历史调节信息，进而获取对应历史拍照场景下的拍照参数的历史调节信息；
    保存所述多个历史拍照场景以及每个所述历史拍照场景下的拍照参数的历史调节信息，并建立每个所述历史拍照场景和对应历史拍照场景下的拍照参数的历史调节信息之间的对应关系；
    所述根据所述当前拍照场景，获取预先存储的与所述当前拍照场景相匹配的拍照参数的历史调节信息，包括：根据所述对应关系，获取与所述当前拍照场景相匹配的拍照参数的历史调节信息。
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