CN109508321A - Image presentation method and Related product - Google Patents
Image presentation method and Related product Download PDFInfo
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- CN109508321A CN109508321A CN201811161360.4A CN201811161360A CN109508321A CN 109508321 A CN109508321 A CN 109508321A CN 201811161360 A CN201811161360 A CN 201811161360A CN 109508321 A CN109508321 A CN 109508321A
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- 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
- H04N23/62—Control of parameters via user interfaces
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Abstract
The embodiment of the present application discloses a kind of image presentation method and Related product, and wherein method includes: the historical operational parameters collection for obtaining each image in multiple images, obtains multiple historical operational parameters collection；Preference evaluation is carried out to image each in multiple images according to multiple historical operational parameters collection, obtains multiple evaluations of estimate, the corresponding evaluation of estimate of each image, preference is for indicating target object to the fancy grade of image；Classify according to predetermined depth learning model to multiple images, obtain multiclass image, every class image includes at least an image；It determines the corresponding evaluation of estimate of every class image in multiclass image, obtains multiple evaluation of estimate collection, every corresponding evaluation of estimate collection of one kind image；The corresponding preference gradations of every class image in multiclass image are determined according to multiple evaluation of estimate collection, obtain multiple preference gradations；Multiclass image is shown according to multiple preference gradations.Realize that photograph album shows function according to preference using the embodiment of the present application.
Description
Technical field
This application involves technical field of electronic equipment, and in particular to a kind of image presentation method and Related product.
Background technique
With a large amount of popularization and applications of electronic equipment (such as mobile phone, tablet computer), the application that electronic equipment can be supported
More and more, function is stronger and stronger, and electronic equipment can not only take pictures, additionally it is possible to realize various PS (Photoshop) function.
At present, electronic equipment cannot know that user to the preference of image, in turn, can not carry out image accurate
It shows.
Summary of the invention
The embodiment of the present application provides a kind of image presentation method and Related product, it may be possible to precisely be opened up to image
Show, improves the intelligence and convenience of electronic equipment.
In a first aspect, the embodiment of the present application provides a kind of image presentation method, comprising:
The historical operational parameters collection for obtaining each image in multiple images obtains multiple historical operational parameters collection, each
Historical operational parameters collection includes at least one operating parameter, and each operating parameter is used to state an operational motion to image；
Preference evaluation is carried out to image each in multiple described images according to the multiple historical operational parameters collection, is obtained
Multiple evaluations of estimate, the corresponding evaluation of estimate of each image, preference is for indicating target object to the fancy grade of image；
Classify according to predetermined deep learning model to multiple described images, obtains multiclass image, every class image is at least
Including an image；
It determines the corresponding evaluation of estimate of every class image in the multiclass image, obtains multiple evaluation of estimate collection, every one kind image pair
Answer an evaluation of estimate collection；
The corresponding preference gradations of every class image in the multiclass image are determined according to the multiple evaluation of estimate collection, are obtained multiple
Preference gradations；
The multiclass image is shown according to the multiple preference gradations.
Second aspect, the embodiment of the present application provide a kind of figure image demonstration apparatus, and described device includes:
Acquiring unit obtains multiple history behaviour for obtaining the historical operational parameters collection of each image in multiple images
Make parameter set, each historical operational parameters collection includes at least one operating parameter, and each operating parameter is for stating to image
One operational motion；
Evaluation unit, it is inclined for being carried out according to the multiple historical operational parameters collection to image each in multiple described images
Good degree evaluation obtains multiple evaluations of estimate, and the corresponding evaluation of estimate of each image, preference is for indicating target object to image
Fancy grade；
Taxon classifies to multiple described images for foundation predetermined deep learning model, obtains multiclass image,
Every class image includes at least an image；
Determination unit obtains multiple evaluation of estimate collection for determining the corresponding evaluation of estimate of every class image in the multiclass image,
Every corresponding evaluation of estimate collection of one kind image；And every class image in the multiclass image is determined according to the multiple evaluation of estimate collection
Corresponding preference gradations obtain multiple preference gradations；
Display unit, for showing the multiclass image according to the multiple preference gradations.
The third aspect, the embodiment of the present application provide a kind of electronic equipment, including processor, memory, communication interface and
One or more programs, wherein said one or multiple programs are stored in above-mentioned memory, and are configured by above-mentioned
It manages device to execute, above procedure is included the steps that for executing the instruction in the embodiment of the present application first aspect.
Fourth aspect, the embodiment of the present application provide a kind of computer readable storage medium, wherein above-mentioned computer-readable
Storage medium storage is used for the computer program of electronic data interchange, wherein above-mentioned computer program executes computer such as
Step some or all of described in the embodiment of the present application first aspect.
5th aspect, the embodiment of the present application provide a kind of computer program product, wherein above-mentioned computer program product
Non-transient computer readable storage medium including storing computer program, above-mentioned computer program are operable to make to calculate
Machine executes the step some or all of as described in the embodiment of the present application first aspect.The computer program product can be one
A software installation packet.
As can be seen that image presentation method and Related product described in the embodiment of the present application, are applied to electronic equipment,
The historical operational parameters collection for obtaining each image in multiple images obtains multiple historical operational parameters collection, each historical operation
Parameter set includes at least one operating parameter, and each operating parameter is used to state an operational motion to image, according to multiple
Historical operational parameters collection carries out preference evaluation to image each in multiple images, obtains multiple evaluations of estimate, and each image is corresponding
One evaluation of estimate, preference is for indicating target object to the fancy grade of image, according to predetermined deep learning model to multiple
Image is classified, and multiclass image is obtained, and every class image includes at least an image, determines that every class image is corresponding in multiclass image
Evaluation of estimate, obtain multiple evaluation of estimate collection, every corresponding evaluation of estimate collection of one kind image determines multiclass according to multiple evaluation of estimate collection
The corresponding preference gradations of every class image, obtain multiple preference gradations in image, show multiclass image according to multiple preference gradations, from
And can determine the preference of every class image, in turn, realize that photograph album shows function, improves electronics and sets according to preference
Standby intelligence and convenience.
Detailed description of the invention
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of application for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.
Figure 1A is the structural schematic diagram of a kind of electronic equipment provided by the embodiments of the present application；
Figure 1B is a kind of flow diagram of image presentation method provided by the embodiments of the present application；
Fig. 2 is the flow diagram of another image presentation method provided by the embodiments of the present application；
Fig. 3 is the structural schematic diagram of a kind of electronic equipment provided by the embodiments of the present application；
Fig. 4 A is a kind of functional unit composition block diagram of image demonstration apparatus provided by the embodiments of the present application；
Fig. 4 B is the functional unit composition block diagram of another image demonstration apparatus provided by the embodiments of the present application.
Specific embodiment
In order to make those skilled in the art more fully understand application scheme, below in conjunction in the embodiment of the present application
Attached drawing, the technical scheme in the embodiment of the application is clearly and completely described, it is clear that described embodiment is only
Some embodiments of the present application, instead of all the embodiments.Based on the embodiment in the application, those of ordinary skill in the art
Every other embodiment obtained without creative efforts, shall fall in the protection scope of this application.
The description and claims of this application and term " first " in above-mentioned attached drawing, " second " etc. are for distinguishing
Different objects, are not use to describe a particular order.In addition, term " includes " and " having " and their any deformations, it is intended that
It is to cover and non-exclusive includes.Such as the process, method, system, product or equipment for containing a series of steps or units do not have
It is defined in listed step or unit, but optionally further comprising the step of not listing or unit, or optionally also wrap
Include other step or units intrinsic for these process, methods, product or equipment.
Referenced herein " embodiment " is it is meant that a particular feature, structure, or characteristic described can wrap in conjunction with the embodiments
It is contained at least one embodiment of the application.Each position in the description occur the phrase might not each mean it is identical
Embodiment, nor the independent or alternative embodiment with other embodiments mutual exclusion.Those skilled in the art explicitly and
Implicitly understand, embodiment described herein can be combined with other embodiments.
Electronic equipment involved by the embodiment of the present application may include the various handheld devices with wireless communication function,
Mobile unit, wearable device (smartwatch, Intelligent bracelet, wireless headset, augmented reality/virtual reality device, Brilliant Eyes
Mirror), calculate equipment or be connected to radio modem other processing equipments and various forms of user equipment (user
Equipment, UE), mobile station (mobile station, MS), terminal device (terminal device) etc..For convenience
Description, apparatus mentioned above are referred to as electronic equipment.
It describes in detail below to the embodiment of the present application.
Figure 1A is please referred to, Figure 1A is that the embodiment of the present application provides the structural schematic diagram of a kind of electronic equipment, electronic equipment
Including control circuit and input-output circuit, imput output circuit is connected to the control circuit.
Wherein, control circuit may include storage and processing circuit.Storage circuit in the storage and processing circuit can be with
It is memory, such as hard drive memory, nonvolatile memory (such as flash memory or it is used to form the other of solid state drive
Electrically programmable read only memory etc.), volatile memory (such as either statically or dynamically random access memory etc.) etc., the application
Embodiment is with no restriction.Processing circuit in storage and processing circuit can be used for the operating of controlling electronic devices.Processing electricity
Road can microprocessor based on one or more, microcontroller, digital signal processor, baseband processor, power management unit,
Audio codec chip, specific integrated circuit, display-driver Ics, alternatively, quantum chip, nano chips etc. come real
It is existing.
Storage and processing circuit can be used for running the software in electronic equipment, such as play incoming call prompting jingle bell application journey
Sequence, play short message prompt jingle bell application program, play alarm clock prompting jingle bell application program, play media file application program,
Voice over internet protocol (voice over internet protocol, VOIP) call application program, operating system function
Energy is equal.These softwares can be used for executing some control operations, for example, playing incoming call prompting jingle bell, playing short message prompt sound
Other functions etc. in bell, broadcasting alarm clock prompting jingle bell, broadcasting media file, progress voice telephone calls and electronic equipment,
The embodiment of the present application is with no restriction.
Wherein, input-output circuit can be used for that electronic equipment is made to realize outputting and inputting for data, i.e. permission electronic equipment
From outer equipment receiving data and electronic equipment is allowed to export data to external equipment from electronic equipment.
Input-output circuit may further include sensor.Sensor may include ambient light sensor, based on light and
The infrared proximity transducer of capacitor, fingerprint sensor, ultrasonic sensor, touch sensor is (for example, be based on light touch sensor
And/or capacitive touch sensors, wherein touch sensor can be a part of touching display screen, can also be used as one
Touch sensor arrangement independently uses), acceleration transducer, gravity sensor and other sensors etc., fingerprint sensor be with
Lower at least one: capacitive fingerprint sensor, ultrasonic fingerprint sensor, optical fingerprint sensor etc. are not limited thereto.It is defeated
Enter-output circuit can further include audio component, audio component can be used for providing for electronic equipment audio input and
Output function.Audio component can also include tone generator and other components for being used to generate and detect sound.
Input-output circuit can also include multiple display screens.Above-mentioned multiple display screens include 2 or 2 or more aobvious
The front and back with electronic equipment can be respectively set in display screen, multiple display screens, certainly in practical applications, multiple display screens
Other positions can also be set, and display screen may include liquid crystal display, organic light-emitting diode (OLED) display screen, and electric ink is aobvious
Display screen, plasma panel, one or several kinds of combination in the display screen using other display technologies.Display screen may include
Touch sensor array (that is, display screen can be touching display screen).Touch sensor can be by transparent touch sensor
The capacitive touch sensors that electrode (such as tin indium oxide (ITO) electrode) array is formed, or can be and use other touches
The touch sensor that technology is formed, such as sound wave touch-control, pressure sensible touch, resistive touch, optical touch etc., the embodiment of the present application is not
It is restricted.
Input-output circuit, which can further include telecommunication circuit, can be used for providing for electronic equipment and external equipment
The ability of communication.Telecommunication circuit may include analog- and digital- input-output interface circuit, and be based on radiofrequency signal and/or light
The radio communication circuit of signal.Radio communication circuit in telecommunication circuit may include radio-frequency transceiver circuitry, power amplifier
Circuit, low-noise amplifier, switch, filter and antenna.For example, the radio communication circuit in telecommunication circuit may include
For supported by emitting and receiving near-field coupling electromagnetic signal near-field communication (near field communication,
NFC circuit).For example, telecommunication circuit may include near-field communication aerial and near-field communication transceiver.Telecommunication circuit can also wrap
Include cellular telephone transceiver and antenna, wireless lan transceiver circuit and antenna etc..
Input-output circuit can further include other input-output units.Input-output unit may include
Button, control stick, click wheel, scroll wheel, touch tablet, keypad, keyboard, camera, light emitting diode and other state instructions
Device etc..
Wherein, electronic equipment can further include battery (not shown), and battery provides electric energy for electron equipment.
Figure 1B is please referred to, Figure 1B is a kind of flow diagram of image presentation method provided by the embodiments of the present application, is such as schemed
Shown, applied to electronic equipment as shown in Figure 1A, this image presentation method includes:
101, the historical operational parameters collection for obtaining each image in multiple images obtains multiple historical operational parameters collection,
Each historical operational parameters collection includes at least one operating parameter, and the operation that each operating parameter is used to state to image is dynamic
Make.
Wherein, multiple images can be stored in advance in electronic equipment.User can carry out different operations to each image
Movement, for example, image is opened, closing image, deletion image, restored image, forwarding image, U.S. face image, collection image etc.,
It is not limited here, therefore, different operation then can produce different operating parameters, for example, opening image, then can remember
Image duration is opened in record, in another example, collection image, then can recorde operating parameter is 1, and non-collection image then can recorde behaviour
Making parameter is 0.Each image can then correspond to a historical operational parameters collection, multiple images then correspond to multiple historical operation ginsengs
Manifold, each historical operational parameters collection can then correspond to an operating parameter, each operating parameter be then used to state to image into
One operational motion of row operation.Certainly, image operation can be stored in the historical operational parameters collection of each image to go through
History database of record.
Optionally, above-mentioned each historical operational parameters collection may include at least one operating parameter, and operating parameter can be
Following at least one: whether the average residence duration (i.e. the average duration of user's displaying image) of image collect operation, turn
Hair operation, delete number, whether restoring operation etc., whether picture mosaic operation etc., it is not limited here.
Optionally, above-mentioned steps 101 obtain the historical operational parameters collection of each image in multiple images, obtain multiple
Historical operational parameters collection can be implemented as follows:
It obtains each image in multiple images and obtains multiple historical operations in the historical operational parameters collection of preset time period
Parameter set.
Wherein, preset time period can be by user's self-setting or system default.It is the different periods, then corresponding to go through
History operating parameter collection is different, for example, user may be for a period of time to a certain interesting image, at another section in real life
Time may then lose interest in the image, in this way, can then reasonably select the operation of user's interested period.
102, preference evaluation is carried out to image each in multiple described images according to the multiple historical operational parameters collection,
Multiple evaluations of estimate are obtained, the corresponding evaluation of estimate of each image, preference is for indicating target object to the fancy grade of image.
Wherein, it includes at least one operating parameter that multiple historical operational parameters, which concentrate each historical operation collection, in turn, can be with
Preference evaluation is carried out to image according to these operating parameters, it is generally the case that user largely can be to the image of hobby
It is repeatedly opened, or even collection, for the image not liked, then it is few largely to open number.Therefore, it can be based on more
A historical operational parameters collection carries out preference evaluation to image each in multiple images, obtains multiple evaluations of estimate, each image pair
An evaluation of estimate is answered, for preference for indicating target object to the fancy grade of image, target object can be user or electricity
The owner of sub- equipment.
Wherein, above-mentioned steps 102, according to the multiple historical operational parameters collection to each image in multiple described images into
The evaluation of row preference, obtains multiple evaluations of estimate, it may include following steps:
21, the corresponding weight of each operating parameter in the historical operational parameters collection i is obtained, at least one weight is obtained,
The historical operational parameters collection i is either one or two of the multiple historical operational parameters concentration；
22, according in the historical operational parameters collection i operating parameter and at least one described weight be weighted fortune
It calculates, obtains evaluation of estimate.
Wherein, by taking historical operational parameters collection i as an example, historical operational parameters collection i is times that multiple historical operational parameters are concentrated
One historical operational parameters collection, each historical operational parameters collection include at least one operating parameter, and each operating parameter is corresponding extremely
Lack a weight, the mapping relations between operating parameter and weight can be stored in advance in electronic equipment, in turn, according to the mapping
Relationship can determine the corresponding weight of each operating parameter.Assuming that historical operational parameters collection i includes n operating parameter, it is each
Operating parameter corresponds to a weight, and each weight may be between 0~1, as follows:
| Operating parameter | Weight |
| Operating parameter 1 | Weight 1 |
| Operating parameter 2 | Weight 2 |
| … | … |
| Operating parameter n | Weight n |
In turn, can according in historical operational parameters i operating parameter and at least one weight be weighted,
Evaluation of estimate=operating parameter 1* weight 1+ operating parameter 2* weight 2+ ...+operating parameter n* weight n, in this way, may be implemented each
The corresponding evaluation of estimate of historical operational parameters collection.
103, classify according to predetermined deep learning model to multiple described images, obtain multiclass image, every class image
Including at least an image.
Wherein, above-mentioned predetermined deep learning model can be following at least one: convolutional neural networks deep learning model,
Adaboost deep learning model, random forest deep learning model, details are not described herein, in the specific implementation, electronic equipment can
Think that the positive sample image for acquiring every a kind of image and negative sample image are trained, in turn, obtains predetermined deep learning model.
Specifically, electronic equipment can classify to multiple images according to predetermined deep learning model, obtain multiclass image, every one kind
Image includes at least an image, and every class image can also correspond to a classification logotype.Classification logotype can be following at least one
Kind: night portrait, seabeach, snowfield, baby, pet, it is not limited here.
Optionally, above-mentioned steps 102, step 103 can execute parallel, alternatively, step 103 can be executed prior to step 102,
It is not limited here.
104, it determines the corresponding evaluation of estimate of every class image in the multiclass image, obtains multiple evaluation of estimate collection, every a kind of figure
As a corresponding evaluation of estimate collection.
It wherein, include at least one image in every class image, each image corresponds to an evaluation of estimate, in turn, every class image
An evaluation of estimate collection can be corresponded to, then multiclass image, then correspond to multiple evaluation of estimate collection.
105, the corresponding preference gradations of every class image in the multiclass image are determined according to the multiple evaluation of estimate collection, obtained
Multiple preference gradations.
Wherein, evaluation of estimate reflects user to the preference of single image to a certain extent, and evaluation of estimate collection is then one
Determine to reflect therefore user can determine in multiclass image the preference of a kind of image according to multiple evaluation of estimate collection in degree
The corresponding preference gradations of every class image, obtain multiple preference gradations, for example, the average ratings that can be concentrated according to multiple evaluations of estimate
Value determines the corresponding preference gradations of every class image, that is, the mapping relations between average ratings value and preference gradations are stored in advance,
In turn, the corresponding preference gradations of each average ratings value can be determined, such as: average ratings value is bigger, then preference gradations are higher, again
For example, can determine the corresponding preference gradations of every class image according to the evaluation of estimate summation of multiple evaluations of estimate concentration, i.e., deposit in advance
Mapping relations between storage evaluation of estimate and preference gradations can determine the corresponding preference gradations of each evaluation of estimate summation in turn,
Such as: evaluation of estimate summation is bigger, then preference gradations are higher.
Optionally, above-mentioned steps 105 determine that every class image is corresponding in the multiclass image according to the multiple evaluation of estimate collection
Preference gradations, obtain multiple preference gradations, it may include following steps:
51, determine that the multiple evaluation of estimate concentrates the evaluation of estimate quantity and evaluation of estimate mean value of each evaluation of estimate collection respectively,
Obtain multiple evaluation of estimate quantity and multiple evaluation of estimate mean values；
52, obtaining multiple evaluations of estimate concentrates each evaluation of estimate to concentrate corresponding first weight of evaluation of estimate quantity, and evaluation
It is worth corresponding second weight of mean value；
53, the corresponding evaluation of estimate quantity of each evaluation of estimate collection, evaluation of estimate mean value, first are concentrated according to the multiple evaluation of estimate
Weight and the second weight are weighted, and obtain multiple preference values；
54, it according to the mapping relations between preset preference value and preference gradations, determines each in the multiple preference value
The corresponding preference gradations of preference value, obtain multiple preference gradations.
Wherein, the application considers the image of some classifications, it is possible to which quantity is more, but average ratings value is low, alternatively, evaluation of estimate
Summation is low, and therefore, two dimensions of combining assessment value quantity and evaluation of estimate mean value to carry out hobby of the user to certain class image
Overall merit, in the specific implementation, electronic equipment can determine that multiple evaluations of estimate concentrate the corresponding evaluation of estimate number of each evaluation of estimate collection
Amount and evaluation of estimate mean value, obtain multiple evaluation of estimate quantity and multiple evaluation of estimate mean values, can be stored in advance and comment in electronic equipment
It is every can to determine that multiple evaluations of estimate are concentrated according to the mapping relations in turn for the mapping relations being worth between quantity and the first weight
One evaluation of estimate concentrates corresponding first weight of evaluation of estimate quantity, and reflecting between evaluation of estimate mean value and the second weight is stored in advance
Relationship is penetrated, in turn, according to the mapping relations, determines that multiple evaluations of estimate concentrate corresponding second weight of each evaluation of estimate mean value, into
And the corresponding evaluation of estimate quantity of each evaluation of estimate collection, evaluation of estimate mean value, the first weight and the second power are concentrated according to multiple evaluations of estimate
Value is weighted, and obtains multiple preference values, specifically, for any evaluation of estimate collection, corresponding preference value=comment
Be worth the first weight of quantity *+average ratings value the second weight of *, can also be stored in advance in electronic equipment preset preference value with
Mapping relations between preference gradations, in this way, determining that each preference value is corresponding partially in multiple preference values according to the mapping relations
Good grade, obtains multiple preference gradations.For example, preference gradations can be with are as follows: it is best, like, commonly, it is not limited here.
106, the multiclass image is shown according to the multiple preference gradations.
Wherein, different preference gradations illustrate that user to the fancy grade of such image, therefore, is having to a certain extent
, can be higher with preference gradations during body is realized, then it can the corresponding image of more preferential displaying preference gradations.
Optionally, above-mentioned steps 106 show the multiclass image according to the multiple preference gradations, it may include following step
It is rapid:
61, the maximum at least target image of evaluation of estimate is chosen from one kind image every in the multiclass image；
62, at least a target image is obtained into multiple cover images as cover image, every one kind image is corresponding
One cover image；
63, the displaying sequence of the multiclass image is determined according to the multiple preference gradations；
64, the multiple cover image is shown according to the displaying sequence.
Wherein, multiple preference gradations then can be used as to form a priority orders, in turn, according to multiple preference gradations
Determine the displaying sequence of multiclass image, for example, preference gradations are higher, then more preferential displaying.It is every in multiclass image in electronic equipment
Each image corresponds to an evaluation of estimate in a kind of image, and therefore, largest evaluation value is corresponding in available every a kind of image
Target image, it is of course also possible to include the corresponding multiple target images of multiple largest evaluation values in every one kind image, in turn,
It can be using an at least target image as cover image, every corresponding cover image of one kind image, multiple target images
It then can be by jigsaw puzzle fashion as a cover image, finally, showing multiple cover images, Mei Yifeng according to displaying sequence
Face image then corresponds to a kind of image, and the cover image, then can show all images in such image when the user clicks.
Optionally, before above-mentioned steps 101, can also include the following steps:
A1, image library is obtained；
A2, default identification sets are obtained；
A3, described image library is screened according to the default identification sets, obtains multiple described images.
Wherein, default identification sets can be by user's self-setting or system default.Default identification sets can be for below extremely
A kind of less: preset time period, preset format type, default photographing mode, default camera, is preset and takes pictures default store path
Place etc., it is not limited here.Specifically, the available image library of electronic equipment may include big in the image library certainly
Spirogram picture can screen these images in turn, it can obtain default identification sets, according to this preset identification sets can be with
Image library is screened, multiple images are obtained.
Illustrating lower electronic equipment can be set default identification sets, such as: image file type white list (specified image pane
Formula), such as retain jpg format, bmp format, png format, alternatively, path white list (specified path) where setting image, such as only
Reservation/storage/0/DCIM catalogue establishes image operation historical record database in turn, modifies the open in system libc
Function and close function judge whether open be the image that picture format is specified in specified path when having File Open every time,
If it is, being recorded into filename, routing information and opening time is opened in image operation historical record database, in image
Image shut-in time point is recorded into image operation historical record database when being closed, using preset deep learning model
Classify to the image in database, for example, classification logotype can divide are as follows: night portrait, seabeach, snowfield, baby, pet
Deng in turn, according to the operation data in image operation historical record database, (such as: number that image is opened, image are averaged
Residence time) and classification results count the average residence time that all kinds of images open numbers and all kinds of images, it is of course also possible to root
The time interval that each image opens moment and establishment moment is calculated according to the data of database, by residence time and time interval
Regularization carries out the generic out of image classification to each image in photograph album to 1~5 numerical intervals, and calculates
The time interval of the image distance establishment moment calculates the category score of this image, specifically: it can be by the opening number of every class
It is added with average residence time, summation is weighted by the category score of each image and apart from establishment moment time interval, by institute
Image is determined that every class image is corresponding according to preference numerical value in photograph album by potential preference numerical value of the value as user's image
Preference gradations, show the multiclass image according to preference gradations.
As can be seen that image presentation method described in the embodiment of the present application, is applied to electronic equipment, obtains multiple figures
The historical operational parameters collection of each image, obtains multiple historical operational parameters collection, each historical operational parameters collection includes as in
At least one operating parameter, each operating parameter are used to state an operational motion to image, be joined according to multiple historical operations
Manifold carries out preference evaluation to image each in multiple images, obtains multiple evaluations of estimate, and each image corresponds to an evaluation of estimate,
Preference is for indicating that target object to the fancy grade of image, divides multiple images according to predetermined deep learning model
Class, obtains multiclass image, and every class image includes at least an image, determines the corresponding evaluation of estimate of every class image in multiclass image,
Multiple evaluation of estimate collection are obtained, every corresponding evaluation of estimate collection of one kind image determines every in multiclass image according to multiple evaluation of estimate collection
The corresponding preference gradations of class image, obtain multiple preference gradations, show multiclass image according to multiple preference gradations, thus, it is possible to
It determines the preference of every class image, in turn, realizes that photograph album shows function according to preference, improve the intelligence of electronic equipment
Property and convenience.
Consistently with embodiment shown in above-mentioned Figure 1B, referring to Fig. 2, Fig. 2 is a kind of figure provided by the embodiments of the present application
As the flow diagram of methods of exhibiting, as shown, being applied to electronic equipment as shown in Figure 1A, this image presentation method packet
It includes:
201, image library is obtained.
202, default identification sets are obtained.
203, described image library is screened according to the default identification sets, obtains multiple images.
204, the historical operational parameters collection for obtaining each image in multiple described images, obtains multiple historical operational parameters
Collection, each historical operational parameters collection include at least one operating parameter, and each operating parameter is used to state a behaviour to image
It acts.
205, preference evaluation is carried out to image each in multiple described images according to the multiple historical operational parameters collection,
Multiple evaluations of estimate are obtained, the corresponding evaluation of estimate of each image, preference is for indicating target object to the fancy grade of image.
206, classify according to predetermined deep learning model to multiple described images, obtain multiclass image, every class image
Including at least an image.
207, it determines the corresponding evaluation of estimate of every class image in the multiclass image, obtains multiple evaluation of estimate collection, every a kind of figure
As a corresponding evaluation of estimate collection.
208, the corresponding preference gradations of every class image in the multiclass image are determined according to the multiple evaluation of estimate collection, obtained
Multiple preference gradations.
209, the multiclass image is shown according to the multiple preference gradations.
Wherein, the specific descriptions of above-mentioned steps 201- step 209 are referred to image displaying side described in above-mentioned Figure 1B
The corresponding steps of method, details are not described herein.
As can be seen that image presentation method described in the embodiment of the present application, is applied to electronic equipment, image is obtained
Library obtains default identification sets, screens according to identification sets are preset to image library, obtains multiple images, obtain multiple images
In each image historical operational parameters collection, obtain multiple historical operational parameters collection, each historical operational parameters collection includes extremely
A few operating parameter, each operating parameter is used to state an operational motion to image, according to multiple historical operational parameters
Collection carries out preference evaluation to image each in multiple images, obtains multiple evaluations of estimate, and each image corresponds to an evaluation of estimate, partially
For good degree for indicating target object to the fancy grade of image, foundation predetermined deep learning model classifies to multiple images,
Obtain multiclass image, every class image includes at least an image, determines the corresponding evaluation of estimate of every class image in multiclass image, obtains
Multiple evaluation of estimate collection, every corresponding evaluation of estimate collection of one kind image, determine every class figure in multiclass image according to multiple evaluation of estimate collection
As corresponding preference gradations, multiple preference gradations are obtained, show multiclass image according to multiple preference gradations, thus, it is possible to determine
The preference of every class image, in turn, according to preference realize photograph album show function, improve electronic equipment intelligence and
Convenience.
Consistently with above-described embodiment, referring to Fig. 3, Fig. 3 is the knot of a kind of electronic equipment provided by the embodiments of the present application
Structure schematic diagram, as shown, the electronic equipment includes processor, memory, communication interface and one or more program,
In, said one or multiple programs are stored in above-mentioned memory, and are configured to be executed by above-mentioned processor, and the application is real
It applies in example, electronic equipment, which is in, puts out screen state, and above procedure includes the instruction for executing following steps:
The historical operational parameters collection for obtaining each image in multiple images obtains multiple historical operational parameters collection, each
Historical operational parameters collection includes at least one operating parameter, and each operating parameter is used to state an operational motion to image；
Preference evaluation is carried out to image each in multiple described images according to the multiple historical operational parameters collection, is obtained
Multiple evaluations of estimate, the corresponding evaluation of estimate of each image, preference is for indicating target object to the fancy grade of image；
Classify according to predetermined deep learning model to multiple described images, obtains multiclass image, every class image is at least
Including an image；
It determines the corresponding evaluation of estimate of every class image in the multiclass image, obtains multiple evaluation of estimate collection, every one kind image pair
Answer an evaluation of estimate collection；
The corresponding preference gradations of every class image in the multiclass image are determined according to the multiple evaluation of estimate collection, are obtained multiple
Preference gradations；
The multiclass image is shown according to the multiple preference gradations.
As can be seen that electronic equipment described in the embodiment of the present application, obtains in multiple images going through for each image
History operating parameter collection obtains multiple historical operational parameters collection, and each historical operational parameters collection includes at least one operating parameter, often
One operating parameter is used to state an operational motion to image, according to multiple historical operational parameters collection to each in multiple images
Image carries out preference evaluation, obtains multiple evaluations of estimate, the corresponding evaluation of estimate of each image, preference is for indicating target pair
As the fancy grade to image, classifies according to predetermined deep learning model to multiple images, obtain multiclass image, every class figure
As including at least an image, determines the corresponding evaluation of estimate of every class image in multiclass image, obtain multiple evaluation of estimate collection, every one kind
Image corresponds to an evaluation of estimate collection, determines the corresponding preference gradations of every class image in multiclass image according to multiple evaluation of estimate collection, obtains
To multiple preference gradations, multiclass image is shown according to multiple preference gradations, thus, it is possible to determine the preference of every class image,
In turn, it realizes that photograph album shows function according to preference, improves the intelligence and convenience of electronic equipment.
In a possible example, it is described according to the multiple historical operational parameters collection to every in multiple described images
One image carries out preference evaluation, and in terms of obtaining multiple evaluations of estimate, above procedure includes the instruction for executing following steps:
The corresponding weight of each operating parameter in the historical operational parameters collection i is obtained, at least one weight is obtained, it is described
Historical operational parameters collection i is any one historical operational parameters collection that the multiple historical operational parameters are concentrated；
According in the historical operational parameters collection i operating parameter and at least one described weight be weighted,
Obtain evaluation of estimate.
In a possible example, above procedure further includes the instruction for executing following steps:
Obtain image library；
Obtain default identification sets；
Described image library is screened according to the default identification sets, obtains multiple described images.
In a possible example, every class figure in the multiclass image is determined according to the multiple evaluation of estimate collection described
As corresponding preference gradations, in terms of obtaining multiple preference gradations, above procedure includes the instruction for executing following steps:
It determines that the multiple evaluation of estimate concentrates the evaluation of estimate quantity and evaluation of estimate mean value of each evaluation of estimate collection respectively, obtains
Multiple evaluation of estimate quantity and multiple evaluation of estimate mean values；
Obtaining multiple evaluations of estimate concentrates each evaluation of estimate to concentrate corresponding first weight of evaluation of estimate quantity and evaluation of estimate equal
It is worth corresponding second weight；
The corresponding evaluation of estimate quantity of each evaluation of estimate collection, evaluation of estimate mean value, the first power are concentrated according to the multiple evaluation of estimate
Value and the second weight are weighted, and obtain multiple preference values；
According to the mapping relations between preset preference value and preference gradations, each preference in the multiple preference value is determined
It is worth corresponding preference gradations, obtains multiple preference gradations.
In a possible example, in terms of the multiclass image according to the displaying of the multiple preference gradations, on
Stating program includes the instruction for executing following steps:
The maximum at least target image of evaluation of estimate is chosen from one kind image every in the multiclass image；
By an at least target image as cover image, multiple cover images, every one kind image corresponding one are obtained
A cover image；
The displaying sequence of the multiclass image is determined according to the multiple preference gradations；
The multiple cover image is shown according to the displaying sequence.
It is above-mentioned that mainly the scheme of the embodiment of the present application is described from the angle of method side implementation procedure.It is understood that
, in order to realize the above functions, it comprises execute the corresponding hardware configuration of each function and/or software mould for electronic equipment
Block.Those skilled in the art should be readily appreciated that, in conjunction with each exemplary unit of embodiment description presented herein
And algorithm steps, the application can be realized with the combining form of hardware or hardware and computer software.Some function actually with
Hardware or computer software drive the mode of hardware to execute, the specific application and design constraint item depending on technical solution
Part.Professional technician can specifically realize described function to each using distinct methods, but this reality
Now it is not considered that exceeding scope of the present application.
The embodiment of the present application can carry out the division of functional unit according to above method example to electronic equipment, for example, can
With each functional unit of each function division of correspondence, two or more functions can also be integrated in a processing unit
In.Above-mentioned integrated unit both can take the form of hardware realization, can also realize in the form of software functional units.It needs
It is noted that be schematical, only a kind of logical function partition to the division of unit in the embodiment of the present application, it is practical real
It is current that there may be another division manner.
Fig. 4 A is the functional unit composition block diagram of image demonstration apparatus 400 involved in the embodiment of the present application.The image
It shows device 400, is applied to electronic equipment, described device 400 includes: acquiring unit 401, evaluation unit 402, taxon
403, determination unit 404 and display unit 405, wherein
Acquiring unit 401 obtains multiple history for obtaining the historical operational parameters collection of each image in multiple images
Operating parameter collection, each historical operational parameters collection include at least one operating parameter, and each operating parameter is for stating to image
An operational motion；
Evaluation unit 402, for according to the multiple historical operational parameters collection to each image in multiple described images into
The evaluation of row preference obtains multiple evaluations of estimate, and the corresponding evaluation of estimate of each image, preference is for indicating target object to figure
The fancy grade of picture；
Taxon 403 obtains multiclass figure for classifying according to predetermined deep learning model to multiple described images
Picture, every class image include at least an image；
Determination unit 404 obtains multiple evaluations of estimate for determining the corresponding evaluation of estimate of every class image in the multiclass image
Collection, every corresponding evaluation of estimate collection of one kind image；And every class in the multiclass image is determined according to the multiple evaluation of estimate collection
The corresponding preference gradations of image, obtain multiple preference gradations；
Display unit 405, for showing the multiclass image according to the multiple preference gradations.
As can be seen that image demonstration apparatus described in the embodiment of the present application, is applied to electronic equipment, obtains multiple figures
The historical operational parameters collection of each image, obtains multiple historical operational parameters collection, each historical operational parameters collection includes as in
At least one operating parameter, each operating parameter are used to state an operational motion to image, be joined according to multiple historical operations
Manifold carries out preference evaluation to image each in multiple images, obtains multiple evaluations of estimate, and each image corresponds to an evaluation of estimate,
Preference is for indicating that target object to the fancy grade of image, divides multiple images according to predetermined deep learning model
Class, obtains multiclass image, and every class image includes at least an image, determines the corresponding evaluation of estimate of every class image in multiclass image,
Multiple evaluation of estimate collection are obtained, every corresponding evaluation of estimate collection of one kind image determines every in multiclass image according to multiple evaluation of estimate collection
The corresponding preference gradations of class image, obtain multiple preference gradations, show multiclass image according to multiple preference gradations, thus, it is possible to
It determines the preference of every class image, in turn, realizes that photograph album shows function according to preference, improve the intelligence of electronic equipment
Property and convenience.
In a possible example, it is described according to the multiple historical operational parameters collection to every in multiple described images
One image carries out preference evaluation, and in terms of obtaining multiple evaluations of estimate, the evaluation unit 402 is specifically used for:
The corresponding weight of each operating parameter in the historical operational parameters collection i is obtained, at least one weight is obtained, it is described
Historical operational parameters collection i is any one historical operational parameters collection that the multiple historical operational parameters are concentrated；
According in the historical operational parameters collection i operating parameter and at least one described weight be weighted,
Obtain evaluation of estimate.
In a possible example, as shown in Figure 4 B, Fig. 4 B is the another modification of image demonstration apparatus shown in Fig. 4 A
Structure can also include: screening unit 406 compared with Fig. 4 A, specific as follows:
The acquiring unit 401, also particularly useful for acquisition image library；And obtain default identification sets；
The screening unit 406 obtains described more for screening according to the default identification sets to described image library
Open image.
In a possible example, every class figure in the multiclass image is determined according to the multiple evaluation of estimate collection described
As corresponding preference gradations, in terms of obtaining multiple preference gradations, the determination unit 404 is specifically used for:
It determines that the multiple evaluation of estimate concentrates the evaluation of estimate quantity and evaluation of estimate mean value of each evaluation of estimate collection respectively, obtains
Multiple evaluation of estimate quantity and multiple evaluation of estimate mean values；
Obtaining multiple evaluations of estimate concentrates each evaluation of estimate to concentrate corresponding first weight of evaluation of estimate quantity and evaluation of estimate equal
It is worth corresponding second weight；
The corresponding evaluation of estimate quantity of each evaluation of estimate collection, evaluation of estimate mean value, the first power are concentrated according to the multiple evaluation of estimate
Value and the second weight are weighted, and obtain multiple preference values；
According to the mapping relations between preset preference value and preference gradations, each preference in the multiple preference value is determined
It is worth corresponding preference gradations, obtains multiple preference gradations.
In a possible example, in terms of the multiclass image according to the displaying of the multiple preference gradations, institute
Display unit 405 is stated to be specifically used for:
The maximum at least target image of evaluation of estimate is chosen from one kind image every in the multiclass image；
By an at least target image as cover image, multiple cover images, every one kind image corresponding one are obtained
A cover image；
The displaying sequence of the multiclass image is determined according to the multiple preference gradations；
The multiple cover image is shown according to the displaying sequence.
The embodiment of the present application also provides a kind of computer storage medium, wherein computer storage medium storage is for electricity
The computer program of subdata exchange, the computer program make computer execute any as recorded in above method embodiment
Some or all of method step, above-mentioned computer include electronic equipment.
The embodiment of the present application also provides a kind of computer program product, and above-mentioned computer program product includes storing calculating
The non-transient computer readable storage medium of machine program, above-mentioned computer program are operable to that computer is made to execute such as above-mentioned side
Some or all of either record method step in method embodiment.The computer program product can be a software installation
Packet, above-mentioned computer includes electronic equipment.
It should be noted that for the various method embodiments described above, for simple description, therefore, it is stated as a series of
Combination of actions, but those skilled in the art should understand that, the application is not limited by the described action sequence because
According to the application, some steps may be performed in other sequences or simultaneously.Secondly, those skilled in the art should also know
It knows, the embodiments described in the specification are all preferred embodiments, related actions and modules not necessarily the application
It is necessary.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, there is no the portion being described in detail in some embodiment
Point, reference can be made to the related descriptions of other embodiments.
In several embodiments provided herein, it should be understood that disclosed device, it can be by another way
It realizes.For example, the apparatus embodiments described above are merely exemplary, such as the division of said units, it is only a kind of
Logical function partition, there may be another division manner in actual implementation, such as multiple units or components can combine or can
To be integrated into another system, or some features can be ignored or not executed.Another point, shown or discussed is mutual
Coupling, direct-coupling or communication connection can be through some interfaces, the indirect coupling or communication connection of device or unit,
It can be electrical or other forms.
Above-mentioned unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, each functional unit in each embodiment of the application can integrate in one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If above-mentioned integrated unit is realized in the form of SFU software functional unit and sells or use as independent product
When, it can store in a computer-readable access to memory.Based on this understanding, the technical solution of the application substantially or
Person says that all or part of the part that contributes to existing technology or the technical solution can body in the form of software products
Reveal and, which is stored in a memory, including some instructions are used so that a computer equipment
(can be personal computer, server or network equipment etc.) executes all or part of each embodiment above method of the application
Step.And memory above-mentioned includes: USB flash disk, read-only memory (ROM, Read-Only Memory), random access memory
The various media that can store program code such as (RAM, Random Access Memory), mobile hard disk, magnetic or disk.
Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of above-described embodiment is can
It is completed with instructing relevant hardware by program, which can store in a computer-readable memory, memory
May include: flash disk, read-only memory (English: Read-Only Memory, referred to as: ROM), random access device (English:
Random Access Memory, referred to as: RAM), disk or CD etc..
The embodiment of the present application is described in detail above, specific case used herein to the principle of the application and
Embodiment is expounded, the description of the example is only used to help understand the method for the present application and its core ideas；
At the same time, for those skilled in the art can in specific embodiments and applications according to the thought of the application
There is change place, in conclusion the contents of this specification should not be construed as limiting the present application.
Claims (10)
1. a kind of image presentation method characterized by comprising
The historical operational parameters collection for obtaining each image in multiple images obtains multiple historical operational parameters collection, each history
Operating parameter collection includes at least one operating parameter, and each operating parameter is used to state an operational motion to image；
Preference evaluation is carried out to image each in multiple described images according to the multiple historical operational parameters collection, is obtained multiple
Evaluation of estimate, the corresponding evaluation of estimate of each image, preference is for indicating target object to the fancy grade of image；
Classify according to predetermined deep learning model to multiple described images, obtains multiclass image, every class image includes at least
One image；
It determines the corresponding evaluation of estimate of every class image in the multiclass image, obtains multiple evaluation of estimate collection, every one kind image corresponding one
A evaluation of estimate collection；
The corresponding preference gradations of every class image in the multiclass image are determined according to the multiple evaluation of estimate collection, obtain multiple preferences
Grade；
The multiclass image is shown according to the multiple preference gradations.
2. the method according to claim 1, wherein it is described according to the multiple historical operational parameters collection to described
Each image carries out preference evaluation in multiple images, obtains multiple evaluations of estimate, comprising:
The corresponding weight of each operating parameter in the historical operational parameters collection i is obtained, at least one weight, the history are obtained
Operating parameter collection i is any one historical operational parameters collection that the multiple historical operational parameters are concentrated；
According in the historical operational parameters collection i operating parameter and at least one described weight be weighted, obtain
Evaluation of estimate.
3. method according to claim 1 or 2, which is characterized in that the method also includes:
Obtain image library；
Obtain default identification sets；
Described image library is screened according to the default identification sets, obtains multiple described images.
4. method according to claim 1-3, which is characterized in that described to be determined according to the multiple evaluation of estimate collection
The corresponding preference gradations of every class image, obtain multiple preference gradations in the multiclass image, comprising:
It determines that the multiple evaluation of estimate concentrates the evaluation of estimate quantity and evaluation of estimate mean value of each evaluation of estimate collection respectively, obtains multiple
Evaluation of estimate quantity and multiple evaluation of estimate mean values；
Obtaining multiple evaluations of estimate concentrates each evaluation of estimate to concentrate corresponding first weight of evaluation of estimate quantity and evaluation of estimate mean value pair
The second weight answered；
According to the multiple evaluation of estimate concentrate the corresponding evaluation of estimate quantity of each evaluation of estimate collection, evaluation of estimate mean value, the first weight and
Second weight is weighted, and obtains multiple preference values；
According to the mapping relations between preset preference value and preference gradations, each preference value pair in the multiple preference value is determined
The preference gradations answered obtain multiple preference gradations.
5. method according to claim 1-4, which is characterized in that described to be shown according to the multiple preference gradations
The multiclass image, comprising:
The maximum at least target image of evaluation of estimate is chosen from one kind image every in the multiclass image；
By an at least target image as cover image, multiple cover images, every corresponding envelope of one kind image are obtained
Face image；
The displaying sequence of the multiclass image is determined according to the multiple preference gradations；
The multiple cover image is shown according to the displaying sequence.
6. a kind of image demonstration apparatus, which is characterized in that described device includes:
Acquiring unit obtains multiple historical operation ginsengs for obtaining the historical operational parameters collection of each image in multiple images
Manifold, each historical operational parameters collection include at least one operating parameter, and each operating parameter is used to state one to image
Operational motion；
Evaluation unit, for carrying out preference to image each in multiple described images according to the multiple historical operational parameters collection
Evaluation obtains multiple evaluations of estimate, and the corresponding evaluation of estimate of each image, preference is for indicating target object to the hobby of image
Degree；
Taxon obtains multiclass image, every class for classifying according to predetermined deep learning model to multiple described images
Image includes at least an image；
Determination unit obtains multiple evaluation of estimate collection for determining the corresponding evaluation of estimate of every class image in the multiclass image, each
Class image corresponds to an evaluation of estimate collection；And determine that every class image is corresponding in the multiclass image according to the multiple evaluation of estimate collection
Preference gradations, obtain multiple preference gradations；
Display unit, for showing the multiclass image according to the multiple preference gradations.
7. device according to claim 6, which is characterized in that it is described according to the multiple historical operational parameters collection to institute
It states each image in multiple images and carries out preference evaluation, in terms of obtaining multiple evaluations of estimate, the evaluation unit is specifically used for:
The corresponding weight of each operating parameter in the historical operational parameters collection i is obtained, at least one weight, the history are obtained
Operating parameter collection i is any one historical operational parameters collection that the multiple historical operational parameters are concentrated；
According in the historical operational parameters collection i operating parameter and at least one described weight be weighted, obtain
Evaluation of estimate.
8. device according to claim 6 or 7, which is characterized in that described device further include: screening unit；
The acquiring unit, also particularly useful for acquisition image library；And obtain default identification sets；
The screening unit obtains multiple described images for screening according to the default identification sets to described image library.
9. a kind of electronic equipment, which is characterized in that including processor, memory, the memory is for storing one or more
Program, and be configured to be executed by the processor, described program includes as described in any one in claim 1-5 for executing
The instruction of step in method.
10. a kind of computer readable storage medium, which is characterized in that storage is used for the computer program of electronic data interchange,
In, the computer program makes computer execute the method according to claim 1 to 5.
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| CN109508321B (en) | 2022-01-28 |
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