CN109886852A - Face datection recognition capability Training Methodology, device, equipment, medium and system - Google Patents
Face datection recognition capability Training Methodology, device, equipment, medium and system Download PDFInfo
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Abstract
The present disclosure discloses Face datection recognition capability Training Methodology, device, equipment, medium and systems, receive the operational order that user terminal is sent, the image procossing rudimentary knowledge topic that corresponding degree-of-difficulty factor is transferred according to the current educational background of user, is sent to the user terminal；The selection answer that user terminal is provided according to each topic is received, selection answer is judged, rudimentary knowledge test result is exported；If rudimentary knowledge test result is greater than the first threshold of setting, Face datection operation manual is then sent to user terminal, the Face datection for receiving user terminal feedback operates enabled instruction, starts Face datection performance tests, Face datection operation interface is pushed to user terminal；Receive click location of the user's mouse of user terminal capture in Face datection operation interface, click location of user's mouse in Face datection operation interface is compared with the first setting regions, Face datection operant score is generated, Face datection operant score is pushed to user terminal.
Description
Technical field
This disclosure relates to a kind of Face datection recognition capability Training Methodology, device, equipment, medium and system.
Background technique
The statement of this part is only to refer to background technique relevant to the disclosure, not necessarily constitutes the prior art.
With society be constantly progressive and an urgent demand of the various aspects for quickly and effectively auto authentication, biology
Feature identification technique has obtained development at full speed in recent decades.As a kind of inherent attribute of people, and have very strong
Self stability and individual difference, biological characteristic become the most ideal foundation of auto authentication.Current biological characteristic
Identification technology mainly includes: fingerprint recognition, retina identification, iris recognition, Gait Recognition, hand vein recognition, recognition of face etc..
Compared with other recognition methods, recognition of face is due to having directly, friendly, convenient feature, user without any mental handicape,
It is easy to be received by user, to obtain extensive research and application.
In the implementation of the present invention, following technical problem exists in the prior art in inventor:
Although the research of face recognition technology has had the history of many years, however, for a beginner or rigid introduction
Student for or have certain technical threshold, in the prior art lack one actively guide student study Face datection knowledge
The device of other ability；
It is in the prior art only that teacher gives lessons, student passively receives, and lacks manipulative ability, and explain dull in content weary
Taste lacks the initiative of student, can not carry out the training of system for the different Knowledge Base of student, lack one in the prior art
A device for actively guiding student to learn Face datection recognition capability.
Summary of the invention
In order to solve the deficiencies in the prior art, present disclose provides Face datection recognition capability Training Methodology, device, set
Standby, medium and system have the professional weakness knowledge for strengthening trainee, reach the purpose and effect of balanced training；
In a first aspect, present disclose provides Face datection recognition capability Training Methodologies；
Face datection recognition capability Training Methodology, comprising:
The operational order that user terminal is sent is received, the operational order is used to indicate the corresponding image of the user terminal
Handle the parameter information of training；The parameter information, comprising: user account and user are currently academic；
The image procossing rudimentary knowledge topic that corresponding degree-of-difficulty factor is transferred according to the current educational background of user, is sent to the user
Terminal；
The selection answer that user terminal is provided according to each topic is received, the selection answer is judged, exports base
Plinth knowledge test result；
If rudimentary knowledge test result is greater than the first threshold of setting, Face datection operation manual is sent to user
Terminal, the Face datection for receiving user terminal feedback operate enabled instruction, start Face datection performance tests, Face datection is grasped
User terminal is pushed to as interface；
Click location of the user's mouse of user terminal capture in Face datection operation interface is received, face is done directly
It detects or completes Face datection after guiding to user's mouse click location, circle finally is operated in Face datection to user's mouse
Click location on face is compared with the first setting regions, Face datection operant score is generated, by Face datection operant score
It is pushed to user terminal.
If Face datection operant score is greater than the second threshold of setting, face recognition operation handbook is sent to user
Terminal, receives the face recognition operation enabled instruction of user terminal feedback, and starting face recognition operation is examined, recognition of face is grasped
User terminal is pushed to as interface；
Click location of the user's mouse of user terminal capture on face recognition operation interface is received, face is done directly
It identifies or completes recognition of face after guiding to user's mouse click location, finally to user's mouse in face recognition operation circle
Click location on face is compared with the second setting regions, face recognition operation score is generated, by face recognition operation score
It is pushed to user terminal；If face recognition operation score is greater than the third threshold value of setting, training terminates.
Second aspect, the disclosure additionally provide Face datection recognition capability training device；
Face datection recognition capability training device, comprising:
Input module, receives the operational order that user terminal is sent, and the operational order is used to indicate the user terminal
The parameter information of corresponding image procossing training；The parameter information, comprising: user account and user are currently academic；
Module is transferred, the image procossing rudimentary knowledge topic of corresponding degree-of-difficulty factor is transferred according to the current educational background of user, is sent
To the user terminal；
Judgment module receives the selection answer that user terminal is provided according to each topic, sentences to the selection answer
It is disconnected, export rudimentary knowledge test result；If rudimentary knowledge test result is greater than the first threshold of setting, Face datection is grasped
It is sent to user terminal as handbook, the Face datection for receiving user terminal feedback operates enabled instruction, starting Face datection operation
It examines, Face datection operation interface is pushed to user terminal；
Pushing module receives click location of the user's mouse of user terminal capture in Face datection operation interface, directly
It connects and completes Face datection or complete Face datection after guiding to user's mouse click location, finally to user's mouse in face
Click location in detection operation interface is compared with the first setting regions, generates Face datection operant score, face is examined
It surveys operant score and is pushed to user terminal.
The third aspect, the disclosure additionally provide a kind of electronic equipment, including memory and processor and are stored in storage
The computer instruction run on device and on a processor when the computer instruction is run by processor, is completed first aspect and is appointed
Method in one possible implementation.
Fourth aspect, the disclosure additionally provide a kind of computer readable storage medium, described for storing computer instruction
When computer instruction is executed by processor, in the completion any possible implementation of first aspect the step of method.
5th aspect, the disclosure additionally provide a kind of image procossing training system, the training including using first aspect method
Instruct equipment and user terminal.
Compared with prior art, the beneficial effect of the disclosure is:
Because transferring the image procossing rudimentary knowledge topic of corresponding degree-of-difficulty factor according to the current educational background of user, it is sent to described
User terminal, the user for solving different academic backgrounds level is different to the degree of understanding of image procossing, caused by result of training
The problem of difference realizes and pushes corresponding image procossing rudimentary knowledge according to academic level, user can be allowed more quickly to slap
Hold image procossing rudimentary knowledge；
Because of the gap of comparison basis knowledge test result and first threshold, can know to avoid user on no grasp basis
Knowledge just directly Face datection is started to operate, caused by poor user experience, hit Students' enthusiasm the problem of；
It, can be with because of successively comparison basis knowledge test result, Face datection operant score and face recognition operation score
It allows student to learn and grasp the rudimentary knowledge and operational motion of image procossing by easy stages, promotes the Active Learning energy of student
Power.
Detailed description of the invention
The accompanying drawings constituting a part of this application is used to provide further understanding of the present application, and the application's shows
Meaning property embodiment and its explanation are not constituted an undue limitation on the present application for explaining the application.
Fig. 1 is the method flow diagram of one embodiment；
Fig. 2 is the system function module figure of second embodiment.
Specific embodiment
It is noted that described further below be all exemplary, it is intended to provide further instruction to the application.Unless another
It indicates, all technical and scientific terms used herein has usual with the application person of an ordinary skill in the technical field
The identical meanings of understanding.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root
According to the illustrative embodiments of the application.As used herein, unless the context clearly indicates otherwise, otherwise singular
Also it is intended to include plural form, additionally, it should be understood that, when in the present specification using term "comprising" and/or " packet
Include " when, indicate existing characteristics, step, operation, device, component and/or their combination.
Embodiment 1 present embodiments provides Face datection recognition capability Training Methodology；
As shown in Figure 1, Face datection recognition capability Training Methodology, comprising:
S101: the operational order that user terminal is sent is received, it is corresponding that the operational order is used to indicate the user terminal
Image procossing training parameter information；The parameter information, comprising: user account and user are currently academic；
It is to be understood that the educational background includes: training, undergraduate course, Master degree candidate, doctoral candidate, but it is not limited to these and shows
Example.
S102: the image procossing rudimentary knowledge topic of corresponding degree-of-difficulty factor is transferred according to the current educational background of user, is sent to institute
State user terminal；
S103: receiving the selection answer that user terminal is provided according to each topic, judge the selection answer, defeated
Rudimentary knowledge test result out；
If rudimentary knowledge test result is greater than the first threshold of setting, Face datection operation manual is sent to user
Terminal, the Face datection for receiving user terminal feedback operate enabled instruction, start Face datection performance tests, Face datection is grasped
User terminal is pushed to as interface；
S104: receiving click location of the user's mouse of user terminal capture in Face datection operation interface, directly complete
Face datection is completed after guiding at Face datection or to user's mouse click location, finally to user's mouse in Face datection
Click location in operation interface is compared with the first setting regions, generates Face datection operant score, Face datection is grasped
User terminal is pushed to as score.
Specifically, the Face datection operation manual, is calculated including the specific steps explanation of Face datection operation, Face datection
Method detailed annotation and the parsing of Face datection operation code.
Specifically, receive click location of user's mouse in Face datection operation interface that user terminal captures, to
Family mouse-click position, which guides, completes Face datection:
The Face datection operation interface, comprising: image to be detected selects component, picture library to select component, Face datection
Algorithms selection component；Face datection algorithm starts executive module；
If image to be detected selects component, triggering command is received, then is selected from image to be detected library according to user
Instruction selects corresponding image to be detected to export；
If picture library selects component, triggering command is received, then according to user's selection instruction, selection pair from picture library
The picture output answered；
If Face datection algorithms selection component, receives triggering command, then from algorithms library according to user's selection instruction,
Corresponding Face datection algorithm is selected to be filled into Face datection main program；
If Face datection algorithm starts executive module, receiving triggering command, then Face datection main program starts to execute,
Complete Face datection.
Specifically, the Face datection main program starts to execute, the specific steps of Face datection are completed are as follows:
Step (1a): judging whether selected image to be detected, if selected image to be detected, enters step
(1b), if image to be detected selects component flashing several times without image to be detected, until user selects image to be detected,
Enter step (1b)；
Step (1b): judging whether the image of selected picture library, if the image of selected picture library, enters step
(1c), if the image without picture library, picture library selects component flashing several times；Until user selects the image of picture library,
Enter step (1c)；
Step (1c): judge whether selected Face datection algorithm；If selected Face datection algorithm, just completes face
Detection, if nobody's face detection algorithm, just several times by the flashing of Face datection algorithms selection component, until user selects face
Detection algorithm just completes Face datection, terminates.
Specifically, face recognition operation handbook is sent out if Face datection operant score is greater than the second threshold of setting
User terminal is given, receives the face recognition operation enabled instruction of user terminal feedback, starting face recognition operation is examined, by people
Face identification operation interface is pushed to user terminal；
Specifically, the face recognition operation handbook, the specific steps explanation including face recognition operation, recognition of face are calculated
Method parsing and face recognition operation code analysis.
It is to be understood that click location, can be the position that cursor of mouse is clicked or double-clicked；It is also possible to finger to click or double
The position hit；Or the position that finger slided；But it is not limited to these examples.
It is to be understood that the first setting regions refers to the region where image selection component, the area where algorithms selection component
Region where domain, Face datection component, but it is not limited to these examples.
Click location of the user's mouse of user terminal capture on face recognition operation interface is received, is existed to user's mouse
Click location on face recognition operation interface is compared with the second setting regions, face recognition operation score is generated, by people
Face identification operant score is pushed to user terminal；If face recognition operation score is greater than the third threshold value of setting, knot is trained
Beam.
In a kind of embodiment, the click position of user's mouse that user terminal captures on face recognition operation interface is received
It sets, completes recognition of face after guiding to user's mouse click location:
The face recognition operation interface, comprising: images to be recognized selects component, picture library selection component, video library choosing
It selects component, face alignment algorithm selection component, face recognition algorithms selection component and face recognition algorithms and starts executive module；
If images to be recognized selects component, triggering command is received, then is selected from images to be recognized library according to user
Instruction selects corresponding images to be recognized to export；
If picture library selects component, triggering command is received, then according to user's selection instruction, selection pair from picture library
The picture output answered；
If video library selects component, triggering command is received, then according to user's selection instruction, selection pair from video library
The video output answered；
If face alignment algorithm selects component, receive triggering command, then from corresponding face alignment algorithm library, choosing
Corresponding face alignment algorithm is selected, and face alignment algorithm is embedded into recognition of face main program；
If face recognition algorithms select component, receive triggering command, then from corresponding face recognition algorithms library, choosing
Corresponding face recognition algorithms are selected, and face recognition algorithms are embedded into recognition of face main program；
If face recognition algorithms start executive module, receiving triggering command, then recognition of face main program starts to execute,
Complete recognition of face.
In a kind of embodiment, the recognition of face main program starts to execute, and completes the specific steps of recognition of face are as follows:
Step (2a): judging whether selected images to be recognized, if selected images to be recognized, enters step
(2b), if non-selected images to be recognized, images to be recognized selects component flashing several times, until user selects figure to be identified
Picture enters step (2b)；
Step (2b): if the video of the image or video library that judge whether selected picture library enters selected
Step (2c), if non-selected, picture library selects component or the flashing of video library selection component several times, until user selects figure
The image of valut or the video of video library, enter step (2c)；
Step (2c): judging whether selected face alignment algorithm, if selected face alignment algorithm, enters step
(2d), if non-selected, face alignment algorithm selects component flashing several times, until user selects face alignment algorithm, into
Enter step (2d)；
Step (2d): judging whether that face recognition algorithms have been selected, if selected face recognition algorithms, just complete people
Face identification；If non-selected face recognition algorithms, several times with regard to the flashing of face recognition algorithms selection component, until user selects people
Face recognizer just completes recognition of face, terminates.
It is to be understood that the second setting regions refers to region where image selection component, face alignment algorithm selection component
Region where the region at place, face characteristic extraction assembly, the region where Face datection component, where recognition of face component
Region, but be not limited to these examples.
Specifically, if rudimentary knowledge test result is less than or equal to the first threshold of setting, from rudimentary knowledge database
In transfer the rudimentary knowledge of degree-of-difficulty factor corresponding with rudimentary knowledge test result and be pushed to user terminal, then, according to user's end
The rudimentary knowledge test request initiated is held, carries out rudimentary knowledge test again, exports rudimentary knowledge test result, until basis is known
Know the first threshold that test result is greater than setting, just stops the study of rudimentary knowledge, open Face datection performance tests.
It is to be understood that the rudimentary knowledge of corresponding degree-of-difficulty factor, comprising: the algorithmic formula of algorithm title, corresponding algorithm title
Operation instruction while introduction, the advantage introduction of algorithm, polyalgorithm.
Specifically, if Face datection operant score is less than or equal to the second threshold of setting, from Face datection operand
User terminal is fed back to according to the Face datection operating instruction for transferring degree-of-difficulty factor corresponding with Face datection operant score in library；So
Afterwards, test request is operated according to the Face datection that user terminal is initiated, carries out Face datection operation test, output face inspection again
Operant score is surveyed, until Face datection operant score is greater than the second threshold of setting, just stops Face datection operation study, opens
Face recognition operation is examined.
It is to be understood that the Face datection operating instruction of corresponding degree-of-difficulty factor, comprising: the step of Face datection operates, such as:
(a1) single image to be detected is selected, selection target detection image selects a detection algorithm, starts to detect；
(a2) multiple image to be detected are selected, selection target detection image selects combinational algorithm, starts to detect；
(a3) video to be detected is selected, selection target detection image selects different faces detection algorithm to be compared, and starts
Detection, exports the testing result of each algorithm, and provide conclusion；
Specifically, if face recognition operation score is less than or equal to the third threshold value of setting, from face recognition operation number
Illustrate to feed back to user terminal according to the face recognition operation for transferring degree-of-difficulty factor corresponding with face recognition operation score in library；So
Afterwards, the face recognition operation test request initiated according to user terminal；Then, face recognition operation test, output are carried out again
Face recognition operation score just stops face recognition operation until face recognition operation score is greater than the third threshold value of setting
Study terminates training.
It is to be understood that the degree-of-difficulty factor, comprising: low difficulty, middle difficulty and highly difficult.
It is to be understood that the face recognition operation explanation of corresponding degree-of-difficulty factor, comprising: the step of face recognition operation, such as:
(b1) single image to be detected is selected, selection target detection image selects a feature extraction algorithm, starts to know
Not；
(b2) multiple image to be detected are selected, selection target detection image selects face alignment algorithm, selects feature extraction
It calculates
Method selects Feature Fusion Algorithm, starts to identify；
(b3) video to be detected is selected, selection target detection image selects different faces detection algorithm to be compared, and starts
Identification, exports the recognition result of each algorithm, and provide conclusion；
Specifically, the first setting regions in Face datection operation interface, including picture select component region, algorithm
It selects component region and starts Face datection component region；
Specifically, the second setting regions on face recognition operation interface, comprising: picture selects component region, view
Frequency selection component region, starts recognition of face detection components region at face alignment component region；
Embodiment 2, the present embodiment additionally provide Face datection recognition capability training device；
As shown in Fig. 2, Face datection recognition capability training device, comprising:
Input module, receives the operational order that user terminal is sent, and the operational order is used to indicate the user terminal
The parameter information of corresponding image procossing training；The parameter information, comprising: user account and user are currently academic；
Module is transferred, the image procossing rudimentary knowledge topic of corresponding degree-of-difficulty factor is transferred according to the current educational background of user, is sent
To the user terminal；
Judgment module receives the selection answer that user terminal is provided according to each topic, sentences to the selection answer
It is disconnected, export rudimentary knowledge test result；If rudimentary knowledge test result is greater than the first threshold of setting, Face datection is grasped
It is sent to user terminal as handbook, the Face datection for receiving user terminal feedback operates enabled instruction, starting Face datection operation
It examines, Face datection operation interface is pushed to user terminal；
Pushing module receives click location of the user's mouse of user terminal capture in Face datection operation interface, directly
It connects and completes Face datection or complete Face datection after guiding to user's mouse click location, finally to user's mouse in face
Click location in detection operation interface is compared with the first setting regions, generates Face datection operant score, face is examined
It surveys operant score and is pushed to user terminal.
Embodiment 3, the present embodiment additionally provide a kind of electronic equipment, including memory and processor and are stored in storage
The computer instruction run on device and on a processor when the computer instruction is run by processor, is completed first aspect and is appointed
Method in one possible implementation.
The disclosure additionally provides a kind of electronic equipment, including memory and processor and storage on a memory and are being located
The computer instruction that runs on reason device, when the computer instruction is run by processor, each operation in Method Of Accomplishment, in order to
Succinctly, details are not described herein.
It should be understood that in the disclosure, which can be central processing unit CPU, which, which can be said to be, can be it
His general processor, digital signal processor DSP, application-specific integrated circuit ASIC, ready-made programmable gate array FPGA or other
Programmable logic device, discrete gate or transistor logic, discrete hardware components etc..General processor can be micro process
Device or the processor are also possible to any conventional processor etc..
The memory may include read-only memory and random access memory, and to processor provide instruction and data,
The a part of of memory can also include non-volatile RAM.For example, memory can be with the letter of storage device type
Breath.
During realization, each step of the above method can by the integrated logic circuit of the hardware in processor or
The instruction of software form is completed.The step of method in conjunction with disclosed in the disclosure, can be embodied directly in hardware processor and execute
At, or in processor hardware and software module combination execute completion.Software module can be located at random access memory, dodge
It deposits, this fields are mature deposits for read-only memory, programmable read only memory or electrically erasable programmable memory, register etc.
In storage media.The storage medium is located at memory, and processor reads the information in memory, completes the above method in conjunction with its hardware
The step of.To avoid repeating, it is not detailed herein.Those of ordinary skill in the art may be aware that in conjunction with institute herein
Each exemplary unit, that is, algorithm steps of disclosed embodiment description, can be hard with electronic hardware or computer software and electronics
The combination of part is realized.These functions are implemented in hardware or software actually, the specific application depending on technical solution
And design constraint.Professional technician can realize described function using distinct methods to each specific application
Can, but this realization is it is not considered that exceed scope of the present application.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and unit, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In several embodiments provided herein, it should be understood that disclosed systems, devices and methods, it can be with
It realizes in other way.For example, the apparatus embodiments described above are merely exemplary, for example, the unit
It divides, only a kind of division of logic function, there may be another division manner in actual implementation, such as multiple units or group
Part can be combined or can be integrated into another system, or some features can be ignored or not executed.In addition, showing
The mutual coupling or direct-coupling or communication connection shown or discussed can be through some interfaces, device or unit
Indirect coupling or communication connection, can be electrically, mechanical or other forms.
Embodiment 4, the present embodiment additionally provide a kind of computer readable storage medium, for storing computer instruction, institute
When stating computer instruction and being executed by processor, the step of completing method in any possible implementation of first aspect.
It, can be with if the function is realized in the form of SFU software functional unit and when sold or used as an independent product
It is stored in a computer readable storage medium.Based on this understanding, the technical solution of the application is substantially right in other words
The part of part or the technical solution that the prior art contributes can be embodied in the form of software products, the calculating
Machine software product is stored in a storage medium, including some instructions are used so that a computer equipment (can be individual
Computer, server or network equipment etc.) execute each embodiment the method for the application all or part of the steps.And it is preceding
The storage medium stated includes: USB flash disk, mobile hard 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), magnetic or disk.
Embodiment 5, the present embodiment disclosure additionally provides a kind of image procossing training system, including uses first aspect side
The training apparatus and user terminal of method.
The foregoing is merely preferred embodiment of the present application, are not intended to limit this application, for the skill of this field
For art personnel, various changes and changes are possible in this application.Within the spirit and principles of this application, made any to repair
Change, equivalent replacement, improvement etc., should be included within the scope of protection of this application.
Claims (10)
1. Face datection recognition capability Training Methodology, characterized in that include:
The operational order that user terminal is sent is received, the operational order is used to indicate the corresponding image procossing of the user terminal
The parameter information of training；The parameter information, comprising: user account and user are currently academic；
It is whole to be sent to the user for the image procossing rudimentary knowledge topic that corresponding degree-of-difficulty factor is transferred according to the current educational background of user
End；
The selection answer that user terminal is provided according to each topic is received, the selection answer is judged, output basis is known
Know test result；
If rudimentary knowledge test result is greater than the first threshold of setting, Face datection operation manual is sent to user's end
End, the Face datection for receiving user terminal feedback operate enabled instruction, start Face datection performance tests, Face datection is operated
Interface is pushed to user terminal；
Click location of the user's mouse of user terminal capture in Face datection operation interface is received, Face datection is done directly
Or Face datection is completed after guiding to user's mouse click location, finally to user's mouse in Face datection operation interface
Click location be compared with the first setting regions, generate Face datection operant score, Face datection operant score is pushed
To user terminal.
2. the method as described in claim 1, characterized in that receive user's mouse that user terminal captures and operated in Face datection
Click location on interface guides user's mouse-click position and completes Face datection:
The Face datection operation interface, comprising: image to be detected selects component, picture library to select component, Face datection algorithm
Select component；Face datection algorithm starts executive module；
If image to be detected selects component, receive triggering command, then from image to be detected library according to user's selection instruction,
Corresponding image to be detected is selected to export；
If picture library selects component, triggering command is received, then is selected corresponding from picture library according to user's selection instruction
Picture output；
If Face datection algorithms selection component, receives triggering command, then according to user's selection instruction, selection from algorithms library
Corresponding Face datection algorithm is filled into Face datection main program；
If Face datection algorithm starts executive module, triggering command is received, then Face datection main program starts to execute, and completes
Face datection.
3. method according to claim 2, characterized in that the Face datection main program starts to execute, and completes Face datection
Specific steps are as follows:
Step (1a): judging whether selected image to be detected, if selected image to be detected, enters step (1b), such as
The non-selected image to be detected of fruit, then the flashing of image to be detected selection component several times, until user selects image to be detected, enters
Step (1b)；
Step (1b): judging whether the image of selected picture library, if the image of selected picture library, enters step
(1c), if the image without picture library, picture library selects component flashing several times；Until user selects the image of picture library,
Enter step (1c)；
Step (1c): judge whether selected Face datection algorithm；If selected Face datection algorithm just completes face inspection
It surveys, if nobody's face detection algorithm, just several times by the flashing of Face datection algorithms selection component, until user selects face inspection
Method of determining and calculating just completes Face datection, terminates.
4. the method as described in claim 1, characterized in that if Face datection operant score is greater than the second threshold of setting,
Face recognition operation handbook is then sent to user terminal, the face recognition operation enabled instruction of user terminal feedback is received, opens
Dynamic recognition of face performance tests, is pushed to user terminal for face recognition operation interface；
Click location of the user's mouse of user terminal capture on face recognition operation interface is received, recognition of face is done directly
Or recognition of face is completed after guiding to user's mouse click location, finally to user's mouse on face recognition operation interface
Click location be compared with the second setting regions, generate face recognition operation score, face recognition operation score is pushed
To user terminal；If face recognition operation score is greater than the third threshold value of setting, training terminates.
5. method as claimed in claim 4, characterized in that receive user's mouse of user terminal capture in face recognition operation
Click location on interface completes recognition of face after guiding to user's mouse click location:
The face recognition operation interface, comprising: images to be recognized selects component, picture library to select component, video library selection group
Part, face alignment algorithm selection component, face recognition algorithms selection component and face recognition algorithms start executive module；
If images to be recognized selects component, receive triggering command, then from images to be recognized library according to user's selection instruction,
Corresponding images to be recognized is selected to export；
If picture library selects component, triggering command is received, then is selected corresponding from picture library according to user's selection instruction
Picture output；
If video library selects component, triggering command is received, then is selected corresponding from video library according to user's selection instruction
Video output；
If face alignment algorithm selects component, receive triggering command, then from corresponding face alignment algorithm library, selection pair
The face alignment algorithm answered, and face alignment algorithm is embedded into recognition of face main program；
If face recognition algorithms select component, receive triggering command, then from corresponding face recognition algorithms library, selection pair
The face recognition algorithms answered, and face recognition algorithms are embedded into recognition of face main program；
If face recognition algorithms start executive module, triggering command is received, then recognition of face main program starts to execute, and completes
Recognition of face；
The recognition of face main program starts to execute, and completes the specific steps of recognition of face are as follows:
Step (2a): judging whether selected images to be recognized, if selected images to be recognized, enters step (2b), such as
The non-selected images to be recognized of fruit, then the flashing of images to be recognized selection component several times, until user selects images to be recognized, enters
Step (2b)；
Step (2b): if the video of the image or video library that judge whether selected picture library enters step selected
(2c), if non-selected, picture library selects component or the flashing of video library selection component several times, until user selects picture library
Image or video library video, enter step (2c)；
Step (2c): judging whether selected face alignment algorithm, if selected face alignment algorithm, enters step
(2d), if non-selected, face alignment algorithm selects component flashing several times, until user selects face alignment algorithm, into
Enter step (2d)；
Step (2d): judging whether that face recognition algorithms have been selected, if selected face recognition algorithms, just completes face and knows
Not；If non-selected face recognition algorithms, several times with regard to the flashing of face recognition algorithms selection component, until user selects face to know
Other algorithm just completes recognition of face, terminates.
6. the method as described in claim 1, characterized in that
If rudimentary knowledge test result is less than or equal to the first threshold of setting, transferred from rudimentary knowledge database and basis
The rudimentary knowledge that knowledge test result corresponds to degree-of-difficulty factor is pushed to user terminal, then, the basis initiated according to user terminal
Knowledge test request carries out rudimentary knowledge test again, exports rudimentary knowledge test result, until rudimentary knowledge test result is big
In the first threshold of setting, just stop the study of rudimentary knowledge, opens Face datection performance tests；
If Face datection operant score be less than or equal to setting second threshold, transferred from Face datection operating database with
The Face datection operating instruction that Face datection operant score corresponds to degree-of-difficulty factor feeds back to user terminal；Then, according to user's end
The Face datection that end is initiated operates test request, carries out Face datection operation test again, exports Face datection operant score, directly
It is greater than the second threshold of setting to Face datection operant score, just stops Face datection operation study, open face recognition operation
It examines；
If face recognition operation score be less than or equal to setting third threshold value, transferred from face recognition operation database with
The face recognition operation explanation that face recognition operation score corresponds to degree-of-difficulty factor feeds back to user terminal；Then, according to user's end
Hold the face recognition operation test request initiated；Then, face recognition operation test, output face recognition operation point are carried out again
Number just stops the study of face recognition operation until face recognition operation score is greater than the third threshold value of setting, terminates training.
7. Face datection recognition capability training device, comprising:
Input module receives the operational order that user terminal is sent, and it is corresponding that the operational order is used to indicate the user terminal
Image procossing training parameter information；The parameter information, comprising: user account and user are currently academic；
Module is transferred, the image procossing rudimentary knowledge topic of corresponding degree-of-difficulty factor is transferred according to the current educational background of user, is sent to institute
State user terminal；
Judgment module receives the selection answer that user terminal is provided according to each topic, judges the selection answer, defeated
Rudimentary knowledge test result out；If rudimentary knowledge test result is greater than the first threshold of setting, by Face datection manipulator
Volume is sent to user terminal, and the Face datection for receiving user terminal feedback operates enabled instruction, starts Face datection performance tests,
Face datection operation interface is pushed to user terminal；
Pushing module receives click location of the user's mouse of user terminal capture in Face datection operation interface, directly complete
Face datection is completed after guiding at Face datection or to user's mouse click location, finally to user's mouse in Face datection
Click location in operation interface is compared with the first setting regions, generates Face datection operant score, Face datection is grasped
User terminal is pushed to as score.
8. a kind of electronic equipment, the calculating run on a memory and on a processor including memory and processor and storage
Machine instruction when the computer instruction is run by processor, completes step described in any one of claim 1-6 method.
9. a kind of computer readable storage medium, for storing computer instruction, when the computer instruction is executed by processor,
Complete step described in any one of claim 1-6 method.
10. a kind of image procossing training system, including use step described in any one of claim 1-6 method training apparatus and
User terminal.
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