CN107966914A - Method, device and system for displaying image - Google Patents
Method, device and system for displaying image Download PDFInfo
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- CN107966914A CN107966914A CN201711069324.0A CN201711069324A CN107966914A CN 107966914 A CN107966914 A CN 107966914A CN 201711069324 A CN201711069324 A CN 201711069324A CN 107966914 A CN107966914 A CN 107966914A
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- 238000010586 diagram Methods 0.000 description 12
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- 238000004891 communication Methods 0.000 description 5
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
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Abstract
The invention discloses a method, a device and a system for displaying images. Wherein, the method comprises the following steps: the method comprises the steps of obtaining a display image of a to-be-displayed area on a control panel of the equipment, analyzing the display image by using a preset model, determining whether the display state of the control panel in the display image is normal, sending the display state of the display image and the display state of the control panel to a user terminal, wherein the display image is collected by an image collecting device installed on the equipment, the preset model is obtained by using multiple groups of data through machine learning training, and each group of data in the multiple groups of data comprises: and displaying the display image and the display state on the user terminal. The invention solves the technical problem that the display state of the control panel of the equipment cannot be monitored in the prior art.
Description
Technical field
The present invention relates to artificial intelligence field, in particular to a kind of methods, devices and systems for showing image.
Background technology
With the fast development of science and technology, image recognition technology has been widely applied to home wiring control field, for example, passing through
Image recognition technology obtains the positional information of user in room, face information, the quantity of human body, predeterminable area in predeterminable area
Scene information and user action message etc., after above-mentioned view data is got, the controller of relevant device is to upper
State view data to be collected, parse and transmit, so that controller controls accordingly according to above-mentioned collected view data
Equipment completes operation.
In the prior art, it is mainly the side by wireless communication (for example, WIFI) household electrical appliance to be carried out with remote control
The user terminal that formula is held household electrical appliance and user carries out wireless connection, so that the remote controlled household electrical appliance of user, and
Receive the control result that household electrical appliance are fed back.However, the received feedback result of user terminal is primarily directed to control at present
The action data of panel is collected and identification, for example, user terminal receives the temperature information that air conditioner is fed back, but can not be to control
The dispaly state of panel processed is monitored, and to determine whether the dispaly state of control panel is abnormal, or just whether other users
Often operation equipment.
For above-mentioned the problem of can not being monitored in the prior art to the dispaly state of the control panel of equipment, at present still
Effective solution is not proposed.
The content of the invention
An embodiment of the present invention provides a kind of methods, devices and systems for showing image, at least to solve in the prior art
The technical problem that the dispaly state of the control panel of equipment can not be monitored.
One side according to embodiments of the present invention, there is provided a kind of method for showing image, including：Obtain the control of equipment
The display image in the region to be shown on panel processed, wherein, image is shown by the image acquisition device in equipment；
Display image is analyzed using preset model, determines to show whether the dispaly state of the control panel in image is normal, its
In, preset model trains to obtain using multi-group data by machine learning, and every group of data in multi-group data include：It is aobvious
The label of the dispaly state of diagram picture and mark control panel；Send and show that the dispaly state of image and control panel is extremely used
Family terminal, wherein, display image and dispaly state are shown on the subscriber terminal.
Another aspect according to embodiments of the present invention, additionally provides a kind of device for showing image, including：Acquisition module,
The display image in the region to be shown on control panel for obtaining equipment, wherein, by the Image Acquisition in equipment
Device collection shows image；Determining module, for being analyzed using preset model display image, is determined in display image
Whether the dispaly state of control panel is normal, wherein, preset model trains to obtain using multi-group data by machine learning,
Every group of data in multi-group data include：Show image and identify the label of the dispaly state of control panel；Sending module,
The dispaly state of image and control panel is shown for sending to user terminal, wherein, display figure is shown on the subscriber terminal
Picture and dispaly state.
Another aspect according to embodiments of the present invention, additionally provides a kind of system for showing image, including：Controller, is used
Display image in the region to be shown on the control panel for obtaining equipment, and display image is divided using preset model
Analysis, determines to show whether the dispaly state of the control panel in image is normal, wherein, by the image collector in equipment
Put collection and show image, preset model trains to obtain using multi-group data by machine learning, every group in multi-group data
Data include：Show image and identify the label of the dispaly state of control panel；User terminal, it is aobvious for receiving and showing
The dispaly state of diagram picture and control panel.
Another aspect according to embodiments of the present invention, additionally provides a kind of storage medium, which includes storage
Program, wherein, program performs the method for showing image.
Another aspect according to embodiments of the present invention, additionally provides a kind of processor, which is used for operation program, its
In, the method for showing image is performed when program is run.
In embodiments of the present invention, it is to be shown on the control panel by obtaining equipment by the way of machine learning
The display image in region, analyzes display image using preset model, determines the display of the control panel in display image
Whether state is normal, sends the dispaly state for showing image and control panel to user terminal, wherein, by equipment
Image acquisition device show image, preset model trains to obtain using multi-group data by machine learning, multigroup
Every group of data in data include：Show image and identify the label of the dispaly state of control panel, on the subscriber terminal
Display shows image and dispaly state, has achieveed the purpose that to monitor the dispaly state of the control panel of equipment in real time,
It is achieved thereby that according to the dispaly state of the control panel of equipment determine equipment whether the technique effect of normal operation, and then solve
The technical problem that the dispaly state of the control panel of equipment can not be monitored in the prior art.
Brief description of the drawings
Attached drawing described herein is used for providing a further understanding of the present invention, forms the part of the application, this hair
Bright schematic description and description is used to explain the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings：
Fig. 1 is a kind of method flow diagram of display image according to embodiments of the present invention；
Fig. 2 is a kind of structure diagram of optional equipment according to embodiments of the present invention；
Fig. 3 is a kind of method flow diagram of optional display image according to embodiments of the present invention；
Fig. 4 is a kind of apparatus structure schematic diagram of display image according to embodiments of the present invention；And
Fig. 5 is a kind of system structure diagram of display image according to embodiments of the present invention.
Embodiment
In order to make those skilled in the art more fully understand the present invention program, below in conjunction with the embodiment of the present invention
Attached drawing, is clearly and completely described the technical solution in the embodiment of the present invention, it is clear that described embodiment is only
The embodiment of a part of the invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
Member's all other embodiments obtained without making creative work, should all belong to the model that the present invention protects
Enclose.
It should be noted that term " first " in description and claims of this specification and above-mentioned attached drawing, "
Two " etc. be for distinguishing similar object, without for describing specific order or precedence.It should be appreciated that so use
Data can exchange in the appropriate case, so as to the embodiment of the present invention described herein can with except illustrating herein or
Order beyond those of description is implemented.In addition, term " comprising " and " having " and their any deformation, it is intended that cover
Cover it is non-exclusive include, be not necessarily limited to for example, containing the process of series of steps or unit, method, system, product or equipment
Those steps or unit clearly listed, but may include not list clearly or for these processes, method, product
Or the intrinsic other steps of equipment or unit.
Embodiment 1
According to embodiments of the present invention, there is provided a kind of embodiment of the method for showing image is, it is necessary to illustrate, in attached drawing
The step of flow illustrates can perform in the computer system of such as a group of computer-executable instructions, although also,
Logical order is shown in flow chart, but in some cases, can be to perform shown different from order herein or retouch
The step of stating.
Fig. 1 is the method flow diagram of display image according to embodiments of the present invention, as shown in Figure 1, this method is including as follows
Step：
Step S102, obtains the display image in the region to be shown on the control panel of equipment, wherein, by installed in equipment
On image acquisition device show image.
It should be noted that above-mentioned image collecting device can be but be not limited to video camera, camera etc., above-mentioned display figure
As can be but be not limited to static state picture, dynamic video.Wherein, the installation site of image collecting device and control panel can
Think but be not limited to the position relationship of the image collecting device shown in Fig. 2 and control panel.In addition, the said equipment can be any
Equipment that is including control panel and carrying out wireless communication, for example, intelligent air condition, intelligent refrigerator etc..
In a kind of optional embodiment, a kind of structure diagram of optional equipment as shown in Figure 2.In fig. 2, scheme
The display image on control panel can be collected in real time as harvester, and the display image collected is sent to controller,
By controller to image acquisition device to display image handled and identified.Wherein, when the surface area of control panel
When smaller, as shown in Fig. 2, image collecting device can get the display image of whole control panel；And work as control panel
Surface area ratio it is larger when, according to the position relationship of image collecting device and control panel as shown in Figure 2, image collecting device
The display image less than whole control panel may be obtained.At this time, the controller of equipment adjusts the posture of image collecting device,
For example, the rotation angle of adjustment camera, so that image collecting device can be collected on the control panel that user's needs monitor
Region to be shown.
In addition it is also necessary to explanation, the control panel that can get user by step S102 needs to monitor is treated
Monitoring area (i.e. above-mentioned region to be shown), so as to achieve the purpose that selectively to be monitored control panel.
Step S104, analyzes display image using preset model, determines showing for the control panel in display image
Show whether state is normal, wherein, preset model trains to obtain using multi-group data by machine learning, in multi-group data
Every group of data include：Show image and identify the label of the dispaly state of control panel.
It should be noted that the dispaly state of above-mentioned control panel can the display lamp on panel in order to control display shape
State, or the damage condition of the control button on control panel, can also be the operation order of user's operation control button.
In a kind of optional embodiment, controller get the region to be shown of control panel display image it
Afterwards, display image is analyzed using by machine learning trained preset model, for example, determining aobvious on control panel
Show the operation order of the state of lamp, the damage condition of control button and user's operation control button, and then according to above-mentioned display
Content shown by image determines whether the dispaly state of control panel is abnormality.Wherein, in order to obtaining chain of command
The corresponding dispaly state of plate, controller can establish neural network model, obtain the display of multigroup different control panel in advance
Image, and be the label of every group of corresponding dispaly state of display image setting by way of manually marking, so as to obtain above-mentioned
Data, are then trained neural network model using the data after equipment, obtain above-mentioned preset model.
Step S106, sends the dispaly state for showing image and control panel to user terminal, wherein, in user terminal
Upper display shows image and dispaly state.
In a kind of optional embodiment, after the dispaly state of control panel is determined, by the area to be shown of control panel
The display image in domain and the dispaly state of control panel are sent to long-range use by wireless communication module (for example, WIFI module)
In the terminal of family, user can determine that by user terminal equipment whether normal operation, and in equipment end equipment is operated
Staff operation it is whether correct.When there is mistake in the operating procedure of discovering device operation exception or staff,
User can by user terminal to maintenance personal initiate failed request, with maintenance of equipment, or by user terminal to work people
Member gives a warning, and with the operation of work for correction personnel, avoids the generation of accident.In addition, above-mentioned user terminal can be but unlimited
There is the equipment of display screen in smart mobile phone, tablet, computer etc..
It can be known based on above-mentioned steps S102 to the step S106 schemes limited, by the control panel for obtaining equipment
On region to be shown display image, using preset model to display image analyze, determine display image in control
Whether the dispaly state of panel is normal, sends the dispaly state for showing image and control panel to user terminal, wherein, by pacifying
Image acquisition device in equipment shows image, and preset model is trained by machine learning using multi-group data
Arrive, every group of data in multi-group data include：Show image and identify control panel dispaly state label, with
Display image and dispaly state are shown in the terminal of family.
Be easily noted that, due to acquisition be region to be shown on control panel dispaly state, can be with
Reach and the dispaly state in region to be shown on control panel is monitored in real time.Wherein, the dispaly state of control panel can be with
Reflect the operating status of equipment, therefore, whether equipment can be further determined that according to the display image of the control panel got
Normal operation, so as to achieve the purpose that to be monitored the operating status of equipment.In addition, the application acquisition is control panel
Image information (image information herein can be but be not limited to static state picture and dynamic video), user passes through user
Terminal can intuitively get the dispaly state of control panel, further reach the technique effect for improving user experience effect.
As shown in the above, the present embodiment, which can reach, monitors the dispaly state of the control panel of equipment in real time
Purpose, it is achieved thereby that according to the dispaly state of the control panel of equipment determine equipment whether the technique effect of normal operation,
And then solves the technical problem that can not be monitored in the prior art to the dispaly state of the control panel of equipment.
It should be noted that when the surface area ratio of control panel is larger, image collecting device cannot collect whole control
The image of panel processed.Before needing the region to be shown that shows on the subscriber terminal on acquisition control panel, it is thus necessary to determine that control
The region to be shown of panel processed.Specific method is as follows：
Step S202, determines the region to be shown of control panel；
Step S204, the display image of control panel is obtained according to region to be shown.
In a kind of optional embodiment, user can pass through user's terminal remote control camera (i.e. image collector
Put), the attitude information of camera is adjusted, for example, adjusting the camera angle that rotating angle, camera are rotated down to the left
Deng, after the attitude information of camera is adjusted, the image of the display area for the control panel that image acquisition device arrives
The image in region as to be shown.Wherein, user will gather the acquisition instructions of image after the attitude information of camera is set
It is sent to equipment, the controller in equipment determines the region to be shown of control panel according to the control instruction received, such as Fig. 3 institutes
A kind of method flow diagram of the optional display image shown, shows that the method for image specifically comprises the following steps：
Step S302, receives the acquisition instructions that user terminal is sent；
Step S304, the attitude information of image collecting device is determined according to acquisition instructions；
Step S306, the pickup area for the image that image collecting device can collect is adjusted according to attitude information, wherein,
The region to be shown of pickup area characterization control panel.
Specifically, equipment can receive the acquisition instructions for the collection image that user terminal is sent, equipment by WIFI module
Controller acquisition instructions are parsed, obtain the attitude information of image collecting device, controller obtains image in parsing and adopts
After the attitude information of acquisition means, image collecting device is adjusted according to the attitude information of image collecting device, so that figure
The display image in the region to be shown on control panel can be collected as harvester.
It should be noted that controller is after the display image that image acquisition device arrives is got, it is also necessary to right
Display image is corrected processing, for example, to image progress gray correction and geometric correction, allows the user to see and meets people
The image of class vision requirement.
In a kind of optional embodiment, send the dispaly state that shows image and control panel to user terminal it
Afterwards, if the controller determine that dispaly state is abnormality, then controller can also further determine that the failure classes of control panel
Type, specific method are as follows：
Step S108a, in the case of definite dispaly state exception, determines that the corresponding display image of abnormality is failure
Image；
Step S110a, analyzes fault picture using fault model, determines the fault type of control panel, wherein,
Fault model trains to obtain using multigroup fault data by machine learning, every group of fault data in multigroup fault data
Including：The label of the fault type of control panel in fault picture and fault picture；
Step S112a, sends fault type to user terminal.
Specifically, in order to obtain the fault type of control panel, can be obtained in advance by establishing neural network model
Take the damage condition either user's operation control of multigroup dispaly state for including the indicator light on control panel, control button
The fault datas such as the operation order of button, and corresponding failure classes are set for every group of fault data by way of manually marking
Type, for example, during equipment is run, power supply indicator is in OFF state, then manually marks the failure classes of control panel
Type is power failure.After being labeled to fault type, it is trained by neural network model so as to obtain
State fault model.In the case of definite dispaly state exception, controller gets corresponding display image under the dispaly state,
As the input of fault model, and it is output, i.e. fault type to obtain fault model, and at this time, controller passes through WIFI moulds
Fault type is sent to user terminal by block, and user terminal, can be according to failure after the information comprising fault type is received
Type performs solution.
In an alternative embodiment, in the dispaly state of transmission display image and control panel to user terminal
Afterwards, the fault type of equipment or control panel is determined by user terminal, specific method includes the following steps：
Step S108b, in the case of definite dispaly state exception, user terminal determines the corresponding display figure of abnormality
As being fault picture；
Step S110b, analyzes fault picture using fault model, user terminal determines the failure classes of control panel
Type, wherein, fault model trains to obtain using multigroup fault data by machine learning, every group in multigroup fault data
Fault data includes：The label of the fault type of control panel in fault picture and fault picture.
It should be noted that analyze to obtain the side of the fault type of control panel by fault model in subscriber terminal side
Method, the method with determining fault type in equipment side is identical, and details are not described herein.
Embodiment 2
According to embodiments of the present invention, a kind of device embodiment for showing image is additionally provided.Wherein, Fig. 4 is according to this hair
The apparatus structure schematic diagram of the display image of bright embodiment, as shown in figure 4, the device includes：Acquisition module 401, determining module
403 and sending module 405.
Wherein, acquisition module 401, the display image in the region to be shown on control panel for obtaining equipment, wherein,
Image is shown by the image acquisition device in equipment；Determining module 403, for being schemed using preset model to display
As being analyzed, determine to show whether the dispaly state of the control panel in image is normal, wherein, preset model is using multigroup
Data are trained by machine learning, and every group of data in multi-group data include：Show image and mark chain of command
The label of the dispaly state of plate；Sending module 405, shows that the dispaly state of image and control panel is whole to user for sending
End, wherein, display image and dispaly state are shown on the subscriber terminal.
It should be noted that above-mentioned acquisition module 401, determining module 403 and sending module 405 correspond to embodiment 1
In step S102 to step S106, the example and application scenarios that three modules are realized with corresponding step be identical but unlimited
In 1 disclosure of that of above-described embodiment.
In a kind of optional embodiment, show that the device of image further includes：First determining module and the first acquisition mould
Block.Wherein, the first determining module, for determining the region to be shown of control panel；First acquisition module, for according to be shown
Region obtains the display image of control panel.
It should be noted that above-mentioned first determining module and the first acquisition module correspond to the step in embodiment 1
S202 to step S204, two modules are identical with example and application scenarios that corresponding step is realized, but are not limited to above-mentioned reality
Apply 1 disclosure of that of example.
In a kind of optional embodiment, the first determining module includes：Receiving module, the second determining module and adjustment mould
Block.Wherein, receiving module, for receiving the acquisition instructions of user terminal transmission；Second determining module, for according to acquisition instructions
Determine the attitude information of image collecting device；Module is adjusted, can be gathered for adjusting image collecting device according to attitude information
The pickup area of the image arrived, wherein, the region to be shown of pickup area characterization control panel.
It should be noted that above-mentioned receiving module, the second determining module and adjustment module correspond to the step in embodiment 1
Rapid S302 to step S306, three modules are identical with example and application scenarios that corresponding step is realized, but are not limited to above-mentioned
1 disclosure of that of embodiment.
In a kind of optional embodiment, show that the device of image further includes：3rd determining module, the 4th determining module with
And first sending module.Wherein, the 3rd determining module, in the case of definite dispaly state exception, determining abnormality
Corresponding display image is fault picture；4th determining module, for being analyzed using fault model fault picture, is determined
The fault type of control panel, wherein, fault model trains to obtain using multigroup fault data by machine learning, multigroup
Every group of fault data in fault data includes：The mark of the fault type of control panel in fault picture and fault picture
Label；First sending module, for sending fault type to user terminal.
Implement it should be noted that above-mentioned 3rd determining module, the 4th determining module and the first sending module correspond to
Step S108a to step S112a in example 1, three modules are identical with example and application scenarios that corresponding step is realized, but
It is not limited to 1 disclosure of that of above-described embodiment.
In a kind of optional embodiment, show that the device of image further includes：5th determining module and the 6th definite mould
Block.Wherein, the 5th determining module, in the case of definite dispaly state exception, user terminal to determine that abnormality corresponds to
Display image be fault picture；6th determining module, for being analyzed using fault model fault picture, user terminal
Determine the fault type of control panel, wherein, fault model trains to obtain using multigroup fault data by machine learning,
Every group of fault data in multigroup fault data includes：The fault type of control panel in fault picture and fault picture
Label.
It should be noted that above-mentioned 5th determining module and the 6th determining module correspond to the step in embodiment 1
S108b to step S110b, two modules are identical with example and application scenarios that corresponding step is realized, but are not limited to above-mentioned
1 disclosure of that of embodiment.
Embodiment 3
According to embodiments of the present invention, a kind of system embodiment for showing image is additionally provided.Wherein, Fig. 5 is according to this hair
The system structure diagram of the display image of bright embodiment, as shown in figure 5, the system includes：Controller 501 and user terminal
503。
Wherein, controller 501, the display image in the region to be shown on control panel for obtaining equipment, and use
Preset model analyzes display image, determines to show whether the dispaly state of the control panel in image is normal, wherein, by
Image acquisition device in equipment shows image, and preset model is to be trained using multi-group data by machine learning
Obtain, every group of data in multi-group data include：Show image and identify the label of the dispaly state of control panel；With
Family terminal 503, for receiving and showing the dispaly state of display image and control panel.
It should be noted that equipment includes controller, image collecting device and control panel, wherein, controller can be right
The image that image collecting device is collected is handled, including but not limited to the image that collects is carried out image rectification and
Image recognition.
It follows that obtaining the display image in the region to be shown on the control panel of equipment by controller, and use
Advance model analyzes display image, determines to show whether the dispaly state of the control panel in image is normal, user is whole
End receives and shows the dispaly state of display image and control panel, wherein, by the image collecting device in equipment
Collection shows image, and preset model trains to obtain using multi-group data by machine learning, every group of number in multi-group data
According to including：Show image and identify the label of the dispaly state of control panel.
Be easily noted that, due to acquisition be region to be shown on control panel dispaly state, can be with
Reach and the dispaly state in region to be shown on control panel is monitored in real time.Wherein, the dispaly state of control panel can be with
Reflect the operating status of equipment, therefore, whether equipment can be further determined that according to the display image of the control panel got
Normal operation, so as to achieve the purpose that to be monitored the operating status of equipment.In addition, the application acquisition is control panel
Image information (image information herein can be but be not limited to static state picture and dynamic video), user passes through user
Terminal can intuitively get the dispaly state of control panel, further reach the technique effect for improving user experience effect.
As shown in the above, the present embodiment, which can reach, monitors the dispaly state of the control panel of equipment in real time
Purpose, it is achieved thereby that according to the dispaly state of the control panel of equipment determine equipment whether the technique effect of normal operation,
And then solves the technical problem that can not be monitored in the prior art to the dispaly state of the control panel of equipment.
In a kind of optional embodiment, controller is additionally operable to determine the region to be shown of control panel；According to be shown
Region obtains the display image of control panel.
In a kind of optional embodiment, controller is additionally operable to receive the acquisition instructions that user terminal is sent；According to collection
Instruction determines the attitude information of image collecting device；The image that can be collected according to attitude information adjustment image collecting device
Pickup area, wherein, the region to be shown of pickup area characterization control panel.
In a kind of optional embodiment, controller is additionally operable in the case of definite dispaly state exception, is determined abnormal
The corresponding display image of state is fault picture；Fault picture is analyzed using fault model, determines the event of control panel
Hinder type, wherein, fault model trains to obtain using multigroup fault data by machine learning, in multigroup fault data
Every group of fault data includes：The label of the fault type of control panel in fault picture and fault picture；Send failure classes
Type is to user terminal.
In a kind of optional embodiment, user terminal is additionally operable in the case of definite dispaly state exception, and user is whole
End determines that the corresponding display image of abnormality is fault picture；Fault picture is analyzed using fault model, user is whole
End determines the fault type of control panel, wherein, fault model is to train to obtain by machine learning using multigroup fault data
, every group of fault data in multigroup fault data includes：The failure classes of control panel in fault picture and fault picture
The label of type.
Embodiment 4
Another aspect according to embodiments of the present invention, additionally provides a kind of storage medium, which includes storage
Program, wherein, the method that program performs the display image in embodiment 1.
Embodiment 5
Another aspect according to embodiments of the present invention, additionally provides a kind of processor, which is used for operation program, its
In, the method for showing image in embodiment 1 is performed when program is run.
The embodiments of the present invention are for illustration only, do not represent the quality of embodiment.
In the above embodiment of the present invention, the description to each embodiment all emphasizes particularly on different fields, and does not have in some embodiment
The part of detailed description, may refer to the associated description of other embodiment.
In several embodiments provided herein, it should be understood that disclosed technology contents, can pass through others
Mode is realized.Wherein, device embodiment described above is only schematical, such as the division of the unit, Ke Yiwei
A kind of division of logic function, can there is an other dividing mode when actually realizing, for example, multiple units or component can combine or
Person is desirably integrated into another system, or some features can be ignored, or does not perform.Another, shown or discussed is mutual
Between coupling, direct-coupling or communication connection can be INDIRECT COUPLING or communication link by some interfaces, unit or module
Connect, can be electrical or other forms.
The unit illustrated as separating component may or may not be physically separate, be shown as unit
The component shown may or may not be physical location, you can with positioned at a place, or can also be distributed to multiple
On unit.Some or all of unit therein can be selected to realize the purpose of this embodiment scheme according to the actual needs.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, can also
That unit is individually physically present, can also two or more units integrate in a unit.Above-mentioned integrated list
Member can both be realized in the form of hardware, can also be realized in the form of SFU software functional unit.
If the integrated unit is realized in the form of SFU software functional unit and is used as independent production marketing or use
When, it can be stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantially
The part to contribute in other words to the prior art or all or part of the technical solution can be in the form of software products
Embody, which is stored in a storage medium, including some instructions are used so that a computer
Equipment (can be personal computer, server or network equipment etc.) perform each embodiment the method for the present invention whole or
Part steps.And foregoing storage medium includes：USB flash disk, read-only storage (ROM, Read-OnlyMemory), arbitrary access are deposited
Reservoir (RAM, Random Access Memory), mobile hard disk, magnetic disc or CD etc. are various can be with store program codes
Medium.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications also should
It is considered as protection scope of the present invention.
Claims (10)
- A kind of 1. method for showing image, it is characterised in that including：The display image in the region to be shown on the control panel of equipment is obtained, wherein, by installing image on said device Harvester gathers the display image；The display image is analyzed using preset model, determines the dispaly state of the control panel in the display image It is whether normal, wherein, the preset model trains to obtain using multi-group data by machine learning, in the multi-group data Every group of data include：The label of the dispaly state of the display image and the mark control panel；The dispaly state of the display image and the control panel is sent to user terminal, wherein, in the user terminal The upper display display image and the dispaly state.
- 2. according to the method described in claim 1, it is characterized in that, region to be shown on the control panel for obtaining equipment Before showing image, the method further includes：Determine the region to be shown of the control panel；The display image of the control panel is obtained according to the region to be shown.
- 3. according to the method described in claim 2, it is characterized in that, determining the region to be shown of the control panel includes：Receive the acquisition instructions that the user terminal is sent；The attitude information of described image harvester is determined according to the acquisition instructions；The pickup area for the image that described image harvester can collect is adjusted according to the attitude information, wherein, it is described Pickup area characterizes the region to be shown of the control panel.
- 4. according to the method described in claim 1, it is characterized in that, sending the display image and the control panel After dispaly state to user terminal, the method further includes：In the case where determining the dispaly state exception, determine that the corresponding display image of abnormality is fault picture；The fault picture is analyzed using fault model, determines the fault type of the control panel, wherein, the event Barrier model trains to obtain using multigroup fault data by machine learning, every group of number of faults in multigroup fault data According to including：The label of the fault type of the fault picture and the control panel in the fault picture；The fault type is sent to the user terminal.
- 5. according to the method described in claim 1, it is characterized in that, sending the display image and the control panel After dispaly state to user terminal, the method further includes：In the case where determining the dispaly state exception, the user terminal determines that the corresponding display image of abnormality is event Hinder image；The fault picture is analyzed using fault model, the user terminal determines the failure classes of the control panel Type, wherein, the fault model trains to obtain using multigroup fault data by machine learning, multigroup fault data In every group of fault data include：The mark of the fault type of the fault picture and the control panel in the fault picture Label.
- A kind of 6. device for showing image, it is characterised in that including：Acquisition module, the display image in the region to be shown on control panel for obtaining equipment, wherein, by installed in described Image is shown described in image acquisition device in equipment；Determining module, for being analyzed using preset model the display image, determines the control in the display image Whether the dispaly state of panel is normal, wherein, the preset model trains to obtain using multi-group data by machine learning, Every group of data in the multi-group data include：The mark of the dispaly state of the display image and the mark control panel Label；Sending module, for send it is described display image and the control panel dispaly state to user terminal, wherein, The display image and the dispaly state are shown on the user terminal.
- 7. device according to claim 6, it is characterised in that described device further includes：First determining module, for determining the region to be shown of the control panel；First acquisition module, for obtaining the display image of the control panel according to the region to be shown.
- A kind of 8. system for showing image, it is characterised in that including：Controller, the display image in the region to be shown on control panel for obtaining equipment, and using preset model to institute State display image to be analyzed, determine whether the dispaly state for showing the control panel in image is normal, wherein, by installing Image is shown described in image acquisition device on said device, the preset model is to pass through machine using multi-group data What learning training obtained, every group of data in the multi-group data include：The display image and the mark chain of command The label of the dispaly state of plate；User terminal, for receiving and showing the dispaly state of the display image and the control panel.
- A kind of 9. storage medium, it is characterised in that the storage medium includes the program of storage, wherein, described program right of execution The method that profit requires the display image described in any one in 1 to 5.
- A kind of 10. processor, it is characterised in that the processor is used for operation program, wherein, right of execution when described program is run The method that profit requires the display image described in any one in 1 to 5.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108818531A (en) * | 2018-06-25 | 2018-11-16 | 珠海格力智能装备有限公司 | Robot control method and device |
| CN109376646A (en) * | 2018-10-19 | 2019-02-22 | 佛山市联科发信息科技有限公司 | A kind of electric appliance intelligent controller of image recognition |
| CN110647894A (en) * | 2018-06-07 | 2020-01-03 | 佛山市顺德区美的电热电器制造有限公司 | Fault diagnosis method and system of electrical equipment, cloud server and storage medium |
| CN110909891A (en) * | 2018-09-17 | 2020-03-24 | 珠海格力电器股份有限公司 | Method and device for maintaining electric appliance fault |
| CN111340808A (en) * | 2020-05-20 | 2020-06-26 | 北京小米移动软件有限公司 | Screen display monitoring method and device, electronic equipment and storage medium |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102289308A (en) * | 2011-09-06 | 2011-12-21 | 宇龙计算机通信科技(深圳)有限公司 | Method and system for adjusting orientation of object by using mobile terminal, and mobile terminal |
| CN102616617A (en) * | 2012-03-23 | 2012-08-01 | 佛山市智邦电子科技有限公司 | Elevator monitoring method |
| CN102901180A (en) * | 2012-09-29 | 2013-01-30 | 四川长虹电器股份有限公司 | Method and system for controlling air conditioner |
| CN103634576A (en) * | 2013-12-17 | 2014-03-12 | 紫光捷通科技股份有限公司 | Expressway mobile terminal monitoring system and method |
| CN104167088A (en) * | 2014-08-26 | 2014-11-26 | 上海青芒科技有限公司 | Remote control method and system of domestic appliances |
| CN104683699A (en) * | 2015-03-20 | 2015-06-03 | 崔时泓 | Wireless internet protocol camera control method based on mobile terminal |
| CN105141889A (en) * | 2015-07-28 | 2015-12-09 | 国家电网公司 | Power transmission line intelligent patrol system based on image vision |
| CN106817560A (en) * | 2015-11-30 | 2017-06-09 | 北京京投亿雅捷交通科技有限公司 | It is a kind of to distributed terminal display device real-time monitoring system and monitoring method |
| CN106874926A (en) * | 2016-08-04 | 2017-06-20 | 阿里巴巴集团控股有限公司 | Service exception detection method and device based on characteristics of image |
| JP6364294B2 (en) * | 2014-09-17 | 2018-07-25 | 株式会社ジェイマックシステム | Diagnosis support apparatus, diagnosis support method, and diagnosis support program |
-
2017
- 2017-11-02 CN CN201711069324.0A patent/CN107966914A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102289308A (en) * | 2011-09-06 | 2011-12-21 | 宇龙计算机通信科技(深圳)有限公司 | Method and system for adjusting orientation of object by using mobile terminal, and mobile terminal |
| CN102616617A (en) * | 2012-03-23 | 2012-08-01 | 佛山市智邦电子科技有限公司 | Elevator monitoring method |
| CN102901180A (en) * | 2012-09-29 | 2013-01-30 | 四川长虹电器股份有限公司 | Method and system for controlling air conditioner |
| CN103634576A (en) * | 2013-12-17 | 2014-03-12 | 紫光捷通科技股份有限公司 | Expressway mobile terminal monitoring system and method |
| CN104167088A (en) * | 2014-08-26 | 2014-11-26 | 上海青芒科技有限公司 | Remote control method and system of domestic appliances |
| JP6364294B2 (en) * | 2014-09-17 | 2018-07-25 | 株式会社ジェイマックシステム | Diagnosis support apparatus, diagnosis support method, and diagnosis support program |
| CN104683699A (en) * | 2015-03-20 | 2015-06-03 | 崔时泓 | Wireless internet protocol camera control method based on mobile terminal |
| CN105141889A (en) * | 2015-07-28 | 2015-12-09 | 国家电网公司 | Power transmission line intelligent patrol system based on image vision |
| CN106817560A (en) * | 2015-11-30 | 2017-06-09 | 北京京投亿雅捷交通科技有限公司 | It is a kind of to distributed terminal display device real-time monitoring system and monitoring method |
| CN106874926A (en) * | 2016-08-04 | 2017-06-20 | 阿里巴巴集团控股有限公司 | Service exception detection method and device based on characteristics of image |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110647894A (en) * | 2018-06-07 | 2020-01-03 | 佛山市顺德区美的电热电器制造有限公司 | Fault diagnosis method and system of electrical equipment, cloud server and storage medium |
| CN110647894B (en) * | 2018-06-07 | 2022-05-10 | 佛山市顺德区美的电热电器制造有限公司 | Fault diagnosis method and system of electrical equipment, cloud server and storage medium |
| CN108818531A (en) * | 2018-06-25 | 2018-11-16 | 珠海格力智能装备有限公司 | Robot control method and device |
| CN110909891A (en) * | 2018-09-17 | 2020-03-24 | 珠海格力电器股份有限公司 | Method and device for maintaining electric appliance fault |
| CN110909891B (en) * | 2018-09-17 | 2024-04-05 | 珠海格力电器股份有限公司 | Maintenance method and device for electrical appliance faults |
| CN109376646A (en) * | 2018-10-19 | 2019-02-22 | 佛山市联科发信息科技有限公司 | A kind of electric appliance intelligent controller of image recognition |
| CN111340808A (en) * | 2020-05-20 | 2020-06-26 | 北京小米移动软件有限公司 | Screen display monitoring method and device, electronic equipment and storage medium |
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Application publication date: 20180427 |