CN111860607A - Garbage classification method and device, storage medium and electronic device - Google Patents
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Abstract
The invention provides a garbage classification method and a garbage classification device, wherein the method comprises the following steps: acquiring a garbage image to be identified; under the condition of being in a sign language interaction mode, acquiring a target gesture of a target object, wherein the target gesture is used for indicating and determining the garbage type of garbage in the garbage image to be recognized; and responding to the target gesture, and determining the garbage type of the garbage in the garbage image to be recognized. By adopting the technical scheme, the problem that the deaf-mute people cannot communicate with each other like normal people, so that garbage classification is difficult and the like in the related technology is solved.
Description
Technical Field
The invention relates to the field of computers, in particular to a garbage classification method and device, a storage medium and an electronic device.
Background
At present, garbage disposal has become a troublesome problem in urban development. At present, the city garbage classification that has been released at first in Shanghai starts from the improvement of people's garbage classification's consciousness, but because people lack garbage classification knowledge, has caused people to be unable to confirm the type of rubbish when throwing away rubbish accurately. At present, can be through carrying on the camera, rubbish in the intelligent recognition life has certain help to people of waste classification difficulty, but because people have become used to and have thrown rubbish into the bag at will, the multiple rubbish of garbage bin bottom can be sheltered from even cover, can't realize the type of intelligent recognition rubbish through the image, still needs people on the inquiry search of network.
For deaf-dumb people, it is more difficult to classify garbage because they cannot communicate as normal people do.
Aiming at the problems that the deaf-mute people can not communicate like normal people, the garbage classification is difficult and the like in the related technology, an effective technical scheme is not provided yet.
Disclosure of Invention
The embodiment of the invention provides a garbage classification method and a garbage classification device, which at least solve the problems that in the related art, because deaf-mute people cannot communicate with each other like normal people, garbage classification is difficult and the like.
According to an embodiment of the present invention, there is provided a garbage classification method including: acquiring a garbage image to be identified; under the condition of being in a sign language interaction mode, acquiring a target gesture of a target object, wherein the target gesture is used for indicating and determining the garbage type of garbage in the garbage image to be recognized; and responding to the target gesture, and determining the garbage type of the garbage in the garbage image to be recognized.
In an embodiment of the present invention, after the obtaining of the spam image to be identified, the method further includes: performing image recognition on the garbage image to be recognized through image recognition equipment; and controlling the image recognition device to be in the sign language interaction mode when the image recognition device does not recognize the garbage type of the garbage in the garbage image to be recognized through the garbage image to be recognized.
In an embodiment of the present invention, the acquiring a target gesture of a target object includes: under the condition of the sign language interaction mode, outputting prompt information, wherein the prompt information is used for prompting the target object to send the target gesture, and the target gesture is used for describing the garbage in the garbage image to be recognized; and acquiring the target gesture of the target object under the condition that the target object sends out the target gesture according to the indication of the prompt message.
In an embodiment of the present invention, the determining a garbage type of the garbage in the to-be-recognized garbage image in response to the target gesture includes: identifying a first semantic identification result corresponding to the target gesture; determining a second semantic result corresponding to the first semantic recognition result in a target knowledge base module, wherein a first semantic set and a second semantic set are stored in the target knowledge base module, the first semantic set is used for requesting to confirm a garbage type corresponding to garbage to be recognized, the second semantic set is used for indicating the garbage type corresponding to the garbage to be recognized, the first semantic set comprises the first semantic recognition result, and the second semantic set comprises the second semantic recognition result; and determining the garbage type of the garbage in the garbage image to be identified according to the second semantic result.
In an embodiment of the present invention, the method further includes: acquiring a first semantic sample and a second semantic sample, wherein the first semantic sample is used for requesting to confirm a garbage type corresponding to garbage to be identified, and the second semantic sample is used for indicating the garbage type corresponding to the garbage to be identified; and training the target knowledge base according to the first semantic sample and the second semantic sample, and determining that the training of the target knowledge base is finished under the condition that the parameters of the target knowledge base are converged.
In an embodiment of the present invention, after determining the garbage type of the garbage in the garbage image to be identified, the method further includes: displaying the classification result of the garbage types through at least one of the following steps: pictures, text, video.
According to another embodiment of the present invention, there is also provided a garbage classification apparatus including: the first acquisition unit is used for acquiring a garbage image to be identified; the second acquisition unit is used for acquiring a target gesture of a target object under the condition of being in a sign language interaction mode, wherein the target gesture is used for indicating and determining the garbage type of the garbage in the garbage image to be recognized; and the first determining unit is used for responding to the target gesture and determining the garbage type of the garbage in the garbage image to be recognized.
According to another embodiment of the present invention, there is also provided a computer-readable storage medium including a stored program, wherein the program is executed to perform any of the above garbage classification methods.
According to another embodiment of the present invention, there is also provided an electronic apparatus, where the storage medium includes a stored program, and the program executes the garbage classification method according to any one of the above methods.
According to the method and the device, firstly, the garbage image to be recognized is obtained, the target gesture of the target object can be obtained under the condition of a sign language interaction mode, wherein the target gesture is used for indicating and determining the garbage type of the garbage in the garbage image to be recognized, and then the garbage type of the garbage in the garbage image to be recognized can be determined in response to the target gesture. By adopting the technical scheme, the deaf-mute people can determine the type of the garbage in a sign language interaction mode, and the problems that the deaf-mute people cannot communicate with each other like normal people, the garbage classification is difficult and the like in the related technology are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
Fig. 1 is a block diagram of a hardware structure of a garbage classification method according to an embodiment of the present invention;
FIG. 2 is a flow diagram of an alternative garbage classification method according to an embodiment of the present invention;
FIG. 3 is a flow diagram of an alternative garbage classification method according to an embodiment of the present invention;
fig. 4 is a block diagram of an alternative garbage classification apparatus according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
The method embodiments provided by the embodiments of the present application may be executed in a terminal, a computer terminal, a server, a base station, or a similar computing device. Taking an example of the operation on a terminal, fig. 1 is a hardware structure block diagram of the terminal of the data transmission method according to the embodiment of the present application. As shown in fig. 1, the terminal may include one or more (only one shown in fig. 1) processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, and optionally, a transmission device 106 for communication functions and an input-output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration and is not intended to limit the structure of the terminal. For example, the terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration with equivalent functionality to that shown in FIG. 1 or with more functionality than that shown in FIG. 1.
The memory 104 may be used to store computer programs, for example, software programs and modules of application software, such as a computer program corresponding to the garbage classification method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, so as to implement the method described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the mobile terminal 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the terminal 10. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
In this embodiment, a method for classifying garbage is provided, and fig. 2 is a flowchart of an alternative garbage classification method according to an embodiment of the present invention, as shown in fig. 2, the method includes the following steps:
step S202, acquiring a garbage image to be identified;
step S204, under the condition of being in a sign language interaction mode, acquiring a target gesture of a target object, wherein the target gesture is used for indicating and determining the garbage type of the garbage in the garbage image to be recognized;
and step S206, responding to the target gesture, and determining the garbage type of the garbage in the garbage image to be recognized.
Wherein, the garbage types may include: the garbage, dry garbage, wet garbage, toxic and harmful garbage, other garbage, kitchen garbage and the like can be recycled.
According to the method and the device, firstly, the garbage image to be recognized is obtained, the target gesture of the target object can be obtained under the condition of a sign language interaction mode, wherein the target gesture is used for indicating and determining the garbage type of the garbage in the garbage image to be recognized, and then the garbage type of the garbage in the garbage image to be recognized can be determined in response to the target gesture. By adopting the technical scheme, the deaf-mute people can determine the type of the garbage in a sign language interaction mode, and the problems that the deaf-mute people cannot communicate with each other like normal people, the garbage classification is difficult and the like in the related technology are solved.
After the step S202, the method may further include the following step, and after the step of acquiring the spam image to be identified, the method further includes: performing image recognition on the garbage image to be recognized through image recognition equipment; and controlling the image recognition device to be in the sign language interaction mode when the image recognition device does not recognize the garbage type of the garbage in the garbage image to be recognized through the garbage image to be recognized.
In step S204, the acquiring a target gesture of a target object includes: under the condition of the sign language interaction mode, outputting prompt information, wherein the prompt information is used for prompting the target object to send the target gesture, and the target gesture is used for describing the garbage in the garbage image to be recognized; and acquiring the target gesture of the target object under the condition that the target object sends out the target gesture according to the indication of the prompt message.
Optionally, for step S206, the determining the garbage type of the garbage in the garbage image to be recognized in response to the target gesture may include: identifying a first semantic identification result corresponding to the target gesture; determining a second semantic result corresponding to the first semantic recognition result in a target knowledge base module, wherein a first semantic set and a second semantic set are stored in the target knowledge base module, the first semantic set is used for requesting to confirm a garbage type corresponding to garbage to be recognized, the second semantic set is used for indicating the garbage type corresponding to the garbage to be recognized, the first semantic set comprises the first semantic recognition result, and the second semantic set comprises the second semantic recognition result; and determining the garbage type of the garbage in the garbage image to be identified according to the second semantic result.
In an alternative embodiment, the method further comprises: acquiring a first semantic sample and a second semantic sample, wherein the first semantic sample is used for requesting to confirm a garbage type corresponding to garbage to be identified, and the second semantic sample is used for indicating the garbage type corresponding to the garbage to be identified; and training the target knowledge base according to the first semantic sample and the second semantic sample, and determining that the training of the target knowledge base is finished under the condition that the parameters of the target knowledge base are converged.
In an optional embodiment, after determining the garbage type of the garbage in the garbage image to be identified, the method further includes: displaying the classification result of the garbage types through at least one of the following steps: pictures, text, video.
The following describes a flow of a task allocation method with reference to an alternative example, as shown in fig. 3, the method includes the following steps:
and S301, shooting the garbage to obtain a garbage image to be identified.
Optionally, the garbage that the user wants to discard at present is photographed and uploaded through a mobile device, such as a mobile phone, a tablet, or other device with a camera.
And step S302, performing image recognition on the garbage image to be recognized.
Optionally, the junk photos (corresponding to the junk images to be recognized) collected by the mobile device are sent to an image junk recognition module for classifying the junk categories, and a junk classification result is returned.
Step S303, if the garbage type of the garbage image to be identified is determined through image identification, the garbage classification is successful, and if the garbage type of the garbage image to be identified is not determined through image identification, the step S304 is skipped.
Optionally, the image spam recognition module has a certain confidence level for image recognition of spam photos, the confidence level of spam in each category can be set as a higher threshold, when spam with a higher confidence level is recognized, spam classification can be directly performed, otherwise, spam photos which cannot be analyzed enter the hand language interaction module for interaction.
And S304, entering a sign language interaction mode, enabling the deaf-mute and the image recognition equipment to perform gesture interaction to obtain a target gesture, performing gesture-mute recognition on the obtained target gesture, and determining a first semantic recognition result corresponding to the target gesture.
Optionally, the gesture-muted-language recognition module helps the deaf-mutes to perform mute-language interaction when the image-muted recognition module cannot automatically recognize the junk photos, the deaf-mutes send sign language to explain what is to be discarded currently, then the sign language sent by the deaf-mutes is recognized, and the result of the mute-language recognition is input to the junk knowledge base question-answering system in a text form.
Step S305, the first semantic recognition result is analyzed through a garbage knowledge base, a second semantic recognition result corresponding to the first semantic recognition result is determined, and garbage classification is successful.
Optionally, when the image recognition cannot accurately locate the category of the garbage, the question and answer module of the garbage knowledge base can ask the deaf-mute to ask about the garbage knowledge through the APP and send a gesture mute, for example, "how to throw the garbage in the lunch that the deaf-mute has to eat", "how to throw the pearl milk tea that the deaf-mute has to drink", "what garbage the orange peel is", and the like. After the deaf-mute inputs gesture and mute interaction, if the knowledge base can be analyzed correctly, garbage classification is directly carried out, otherwise, interaction of the gesture images of the mute is continuously carried out until the garbage knowledge base is analyzed correctly.
Optionally, the garbage knowledge may be collected in advance and stored in an ElasticSearch engine in a form of question-answer pairs, the user's question is used to make a rough recall to the ElasticSearch engine, and a knowledge base question-answer module is trained to help solve the garbage classification problem. After the deaf-mute inputs gesture and mute interaction, if the knowledge base can be analyzed correctly, garbage classification is directly carried out, otherwise, interaction of the gesture images of the mute is continuously carried out until the garbage knowledge base is analyzed correctly.
Optionally, the spam classification reply module may show the classified spam correctly identified by the system in the form of text + picture, where the text may describe which category the current spam belongs to, and expand similar spam, and the picture may directly give a visual classification flag result of the spam to present to the user.
Optionally, the category of the current spam can also be shown in the form of picture + text + video.
It is understood that the above is only an example, and the present embodiment is not limited thereto.
According to the embodiment, the garbage classification condition of the deaf-mute people is treated, the garbage classified by the images cannot be automatically identified, the garbage discarded at present is analyzed by directly performing gesture-mute language interaction, the correct garbage classification result is given by matching a garbage knowledge base, the popularization of garbage classification knowledge and the classification result of the current garbage are given by combining the result of pictures with characters, and the problems that the deaf-mute people cannot communicate like normal people, the garbage classification is difficult and the like are solved.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
The present embodiment further provides a garbage classification apparatus, which is applied to a distributed system, and the apparatus is used to implement the foregoing embodiments and preferred embodiments, and the description of the apparatus has been already made and is not repeated. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 4 is a block diagram of an alternative garbage classification apparatus according to an embodiment of the present invention, and as shown in fig. 4, the apparatus includes:
a first obtaining unit 402, configured to obtain a spam image to be identified;
a second obtaining unit 404, configured to obtain a target gesture of a target object when the target object is in a sign language interaction mode, where the target gesture is used to indicate that a spam type of spam in the spam image to be recognized is determined;
the first determining unit 406 is configured to determine a garbage type of garbage in the to-be-recognized garbage image in response to the target gesture.
According to the method and the device, firstly, the garbage image to be recognized is obtained, the target gesture of the target object can be obtained under the condition of a sign language interaction mode, wherein the target gesture is used for indicating and determining the garbage type of the garbage in the garbage image to be recognized, and then the garbage type of the garbage in the garbage image to be recognized can be determined in response to the target gesture. By adopting the technical scheme, the deaf-mute people can determine the type of the garbage in a sign language interaction mode, and the problems that the deaf-mute people cannot communicate with each other like normal people, the garbage classification is difficult and the like in the related technology are solved.
In an embodiment of the present invention, the apparatus further includes: the identification unit is used for carrying out image identification on the garbage image to be identified through image identification equipment; a control unit, configured to control the image recognition device to be in the sign language interaction mode when the image recognition device does not recognize the spam type of the spam in the spam image to be recognized through the spam image to be recognized.
In an embodiment of the present invention, the second obtaining unit includes: an output module, configured to output a prompt message when the target object is in the sign language interaction mode, where the prompt message is used to prompt the target object to send the target gesture, and the target gesture is used to describe spam in the spam image to be recognized; and the acquisition module is used for acquiring the target gesture of the target object under the condition that the target object sends out the target gesture according to the indication of the prompt message.
In an embodiment of the present invention, the first determining unit includes: the recognition module is used for recognizing a first semantic recognition result corresponding to the target gesture; a first determining module, configured to determine a second semantic result corresponding to the first semantic identification result in a target knowledge base module, where the target knowledge base module stores a first semantic set and a second semantic set, the first semantic set is used to request to confirm a garbage type corresponding to garbage to be identified, the second semantic set is used to indicate the garbage type corresponding to the garbage to be identified, the first semantic set includes the first semantic identification result, and the second semantic set includes the second semantic identification result; and the second determining module is used for determining the garbage type of the garbage in the garbage image to be identified according to the second semantic result.
In an embodiment of the present invention, the apparatus further includes: a third obtaining unit, configured to obtain a first semantic sample and a second semantic sample, where the first semantic sample is used to request to confirm a garbage type corresponding to garbage to be identified, and the second semantic sample is used to indicate the garbage type corresponding to the garbage to be identified; a second determining unit, configured to train the target knowledge base according to the first semantic sample and the second semantic sample, and determine that the training of the target knowledge base is completed when parameters of the target knowledge base are converged.
In an embodiment of the present invention, the apparatus further includes: a display unit, configured to display the classification result of the garbage type by at least one of: pictures, text, video.
Embodiments of the present invention also provide a computer-readable storage medium including a stored program, wherein the program performs any one of the methods described above when executed.
Alternatively, in the present embodiment, the storage medium may be configured to store program codes for performing the following steps:
s1, acquiring a garbage image to be identified;
s2, under the condition of being in a sign language interaction mode, acquiring a target gesture of a target object, wherein the target gesture is used for indicating and determining the garbage type of the garbage in the garbage image to be recognized;
S3, responding to the target gesture, and determining the garbage type of the garbage in the garbage image to be recognized.
Optionally, in this embodiment, the storage medium may include, but is not limited to: various media capable of storing program codes, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
s1, acquiring a garbage image to be identified;
s2, under the condition of being in a sign language interaction mode, acquiring a target gesture of a target object, wherein the target gesture is used for indicating and determining the garbage type of the garbage in the garbage image to be recognized;
S3, responding to the target gesture, and determining the garbage type of the garbage in the garbage image to be recognized. Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and this embodiment is not described herein again.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method of sorting waste, comprising:
acquiring a garbage image to be identified;
under the condition of being in a sign language interaction mode, acquiring a target gesture of a target object, wherein the target gesture is used for indicating and determining the garbage type of the garbage in the garbage image to be recognized;
and responding to the target gesture, and determining the garbage type of the garbage in the garbage image to be recognized.
2. The method of claim 1, wherein after the obtaining the spam image to be identified, the method further comprises:
performing image recognition on the garbage image to be recognized through image recognition equipment;
and controlling the image recognition device to be in the sign language interaction mode under the condition that the image recognition device does not recognize the garbage type of the garbage in the garbage image to be recognized through the garbage image to be recognized.
3. The method of claim 1, wherein the obtaining a target gesture of a target object comprises:
outputting prompt information under the condition of the sign language interaction mode, wherein the prompt information is used for prompting the target object to send out the target gesture, and the target gesture is used for describing the garbage in the garbage image to be recognized;
And under the condition that the target object sends out the target gesture according to the indication of the prompt message, acquiring the target gesture of the target object.
4. The method of claim 1, wherein the determining the spam type of the spam in the spam image to be identified in response to the target gesture comprises:
identifying a first semantic identification result corresponding to the target gesture;
determining a second semantic result corresponding to the first semantic recognition result in a target knowledge base module, wherein a first semantic set and a second semantic set are stored in the target knowledge base module, the first semantic set is used for requesting to confirm a garbage type corresponding to garbage to be recognized, the second semantic set is used for indicating the garbage type corresponding to the garbage to be recognized, the first semantic set comprises the first semantic recognition result, and the second semantic set comprises the second semantic recognition result;
and determining the garbage type of the garbage in the garbage image to be identified according to the second semantic result.
5. The method of claim 4, further comprising:
acquiring a first semantic sample and a second semantic sample, wherein the first semantic sample is used for requesting to confirm a garbage type corresponding to garbage to be identified, and the second semantic sample is used for indicating the garbage type corresponding to the garbage to be identified;
Training the target knowledge base according to the first semantic sample and the second semantic sample, and determining that the training of the target knowledge base is completed under the condition that the parameters of the target knowledge base are converged.
6. The method according to any one of claims 1 to 5, wherein after the determining the garbage type of the garbage in the garbage image to be identified, the method further comprises:
displaying the classification result of the garbage type through at least one of the following steps:
pictures, text, video.
7. A waste sorting device, comprising:
the first acquisition unit is used for acquiring a garbage image to be identified;
the second acquisition unit is used for acquiring a target gesture of a target object under the condition of being in a sign language interaction mode, wherein the target gesture is used for indicating and determining the garbage type of the garbage in the garbage image to be recognized;
and the first determining unit is used for responding to the target gesture and determining the garbage type of the garbage in the garbage image to be recognized.
8. The apparatus of claim 7, further comprising:
the identification unit is used for carrying out image identification on the garbage image to be identified through image identification equipment;
The control unit is used for controlling the image recognition device to be in the sign language interaction mode under the condition that the image recognition device does not recognize the garbage type of the garbage in the garbage image to be recognized through the garbage image to be recognized.
9. A computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to carry out the method of any one of claims 1 to 6 when executed.
10. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and wherein the processor is arranged to execute the computer program to perform the method of any of claims 1 to 6.
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