CN110550347A - Garbage classification recycling method, user terminal and garbage can - Google Patents
Garbage classification recycling method, user terminal and garbage can Download PDFInfo
- Publication number
- CN110550347A CN110550347A CN201910782852.3A CN201910782852A CN110550347A CN 110550347 A CN110550347 A CN 110550347A CN 201910782852 A CN201910782852 A CN 201910782852A CN 110550347 A CN110550347 A CN 110550347A
- Authority
- CN
- China
- Prior art keywords
- garbage
- category
- classified
- recycling
- determining
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F1/00—Refuse receptacles; Accessories therefor
- B65F1/0033—Refuse receptacles; Accessories therefor specially adapted for segregated refuse collecting, e.g. receptacles with several compartments; Combination of receptacles
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F1/00—Refuse receptacles; Accessories therefor
- B65F1/14—Other constructional features; Accessories
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F2210/00—Equipment of refuse receptacles
- B65F2210/128—Data transmitting means
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
- Y02W30/00—Technologies for solid waste management
- Y02W30/10—Waste collection, transportation, transfer or storage, e.g. segregated refuse collecting, electric or hybrid propulsion
Abstract
The invention discloses a garbage classification recycling method, a user terminal and a garbage can, which are used for solving the problem that the recycling category of garbage cannot be correctly identified in the prior art. The method comprises the following steps: acquiring a detection image of garbage to be classified, processing the detection image by adopting a pre-training model, and determining a garbage category corresponding to the garbage to be classified according to a processing result of the pre-training model; the pre-training model is a functional relation model of a sample image and class information, and the class information is used for representing the garbage class corresponding to the sample image; calling a sample data set of the pre-training model according to the garbage category, and determining the recycling category of the garbage to be classified; the sample data set comprises a plurality of groups of garbage categories of garbage to be classified and parameter groups corresponding to recycling categories.
Description
Technical Field
the invention relates to the technical field of environmental protection, in particular to a garbage classification recycling method, a user terminal and a garbage can.
Background
with the rapid development of social economy and the rapid improvement of the living standard of people, the garbage generated in the urban production and living process is rapidly increased, and the conditions that the household garbage occupies the land and pollutes the environment are more obvious. How to recover and process garbage more efficiently becomes a focus of attention of all circles, and in the process of recovering and processing garbage, it is important to classify and process the garbage. The garbage classification means that the garbage is classified and stored, classified and put in, and classified and carried according to certain rules or standards, so that the garbage is converted into public resources. Compared with the traditional garbage recycling method, the garbage classification is a more effective garbage recycling method, and has the advantages of reducing environmental pollution, changing waste into valuable, recycling resources and the like.
At present, the work of garbage classification recycling is mainly carried out manually, and people are not familiar with the recycling type of garbage, so that people cannot avoid placing the garbage into the garbage bin with the wrong type even if the recycling type corresponding to the garbage bin is marked on the garbage bin. Therefore, the problem that people cannot correctly identify the recycling type of the garbage exists in the prior art.
Disclosure of Invention
the embodiment of the invention provides a garbage classification and recovery method, a user terminal and a garbage can, which are used for solving the technical problem that the recovery category of garbage cannot be correctly identified in the prior art.
in a first aspect, to solve the foregoing technical problem, an embodiment of the present application provides a method for classifying and recycling garbage, which is applied to a user terminal, and has a technical scheme as follows:
Acquiring a detection image of garbage to be classified, processing the detection image by adopting a pre-training model, and determining a garbage category corresponding to the garbage to be classified according to a processing result of the pre-training model; the pre-training model is a functional relation model of a sample image and class information, and the class information is used for representing the garbage class corresponding to the sample image;
Calling a sample data set of the pre-training model according to the garbage category, and determining the recycling category of the garbage to be classified; the sample data set comprises a plurality of groups of garbage categories of garbage to be classified and parameter groups corresponding to recycling categories.
in the embodiment of the application, a detection image of garbage to be classified can be acquired, a pre-training model is adopted to process the detection image, the garbage category corresponding to the garbage to be classified is determined according to the processing result of the pre-training model, and the sample data set of the pre-training model is called according to the garbage category to determine the recovery category of the garbage to be classified, so that the technical problems that people are unfamiliar with the recovery category of the garbage, the recovery category of the garbage cannot be correctly identified, and further the garbage can not be classified and recovered in the prior art are solved. The difficulty of garbage recycling treatment is reduced, the enthusiasm of people for garbage classification is improved, and the orderly garbage classification work is promoted.
with reference to the first aspect, in a first optional implementation manner of the first aspect, before acquiring the detection image of the garbage to be classified, the method includes:
obtaining a sample image set of a pre-trained model, wherein the sample image set comprises at least one sample image;
receiving preset category information of the sample image, wherein the preset category information is used for representing a garbage category corresponding to the sample image;
And generating the pre-training model according to the preset category information of the sample image.
with reference to the first aspect and the first optional implementation manner of the first aspect, in a second optional implementation manner of the first aspect, acquiring a detection image of garbage to be classified, processing the detection image by using a pre-training model, and determining a garbage category corresponding to the garbage to be classified according to a processing result of the pre-training model includes:
acquiring a first detection image of garbage to be classified, inputting the first detection image into the pre-training model, and determining a garbage category and a garbage category probability value corresponding to the first detection image;
If the garbage category probability value is larger than or equal to a preset threshold value, determining that the garbage category is a garbage category corresponding to the garbage to be classified;
if the garbage category probability value is smaller than a preset threshold value, acquiring a second detection image of the garbage to be classified, wherein the shooting angle of the second detection image is different from that of the first detection image;
And inputting the second detection image into the pre-training model, and determining the garbage category corresponding to the garbage to be classified.
with reference to the second optional implementation manner of the first aspect, in a third optional implementation manner of the first aspect, the method further includes:
If the garbage category corresponding to the garbage to be classified is determined to fail, displaying a dialog box for entering the garbage category of the garbage to be classified, and determining the garbage category of the garbage to be classified based on information obtained by the dialog box.
with reference to the first aspect, in a fourth optional implementation manner of the first aspect, before invoking the sample data set of the pre-training model, the method further includes:
acquiring a sample data set of each urban garbage recycling category;
Detecting whether a positioning authority is opened or not, if the positioning authority is opened, positioning the current position, and determining city information; if the positioning authority is not opened, displaying a dialog box for inputting the city information, and determining the city information based on the operation acquired by the dialog box;
and determining a sample data set corresponding to the city information as a sample data set of a pre-training model according to the city information.
With reference to the first aspect, in a fifth optional implementation manner of the first aspect, the method further includes:
And if the recovery category of the garbage to be classified is determined to be failed, displaying a garbage classification introduction page, wherein the garbage classification introduction page is used for outputting prompt information to indicate a user to determine the recovery category of the garbage to be classified according to introduction contents.
with reference to the first aspect, in a sixth optional implementation manner of the first aspect, the method further includes:
Counting the quantity of the garbage of the determined recycling category;
Calling a built-in map or a network map of the user terminal, and positioning the garbage cans of different recycling types closest to the current position;
sending indication information to the trash can, wherein the indication information is used for indicating the trash can to calculate the quantity of loadable trash;
Acquiring the quantity of the bearable garbage fed back by the garbage can according to the indication information, and judging whether the quantity of the garbage of which the recovery category is determined is matched with the quantity of the bearable garbage of the garbage can or not according to the quantity of the bearable garbage;
If the garbage is matched with the recycling classification, determining that the garbage can bear the garbage of which the recycling classification is determined;
If the garbage is not matched with the preset garbage, calling a built-in map or a network map of the user terminal, repositioning the garbage can, and determining the garbage can capable of bearing the garbage with the determined recycling type in the repositioned garbage can.
in the embodiment of the application, the garbage cans of different recycling categories closest to the current position can be located by calling a built-in map or a network map of a user terminal, then an indication message for indicating the garbage cans to calculate the quantity of the loadable garbage is sent to the garbage cans, so that the quantity of the loadable garbage fed back by the garbage cans according to the indication message is obtained, and then whether the quantity of the loadable garbage of the garbage cans is matched with the quantity of the determined recycling category garbage counted before is judged according to the quantity of the loadable garbage, so that the garbage cans capable of bearing the determined recycling category garbage are determined, the problem that whether the garbage cans are full can not be determined before people put the garbage is solved, and the time cost for putting the garbage is reduced.
In a second aspect, a method for sorting and recycling garbage is provided, which is applied to a garbage can and includes:
receiving indication information sent by a user terminal, wherein the indication information is used for indicating a garbage can to calculate the quantity of loadable garbage;
According to the indication information, calculating the quantity of the loadable garbage of the garbage can;
And sending the bearable garbage quantity to the user terminal.
In a third aspect, an apparatus for classifying and recycling garbage is provided, which is applied to a user terminal, and includes:
the garbage classification method comprises the steps that a first determining module is used for obtaining a detection image of garbage to be classified, processing the detection image by adopting a pre-training model, and determining the garbage classification corresponding to the garbage to be classified according to the processing result of the pre-training model; the pre-training model is a functional relation model of a sample image and class information, and the class information is used for representing the garbage class corresponding to the sample image;
the second determining module is used for calling the sample data set of the pre-training model according to the garbage category and determining the recycling category of the garbage to be classified; the sample data set comprises a plurality of groups of garbage categories of garbage to be classified and parameter groups corresponding to recycling categories.
With reference to the third aspect, in a first optional implementation manner of the third aspect, the apparatus further includes a generating module configured to:
Obtaining a sample image set of a pre-trained model, wherein the sample image set comprises at least one sample image;
Receiving preset category information of the sample image, wherein the preset category information is used for representing a garbage category corresponding to the sample image;
and generating the pre-training model according to the preset category information of the sample image.
with reference to the third aspect and the first optional implementation manner of the third aspect, in a second optional implementation manner of the third aspect, the first determining module is specifically configured to:
acquiring a first detection image of garbage to be classified, inputting the first detection image into the pre-training model, and determining a garbage category and a garbage category probability value corresponding to the first detection image;
if the garbage category probability value is larger than or equal to a preset threshold value, determining that the garbage category is a garbage category corresponding to the garbage to be classified;
If the garbage category probability value is smaller than a preset threshold value, acquiring a second detection image of the garbage to be classified, wherein the shooting angle of the second detection image is different from that of the first detection image;
and inputting the second detection image into the pre-training model, and determining the garbage category corresponding to the garbage to be classified.
With reference to the second optional implementation manner of the third aspect, in a third optional implementation manner of the third aspect, the apparatus further includes a third determining module:
If the garbage category corresponding to the garbage to be classified is determined to fail, displaying a dialog box for entering the garbage category of the garbage to be classified, and determining the garbage category of the garbage to be classified based on information obtained by the dialog box.
with reference to the third aspect, in a fourth optional implementation manner of the third aspect, the apparatus further includes a fourth determining module configured to:
acquiring a sample data set of each urban garbage recycling category;
detecting whether a positioning authority is opened or not, if the positioning authority is opened, positioning the current position, and determining city information; if the positioning authority is not opened, displaying a dialog box for inputting the city information, and determining the city information based on the operation acquired by the dialog box;
and determining a sample data set corresponding to the city information as a sample data set of a pre-training model according to the city information.
With reference to the third aspect, in a fifth alternative implementation manner of the third aspect, the apparatus further includes a display module configured to:
And if the recovery category of the garbage to be classified is determined to be failed, displaying a garbage classification introduction page, wherein the garbage classification introduction page is used for outputting prompt information to indicate a user to determine the recovery category of the garbage to be classified according to introduction contents.
with reference to the third aspect, in a sixth optional implementation manner of the third aspect, the apparatus further includes a fifth determining module configured to:
Counting the quantity of the garbage of the determined recycling category;
calling a built-in map or a network map of the user terminal, and positioning the garbage cans of different recycling types closest to the current position;
Sending indication information to the trash can, wherein the indication information is used for indicating the trash can to calculate the quantity of loadable trash;
acquiring the quantity of the bearable garbage fed back by the garbage can according to the indication information, and judging whether the quantity of the garbage of which the recovery category is determined is matched with the quantity of the bearable garbage of the garbage can or not according to the quantity of the bearable garbage;
If the garbage is matched with the recycling classification, determining that the garbage can bear the garbage of which the recycling classification is determined;
if the garbage is not matched with the preset garbage, calling a built-in map or a network map of the user terminal, repositioning the garbage can, and determining the garbage can capable of bearing the garbage with the determined recycling type in the repositioned garbage can.
In a fourth aspect, a device for classifying and recycling garbage is provided, which is applied to a garbage can, and comprises:
The system comprises a receiving module, a judging module and a sending module, wherein the receiving module is used for receiving indication information sent by a user terminal, and the indication information is used for indicating a garbage can to calculate the quantity of loadable garbage;
the processing module is used for calculating the quantity of the loadable garbage of the garbage can according to the indication information;
a sending module, configured to send the bearable garbage amount to the user terminal. In a fifth aspect, a user terminal is provided, which includes:
A memory for storing program instructions;
a processor, configured to call a program instruction stored in the memory, and execute the steps included in any one of the embodiments of the first aspect and the second aspect according to the obtained program instruction;
and the transceiver is used for sending the indication information to the garbage can and receiving the bearable garbage quantity sent by the garbage can.
In a sixth aspect, a trash can is provided, comprising:
a memory for storing program instructions;
a processor, configured to call the program instruction stored in the memory, and execute the steps included in any one of the sixth optional implementation manner of the first aspect and the second aspect according to the obtained program instruction;
and the transceiver receives the indication information sent by the user terminal and sends the loadable garbage amount to the user terminal.
In a fifth aspect, a storage medium is provided, the storage medium storing computer-executable instructions for causing a computer to perform the steps included in any one of the embodiments of the first and second aspects.
drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
fig. 1 is a schematic structural diagram of a user terminal in an embodiment of the present application;
Fig. 2 is a flowchart of a method for garbage classification and recycling applied to a user terminal in an embodiment of the present application;
fig. 3 is a schematic structural diagram of a trash can in an embodiment of the present application;
FIG. 4 is a flow chart of a method for sorting and recycling garbage applied to a garbage bin in an embodiment of the present application;
Fig. 5 is a device for garbage classification and recycling applied to a user terminal in an embodiment of the present application;
FIG. 6 is a device for sorting and recycling garbage applied to a garbage can in an embodiment of the present application;
fig. 7 is a schematic structural diagram of a user terminal in an embodiment of the present application;
fig. 8 is a schematic structural diagram of a trash can in an embodiment of the present application.
Detailed Description
in order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application. In the present application, the embodiments and features of the embodiments may be arbitrarily combined with each other without conflict. Also, while a logical order is shown in the flow diagrams, in some cases, steps shown or described may be performed in an order different than presented herein.
the terms "first" and "second" in the description and claims of the present application and the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the term "comprises" and any variations thereof, which are intended to cover non-exclusive protection. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
in the embodiments of the present application, "at least one" may mean at least two, for example, two, three, or more, and the embodiments of the present application are not limited.
In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" in this document generally indicates that the preceding and following related objects are in an "or" relationship unless otherwise specified.
At present, the work of garbage classification recycling is mainly carried out manually, and people are not familiar with the recycling type of garbage, so that people cannot avoid placing the garbage into the garbage bin with the wrong type even if the recycling type corresponding to the garbage bin is marked on the garbage bin. Therefore, the problem that people cannot correctly identify the recycling type of the garbage exists in the prior art.
In view of this, an embodiment of the present application provides a method for classifying and recycling garbage, which may obtain a detection image of garbage to be classified, process the detection image by using a pre-training model, determine a garbage class corresponding to the garbage to be classified according to a processing result of the pre-training model, and then call a sample data set of the pre-training model according to the garbage class to determine a recycling class of the garbage to be classified. The garbage classification recycling system has the advantages that the technical problem that people cannot correctly recognize the recycling category of garbage and further cannot classify and recycle the garbage is solved, the difficulty of garbage recycling is reduced, the time cost of garbage putting is reduced, the enthusiasm of people for garbage classification is improved, and the orderly operation of garbage classification work is promoted.
In order to better understand the technical solutions, the technical solutions of the present application are described in detail below through the drawings and the specific embodiments of the specification, and it should be understood that the specific features of the embodiments and examples of the present application are detailed descriptions of the technical solutions of the present application, and are not limitations of the technical solutions of the present application, and the technical features of the embodiments and examples of the present application may be combined with each other without conflict.
Fig. 1 is a user terminal to which the method provided in the embodiment of the present application is applicable, because the user terminal to which the method provided in the embodiment of the present application is applicable is a device having functions of image acquisition and image processing, and in view of compatibility with existing devices, the embodiment of the present application provides a mobile phone as the user terminal to which the method provided in the embodiment of the present application is applicable.
the user terminal shown in fig. 1 comprises a camera 101, a transceiver 102, a memory 103, a processor 104. The camera 101 is used for acquiring a detection image of garbage to be classified. The transceiver 102 is used to transmit and receive information. The memory 103 is used to store program instructions. The processor 104 is configured to obtain the transceiver receiving information, call the program instructions stored in the memory 103, and execute all steps included in the method for garbage classification recycling according to the obtained program instructions.
referring to fig. 2, a method for classifying and recycling garbage is provided for an embodiment of the present application, and the method can be executed by the user terminal shown in fig. 1. The specific flow of the method is described below.
step 201: acquiring a detection image of the garbage to be classified, processing the detection image by adopting a pre-training model, and determining the garbage category corresponding to the garbage to be classified according to the processing result of the pre-training model.
In the embodiment of the application, before a detection image of garbage to be classified is acquired, a pre-training model is generated, wherein the pre-training model is a functional relationship model of a sample image and class information, and the class information is used for representing a garbage class corresponding to the sample image.
Specifically, a sample image set of a pre-training model is obtained, wherein the sample image set comprises at least one sample image, the sample image is preprocessed, and then feature information of an object in the sample image is extracted, wherein the preprocessing can eliminate irrelevant information in the sample image, so that the reliability of feature extraction is improved, and then preset category information of the sample image is determined according to the feature information of the object in the sample image, wherein the preset category information is used for representing a garbage category corresponding to the sample image. And receiving the preset category information according to the acquired sample image set, and determining the corresponding garbage category of each sample image. And generating a pre-training model according to the preset category information of the sample image.
In the embodiment of the application, after the pre-training model is generated, the detection image of the garbage to be classified is obtained, the pre-training model is adopted to process the detection image, and the garbage category corresponding to the garbage to be classified is determined according to the processing result of the pre-training model.
specifically, a first detection image of the garbage to be classified is acquired first through a camera of the user terminal, the first detection image is input to the pre-training model, and the garbage category probability value corresponding to the first detection image are determined, which is described below in an exemplary manner for easy understanding:
For example, the first detection image is input into a pre-training model, and the garbage class corresponding to the first detection image is determined to be a plastic cup and the corresponding garbage class probability value is 0.8.
if the garbage category probability value is greater than or equal to a preset threshold value, determining the garbage category of the first detection image as a garbage category corresponding to the garbage to be classified; and if the garbage category probability value is smaller than a preset threshold value, acquiring a second detection image of the garbage to be classified, wherein the shooting angle of the second detection image is different from that of the first detection image, inputting the second detection image into a pre-training model, and determining the garbage category corresponding to the garbage to be classified. If the garbage category corresponding to the garbage to be classified is determined to be successful, the garbage category of the second detection image is the garbage category corresponding to the garbage to be classified; and if the garbage category corresponding to the garbage to be classified is determined to fail, displaying a dialog box for entering the garbage category of the garbage to be classified, and determining the garbage category of the garbage to be classified based on the information acquired by the dialog box. For ease of understanding, the following description is given by way of example:
For example, if the obtained garbage category probability value corresponding to the first detection image is 0.8, and the preset threshold corresponding to the garbage category probability value is 0.6, determining that the garbage category of the first detection image is the garbage category corresponding to the garbage to be classified;
if the obtained garbage class probability value corresponding to the first detection image is 0.4 and the preset threshold value corresponding to the garbage class probability value is 0.6, determining that the garbage class of the first detection image is not the garbage class corresponding to the garbage to be classified, then obtaining a second detection image of the garbage to be classified, wherein the shooting angle of the second detection image is different from that of the first detection image, inputting the second detection image to a pre-training model, and determining the garbage class and the garbage class probability value corresponding to the garbage to be classified;
If the obtained garbage category probability value corresponding to the second detection image is 0.7 and the preset threshold value corresponding to the garbage category probability value is 0.6, determining the garbage category of the second detection image as the garbage category corresponding to the garbage to be classified;
if the obtained garbage category probability value corresponding to the second detection image is 0.5 and the preset threshold value corresponding to the garbage category probability value is 0.6, determining that the garbage category of the second detection image is not the garbage category corresponding to the garbage to be classified, displaying a dialog box for inputting the garbage category of the garbage to be classified, and determining the garbage category of the garbage to be classified based on the information obtained by the dialog box.
step 202: and calling a sample data set of the pre-training model according to the garbage category corresponding to the garbage to be classified, and determining the recycling category of the garbage to be classified.
In the embodiment of the application, before the sample data set of the pre-training model is called, the sample data set of the pre-training model is determined, wherein the sample data set comprises a plurality of groups of garbage categories of garbage to be classified and parameter groups corresponding to recycling categories.
specifically, a sample data set of each urban garbage recycling category is obtained according to respective garbage recycling criteria of each city, then whether a user terminal opens a positioning authority is detected, if the positioning authority is opened, the current position is positioned, and city information is determined; and if the positioning authority is not opened, displaying a dialog box for inputting the city information, and determining the city information based on the operation acquired by the dialog box. And determining a sample data set corresponding to the city information as a sample data set of the pre-training model according to the city information. For ease of understanding, the following description is given by way of example:
For example, if the user terminal opens the positioning authority, positioning the current location, determining that the current location city is city a, and determining that the sample data set corresponding to city a is the sample data set of the pre-training model according to city a, wherein the sample data set corresponding to city a is the sample data set of the garbage recycling category acquired according to the garbage recycling criterion of city a, and comprises a plurality of groups of garbage categories of garbage to be classified and parameter groups corresponding to the recycling categories;
if the user terminal does not open the positioning authority, displaying a dialog box for inputting city information, determining that the current city is a city B based on the operation obtained by the dialog box, and determining that the sample data set corresponding to the city B is the sample data set of the pre-training model according to the city B, wherein the sample data set corresponding to the city B is the sample data set of the garbage recycling category obtained according to the garbage recycling criterion of the city B and comprises a plurality of groups of garbage categories of garbage to be classified and parameter groups corresponding to the recycling category.
In the embodiment of the application, after the sample data set of the pre-training model is determined, the sample data set of the pre-training model is called according to the garbage category corresponding to the garbage to be classified, and the recycling category of the garbage to be classified is determined.
Specifically, according to the garbage categories of a plurality of groups of garbage to be classified in the sample data set and the parameter groups corresponding to the recycling categories, the recycling categories corresponding to the garbage categories are determined. And if the recovery category corresponding to the garbage category fails to be determined, displaying a garbage classification introduction page, wherein the garbage classification introduction page is used for outputting prompt information to indicate a user to determine the recovery category of the garbage to be classified according to introduction contents. For ease of understanding, the following description is given by way of example:
for example, if the garbage category of the garbage to be classified is a plastic cup, determining that the recovery category corresponding to the garbage category is recyclable garbage; and if the garbage category of the garbage to be classified is the wet tissue, determining that the recycling category corresponding to the garbage category is dry garbage.
After the recycling category of the garbage to be classified is determined, when the garbage of which the recycling category is determined is thrown into the garbage can of the corresponding recycling category, there may be a problem that the garbage can which is to be thrown is full, and based on the problem, in the embodiment of the present application, after the recycling category of the garbage to be classified is determined, the garbage can capable of bearing the garbage of which the recycling category is determined.
specifically, the number of garbage of the determined recycling category is counted. And then positioning the garbage cans of different recycling types closest to the current position by calling a built-in map or a network map of the user terminal, sending indication information indicating that the garbage cans calculate the number of the loadable garbage to the garbage cans, acquiring the number of the loadable garbage fed back by the garbage cans according to the indication information, judging whether the number of the determined recycling types of the garbage is matched with the number of the loadable garbage of the garbage cans according to the number of the loadable garbage, if so, determining that the garbage cans are the garbage cans capable of bearing the determined recycling types of the garbage, if not, calling the built-in map or the network map of the user terminal, repositioning the garbage cans, and determining the garbage cans capable of bearing the determined recycling types of the garbage in the repositioned garbage cans. For ease of understanding, the following description is given by way of example:
For example, according to the recycling type of the garbage, a built-in map or a network map of the user terminal is called, and the quantity of the loadable garbage and the position information of the garbage can fed back by the garbage can according to the indication information are obtained;
If the garbage of the determined recycling type is 0.02 cubic meter and the obtained garbage capable of bearing the load of the corresponding recycling type is 0.03 cubic meter, determining that the quantity of the garbage of the determined recycling type is matched with the quantity of the garbage capable of bearing the load of the garbage can;
if the garbage of the determined recycling type is 0.02 cubic meter and the acquired garbage capable of bearing the load of the corresponding recycling type is 0.01 cubic meter, determining that the quantity of the garbage of the determined recycling type is not matched with the quantity of the garbage capable of bearing the load of the garbage can, calling a built-in map or a network map of the user terminal, repositioning the garbage can of the corresponding recycling type, and determining the garbage can capable of bearing the garbage of the determined recycling type in the repositioned garbage can.
after determining the trash can capable of bearing the trash of the determined recycling category, when a user puts the trash of the determined recycling category into the trash can capable of bearing the trash of the determined recycling category, there may be a problem that the trash can not be identified.
specifically, in consideration of combination with the prior art, a virtual map may be generated at the user terminal through an Augmented Reality (AR) technology, wherein the virtual map is used for representing the style and the position of a garbage can of a city where Reality is located. And determining the style of the garbage can capable of bearing the garbage with the determined recycling category according to the virtual map.
fig. 3 is a garbage can to which the method provided in the embodiment of the present application is applicable, although the method provided in the embodiment of the present application can be applied to various garbage cans, and it should be understood that the garbage can shown in fig. 3 is a detailed description of the garbage can to which the method provided in the embodiment of the present application is applicable, and is not a limitation of the garbage can to which the method provided in the embodiment of the present application is applicable.
The trash can shown in fig. 3 includes a transceiver 301, a memory 302, and a processor 303. The transceiver 301 is used to transmit and receive information. The memory 103 is used to store program instructions. The processor 104 is configured to obtain information received by the transceiver, call the program instructions stored in the memory 103, and execute all steps included in the method for garbage classification recycling according to the obtained program instructions.
referring to fig. 4, a method for sorting and recycling garbage according to an embodiment of the present application is provided, which can be performed by the garbage can shown in fig. 3. The specific flow of the method is described below.
step 401: and receiving indication information sent by the user terminal.
in the embodiment of the application, an indication message sent by a user terminal is received through a transceiver of a trash can, wherein the indication message is used for indicating the trash can to calculate the bearable trash amount.
Step 402: and calculating the quantity of the loadable garbage of the garbage can according to the indication information.
in the embodiment of the application, the processor of the trash can acquires the indication information sent by the user terminal and received by the transceiver, and according to the indication information, the height of the trash stack in the trash can and the height of the trash can are acquired, so that the quantity of the garbage which can be loaded by the trash can is determined.
step 403: and sending the amount of the loadable garbage to the user terminal.
In the embodiment of the application, the bearable garbage amount is sent to the user terminal through the transceiver of the garbage can. Specifically, the quantity of the garbage which can be loaded by the garbage cans of different recycling categories and the position information of the garbage cans are fed back to the user terminal.
based on the same inventive concept, the embodiment of the application provides a garbage classification and recovery device, which is applied to a user terminal and can realize the corresponding functions of the garbage classification and recovery method. The garbage classification recycling device can be a hardware structure, a software module or a hardware structure and a software module. The garbage classification recycling device can be realized by a chip system, and the chip system can be formed by a chip and can also comprise the chip and other discrete devices. Referring to fig. 5, the apparatus for classifying and recycling garbage includes a first determining module 501 and a second determining module 502, where:
A first determining module 501, configured to obtain a detection image of garbage to be classified, process the detection image by using a pre-training model, and determine a garbage category corresponding to the garbage to be classified according to a processing result of the pre-training model; the pre-training model is a functional relation model of a sample image and class information, and the class information is used for representing the garbage class corresponding to the sample image;
A second determining module 502, configured to call a sample data set of the pre-training model according to the garbage category, and determine a recycling category of the garbage to be classified; the sample data set comprises a plurality of groups of garbage categories of garbage to be classified and parameter groups corresponding to recycling categories.
In an optional embodiment, the apparatus further comprises a generating module configured to:
Obtaining a sample image set of a pre-trained model, wherein the sample image set comprises at least one sample image;
receiving preset category information of the sample image, wherein the preset category information is used for representing a garbage category corresponding to the sample image;
And generating the pre-training model according to the preset category information of the sample image.
in an optional implementation manner, the first determining module is specifically configured to:
acquiring a first detection image of garbage to be classified, inputting the first detection image into the pre-training model, and determining a garbage category and a garbage category probability value corresponding to the first detection image;
if the garbage category probability value is larger than or equal to a preset threshold value, determining that the garbage category is a garbage category corresponding to the garbage to be classified;
if the garbage category probability value is smaller than a preset threshold value, acquiring a second detection image of the garbage to be classified, wherein the shooting angle of the second detection image is different from that of the first detection image;
and inputting the second detection image into the pre-training model, and determining the garbage category corresponding to the garbage to be classified.
in an optional embodiment, the apparatus further comprises a third determining module:
If the garbage category corresponding to the garbage to be classified is determined to fail, displaying a dialog box for entering the garbage category of the garbage to be classified, and determining the garbage category of the garbage to be classified based on information obtained by the dialog box.
in an optional implementation, the apparatus further includes a fourth determining module configured to:
Acquiring a sample data set of each urban garbage recycling category;
detecting whether a positioning authority is opened or not, if the positioning authority is opened, positioning the current position, and determining city information; if the positioning authority is not opened, displaying a dialog box for inputting the city information, and determining the city information based on the operation acquired by the dialog box;
And determining a sample data set corresponding to the city information as a sample data set of a pre-training model according to the city information.
in an alternative embodiment, the apparatus further comprises a display module configured to:
And if the recovery category of the garbage to be classified is determined to be failed, displaying a garbage classification introduction page, wherein the garbage classification introduction page is used for outputting prompt information to indicate a user to determine the recovery category of the garbage to be classified according to introduction contents.
in an optional implementation, the apparatus further includes a fifth determining module configured to:
counting the quantity of the garbage of the determined recycling category;
Calling a built-in map or a network map of the user terminal, and positioning the garbage cans of different recycling types closest to the current position;
Sending indication information to the trash can, wherein the indication information is used for indicating the trash can to calculate the quantity of loadable trash;
acquiring the quantity of the bearable garbage fed back by the garbage can according to the indication information, and judging whether the quantity of the garbage of which the recovery category is determined is matched with the quantity of the bearable garbage of the garbage can or not according to the quantity of the bearable garbage;
if the garbage is matched with the recycling classification, determining that the garbage can bear the garbage of which the recycling classification is determined;
if the garbage is not matched with the preset garbage, calling a built-in map or a network map of the user terminal, repositioning the garbage can, and determining the garbage can capable of bearing the garbage with the determined recycling type in the repositioned garbage can.
Based on the same inventive concept, the embodiment of the application provides a garbage classification and recovery device, which is applied to a garbage can and can realize the corresponding functions of the garbage classification and recovery method. The garbage classification recycling device can be a hardware structure, a software module or a hardware structure and a software module. The garbage classification recycling device can be realized by a chip system, and the chip system can be formed by a chip and can also comprise the chip and other discrete devices. Referring to fig. 6, the apparatus for classifying and recycling garbage includes a receiving module 601, a processing module 602, and a sending module 603, where:
a receiving module 601, configured to receive indication information sent by a user terminal, where the indication information is used to indicate a trash can to calculate a loadable trash amount;
the processing module 602 is configured to calculate a loadable garbage amount of the garbage bin according to the indication information;
a sending module 603, configured to send the bearable garbage amount to the user terminal. Based on the same inventive concept, the present application provides a user terminal, please refer to fig. 7, which includes at least one processor 701, a memory 702, and a transceiver 703. In the embodiment of the present application, specific connection media among the processor 701, the memory 702, and the transceiver 703 are not limited, fig. 7 illustrates an example in which the processor 701, the memory 702, and the transceiver 703 are connected by a bus 700, the bus 700 is shown by a thick line in fig. 7, and connection manners among other components are only for illustrative purposes and are not limited thereto. The bus 700 may be divided into an address bus, a data bus, a control bus, etc., and is shown in fig. 7 with only one thick line for ease of illustration, but does not represent only one bus or one type of bus.
in this embodiment of the application, the transceiver 703 sends an indication message to the trash can, where the indication message is used to indicate that the trash can calculate the amount of loadable trash, receive the amount of loadable trash sent by the trash can, the memory 702 stores instructions executable by the at least one processor 701, and the at least one processor 701 may execute the steps included in the method for recycling classified trash by obtaining data received by the transceiver 703 and calling the instructions stored in the memory 702.
The processor 701 is a control center of the ue, and may utilize various interfaces and lines to connect various parts of the entire ue, and execute instructions stored in the memory 702 by obtaining data received by the transceiver, thereby implementing various functions of the ue. Optionally, the processor 701 may include one or more processing units, and the processor 701 may integrate an application processor and a modem processor, wherein the application processor mainly handles an operating system, a user interface, an application program, and the like, and the modem processor mainly handles wireless communication. It will be appreciated that the modem processor described above may not be integrated into the processor 701.
memory 702, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The Memory 702 may include at least one type of storage medium, and may include, for example, a flash Memory, a hard disk, a multimedia card, a card-type Memory, a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Programmable Read Only Memory (PROM), a Read Only Memory (ROM), a charge Erasable Programmable Read Only Memory (EEPROM), a magnetic Memory, a magnetic disk, an optical disk, and so on. The memory 702 is any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory 702 in the embodiments of the present application may also be circuitry or any other device capable of performing a storage function for storing program instructions and/or data.
the processor 701 may be a general-purpose processor, such as a Central Processing Unit (CPU), digital signal processor, application specific integrated circuit, field programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or the like, that may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present application. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the garbage classification and recycling method disclosed in the embodiments of the present application may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.
By programming the processor 701, the code corresponding to the garbage classification recycling method described in the foregoing embodiment may be solidified into a chip, so that the chip can execute the steps of the garbage classification recycling method when running.
based on the same inventive concept, the present application provides a trash can, as described with reference to fig. 8, including at least one processor 801, a memory 802, and a transceiver 803. In the embodiment of the present application, specific connection media among the processor 801, the memory 802, and the transceiver 803 are not limited, fig. 8 illustrates an example in which the processor 801, the memory 802, and the transceiver 803 are connected by a bus 800, the bus 800 is represented by a thick line in fig. 8, and connection manners among other components are only for illustrative purposes and are not limited thereto. The bus 800 may be divided into an address bus, a data bus, a control bus, etc., and is shown in fig. 8 with only one thick line for ease of illustration, but does not represent only one bus or type of bus.
In this embodiment, the transceiver 803 receives indication information sent by a user terminal, and sends information of the amount of loadable garbage to the user terminal, where the indication information is used to indicate that the garbage can calculates the amount of loadable garbage, the memory 802 stores instructions executable by the at least one processor 801, and the at least one processor 801 may execute steps included in the method for recycling garbage classification by obtaining data received by the transceiver 803 and calling the instructions stored in the memory 802.
the processor 801 is a control center of the trash can, and can utilize various interfaces and lines to connect various parts of the whole user terminal, and execute instructions stored in the memory 802 by acquiring data received by the transceiver, thereby implementing various functions of the trash can. Optionally, the processor 801 may include one or more processing units, and the processor 801 may integrate an application processor and a modem processor, wherein the application processor mainly handles operating systems, user interfaces, application programs, and the like, and the modem processor mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 801.
memory 802, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The Memory 802 may include at least one type of storage medium, and may include, for example, a flash Memory, a hard disk, a multimedia card, a card-type Memory, a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Programmable Read Only Memory (PROM), a Read Only Memory (ROM), a charged Erasable Programmable Read Only Memory (EEPROM), a magnetic Memory, a magnetic disk, an optical disk, and so on. The memory 802 is any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory 802 in the embodiments of the present application may also be circuitry or any other device capable of performing a storage function for storing program instructions and/or data.
the processor 801 may be a general-purpose processor, such as a Central Processing Unit (CPU), digital signal processor, application specific integrated circuit, field programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or the like, that may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present application. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the garbage classification and recycling method disclosed in the embodiments of the present application may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.
by programming the processor 801, the codes corresponding to the garbage classification recycling method described in the foregoing embodiment may be solidified into a chip, so that the chip can execute the steps of the garbage classification recycling method when running, and how to program the processor 801 is a technique known by those skilled in the art, and will not be described herein again.
Based on the same inventive concept, the present application further provides a storage medium storing computer instructions, which when executed on a computer, cause the computer to perform the steps of the method for garbage classification and recycling as described above.
in some possible embodiments, the aspects of the method for garbage classification recycling provided by the present application may also be implemented in the form of a program product, which includes program code for causing a user terminal or a garbage can to perform the steps in the method for garbage classification recycling according to various exemplary embodiments of the present application described above in this specification when the program product is run on the user terminal or the garbage can.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
these computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (13)
1. a method for classifying and recycling garbage is applied to a user terminal and comprises the following steps:
Acquiring a detection image of garbage to be classified, processing the detection image by adopting a pre-training model, and determining a garbage category corresponding to the garbage to be classified according to a processing result of the pre-training model; the pre-training model is a functional relation model of a sample image and class information, and the class information is used for representing the garbage class corresponding to the sample image;
calling a sample data set of the pre-training model according to the garbage category, and determining the recycling category of the garbage to be classified; the sample data set comprises a plurality of groups of garbage categories of garbage to be classified and parameter groups corresponding to recycling categories.
2. The method of claim 1, wherein prior to obtaining the detected image of the garbage to be classified, comprising:
Obtaining a sample image set of a pre-trained model, wherein the sample image set comprises at least one sample image;
Receiving preset category information of the sample image, wherein the preset category information is used for representing a garbage category corresponding to the sample image;
and generating the pre-training model according to the preset category information of the sample image.
3. the method according to any one of claims 1-2, wherein the steps of obtaining a detection image of garbage to be classified, processing the detection image by using a pre-training model, and determining the garbage category corresponding to the garbage to be classified according to the processing result of the pre-training model comprise:
Acquiring a first detection image of garbage to be classified, inputting the first detection image into the pre-training model, and determining a garbage category and a garbage category probability value corresponding to the first detection image;
If the garbage category probability value is larger than or equal to a preset threshold value, determining that the garbage category is a garbage category corresponding to the garbage to be classified;
If the garbage category probability value is smaller than a preset threshold value, acquiring a second detection image of the garbage to be classified, wherein the shooting angle of the second detection image is different from that of the first detection image;
And inputting the second detection image into the pre-training model, and determining the garbage category corresponding to the garbage to be classified.
4. the method of claim 3, further comprising:
If the garbage category corresponding to the garbage to be classified is determined to fail, displaying a dialog box for entering the garbage category of the garbage to be classified, and determining the garbage category of the garbage to be classified based on information obtained by the dialog box.
5. the method of claim 1, wherein invoking the set of sample data of the pre-training model further comprises:
Acquiring a sample data set of each urban garbage recycling category;
Detecting whether a positioning authority is opened or not, if the positioning authority is opened, positioning the current position, and determining city information; if the positioning authority is not opened, displaying a dialog box for inputting the city information, and determining the city information based on the operation acquired by the dialog box;
and determining a sample data set corresponding to the city information as a sample data set of a pre-training model according to the city information.
6. the method of claim 1, further comprising:
And if the recovery category of the garbage to be classified is determined to be failed, displaying a garbage classification introduction page, wherein the garbage classification introduction page is used for outputting prompt information to indicate a user to determine the recovery category of the garbage to be classified according to introduction contents.
7. The method of claim 1, further comprising:
counting the quantity of the garbage of the determined recycling category;
Calling a built-in map or a network map of the user terminal, and positioning the garbage cans of different recycling types closest to the current position;
Sending indication information to the trash can, wherein the indication information is used for indicating the trash can to calculate the quantity of loadable trash;
acquiring the quantity of the bearable garbage fed back by the garbage can according to the indication information, and judging whether the quantity of the garbage of which the recovery category is determined is matched with the quantity of the bearable garbage of the garbage can or not according to the quantity of the bearable garbage;
if the garbage is matched with the recycling classification, determining that the garbage can bear the garbage of which the recycling classification is determined;
if the garbage is not matched with the preset garbage, calling a built-in map or a network map of the user terminal, repositioning the garbage can, and determining the garbage can capable of bearing the garbage with the determined recycling type in the repositioned garbage can.
8. a garbage classification and recycling method is applied to a garbage can and comprises the following steps:
Receiving indication information sent by a user terminal, wherein the indication information is used for indicating a garbage can to calculate the quantity of loadable garbage;
According to the indication information, calculating the quantity of the loadable garbage of the garbage can;
And sending the bearable garbage quantity to the user terminal.
9. the utility model provides a device that rubbish classification was retrieved which characterized in that, is applied to user terminal, includes:
the garbage classification method comprises the steps that a first determining module is used for obtaining a detection image of garbage to be classified, processing the detection image by adopting a pre-training model, and determining the garbage classification corresponding to the garbage to be classified according to the processing result of the pre-training model; the pre-training model is a functional relation model of a sample image and class information, and the class information is used for representing the garbage class corresponding to the sample image;
the second determining module is used for calling the sample data set of the pre-training model according to the garbage category and determining the recycling category of the garbage to be classified; the sample data set comprises a plurality of groups of garbage categories of garbage to be classified and parameter groups corresponding to recycling categories.
10. the utility model provides a device that waste classification retrieved which characterized in that is applied to the garbage bin, includes:
the system comprises a receiving module, a judging module and a sending module, wherein the receiving module is used for receiving indication information sent by a user terminal, and the indication information is used for indicating a garbage can to calculate the quantity of loadable garbage;
the processing module is used for calculating the quantity of the loadable garbage of the garbage can according to the indication information;
a sending module, configured to send the bearable garbage amount to the user terminal.
11. A user terminal, comprising:
A memory for storing program instructions;
A processor for calling program instructions stored in said memory and for executing the steps comprised by the method of any one of claims 1 to 8 in accordance with the program instructions obtained;
And the transceiver is used for sending the indication information to the garbage can and receiving the bearable garbage quantity sent by the garbage can.
12. a trash can, comprising:
a memory for storing program instructions;
A processor for calling program instructions stored in said memory and for executing the steps comprised by the method of any one of claims 7 to 8 in accordance with the obtained program instructions;
And the transceiver receives the indication information sent by the user terminal and sends the loadable garbage amount to the user terminal.
13. a storage medium storing computer-executable instructions for causing a computer to perform the steps comprising the method of any one of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910782852.3A CN110550347B (en) | 2019-08-23 | 2019-08-23 | Garbage classification recycling method, user terminal and garbage can |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910782852.3A CN110550347B (en) | 2019-08-23 | 2019-08-23 | Garbage classification recycling method, user terminal and garbage can |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110550347A true CN110550347A (en) | 2019-12-10 |
| CN110550347B CN110550347B (en) | 2020-08-04 |
Family
ID=68737980
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910782852.3A Active CN110550347B (en) | 2019-08-23 | 2019-08-23 | Garbage classification recycling method, user terminal and garbage can |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110550347B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111160186A (en) * | 2019-12-20 | 2020-05-15 | 上海寒武纪信息科技有限公司 | Intelligent garbage classification processing method and related products |
| CN111361889A (en) * | 2020-01-06 | 2020-07-03 | 安然 | Intelligent garbage can and control method thereof |
| CN111444813A (en) * | 2020-03-23 | 2020-07-24 | 北京字节跳动网络技术有限公司 | Method, device, equipment and storage medium for identifying attribute classification of target object |
| CN111553354A (en) * | 2020-05-14 | 2020-08-18 | 詹俊鲲 | Medical waste treatment method and device and storage medium |
| CN112200328A (en) * | 2020-10-15 | 2021-01-08 | 张良虎 | Garbage recycling method, device and system |
| CN112651318A (en) * | 2020-12-19 | 2021-04-13 | 重庆市信息通信咨询设计院有限公司 | Image recognition-based garbage classification method, device and system |
| CN112875077A (en) * | 2021-01-12 | 2021-06-01 | 安徽世绿环保科技有限公司 | Garbage classification method and classification system for large garbage station |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8965117B1 (en) * | 2013-12-17 | 2015-02-24 | Amazon Technologies, Inc. | Image pre-processing for reducing consumption of resources |
| CN206639234U (en) * | 2017-04-14 | 2017-11-14 | 苏州苏灵仪表有限公司 | Intelligent monitoring garbage classification device and its refuse classification management system |
| CN109201514B (en) * | 2017-06-30 | 2019-11-08 | 京东方科技集团股份有限公司 | Waste sorting recycle method, garbage classification device and classified-refuse recovery system |
| CN107809451A (en) * | 2017-09-05 | 2018-03-16 | 深圳市盛路物联通讯技术有限公司 | A kind of capacity information processing method and processing device |
| CN108706246A (en) * | 2018-05-31 | 2018-10-26 | 深圳市零度智控科技有限公司 | Intelligent refuse classification reclaimer, control method, device and storage medium |
| CN109018773A (en) * | 2018-08-06 | 2018-12-18 | 百度在线网络技术（北京）有限公司 | Refuse classification method, device and storage medium |
| CN108820647A (en) * | 2018-08-30 | 2018-11-16 | 深圳市研本品牌设计有限公司 | Rubbish put-on method and system based on image recognition |
| CN109389161B (en) * | 2018-09-28 | 2021-08-31 | 广州大学 | Garbage identification evolutionary learning method, device, system and medium based on deep learning |
-
2019
- 2019-08-23 CN CN201910782852.3A patent/CN110550347B/en active Active
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111160186A (en) * | 2019-12-20 | 2020-05-15 | 上海寒武纪信息科技有限公司 | Intelligent garbage classification processing method and related products |
| CN111160186B (en) * | 2019-12-20 | 2023-05-19 | 上海寒武纪信息科技有限公司 | Intelligent garbage classification processing method and related products |
| CN111361889A (en) * | 2020-01-06 | 2020-07-03 | 安然 | Intelligent garbage can and control method thereof |
| CN111444813A (en) * | 2020-03-23 | 2020-07-24 | 北京字节跳动网络技术有限公司 | Method, device, equipment and storage medium for identifying attribute classification of target object |
| CN111553354A (en) * | 2020-05-14 | 2020-08-18 | 詹俊鲲 | Medical waste treatment method and device and storage medium |
| CN112200328A (en) * | 2020-10-15 | 2021-01-08 | 张良虎 | Garbage recycling method, device and system |
| CN112200328B (en) * | 2020-10-15 | 2023-06-23 | 广东绿润环境科技有限公司 | Garbage recycling method, device and system |
| CN112651318A (en) * | 2020-12-19 | 2021-04-13 | 重庆市信息通信咨询设计院有限公司 | Image recognition-based garbage classification method, device and system |
| CN112875077A (en) * | 2021-01-12 | 2021-06-01 | 安徽世绿环保科技有限公司 | Garbage classification method and classification system for large garbage station |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110550347B (en) | 2020-08-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110550347B (en) | Garbage classification recycling method, user terminal and garbage can | |
| CN106384273B (en) | Malicious bill-swiping detection system and method | |
| CN110525823A (en) | A kind of method, apparatus and system that monitoring rubbish is put on by classification | |
| CN111217055B (en) | Garbage putting supervision method, device, server and system | |
| CN112100461B (en) | Questionnaire data processing method, device, server and medium based on data analysis | |
| CN112669515B (en) | Bill image recognition method and device, electronic equipment and storage medium | |
| CN109961423A (en) | A kind of pulmonary nodule detection method based on disaggregated model, server and storage medium | |
| CN111723772B (en) | Perishable garbage identification method and device based on image identification and computer equipment | |
| CN113128397A (en) | Garbage classification throwing monitoring method, system and device and storage medium | |
| CN109800675A (en) | A kind of method and device of the identification image of determining face object | |
| CN112651318A (en) | Image recognition-based garbage classification method, device and system | |
| CN109582549A (en) | A kind of recognition methods of device type and device | |
| CN212048939U (en) | Intelligent garbage recycling device for community | |
| CN112215147A (en) | Tracing method, device, equipment and storage medium for garbage throwing position | |
| CN112278636A (en) | Garbage classification recycling method, device and system and storage medium | |
| CN111318470A (en) | Method and device for identifying article type | |
| CN113486976B (en) | Automatic classification method and device for map annotation content | |
| CN109615919B (en) | Virtual parking lot user management method, server, and computer-readable storage medium | |
| CN101609453A (en) | A kind of separator page and the method and apparatus that utilizes the document classification of this separator page | |
| CN110533297B (en) | Method and device for identifying abnormal equipment | |
| CN107203561B (en) | Data processing method and equipment | |
| CN114443834A (en) | Method and device for extracting license information and storage medium | |
| CN113610100A (en) | Image recognition-based garbage processing method and device and electronic equipment | |
| CN112183284A (en) | Safety information verification and designated driving order receiving control method and device | |
| CN114627456A (en) | Bill text information detection method, device and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |