CN112836706A - Processing method, device and equipment for clothes color identification and storage medium - Google Patents
Processing method, device and equipment for clothes color identification and storage medium Download PDFInfo
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Abstract
The application provides a processing method, a device, equipment and a storage medium for clothes color identification, wherein the method comprises the following steps: receiving original image data in a drum sent by a washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting an HSV space-based clothes color identification algorithm to perform color identification on the segmented image data to obtain an identification result; and sending the identification result to the washing machine so that the washing machine performs corresponding processing according to the identification result. The accuracy of clothes color identification is effectively improved, so that accurate clothes washing service can be provided for users, and user experience is improved.
Description
Technical Field
The present application relates to the field of intelligent device technologies, and in particular, to a method, an apparatus, a device, and a storage medium for identifying a color of a garment.
Background
The clothes have various colors, except common red, orange, yellow, green, cyan, blue and purple colors, the clothes with the colors can be mixed together for washing, the prior art usually depends on the judgment of the people according to experience, the judgment result is not accurate enough, the clothes which cannot be mixed for washing are easily washed together, and the color mixing is caused, so that the user experience is poor.
Therefore, how to effectively and accurately judge whether the clothes can be mixed and washed becomes a technical problem which needs to be solved urgently.
Disclosure of Invention
In order to solve the above problems in the prior art, that is, to solve the technical problem that the existing user cannot accurately judge whether the clothes can be shuffled, the application provides a processing method, an apparatus, a device and a storage medium for clothes color identification, so as to improve the accuracy of judgment.
The first aspect of the present application provides a processing method for clothes color identification, comprising:
receiving original image data in a drum sent by a washing machine;
determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data;
adopting an HSV space-based clothes color identification algorithm to perform color identification on the segmented image data to obtain an identification result;
and sending the identification result to the washing machine so that the washing machine performs corresponding processing according to the identification result.
In a preferred technical solution of the above method, determining segmented image data of the laundry by using a pre-trained classification network model according to the original image data includes:
and determining the segmentation image data of the clothes to be washed by adopting a pre-trained two-classification neural network model based on deep learning according to the original image data.
In a preferred technical solution of the above method, the performing color recognition on the segmented image data by using a clothing color recognition algorithm based on HSV space to obtain a recognition result includes:
converting the segmentation image data from an RGB space to an HSV space to obtain converted segmentation image data;
acquiring a clothes color representation range;
and determining the color composition of the clothes to be washed as the identification result based on the converted segmentation image data and the clothes color representation range.
In a preferred embodiment of the above method, after determining the color composition of the laundry based on the converted segmented image data and the pre-obtained laundry color characterization range, the method further comprises:
filtering the color composition of the clothes to be washed to obtain the dominant hue color composition of the clothes to be washed;
and forming the main tone color of the laundry as the identification result.
In a second aspect of the present application, there is provided a method for processing color identification of clothes, including:
collecting original image data in a washing machine barrel;
sending the original image data to a server;
receiving the identification result of the color of the clothes to be washed returned by the server;
determining a corresponding target control program according to the identification result;
and controlling the washing machine to perform corresponding treatment according to the target control program.
In a preferred technical solution of the above method, the determining a corresponding target control program according to the recognition result includes:
and determining a corresponding target control program according to the identification result and a preset control logic rule, wherein the preset control logic rule comprises a corresponding relation between the color and the control program.
In a preferred technical solution of the above method, the determining a corresponding target control program according to the recognition result and a preset control logic rule includes:
if the clothes to be washed are determined to have the color cross risk according to the identification result, determining that the target control program is an alarm prompt program;
the controlling the washing machine to perform corresponding processing according to the target control program comprises the following steps:
and controlling the washing machine to send out an alarm prompt according to the alarm prompt program.
The third aspect of the present application provides a processing apparatus for clothes color recognition, comprising:
the first receiving module is used for receiving original image data in the drum sent by the washing machine;
the first determining module is used for determining the segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data;
the processing module is used for carrying out color recognition on the segmented image data by adopting an HSV space-based clothes color recognition algorithm to obtain a recognition result;
and the first sending module is used for sending the identification result to the washing machine so that the washing machine carries out corresponding processing according to the identification result.
In a preferred technical solution of the above apparatus, the first determining module is specifically configured to:
and determining the segmentation image data of the clothes to be washed by adopting a pre-trained two-classification neural network model based on deep learning according to the original image data.
In a preferred technical solution of the above apparatus, the processing module is specifically configured to:
converting the segmentation image data from an RGB space to an HSV space to obtain converted segmentation image data;
acquiring a clothes color representation range;
and determining the color composition of the clothes to be washed as the identification result based on the converted segmentation image data and the clothes color representation range.
In a preferred embodiment of the foregoing apparatus, the processing module is further configured to:
filtering the color composition of the clothes to be washed to obtain the dominant hue color composition of the clothes to be washed;
and forming the main tone color of the laundry as the identification result.
A fourth aspect of the present application provides a processing apparatus for color recognition of clothes, comprising:
the acquisition module is used for acquiring original image data in the washing machine barrel;
the second sending module is used for sending the original image data to a server;
the second receiving module is used for receiving the identification result of the color of the clothes to be washed returned by the server;
the second determining module is used for determining a corresponding target control program according to the identification result;
and the control module is used for controlling the washing machine to perform corresponding treatment according to the target control program.
In a preferred technical solution of the above apparatus, the second determining module is specifically configured to:
and determining a corresponding target control program according to the identification result and a preset control logic rule, wherein the preset control logic rule comprises a corresponding relation between the color and the control program.
In a preferred technical solution of the above apparatus, the second determining module is specifically configured to:
if the clothes to be washed are determined to have the color cross risk according to the identification result, determining that the target control program is an alarm prompt program;
the control module is specifically configured to:
and controlling the washing machine to send out an alarm prompt according to the alarm prompt program.
A fifth aspect of the present application provides a server comprising: at least one processor and memory;
the memory is configured to store computer-executable instructions for causing the at least one processor to execute the computer-executable instructions to implement the method provided by the first aspect.
A sixth aspect of the present application provides a washing machine comprising: at least one processor and memory;
the memory is configured to store computer-executable instructions for causing the at least one processor to execute the computer-executable instructions to implement the method provided by the second aspect.
A seventh aspect of the present application provides a computer-readable storage medium having stored therein computer-executable instructions for implementing the method provided by the first aspect when executed by a processor.
An eighth aspect of the present application provides a computer-readable storage medium having stored therein computer-executable instructions for implementing the method provided by the second aspect when executed by a processor.
As can be understood by those skilled in the art, the processing method, device, equipment and storage medium for clothes color identification of the present application take original images in a drum by a camera on a washing machine, the washing machine sends original image data to a server, and the server receives the original image data in the drum sent by the washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; the identification result is sent to the washing machine, so that the washing machine carries out corresponding processing according to the identification result, the accuracy of clothes color identification is effectively improved, accurate clothes washing service can be provided for a user, and user experience is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
FIG. 1 is a schematic diagram of an architecture of a processing system according to an embodiment of the present application;
fig. 2 is a schematic flowchart of a processing method for recognizing colors of clothes according to an embodiment of the present application;
fig. 3 is a schematic flowchart of a processing method for clothes color identification according to another embodiment of the present application;
fig. 4 is a schematic flowchart of a processing method for recognizing colors of clothes according to yet another embodiment of the present application;
fig. 5 is a schematic flowchart of a processing method for clothes color identification according to another embodiment of the present application;
fig. 6 is a schematic structural diagram of a processing device for clothes color identification according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a processing device for clothes color identification according to another embodiment of the present application;
fig. 8 is a schematic structural diagram of a server according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of a washing machine according to an embodiment of the present application.
With the above figures, there are shown specific embodiments of the present application, which will be described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all 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.
First, it should be understood by those skilled in the art that these embodiments are merely illustrative of the present application and are not intended to limit the scope of the present application. And can be adjusted as needed by those skilled in the art to suit particular applications.
First, the terms referred to in the present application are explained:
RGB space: based on three basic colors of R (Red), G (Green) and B (Blue), the three basic colors are superposed to different degrees to generate rich and wide colors, so the three basic colors are commonly called as a three-primary-color mode. The color is expressed by a cube with unit length, 8 common colors of black, blue, green, red, purple, yellow and white are respectively positioned at 8 vertexes of the cube, the black is usually positioned at the origin of a three-dimensional rectangular coordinate system, the red, the green and the blue are respectively positioned at 3 coordinate axes, and the whole cube is positioned in the 1 st divination limit. The colors cyan and red, violet (or magenta) and green, and yellow and blue are complementary colors. The value ranges of the parameters are as follows: r: 0 to 255; g: 0 to 255; b: 0-255. The parameter values, also referred to as tristimulus coefficients or primary color coefficients or color values, are divided by 255 and normalized to between 0-1, but are not infinite but rather finite. Since each gray level is defined as 256, the red, green and blue components are combined together to represent 256-2-16777216 different colors. It is much more numerous than the number of colors that the human eye can resolve.
HSV space: this refers to HSV (Hue, Saturation, Value) color space, also known as hexagonal pyramid model space.
The processing method for identifying the clothes color is suitable for automatically identifying the clothes color when a user washes clothes, and selecting a proper washing program according to the clothes color to wash the clothes. Referring to fig. 1, fig. 1 is a schematic diagram illustrating an architecture of a processing system according to an embodiment of the present disclosure. The processing system can comprise a washing machine and a server, and the server can be a cloud server or other servers. The washing machine can be a drum washing machine, and can also be other types of washing machines, taking the drum washing machine as an example, the server and the washing machine can be provided with corresponding processing devices for identifying clothes colors. A camera can be arranged above a door and a window of the washing machine, for example, a mini camera is arranged for shooting images of an object scene in the drum, and clear and analyzable images can be shot by means of light supplement of the lamp light in the drum. After the camera takes a scene image (i.e. an original image) of the object in the tube, the original image data can be transmitted to the server through network transmission. Or the processing device for clothes color identification of the washing machine acquires the original image data shot by the camera, transmits the original image data to the server through network transmission, and the processing device for clothes color identification on the server can acquire the original image data. After receiving the original image data, the server determines the segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data, wherein the segmented image data are image data which are segmented from the original image data and only comprise the image part of the clothes to be washed; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; and sending the identification result to the washing machine, and controlling the washing machine to perform corresponding processing according to the identification result and the preset control logic after the washing machine receives the identification result. The clothes to be washed and the background are accurately segmented through the neural network model, color recognition is carried out on segmented image data through a clothes color recognition algorithm based on the HSV space, accuracy of clothes color recognition is effectively improved, accurate washing service can be provided for users, and user experience is improved.
Furthermore, it should be noted that the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. In the description of the following examples, "plurality" means two or more unless specifically limited otherwise.
The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present invention will be described below with reference to the accompanying drawings.
An embodiment of the present application provides a processing method for identifying colors of clothes, which is used for identifying colors of clothes to be washed in a washing machine barrel. The implementation subject of the embodiment is a processing device for clothes color identification, and the device can be arranged in a server.
Referring to fig. 2, fig. 2 is a schematic flow chart of a processing method for recognizing colors of clothes according to the present embodiment, the method includes:
Specifically, a camera, such as a mini camera, may be installed above the door and window of the washing machine, and is used for capturing a scene image (i.e., an original image) of the clothes in the tub, obtaining original image data in the tub of the washing machine, and sending the original image data to the server through the washing machine.
Optionally, the user may open the door and window of the washing machine, put in clothes, and trigger the washing machine camera to shoot the scene image of the clothes in the drum when closing the door and window, or may trigger when the user closes the door and window and starts the washing machine, which may be specifically set according to actual requirements, and this embodiment is not limited.
And step 102, determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data.
Specifically, the original training image data in the cylinder can be collected in advance and labeled to obtain label data corresponding to the original training image data; and establishing a classification neural network, training the established classification neural network based on the original training image data and the corresponding label data, and obtaining a classification network model.
After the original image data is received, the segmentation image data of the clothes to be washed can be determined by adopting a classification network model trained in advance according to the original image data. The segmented image data is image data which is segmented from the original image data and only comprises the image part of the clothes to be washed, namely, the clothes and the background in the original image data are segmented through a classification network model, and the segmented image data which belongs to the background part, the clothes part and the clothes part in the original image data are obtained and are used as the segmented image data of the clothes to be washed.
Optionally, the classification network model is a deep learning-based two-classification neural network model, which gives consideration to the processing rate and accuracy, and divides the original image into two types, namely clothing and background. The network architecture of the classification network model can comprise a cascade network, the cascade network is divided into four layers, each layer can carry out convolution downsampling with different degrees on an original object (namely original image data) to extract semantic features, output feature maps of all layers can be finally fused into a feature map, then a target feature map is obtained by extracting detailed features through an upsampling layer, and finally conventional semantic segmentation is carried out on the obtained target feature map to obtain a final segmented image.
And 103, carrying out color identification on the segmented image data by adopting an HSV space-based clothes color identification algorithm to obtain an identification result.
Specifically, after the segmented image data of the laundry is determined, the color recognition of the segmented image data can be performed by adopting a HSV space-based laundry color recognition algorithm to obtain a recognition result.
The recognition result includes a color composition of the laundry, such as 80% red and 20% white.
Alternatively, the HSV space-based clothing color recognition algorithm is an algorithm for converting the divided image data from the RGB space to the HSV space for color recognition. Specifically, converting the segmentation image data from an RGB space to an HSV space, and obtaining converted segmentation image data; acquiring a clothes color representation range; and determining the color composition of the clothes to be washed as a recognition result based on the converted segmentation image data and the clothes color representation range. The clothing color characterization range comprises different ranges representing different colors, and is determined by combining HSV hexagonal pyramids and a large number of clothing color characterization implementations with different colors. For example, by combining HSV hexagonal pyramids and 1000 clothes color characterization implementations with different colors, an HSV characterization range of 10 common colors is determined. For example, the black characterized range is:
(h>＝0&&h<＝360)&&(s>＝0&&s<＝100)&&(v>＝0&&v<＝25)
wherein h, s, v represent the values of the three channels, respectively.
And 104, sending the identification result to the washing machine so that the washing machine performs corresponding processing according to the identification result.
Specifically, after obtaining the recognition result of the color of the laundry, the recognition result is transmitted to the washing machine. After the washing machine receives the identification result of the color of the clothes to be washed, the corresponding target control program can be determined according to the identification result, and the washing machine is controlled to carry out corresponding treatment according to the target control program.
Illustratively, if the identification result is red and white, and the color composition ratio is greater than a first threshold value, it is determined that the cross color risk exists, it is determined that the target control program is a program which does not start the washing machine and gives an alarm, it is controlled not to start the washing machine according to the target control program, and the washing machine is controlled to give an alarm. The specific alarm prompting mode can be set according to actual requirements, for example, the alarm prompting can be performed through voice broadcasting, corresponding alarm information can be displayed on a display interface of the washing machine, an alarm prompting sound is sent, and the like.
For example, if the recognition result is white and greater than the second threshold, it is determined that the corresponding target control program is the color protection washing program, and the color protection washing program may be selected to control the washing machine to perform the color protection washing process.
For example, if the recognition results are black and blue, and the corresponding target control program is determined to be the mixed washing program, the mixed washing program may be selected to control the washing machine to perform the mixed washing process.
Alternatively, a preset control logic rule may be preset in the washing machine, and may include a correspondence between the color and the control program, and after the washing machine receives the recognition result, the target control program is determined according to the recognition result and the preset control logic rule.
In the processing method for clothes color identification provided by the embodiment, a camera on a washing machine is used for shooting an original image in a drum, the washing machine sends original image data to a server, and the server receives the original image data in the drum sent by the washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; the identification result is sent to the washing machine, so that the washing machine carries out corresponding processing according to the identification result, the accuracy of clothes color identification is effectively improved, accurate clothes washing service can be provided for a user, and user experience is improved.
The method provided by the above embodiment is further described in an additional embodiment of the present application.
Referring to fig. 3, fig. 3 is a schematic flow chart of the processing method for recognizing the color of the clothes according to the embodiment.
As a practical way, on the basis of the above embodiment, optionally, determining the segmented image data of the laundry according to the original image data by using a classification network model trained in advance includes:
Specifically, the classification network model is a two-classification neural network model based on deep learning, gives consideration to the processing speed and accuracy, and divides the original image into two types of clothes and background. The network architecture of the classification network model can comprise a cascade network, the cascade network is divided into four layers, each layer can carry out convolution downsampling with different degrees on an original object (namely original image data) to extract semantic features, output feature maps of all layers can be finally fused into a feature map, then a target feature map is obtained by extracting detailed features through an upsampling layer, and finally conventional semantic segmentation is carried out on the obtained target feature map to obtain a final segmented image.
Before the classification network model is adopted, the classification network model needs to be obtained through training data. Specifically, the original training image data in the cylinder can be collected in advance and labeled to obtain label data corresponding to the original training image data; and establishing a classification neural network, training the established classification neural network based on the original training image data and the corresponding label data, and obtaining a classification network model.
Illustratively, a large number of clothes images can be shot by means of supplementary lighting, original training image data and corresponding label data are obtained through cleaning (images with unclear color information and excessive environmental interference noise are cleaned) and labeling, a pre-established two-class neural network based on deep learning is trained on the basis of the original training image data and the corresponding label data, and a two-class neural network model based on deep learning is obtained.
As another practicable manner, on the basis of the foregoing embodiment, optionally, performing color recognition on the segmentation image data by using an HSV space-based clothing color recognition algorithm to obtain a recognition result, where the method includes:
and step 1031, converting the segmentation image data from the RGB space to the HSV space, and obtaining the converted segmentation image data.
And 1033, determining the color composition of the clothes to be washed based on the converted segmented image data and the clothes color representation range.
Step 1034, the color composition of the laundry is taken as the recognition result.
Specifically, after obtaining the segmentation image data of the clothes to be washed, converting the segmentation image data from an RGB space to an HSV space, and obtaining the converted segmentation image data; acquiring a clothes color representation range; and determining the color composition of the clothes to be washed as a recognition result based on the converted segmentation image data and the clothes color representation range. The clothing color characterization range comprises different ranges representing different colors, and can be specifically combined with HSV hexagonal pyramids and a large number of clothing color characterization implementations with different colors to determine the clothing color characterization range. For example, by combining HSV hexagonal pyramids and 1000 clothes color characterization implementations with different colors, an HSV characterization range of 10 common colors is determined. For example, the black characterized range is:
(h>＝0&&h<＝360)&&(s>＝0&&s<＝100)&&(v>＝0&&v<＝25)
wherein h, s, v represent the values of the three channels, respectively.
Optionally, after determining the color composition of the laundry based on the converted segmented image data and the laundry color characterization range, the method further includes:
In step 1036, the dominant hue color composition of the laundry is used as the recognition result.
Specifically, after determining the color composition of the laundry based on the converted segmented image data and the laundry color characterization range, the color composition that may be obtained includes a very small proportion of other colors, the color composition of the laundry may be filtered to obtain the keytone color composition of the laundry, and the keytone color composition of the laundry is sent to the washing machine as the recognition result.
The processing method for clothes color identification provided by the embodiment of the application realizes automatic identification of clothes color, effectively improves the accuracy of color identification by combining a deep learning binary neural network model and an HSV-based space color identification algorithm, saves a link that a user judges the clothes color by experience, manually selects a washing mode, liberates both hands of the user, improves the convenience of a washing link, and solves the problem that the user judges the clothes color by experience and does not select the washing mode accurately enough.
It should be noted that the respective implementable modes in the present embodiment may be implemented individually, or may be implemented in combination in any combination without conflict, and the present application is not limited thereto.
In the processing method for clothes color identification provided by the embodiment, a camera on a washing machine is used for shooting an original image in a drum, the washing machine sends original image data to a server, and the server receives the original image data in the drum sent by the washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; the identification result is sent to the washing machine, so that the washing machine carries out corresponding processing according to the identification result, the accuracy of clothes color identification is effectively improved, accurate clothes washing service can be provided for a user, and user experience is improved.
In another embodiment of the present application, a processing method for identifying colors of laundry in a washing machine drum is provided. The implementation subject of the embodiment is a processing device for clothes color identification, which can be arranged in a washing machine.
Referring to fig. 4, fig. 4 is a schematic flow chart of a processing method for recognizing colors of clothes according to the present embodiment, where the method includes:
And step 303, receiving the color identification result of the clothes to be washed returned by the server.
And step 304, determining a corresponding target control program according to the identification result.
And 305, controlling the washing machine to perform corresponding processing according to the target control program.
It should be noted that, this embodiment is an embodiment of a method at a washing machine end interacting with the embodiment at the server end, and a specific execution process thereof has been described in detail in the interaction description of the embodiment, and all parts executed by the washing machine side related to the embodiment may be used to explain the steps of this embodiment, and are not described again here.
In the processing method for clothes color identification provided by the embodiment, a camera on a washing machine is used for shooting an original image in a drum, the washing machine sends original image data to a server, and the server receives the original image data in the drum sent by the washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; the identification result is sent to the washing machine, so that the washing machine carries out corresponding processing according to the identification result, the accuracy of clothes color identification is effectively improved, accurate clothes washing service can be provided for a user, and user experience is improved.
The present application further provides a supplementary description of the method provided in the above embodiments.
Referring to fig. 5, fig. 5 is a schematic flow chart of the processing method for identifying the color of the clothes according to the embodiment.
As a practical manner, on the basis of the foregoing embodiment, optionally, determining a corresponding target control program according to the recognition result includes:
step 3041, determining a corresponding target control program according to the recognition result and the preset control logic rule.
The preset control logic rule comprises a corresponding relation between colors and control programs.
As another implementable manner, on the basis of the foregoing embodiment, optionally, determining the corresponding target control program according to the recognition result and the preset control logic rule includes:
Correspondingly, the washing machine is controlled to perform corresponding treatment according to the target control program, and the treatment comprises the following steps:
Optionally, if the identification result is red and white, and the color composition ratio is greater than the first threshold, it is determined that there is a cross color risk, it is determined that the target control program is a program that does not start the washing machine and gives an alarm, and the washing machine is controlled not to start according to the target control program and gives an alarm. The specific alarm prompting mode can be set according to actual requirements, for example, the alarm prompting can be performed through voice broadcasting, corresponding alarm information can be displayed on a display interface of the washing machine, an alarm prompting sound is sent, and the like.
Alternatively, if the recognition result is white and greater than the second threshold, it is determined that the corresponding target control program is the color protection washing program, and the color protection washing program may be selected to control the washing machine to perform the color protection washing process.
Alternatively, if the recognition results are black and blue, the corresponding target control program is determined to be a mixed washing program, and the mixed washing program may be selected to control the washing machine to perform the mixed washing process.
It should be noted that, this embodiment is an embodiment of a method at a washing machine end interacting with the embodiment at the server end, and a specific execution process thereof has been described in detail in the interaction description of the embodiment, and all parts executed by the washing machine side related to the embodiment may be used to explain the steps of this embodiment, and are not described again here.
It should be noted that the respective implementable modes in the embodiment may be implemented individually, or may be implemented in combination in any combination without conflict, and the present application is not limited thereto.
In the processing method for clothes color identification provided by the embodiment, a camera on a washing machine is used for shooting an original image in a drum, the washing machine sends original image data to a server, and the server receives the original image data in the drum sent by the washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; the identification result is sent to the washing machine, so that the washing machine carries out corresponding processing according to the identification result, the accuracy of clothes color identification is effectively improved, accurate clothes washing service can be provided for a user, and user experience is improved.
Still another embodiment of the present application provides a processing apparatus for identifying colors of clothes, which is used for executing the method provided by the server-side embodiment.
Referring to fig. 6, fig. 6 is a schematic structural diagram of the processing device for identifying colors of clothes according to the embodiment. The processing device 50 for clothes color identification includes a first receiving module 51, a first determining module 52, a processing module 53 and a first transmitting module 54.
The first receiving module is used for receiving original image data in the drum sent by the washing machine; the first determining module is used for determining the segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; the processing module is used for carrying out color recognition on the segmentation image data by adopting an HSV space-based clothes color recognition algorithm to obtain a recognition result; and the first sending module is used for sending the identification result to the washing machine so that the washing machine carries out corresponding processing according to the identification result.
The specific manner in which the respective modules perform operations has been described in detail in relation to the apparatus in this embodiment, and will not be elaborated upon here.
According to the processing device for clothes color identification provided by the embodiment, the original image in the drum is shot by the camera on the washing machine, the washing machine sends original image data to the server, and the server receives the original image data in the drum sent by the washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; the identification result is sent to the washing machine, so that the washing machine carries out corresponding processing according to the identification result, the accuracy of clothes color identification is effectively improved, accurate clothes washing service can be provided for a user, and user experience is improved.
The present application further provides a supplementary description of the apparatus provided in the above embodiments.
As a practical manner, on the basis of the foregoing embodiment, optionally, the first determining module is specifically configured to:
and determining the segmentation image data of the clothes to be washed by adopting a pre-trained two-classification neural network model based on deep learning according to the original image data.
As another implementable manner, on the basis of the foregoing embodiment, optionally, the processing module is specifically configured to:
converting the segmentation image data from an RGB space to an HSV space to obtain converted segmentation image data; acquiring a clothes color representation range; and determining the color composition of the clothes to be washed as a recognition result based on the converted segmentation image data and the clothes color representation range.
Optionally, the processing module is further configured to:
filtering the color composition of the clothes to be washed to obtain the dominant hue color composition of the clothes to be washed; and forming the main tone color of the clothes to be washed as a recognition result.
The specific manner in which the respective modules perform operations has been described in detail in relation to the apparatus in this embodiment, and will not be elaborated upon here.
It should be noted that the respective implementable modes in the present embodiment may be implemented individually, or may be implemented in combination in any combination without conflict, and the present application is not limited thereto.
According to the processing device for clothes color identification provided by the embodiment, the original image in the drum is shot by the camera on the washing machine, the washing machine sends original image data to the server, and the server receives the original image data in the drum sent by the washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; the identification result is sent to the washing machine, so that the washing machine carries out corresponding processing according to the identification result, the accuracy of clothes color identification is effectively improved, accurate clothes washing service can be provided for a user, and user experience is improved.
In another embodiment of the present application, a processing device for identifying colors of clothes is provided, which is used for executing the method provided by the above-mentioned washing machine end embodiment.
Referring to fig. 7, fig. 7 is a schematic structural diagram of the processing device for identifying colors of clothes according to the embodiment. The processing device 70 for clothes color identification comprises an acquisition module 71, a second sending module 72, a second receiving module 73, a second determining module 74 and a control module 75.
The washing machine comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring original image data in a washing machine barrel; the second sending module is used for sending the original image data to the server; the second receiving module is used for receiving the identification result of the color of the clothes to be washed returned by the server; the second determining module is used for determining a corresponding target control program according to the recognition result; and the control module is used for controlling the washing machine to perform corresponding treatment according to the target control program.
The specific manner in which the respective modules perform operations has been described in detail in relation to the apparatus in this embodiment, and will not be elaborated upon here.
According to the processing device for clothes color identification provided by the embodiment, the original image in the drum is shot by the camera on the washing machine, the washing machine sends original image data to the server, and the server receives the original image data in the drum sent by the washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; the identification result is sent to the washing machine, so that the washing machine carries out corresponding processing according to the identification result, the accuracy of clothes color identification is effectively improved, accurate clothes washing service can be provided for a user, and user experience is improved.
The present application further provides a supplementary description of the apparatus provided in the above embodiments.
As an implementable manner, on the basis of the foregoing embodiment, optionally, the second determining module is specifically configured to:
and determining a corresponding target control program according to the identification result and a preset control logic rule, wherein the preset control logic rule comprises a corresponding relation between the color and the control program.
As another implementable manner, on the basis of the foregoing embodiment, optionally, the second determining module is specifically configured to:
if the clothes to be washed are determined to have the color cross risk according to the identification result, determining the target control program as an alarm prompt program; the control module is specifically configured to:
and controlling the washing machine to send out an alarm prompt according to the alarm prompt program.
The specific manner in which the respective modules perform operations has been described in detail in relation to the apparatus in this embodiment, and will not be elaborated upon here.
It should be noted that the respective implementable modes in the present embodiment may be implemented individually, or may be implemented in combination in any combination without conflict, and the present application is not limited thereto.
According to the processing device for clothes color identification provided by the embodiment, the original image in the drum is shot by the camera on the washing machine, the washing machine sends original image data to the server, and the server receives the original image data in the drum sent by the washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; the identification result is sent to the washing machine, so that the washing machine carries out corresponding processing according to the identification result, the accuracy of clothes color identification is effectively improved, accurate clothes washing service can be provided for a user, and user experience is improved.
Yet another embodiment of the present application provides a server, configured to execute the method provided in the server-side embodiment.
Referring to fig. 8, fig. 8 is a schematic structural diagram of the server provided in this embodiment. The server 80 includes: at least one processor 81 and memory 82;
the memory is used for storing computer-executable instructions to cause the at least one processor to execute the computer-executable instructions to implement the methods provided by the above-described embodiments.
According to the server of the embodiment, the original image in the drum is shot through the camera on the washing machine, the washing machine sends original image data to the server, and the server receives the original image data in the drum sent by the washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; the identification result is sent to the washing machine, so that the washing machine carries out corresponding processing according to the identification result, the accuracy of clothes color identification is effectively improved, accurate clothes washing service can be provided for a user, and user experience is improved.
In another embodiment, the present application provides a washing machine for performing the method provided by the above-mentioned washing machine end embodiment.
Referring to fig. 9, fig. 9 is a schematic structural diagram of the washing machine provided in this embodiment. The washing machine 90 includes: at least one processor 91 and memory 92;
the memory is configured to store computer-executable instructions for causing the at least one processor to execute the computer-executable instructions to implement the methods provided by the above-described washing machine-side embodiments.
Optionally, the washing machine may further include a display interface.
Optionally, the washing machine may further include a voice announcement device.
According to the washing machine of the embodiment, the original image in the drum is shot through the camera on the washing machine, the washing machine sends original image data to the server, and the server receives the original image data in the drum sent by the washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; the identification result is sent to the washing machine, so that the washing machine carries out corresponding processing according to the identification result, the accuracy of clothes color identification is effectively improved, accurate clothes washing service can be provided for a user, and user experience is improved.
Yet another embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, the computer-executable instructions are used to implement the method performed by the server side provided in any of the above embodiments.
According to the computer-readable storage medium of the embodiment, the original image in the drum is shot by the camera on the washing machine, the washing machine sends original image data to the server, and the server receives the original image data in the drum sent by the washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; the identification result is sent to the washing machine, so that the washing machine carries out corresponding processing according to the identification result, the accuracy of clothes color identification is effectively improved, accurate clothes washing service can be provided for a user, and user experience is improved.
Yet another embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored, and the computer-executable instructions are executed by a processor to implement the method provided by any of the foregoing embodiments.
According to the computer-readable storage medium of the embodiment, the original image in the drum is shot by the camera on the washing machine, the washing machine sends original image data to the server, and the server receives the original image data in the drum sent by the washing machine; determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data; adopting a clothing color recognition algorithm based on HSV space to perform color recognition on the segmented image data to obtain a recognition result; the identification result is sent to the washing machine, so that the washing machine carries out corresponding processing according to the identification result, the accuracy of clothes color identification is effectively improved, accurate clothes washing service can be provided for a user, and user experience is improved.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
It is obvious to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to perform all or part of the above described functions. For the specific working process of the device described above, reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. A processing method for clothes color identification is characterized by comprising the following steps:
receiving original image data in a drum sent by a washing machine;
determining segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data;
adopting an HSV space-based clothes color identification algorithm to perform color identification on the segmented image data to obtain an identification result;
and sending the identification result to the washing machine so that the washing machine performs corresponding processing according to the identification result.
2. The method according to claim 1, wherein determining segmented image data of the laundry using a pre-trained classification network model based on the raw image data comprises:
and determining the segmentation image data of the clothes to be washed by adopting a pre-trained two-classification neural network model based on deep learning according to the original image data.
3. The method according to claim 1, wherein the performing color recognition on the segmented image data by using an HSV space-based clothing color recognition algorithm to obtain a recognition result comprises:
converting the segmentation image data from an RGB space to an HSV space to obtain converted segmentation image data;
acquiring a clothes color representation range;
and determining the color composition of the clothes to be washed as the identification result based on the converted segmentation image data and the clothes color representation range.
4. The method according to claim 3, wherein after determining the color composition of the laundry based on the converted divided image data and the previously obtained laundry color characterization range, the method further comprises:
filtering the color composition of the clothes to be washed to obtain the dominant hue color composition of the clothes to be washed;
and forming the main tone color of the laundry as the identification result.
5. A processing method for clothes color identification is characterized by comprising the following steps:
collecting original image data in a washing machine barrel;
sending the original image data to a server;
receiving the identification result of the color of the clothes to be washed returned by the server;
determining a corresponding target control program according to the identification result;
and controlling the washing machine to perform corresponding treatment according to the target control program.
6. The method of claim 5, wherein determining the corresponding target control program according to the recognition result comprises:
and determining a corresponding target control program according to the identification result and a preset control logic rule, wherein the preset control logic rule comprises a corresponding relation between the color and the control program.
7. The method of claim 5, wherein determining the corresponding target control program according to the recognition result and a preset control logic rule comprises:
if the clothes to be washed are determined to have the color cross risk according to the identification result, determining that the target control program is an alarm prompt program;
the controlling the washing machine to perform corresponding processing according to the target control program comprises the following steps:
and controlling the washing machine to send out an alarm prompt according to the alarm prompt program.
8. A processing device for clothes color identification is characterized by comprising:
the first receiving module is used for receiving original image data in the drum sent by the washing machine;
the first determining module is used for determining the segmented image data of the clothes to be washed by adopting a pre-trained classification network model according to the original image data;
the processing module is used for carrying out color recognition on the segmented image data by adopting an HSV space-based clothes color recognition algorithm to obtain a recognition result;
and the first sending module is used for sending the identification result to the washing machine so that the washing machine carries out corresponding processing according to the identification result.
9. A server, comprising: at least one processor and memory;
the memory is to store computer-executable instructions to cause the at least one processor to execute the computer-executable instructions to implement the method of any one of claims 1-4.
10. A washing machine, characterized by comprising: at least one processor and memory;
the memory is to store computer-executable instructions to cause the at least one processor to execute the computer-executable instructions to implement the method of any one of claims 5-7.
Priority Applications (2)
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| CN201911152484.0A CN112836706A (en) | 2019-11-22 | 2019-11-22 | Processing method, device and equipment for clothes color identification and storage medium |
| PCT/CN2020/125427 WO2021098486A1 (en) | 2019-11-22 | 2020-10-30 | Garment color recognition processing method, device, apparatus, and storage medium |
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| CN201911152484.0A CN112836706A (en) | 2019-11-22 | 2019-11-22 | Processing method, device and equipment for clothes color identification and storage medium |
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