CN117689920A - Garment steamer ironing method and device, garment steamer, storage medium and electronic device - Google Patents
Garment steamer ironing method and device, garment steamer, storage medium and electronic device Download PDFInfo
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- CN117689920A CN117689920A CN202211049158.9A CN202211049158A CN117689920A CN 117689920 A CN117689920 A CN 117689920A CN 202211049158 A CN202211049158 A CN 202211049158A CN 117689920 A CN117689920 A CN 117689920A
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- 238000010409 ironing Methods 0.000 title claims abstract description 356
- 238000000034 method Methods 0.000 title claims abstract description 77
- 238000003860 storage Methods 0.000 title claims abstract description 17
- 238000005406 washing Methods 0.000 claims abstract description 171
- 238000012423 maintenance Methods 0.000 claims abstract description 75
- 238000001514 detection method Methods 0.000 claims abstract description 49
- 238000012549 training Methods 0.000 claims abstract description 49
- 238000013507 mapping Methods 0.000 claims description 23
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- 230000002441 reversible effect Effects 0.000 claims description 6
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- 238000004891 communication Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000004061 bleaching Methods 0.000 description 3
- 238000005108 dry cleaning Methods 0.000 description 3
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
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Classifications
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- D—TEXTILES; PAPER
- D06—TREATMENT OF TEXTILES OR THE LIKE; LAUNDERING; FLEXIBLE MATERIALS NOT OTHERWISE PROVIDED FOR
- D06F—LAUNDERING, DRYING, IRONING, PRESSING OR FOLDING TEXTILE ARTICLES
- D06F73/00—Apparatus for smoothing or removing creases from garments or other textile articles by formers, cores, stretchers, or internal frames, with the application of heat or steam
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0464—Convolutional networks [CNN, ConvNet]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
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- G06V30/413—Classification of content, e.g. text, photographs or tables
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/40—Document-oriented image-based pattern recognition
- G06V30/42—Document-oriented image-based pattern recognition based on the type of document
Abstract
The application discloses a garment steamer ironing method, a garment steamer ironing device, a storage medium and an electronic device, and relates to the technical field of intelligent home/smart home, wherein the garment steamer ironing method comprises the following steps: carrying out image recognition on the washing label image, and carrying out target detection based on an image recognition result; when the clothes maintenance implementation type is determined to be the ironing type, carrying out ironing information identification on the washing label image, and obtaining one or more corresponding ironing parameter identification modes according to ironing information identification results so as to obtain ironing parameters of the garment steamer through the ironing parameter identification modes; based on the ironing parameters, generating an ironing mode corresponding to the garment steamer, and controlling the garment steamer according to the ironing mode. The problem that the target detection model is poor in recognition effect due to the fact that training samples are too few is avoided, and recognition accuracy of ironing information in washing mark images is improved.
Description
Technical Field
The application relates to the technical field of intelligent home, in particular to a garment steamer ironing method and device, a garment steamer, a storage medium and an electronic device.
Background
With the development of smart home, the target detection technology applied to the garment steamer is more and more. The method for detecting the washing ironing target of the garment steamer mainly comprises the steps of marking the frame and the category of washing ironing target training data, training the model through a target detection method in deep learning, such as ResNet, resNext, resNest and the like, so that the position and the category information of a washing label frame in a picture can be detected, and then the current ironing parameters of the garment steamer can be determined according to the type information.
Due to the algorithm property of deep learning, each washing mark class is required to at least reach thousands of labeling data, and the quantity among the classes is relatively balanced. However, in the actual training data acquisition process, statistics show that the quantity distribution difference among all classes of the washing label is extremely large, the high-frequency class can reach thousands of classes, but most class labels do not exceed hundreds of labels, the long tail effect is serious, and therefore the target detection algorithm finally applied to the garment steamer cannot accurately identify ironing information.
Accordingly, there is a need for a garment steamer ironing method, device, garment steamer, storage medium and electronic apparatus that solve the above problems.
Disclosure of Invention
The application provides a garment steamer ironing method, device, garment steamer, storage medium and electronic device for solve among the prior art low frequency iron mark quantity very few and unbalanced, lead to ironing icon discernment accuracy lower defect, realize with setting up multiple testing process, carry out target detection and discernment to ironing icon, thereby improve the discernment rate of accuracy of ironing icon in the washing mark image, generate more accurate ironing parameter for garment steamer.
The application provides a garment steamer ironing method, which comprises the following steps:
carrying out image recognition on the washing label image, and carrying out target detection based on an image recognition result;
when the clothes maintenance implementation type is determined to be the ironing type, carrying out ironing information identification on the washing label image, and obtaining one or more corresponding ironing parameter identification modes according to ironing information identification results so as to obtain ironing parameters of the garment steamer through the ironing parameter identification modes;
based on the ironing parameters, generating an ironing mode corresponding to the garment steamer, and controlling the garment steamer according to the ironing mode.
According to the ironing method of the garment steamer, the method further comprises the following steps:
When the clothes maintenance implementation type is determined to be a non-ironing type, carrying out shape recognition on the washing marks in the washing mark image, and determining whether the washing marks in the washing mark image are non-ironing icons according to a shape recognition result;
if the washing label is not the non-ironing icon, determining the non-executable information of the clothes maintenance corresponding to the washing label according to the shape recognition result of the washing label, and displaying the non-executable information of the clothes maintenance through the garment steamer, wherein the non-executable information of the clothes maintenance comprises one or more of non-washable, non-bleachable and non-reversible drying.
According to the ironing method of the garment steamer provided by the application, according to the shape recognition result, whether the wash mark in the wash mark image is a non-ironing icon is determined, and the ironing method comprises the following steps:
and if the washing mark image does not comprise any preset washing mark shape, determining the washing mark in the washing mark image as an ironing-impossible icon, wherein the preset washing mark shape comprises one or a combination of a plurality of circles, triangles and rectangles.
According to the ironing method of the garment steamer, the image recognition is carried out on the washing label image, and the ironing method comprises the following steps:
Acquiring a washing label image of the target clothes;
and inputting the washing label image into a first identification model to identify a clothes maintenance mode, and obtaining a clothes maintenance implementation type output by the first identification model, wherein the first identification model is obtained by training a sample washing label image marked with a clothes maintenance implementation type label.
According to the ironing method of the garment steamer, the first recognition model is obtained through training of the following steps:
acquiring a plurality of sample washing mark images;
marking corresponding clothes maintenance implementation type labels for the sample washing label images, and constructing a training sample set, wherein the clothes maintenance implementation type labels at least comprise ironing labels and non-ironing labels;
and training the convolutional neural network through the training sample set to obtain the first recognition model.
According to the ironing method of the garment steamer provided by the application, when the garment maintenance implementation type is determined to be the ironing type, the washing label image is subjected to ironing information identification, and one or more corresponding ironing parameter identification modes are obtained according to ironing information identification results, so that ironing parameters of the garment steamer are obtained through the ironing parameter identification modes, and the ironing method comprises the following steps:
When the clothes maintenance implementation type is determined to be an ironing type, carrying out character information identification on the washing mark image, and obtaining a corresponding washing mark character content identification result;
if the character content identification result of the washing label does not contain any character information, inputting the washing label image into a second identification model for ironing information identification to obtain ironing icon information output by the second identification model, wherein the second identification model is obtained by training a sample washing label image marked with ironing icon labels;
and generating ironing parameters of the garment steamer according to the ironing icon information.
According to the ironing method of the garment steamer, the method further comprises the following steps:
and if the character content identification result of the washing label contains character information, carrying out category mapping on the character content identification result of the washing label and a preset ironing rule to obtain ironing parameters of the garment steamer.
According to the ironing method of the garment steamer, the method further comprises the following steps:
under the condition that the character content identification result of the washing label contains character information, carrying out category mapping on the character content identification result of the washing label and a preset ironing rule, and inputting the washing label image into a second identification model for ironing information identification;
And based on the category mapping result and the ironing icon information, obtaining ironing parameters of the garment steamer.
According to the ironing method of the garment steamer provided by the application, after the image recognition is carried out on the washing label image and the target detection is carried out based on the image recognition result, the method further comprises the following steps:
and carrying out image cutting processing on the region range corresponding to the washing mark in the washing mark image to obtain a target image, so as to carry out ironing information identification or shape identification on the target image.
The application also provides a garment steamer ironing device, comprising:
the clothes maintenance implementation type detection module is used for carrying out image recognition on the washing mark image and carrying out target detection based on an image recognition result;
the ironing information detection module is used for carrying out ironing information identification on the washing label image when the clothes maintenance implementation type is determined to be the ironing type, and obtaining one or more corresponding ironing parameter identification modes according to ironing information identification results so as to obtain ironing parameters of the garment steamer through the ironing parameter identification modes;
and the control module is used for generating an ironing mode corresponding to the garment steamer based on the ironing parameters and controlling the garment steamer according to the ironing mode.
The present application also provides a computer readable storage medium comprising a stored program, wherein the program when run performs a garment steamer ironing method as described in any one of the above.
The present application also provides an electronic device comprising a memory and a processor, the memory having stored therein a computer program, the processor being arranged to implement a garment steamer ironing method as described in any one of the above by execution of the computer program.
According to the garment steamer ironing method, device, garment steamer, storage medium and electronic device, firstly, the garment maintenance mode is identified on the washing label image, when the garment maintenance implementation type is determined to be the ironing type, ironing information identification is conducted on the washing label image, ironing parameters for controlling the garment steamer are generated according to ironing information identification results, compared with the prior art, the problem that the identification effect is poor due to the fact that the target detection model is too few in training samples is avoided through multi-stage detection identification on the washing label image, and the identification accuracy of ironing information in the washing label image is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic diagram of a hardware environment of an interaction method of a smart device according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a garment steamer ironing method provided in the present application;
fig. 3 is a schematic structural view of an ironing device of the garment steamer provided by the application;
fig. 4 is a schematic structural diagram of an electronic device provided in the present application.
Detailed Description
In order to make the present application solution better understood by those skilled in the art, the following description will be made in detail and with reference to the accompanying drawings in the embodiments of the present application, it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like herein are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to one aspect of the embodiments of the present application, a garment steamer ironing method is provided. The garment steamer ironing method is widely applied to full-house intelligent digital control application scenes such as intelligent Home (Smart Home), intelligent Home equipment ecology, intelligent Home (Intelligence House) ecology and the like. Alternatively, in the present embodiment, the garment steamer ironing method described above may be applied to a hardware environment constituted by the terminal device 102 and the server 104 as shown in fig. 1. As shown in fig. 1, the server 104 is connected to the terminal device 102 through a network, and may be used to provide services (such as application services and the like) for a terminal or a client installed on the terminal, a database may be set on the server or independent of the server, for providing data storage services for the server 104, and cloud computing and/or edge computing services may be configured on the server or independent of the server, for providing data computing services for the server 104.
The network may include, but is not limited to, at least one of: wired network, wireless network. The wired network may include, but is not limited to, at least one of: a wide area network, a metropolitan area network, a local area network, and the wireless network may include, but is not limited to, at least one of: WIFI (Wireless Fidelity ), bluetooth. The terminal device 102 may not be limited to a PC, a mobile phone, a tablet computer, an intelligent air conditioner, an intelligent smoke machine, an intelligent refrigerator, an intelligent oven, an intelligent cooking range, an intelligent washing machine, an intelligent water heater, an intelligent washing device, an intelligent dish washer, an intelligent projection device, an intelligent television, an intelligent clothes hanger, an intelligent curtain, an intelligent video, an intelligent socket, an intelligent sound box, an intelligent fresh air device, an intelligent kitchen and toilet device, an intelligent bathroom device, an intelligent sweeping robot, an intelligent window cleaning robot, an intelligent mopping robot, an intelligent air purifying device, an intelligent steam box, an intelligent microwave oven, an intelligent kitchen appliance, an intelligent purifier, an intelligent water dispenser, an intelligent door lock, and the like.
In the existing washing label ironing information identification model, the quantity difference among collected washing label ironing training data categories is extremely large, so that the identification model has extremely poor low-frequency quantity category identification effect; in addition, in the training process of some recognition models, as the washing marks of other types except the ironing marks are not marked, the recognition models are similar to the non-ironing marks, including non-dry cleaning, non-bleaching, non-turnover drying and the like, and when the recognition models are used for recognizing the recognition models, the recognition models are easily mistakenly recognized as the non-ironing marks, namely the models easily mistakenly recognize similar non-executable types as the non-ironing types.
Fig. 2 is a schematic flow chart of an ironing method of a garment steamer, as shown in fig. 2, provided in the present application, including:
and step 101, carrying out image recognition on the washing label image, and carrying out target detection based on the image recognition result.
In this application, at first the washing mark image of target clothing is obtained through the camera that sets up on the garment steamer, or user's mobile terminal (e.g. cell-phone and panel computer), and then carries out preliminary discernment to the washing mark image of gathering, carries out clothing maintenance mode discernment promptly. In an embodiment, the washing label image can be identified by a target identification model (i.e., a first identification model) trained in the early stage, and the model is trained by only utilizing two ironing marks which can be ironed and cannot be ironed in the training process, so that the training of the model is completed quickly, and only a result whether the washing label image can be ironed or not can be output after the trained model acquires the washing label image.
102, when the laundry maintenance implementation type is determined to be the ironing type, carrying out ironing information identification on the washing label image, and obtaining one or more corresponding ironing parameter identification modes according to ironing information identification results so as to obtain ironing parameters of the garment steamer through the ironing parameter identification modes.
In this application, when it is determined that the laundry maintenance implementation type of the target laundry is the ironing-capable type, it is necessary to further perform ironing text information recognition on the wash mark image through step 101. Because the training samples of the existing ironing information identification models are mainly training sample images marked with ironing type labels, the models have poor content identification effect on ironing text information, and the number of the sample images related to the ironing text information is small, so that the number of the sample images used in the general training process is small, and the models cannot accurately identify the ironing information when identifying the images. Therefore, in the present application, after determining that the laundry maintenance implementation type is the ironing type, it is necessary to identify the ironing information of the wash mark image, that is, identify the text information in the wash mark image, if the identification result does not include text information (that is, does not include description information of ironing, for example, ironing temperature parameters, ironing time length, etc., the ironing icons including text description content may be defined as low-frequency types, generally, the number of such ironing icons is smaller in the samples on the laundry or during training), the ironing icons may be identified by the trained ironing icon identification model (that is, the second identification model), so as to obtain ironing parameters corresponding to the target laundry. In an embodiment, if the ironing information identification result includes text content, the text content and the ironing icon can be identified respectively, and by combining two different ironing parameter identification modes, a more accurate ironing parameter identification result is obtained, for example, the ironing icon identification result is that the ironing can be performed at a high temperature, the text content identification result is 200 ℃, and according to the two identification results, the gear of the garment steamer can be adjusted to a high temperature first, and then the ironing temperature is set at 200 ℃.
Step 103, generating an ironing mode corresponding to the garment steamer based on the ironing parameters, and controlling the garment steamer according to the ironing mode.
In the application, after the target clothes are determined to be ironable, the ironing icon is further identified again through the ironing icon identification model, so that ironing parameters corresponding to the ironing icon are output, and the ironing parameters are sent to the control unit of the garment steamer, so that ironing control of the garment steamer is completed. In an embodiment, for an ironing icon with ironing text information, the text information in the ironing icon can be matched with the database through a mapping rule database established in the early stage to obtain a corresponding mapping result, so that the ironing icon identification model and the mapping rule database can simultaneously send the obtained output results to the garment steamer for controlling the ironing mode of the garment steamer, for example, the output result of the ironing icon identification model is that the highest ironing temperature is 110 degrees celsius (one symbol of '■' in the corresponding ironing icon, one black solid point in the ironing icon), and the text content below the ironing icon can generate corresponding time length parameters (such as text information about time length below the ironing icon) through the mapping rule database, and after the garment steamer receives the two ironing parameters, the garment steamer is automatically switched to the corresponding ironing mode.
According to the garment steamer ironing method, firstly, the washing label image is subjected to clothes maintenance mode identification, when the clothes maintenance implementation type is determined to be the ironing type, the washing label image is subjected to ironing information identification, ironing parameters for controlling the garment steamer are generated according to ironing information identification results, compared with the prior art, the problem that the target detection model is poor in identification effect due to the fact that training samples are too few is avoided through multi-stage detection identification of the washing label image, and the accuracy of identification of ironing information in the washing label image is improved.
On the basis of the above embodiment, the method further includes:
when the clothes maintenance implementation type is determined to be a non-ironing type, carrying out shape recognition on the washing marks in the washing mark image, and determining whether the washing marks in the washing mark image are non-ironing icons according to a shape recognition result;
if the washing label is not the non-ironing icon, determining the non-executable information of the clothes maintenance corresponding to the washing label according to the shape recognition result of the washing label, and displaying the non-executable information of the clothes maintenance through the garment steamer, wherein the non-executable information of the clothes maintenance comprises one or more of non-washable, non-bleachable and non-reversible drying.
In this application, since the wash marks of most of the clothes are ironable icons, it is generally required that some clothes with special materials are not ironable, so that in the training process, the number of samples of the type (i.e. the non-ironable icons) is small, which results in that the accuracy is not guaranteed when the model identifies the non-ironable icons, for example, the model can incorrectly identify as non-ironable the types of maintenance implementation such as non-dry cleaning, non-bleaching and non-reversible drying due to the too small number of samples, and because the icons all contain an "x" pattern, the model can be incorrectly identified. Therefore, when the model output result is of the laundry maintenance implementation type which cannot be ironed, the output result can be defined as a pending result, that is, the non-implementation type is determined, and further determination is required. Further, when it is determined that the non-executable type of the wash mark is not a non-ironing icon, further, according to the shape of the wash mark, non-executable information of clothes maintenance, such as non-washable or non-bleachable, is determined, corresponding information, such as voice information and text information, is generated, and is displayed through a voice module or a display module of the garment steamer.
On the basis of the above embodiment, the determining, according to the shape recognition result, whether the wash mark in the wash mark image is an ironable-impossible icon includes:
and if the washing mark image does not comprise any preset washing mark shape, determining the washing mark in the washing mark image as an ironing-impossible icon, wherein the preset washing mark shape comprises one or a combination of a plurality of circles, triangles and rectangles.
In the present application, when the output result of the first recognition model is a non-executable type, at this time, the wash mark identified in the wash mark image is tentatively designated as a non-ironable icon, and the non-executable type of the wash mark is determined as a non-ironable icon when it is determined that there is no circle (corresponding to dry cleaning), triangle (corresponding to bleaching) or rectangle (corresponding to overturn drying) by performing hough circle detection, triangle detection and rectangle detection on the wash mark, so that corresponding non-ironable notification information, such as voice information and text information, is generated and sent to the garment steamer or the user mobile terminal, thereby notifying the user. When any one of the circle, triangle and rectangle exists in the wash mark, it means that the wash mark represents other laundry maintenance non-executable type.
On the basis of the above embodiment, the image recognition of the wash mark image includes:
acquiring a washing label image of the target clothes;
and inputting the washing label image into a first identification model to identify a clothes maintenance mode, and obtaining a clothes maintenance implementation type output by the first identification model, wherein the first identification model is obtained by training a sample washing label image marked with a clothes maintenance implementation type label.
In the application, the first recognition model is built by training the convolutional neural network, and the training process of the model only needs to take ironing icons which can be ironed and ironing icons which cannot be ironed as sample data, so that the training of the model is completed quickly.
On the basis of the embodiment, the first recognition model is obtained through training by the following steps:
acquiring a plurality of sample washing mark images;
marking corresponding clothes maintenance implementation type labels for the sample washing label images, and constructing a training sample set, wherein the clothes maintenance implementation type labels at least comprise ironing labels and non-ironing labels;
and training the convolutional neural network through the training sample set to obtain the first recognition model.
In the method, the number of the ironable icons is large, so that the model has high accuracy in identifying the category; for the non-ironing icons, although the number of the sample data of the type is small, the non-ironing icons identified by the first identification model are detected again through shape detection later, so that the identification accuracy of the ironing targets is improved.
On the basis of the above embodiment, when the laundry maintenance implementation type is determined to be an ironing type, performing ironing information identification on the washing label image, and obtaining one or more corresponding ironing parameter identification modes according to the ironing information identification result, so as to obtain ironing parameters of the garment steamer through the ironing parameter identification modes, including:
when the clothes maintenance implementation type is determined to be an ironing type, carrying out character information identification on the washing mark image, and obtaining a corresponding washing mark character content identification result;
if the character content identification result of the washing label does not contain any character information, inputting the washing label image into a second identification model for ironing information identification to obtain ironing icon information output by the second identification model, wherein the second identification model is obtained by training a sample washing label image of an ironing icon label;
And generating ironing parameters of the garment steamer according to the ironing icon information.
In the application, the character information recognition can be performed on the area corresponding to the ironable icon obtained by the recognition of the first recognition model through the optical character recognition (Optical Character Recognition, abbreviated as OCR) technology, and when the area does not contain the character content, the ironable icon is recognized again through the second recognition model to obtain the ironing icon information, for example, the ironing icon comprises 2 symbols of ■, the result output by the second recognition model is that the highest ironing temperature is 150 ℃, and the recognition task can be accurately completed after the second recognition model completes training based on the sample data due to the large number of samples of the ironing icon.
On the basis of the above embodiment, the method further includes:
and if the character content identification result of the washing label contains character information, performing category mapping on the character content identification result of the washing label and a preset ironing rule to obtain ironing parameters corresponding to the garment steamer.
In the method, category mapping is performed according to preset mapping rules of the OCR regular expression, when the identification result of the text content of the washing label can be mapped to the corresponding category through the preset ironing rules, ironing parameters are obtained, and if the mapping cannot be performed, the text content is not related to ironing.
On the basis of the above embodiment, the method further includes:
under the condition that the character content identification result of the washing label contains character information, carrying out category mapping on the character content identification result of the washing label and a preset ironing rule, and inputting the washing label image into a second identification model for ironing information identification;
and based on the category mapping result and the ironing icon information, obtaining ironing parameters of the garment steamer.
In the application, two ironing parameter identification modes can be combined according to the situation that the washing mark image contains text information, namely, the washing mark text content identification result is mapped with a preset ironing rule in category, and meanwhile, the washing mark image is input into a second identification model to carry out ironing information identification, so that identification results corresponding to the two ironing parameter identification modes are obtained, and finally, the two identification modes are combined to generate an ironing mode corresponding to the garment steamer.
On the basis of the above embodiment, after the image recognition is performed on the wash mark image and the target detection is performed based on the image recognition result, the method further includes:
and carrying out image cutting processing on the region range corresponding to the washing mark in the washing mark image to obtain a target image, so as to carry out ironing information identification or shape identification on the target image.
In the application, after the first recognition model completes the preliminary recognition of the washing mark image, the area range of the ironing icon in the washing mark image can be obtained according to the result output by the first recognition model, and then the image only containing the ironing icon content is used as a target image by cutting the area range for subsequent target recognition detection so as to reduce interference in the recognition process.
In an embodiment, an ironing manner of the garment steamer of the present application is integrally described, and the specific steps are as follows:
step 101, dividing all acquired training data of the water washing ironing icons into two main categories: the ironing and non-ironing can be performed (distinguishing whether an X symbol exists in the middle of the ironing icon or not), then the ironing icon is marked according to a target detection mode, and training is performed through a target detection method to obtain a first recognition model for recognizing the ironing/non-ironing targets.
Step 102, recognizing the washing mark image through a first recognition model, and if the recognition result is that ironing is impossible, going to step 103; if the identification results in ironing, go to step 106.
Step 103, clipping the non-ironing icon into a small image (namely a target image) according to frame coordinates (x, y, w and h), then carrying out traditional circle detection, triangle detection and rectangle detection on the small image, and if any shape exists, going to step 104; if none of the shapes are present, go to step 105.
Step 104, if the detected small drawing is a non-dry-cleanable, non-bleachable or non-reversible drying icon, that is, the small drawing contains a circle, triangle or rectangle, the icon is not a non-ironing icon, so that the information of the icon is not output, and the ironing mode of the garment steamer is not required to be adjusted.
Step 105, if the detected small drawing is indeed an ironable icon, go to step 111.
Step 106, the ironable icon is cut into small drawings according to the frame coordinates (x, y, w and h), and OCR recognition is carried out on the small drawings, so that two situations can occur: OCR recognizes text (including digital content) to step 107; OCR recognizes no text and proceeds to step 110.
Step 107, performing category mapping according to the mapping rule of the OCR regular expression, where two situations may occur: may map to a category, step 108; cannot be mapped to the corresponding category, step 109.
Step 108, generating corresponding ironing parameters according to the mapped category, for example, the text content is 80-120 ℃, and the ironing parameters can be mapped to 80-120 temperature parameters (which are the outputtable low-frequency category), and the step 111 is performed.
In step 109, for the categories that do not exist in the mapping rule, no output result needs to be generated, for example, the text content is "199", and no category is output if the text content corresponds to the rule.
And 110, when the OCR can not recognize any text, the ironable icon is directly recognized through the second recognition model, and corresponding ironing parameters are output.
And step 111, combining the results output in the step 108 and the step 110, and sending the results to the garment steamer to execute a corresponding ironing mode.
The garment steamer ironing device provided by the application is described below, and the garment steamer ironing device described below and the garment steamer ironing method described above can be referred to correspondingly.
Fig. 3 is a schematic structural diagram of an ironing device of a garment steamer provided by the present application, and as shown in fig. 3, the present application provides an ironing device of a garment steamer, which includes a laundry maintenance implementation type detection module 301, an ironing information detection module 302, and a control module 303, wherein the laundry maintenance implementation type detection module 301 is configured to perform image recognition on a wash mark image, and perform target detection based on an image recognition result; the ironing information detection module 302 is configured to, when determining that the laundry maintenance implementation type is an ironing type, perform ironing information identification on the wash mark image, and obtain, according to an ironing information identification result, one or more corresponding ironing parameter identification modes, so as to obtain ironing parameters of the garment steamer according to the ironing parameter identification modes; the control module 303 is configured to generate an ironing mode corresponding to the garment steamer based on the ironing parameter, and control the garment steamer according to the ironing mode.
The utility model provides a garment steamer ironing device carries out clothing maintenance mode discernment to washing mark image at first, but when confirming that clothing maintenance implementation type is ironing type, carries out ironing information discernment to washing mark image again, and according to ironing information discernment result, generate the ironing parameter that is used for controlling the garment steamer, compare prior art, through carrying out multistage detection discernment to washing mark image, avoid the target detection model because training sample is too few to lead to the relatively poor problem of recognition effect, improved the recognition accuracy of ironing information in the washing mark image.
On the basis of the embodiment, the device further comprises a wash mark shape detection module and a clothes maintenance prompting module, wherein the wash mark shape detection module is used for carrying out shape recognition on the wash mark in the wash mark image when the clothes maintenance implementation type is determined to be a non-ironing type, and determining whether the wash mark in the wash mark image is a non-ironing icon according to a shape recognition result; and the clothes maintenance prompting module is used for determining clothes maintenance non-executable information corresponding to the washing mark according to the shape recognition result of the washing mark if the washing mark is not a non-ironing icon, and displaying the clothes maintenance non-executable information through the garment steamer, wherein the clothes maintenance non-executable information comprises one or more of non-washable, non-bleachable and non-reversible drying.
On the basis of the above embodiment, the wash mark shape detection module is specifically configured to determine that the wash mark in the wash mark image is an ironing-impossible icon if the wash mark image does not include any preset wash mark shape, where the preset wash mark shape includes one or a combination of several of a circle, a triangle and a rectangle.
On the basis of the embodiment, the clothes maintenance implementation type detection module comprises an image acquisition unit and a first identification unit, wherein the image acquisition unit is used for acquiring a washing label image of target clothes; the first recognition unit is used for inputting the washing label image into a first recognition model to recognize a clothes maintenance mode, and obtaining a clothes maintenance implementation type output by the first recognition model, wherein the first recognition model is obtained by training a sample washing label image marked with a clothes maintenance implementation type label.
On the basis of the embodiment, the device further comprises a sample image acquisition module, a training set construction module and a training module, wherein the sample image acquisition module is used for acquiring a plurality of sample washing mark images; the training set construction module is used for marking corresponding clothes maintenance implementation type labels for the sample washing mark images to construct a training sample set, wherein the clothes maintenance implementation type labels at least comprise ironable labels and non-ironable labels; the training module is used for training the convolutional neural network through the training sample set to obtain the first recognition model.
On the basis of the embodiment, the ironing information detection module comprises a character recognition unit, a second recognition unit and an ironing parameter generation unit, wherein the character recognition unit is used for recognizing character information of the washing label image when determining that the clothes maintenance implementation type is an ironing type, and obtaining a corresponding washing label character content recognition result; the second recognition unit is used for inputting the washing label image into a second recognition model for ironing information recognition if the character content recognition result of the washing label does not contain any character information, so as to obtain ironing icon information output by the second recognition model, wherein the second recognition model is obtained by training a sample washing label image of an ironing icon label; and the ironing parameter generating unit is used for generating ironing parameters of the garment steamer according to the ironing icon information.
On the basis of the above embodiment, the device further includes an ironing parameter mapping module, configured to, if the text content identification result of the washing label includes text information, perform category mapping on the text content identification result of the washing label and a preset ironing rule, and obtain ironing parameters of the garment steamer.
On the basis of the above embodiment, the ironing information detecting module is further configured to: under the condition that the character content identification result of the washing label contains character information, carrying out category mapping on the character content identification result of the washing label and a preset ironing rule, and inputting the washing label image into a second identification model for ironing information identification; and based on the category mapping result and the ironing icon information, obtaining ironing parameters of the garment steamer.
On the basis of the embodiment, the device further comprises an image acquisition module, wherein the image acquisition module is used for carrying out image cutting processing on the area range corresponding to the washing mark in the washing mark image to obtain a target image so as to carry out ironing information identification or shape identification on the target image.
The application also provides a garment steamer, comprising the garment steamer ironing device according to the embodiments, a steam heater, a machine body shell, a water tank, a steam nozzle, a steam conduit and a telescopic bracket. The garment steamer that this application provided carries out clothing maintenance mode discernment through garment steamer ironing device to washing mark image, when confirming that clothing maintenance implementation type is the type of ironing, again carries out ironing information discernment to washing mark image to according to ironing information discernment result, the ironing parameter that generates to be used for controlling garment steamer compares prior art, through carrying out multistage detection discernment to washing mark image, avoid the target detection model because training sample is too few to lead to the relatively poor problem of recognition effect, improved the recognition accuracy of ironing information in the washing mark image.
Fig. 4 is a schematic structural diagram of an electronic device provided in the present application, as shown in fig. 4, the electronic device may include: processor 410, communication interface (Communications Interface) 420, memory 430 and communication bus 440, wherein processor 410, communication interface 420 and memory 430 communicate with each other via communication bus 440. The processor 410 may invoke logic instructions in the memory 430 to perform a garment steamer ironing method comprising: carrying out image recognition on the washing label image, and carrying out target detection based on an image recognition result; when the clothes maintenance implementation type is determined to be the ironing type, carrying out ironing information identification on the washing label image, and obtaining one or more corresponding ironing parameter identification modes according to ironing information identification results so as to obtain ironing parameters of the garment steamer through the ironing parameter identification modes; based on the ironing parameters, generating an ironing mode corresponding to the garment steamer, and controlling the garment steamer according to the ironing mode.
Further, the logic instructions in the memory 430 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present application also provides a computer program product comprising a computer program, the computer program being storable on a computer readable storage medium, the computer program, when executed by a processor, being capable of performing the garment steamer ironing method provided by the methods described above, the method comprising: carrying out image recognition on the washing label image, and carrying out target detection based on an image recognition result; when the clothes maintenance implementation type is determined to be the ironing type, carrying out ironing information identification on the washing label image, and obtaining one or more corresponding ironing parameter identification modes according to ironing information identification results so as to obtain ironing parameters of the garment steamer through the ironing parameter identification modes; based on the ironing parameters, generating an ironing mode corresponding to the garment steamer, and controlling the garment steamer according to the ironing mode.
In still another aspect, the present application further provides a computer readable storage medium, where the computer readable storage medium includes a stored program, where the program executes a garment steamer ironing method provided by the above methods, and the method includes: carrying out image recognition on the washing label image, and carrying out target detection based on an image recognition result; when the clothes maintenance implementation type is determined to be the ironing type, carrying out ironing information identification on the washing label image, and obtaining one or more corresponding ironing parameter identification modes according to ironing information identification results so as to obtain ironing parameters of the garment steamer through the ironing parameter identification modes; based on the ironing parameters, generating an ironing mode corresponding to the garment steamer, and controlling the garment steamer according to the ironing mode.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and are not limiting thereof; 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 scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (13)
1. A garment steamer ironing method comprising:
carrying out image recognition on the washing label image, and carrying out target detection based on an image recognition result;
when the clothes maintenance implementation type is determined to be the ironing type, carrying out ironing information identification on the washing label image, and obtaining one or more corresponding ironing parameter identification modes according to ironing information identification results so as to obtain ironing parameters of the garment steamer through the ironing parameter identification modes;
based on the ironing parameters, generating an ironing mode corresponding to the garment steamer, and controlling the garment steamer according to the ironing mode.
2. The garment steamer ironing method of claim 1, wherein the method further comprises:
When the clothes maintenance implementation type is determined to be a non-ironing type, carrying out shape recognition on the washing marks in the washing mark image, and determining whether the washing marks in the washing mark image are non-ironing icons according to a shape recognition result;
if the washing label is not the non-ironing icon, determining the non-executable information of the clothes maintenance corresponding to the washing label according to the shape recognition result of the washing label, and displaying the non-executable information of the clothes maintenance through the garment steamer, wherein the non-executable information of the clothes maintenance comprises one or more of non-washable, non-bleachable and non-reversible drying.
3. The garment steamer ironing method according to claim 2, wherein the determining whether the wash mark in the wash mark image is a non-ironing icon according to the shape recognition result comprises:
and if the washing mark image does not comprise any preset washing mark shape, determining the washing mark in the washing mark image as an ironing-impossible icon, wherein the preset washing mark shape comprises one or a combination of a plurality of circles, triangles and rectangles.
4. The garment steamer ironing method as claimed in claim 1, wherein the image recognition of the wash mark image comprises:
Acquiring a washing label image of the target clothes;
and inputting the washing label image into a first identification model to identify a clothes maintenance mode, and obtaining a clothes maintenance implementation type output by the first identification model, wherein the first identification model is obtained by training a sample washing label image marked with a clothes maintenance implementation type label.
5. The garment steamer ironing method as claimed in claim 4, characterized in that the first recognition model is trained by the following steps:
acquiring a plurality of sample washing mark images;
marking corresponding clothes maintenance implementation type labels for the sample washing label images, and constructing a training sample set, wherein the clothes maintenance implementation type labels at least comprise ironing labels and non-ironing labels;
and training the convolutional neural network through the training sample set to obtain the first recognition model.
6. The method according to claim 1, wherein when the laundry maintenance implementation type is determined to be an ironing type, the ironing information identification is performed on the wash mark image, and one or more corresponding ironing parameter identification modes are obtained according to the ironing information identification result, so as to obtain ironing parameters of the garment steamer through the ironing parameter identification modes, including:
When the clothes maintenance implementation type is determined to be an ironing type, carrying out character information identification on the washing mark image, and obtaining a corresponding washing mark character content identification result;
if the character content identification result of the washing label does not contain any character information, inputting the washing label image into a second identification model for ironing information identification to obtain ironing icon information output by the second identification model, wherein the second identification model is obtained by training a sample washing label image marked with ironing icon labels;
and generating ironing parameters of the garment steamer according to the ironing icon information.
7. The garment steamer ironing method of claim 6, the method further comprising:
and if the character content identification result of the washing label contains character information, carrying out category mapping on the character content identification result of the washing label and a preset ironing rule to obtain ironing parameters of the garment steamer.
8. The garment steamer ironing method of claim 7, the method further comprising:
under the condition that the character content identification result of the washing label contains character information, carrying out category mapping on the character content identification result of the washing label and a preset ironing rule, and inputting the washing label image into a second identification model for ironing information identification;
And based on the category mapping result and the ironing icon information, obtaining ironing parameters of the garment steamer.
9. The garment steamer ironing method according to any one of claims 2 to 8, characterized in that after the image recognition of the washing label image and the target detection based on the image recognition result, the method further comprises:
and carrying out image cutting processing on the region range corresponding to the washing mark in the washing mark image to obtain a target image, so as to carry out ironing information identification or shape identification on the target image.
10. A garment steamer ironing device comprising:
the clothes maintenance implementation type detection module is used for carrying out image recognition on the washing mark image and carrying out target detection based on an image recognition result;
the ironing information detection module is used for carrying out ironing information identification on the washing label image when the clothes maintenance implementation type is determined to be the ironing type, and obtaining one or more corresponding ironing parameter identification modes according to ironing information identification results so as to obtain ironing parameters of the garment steamer through the ironing parameter identification modes;
and the control module is used for generating an ironing mode corresponding to the garment steamer based on the ironing parameters and controlling the garment steamer according to the ironing mode.
11. A garment steamer comprising a garment steamer ironing device as claimed in claim 10, and a steam heater, a main body housing, a water tank, a steam nozzle, a steam conduit and a telescopic support.
12. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored program, wherein the program when run performs the method of any one of claims 1 to 9.
13. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method according to any of claims 1 to 9 by means of the computer program.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211049158.9A CN117689920A (en) | 2022-08-30 | 2022-08-30 | Garment steamer ironing method and device, garment steamer, storage medium and electronic device |
| PCT/CN2023/085376 WO2024045601A1 (en) | 2022-08-30 | 2023-03-31 | Ironing method and device for garment steamer, and garment steamer, storage medium and electronic device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211049158.9A CN117689920A (en) | 2022-08-30 | 2022-08-30 | Garment steamer ironing method and device, garment steamer, storage medium and electronic device |
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| CN117689920A true CN117689920A (en) | 2024-03-12 |
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| CN202211049158.9A Pending CN117689920A (en) | 2022-08-30 | 2022-08-30 | Garment steamer ironing method and device, garment steamer, storage medium and electronic device |
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| CN (1) | CN117689920A (en) |
| WO (1) | WO2024045601A1 (en) |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106283584A (en) * | 2016-10-28 | 2017-01-04 | 京东方科技集团股份有限公司 | A kind of electric iron and ironing method thereof |
| KR102079661B1 (en) * | 2019-05-24 | 2020-02-20 | 남현욱 | Intelligence technique steam iron |
| CN112252001A (en) * | 2020-08-31 | 2021-01-22 | 青岛云裳羽衣物联科技有限公司 | Intelligent clothes nursing mirror with RFID function |
| CN114763671A (en) * | 2021-01-15 | 2022-07-19 | 广州奕至家居科技有限公司 | Ironing method based on clothes identification, terminal, ironing machine and storage medium |
| CN113417107B (en) * | 2021-06-30 | 2024-03-22 | 青岛海尔科技有限公司 | Method and system for determining washing mode, storage medium and electronic device |
| CN114481584A (en) * | 2022-01-17 | 2022-05-13 | 青岛海尔智护电器有限公司 | Ironing method of garment steamer, control device, garment steamer and electronic equipment |
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2022
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