Garment pattern making, garment pattern detection method, device, equipment and storage medium

Abstract

The embodiment of the present invention provides a method, device, equipment and storage medium for clothing pattern making and clothing pattern detection. The clothing pattern method comprises: obtaining a clothing pattern, wherein the clothing pattern includes multiple parts of the clothing. According to the structural characteristics of each of the multiple parts, the category identification of each of the multiple parts and the multiple part information contained in each of the multiple parts are determined. According to the category identification of each of the multiple parts and the multiple part information contained in each of the multiple parts, it is determined whether the clothing pattern meets the preset detection conditions corresponding to the clothing. In this scheme, the detection conditions corresponding to the clothing are pre-set to complete the automatic detection of the clothing pattern based on the detection conditions and the parts and part information identified from the clothing pattern.

Description

Technical Field

[0001] The present invention relates to the field of manufacturing, and in particular to a method, device, equipment and storage medium for garment pattern making and garment pattern detection. Background Art

[0002] Clothing pattern making is to make a sample of the clothing creative design, also known as clothing pattern, clothing sample or clothing template. The pattern maker uses computer-aided design (CAD) and other tools to digitally express the sample according to the clothing renderings and specifications designed by the creative designer. This is the clothing pattern.

[0003] In practical applications, the clothing patterns provided by the pattern master need to be tested for accuracy to avoid errors that may result in the production of clothing that does not meet the requirements. Currently, this testing task is done manually, which is inefficient and prone to omissions. Summary of the invention

[0004] The embodiments of the present invention provide a method, device, equipment and storage medium for detecting clothing pattern making and clothing paper pattern, which can improve detection efficiency.

[0005] In a first aspect, an embodiment of the present invention provides a detection method, the method comprising:

[0006] Acquire a graphic file corresponding to a preset object, wherein the graphic file includes a plurality of components of the object;

[0007] Determining, according to the structural features of the multiple components, the category identifications of the multiple components and the multiple part information contained in the multiple components;

[0008] According to the respective category identifiers of the plurality of components and the plurality of part information respectively included in the plurality of components, it is determined whether the graphic file satisfies a preset detection condition corresponding to the object.

[0009] In a second aspect, an embodiment of the present invention provides a detection device, the device comprising:

[0010] An acquisition module, used for acquiring a graphic file corresponding to a preset object, wherein the graphic file includes a plurality of components of the object;

[0011] A determination module, configured to determine the category identification of each of the plurality of components and a plurality of part information respectively included in the plurality of components according to the structural characteristics of each of the plurality of components;

[0012] The judgment module is used to determine whether the graphic file meets the preset detection condition corresponding to the object according to the category identifications of the multiple components and the multiple part information contained in the multiple components.

[0013] In a third aspect, an embodiment of the present invention provides an electronic device, comprising: a memory, a processor, and a communication interface; wherein the memory stores executable code, and when the executable code is executed by the processor, the processor can at least implement the detection method described in the first aspect.

[0014] In a fourth aspect, an embodiment of the present invention provides a non-temporary machine-readable storage medium, on which executable code is stored. When the executable code is executed by a processor of an electronic device, the processor can at least implement the detection method described in the first aspect.

[0015] In a fifth aspect, an embodiment of the present invention provides a clothing pattern detection method, the method comprising:

[0016] Obtaining a garment pattern, wherein the garment pattern includes a plurality of garment components;

[0017] Determining, according to the structural features of the multiple components, the category identifications of the multiple components and the multiple part information contained in the multiple components;

[0018] According to the category identifications of the multiple components and the multiple part information contained in the multiple components, it is determined whether the clothing pattern meets the preset detection conditions corresponding to the clothing.

[0019] In a sixth aspect, an embodiment of the present invention provides a clothing pattern detection device, the device comprising:

[0020] An acquisition module, used for acquiring a garment pattern, wherein the garment pattern includes a plurality of garment parts;

[0021] A determination module, configured to determine the category identification of each of the plurality of components and a plurality of part information respectively included in the plurality of components according to the structural characteristics of each of the plurality of components;

[0022] The detection module is used to determine whether the clothing pattern meets the preset detection conditions corresponding to the clothing according to the category identifications of the multiple components and the multiple part information contained in the multiple components.

[0023] In the seventh aspect, an embodiment of the present invention provides an electronic device, comprising: a memory, a processor, and a communication interface; wherein the memory stores executable code, and when the executable code is executed by the processor, the processor can at least implement the clothing pattern detection method described in the fifth aspect.

[0024] In an eighth aspect, an embodiment of the present invention provides a non-temporary machine-readable storage medium, on which executable code is stored. When the executable code is executed by a processor of an electronic device, the processor can at least implement the clothing pattern detection method described in the fifth aspect.

[0025] In a ninth aspect, an embodiment of the present invention provides a clothing pattern making method, the method comprising:

[0026] Obtaining a garment pattern, wherein the garment pattern includes a plurality of garment components;

[0027] Determining, according to the structural features of the multiple components, the category identifications of the multiple components and the multiple part information contained in the multiple components;

[0028] According to the category identifications of the multiple components and the multiple part information contained in the multiple components, the production process information of the manufacturer corresponding to the clothing is obtained, so that the user determines whether the clothing pattern needs to be modified based on the generated process information.

[0029] In a tenth aspect, an embodiment of the present invention provides a clothing pattern making device, the device comprising:

[0030] A first acquisition module is used to acquire a garment pattern, wherein the garment pattern includes a plurality of garment components;

[0031] A determination module, configured to determine the category identification of each of the plurality of components and a plurality of part information respectively included in the plurality of components according to the structural characteristics of each of the plurality of components;

[0032] The second acquisition module is used to acquire the production process information of the manufacturer corresponding to the garment according to the category identification of each of the multiple components and the multiple part information contained in each of the multiple components, so that the user can determine whether the garment pattern needs to be modified based on the generated process information.

[0033] In the eleventh aspect, an embodiment of the present invention provides an electronic device, comprising: a memory, a processor, and a communication interface; wherein the memory stores executable code, and when the executable code is executed by the processor, the processor can at least implement the clothing pattern making method as described in the ninth aspect.

[0034] In the twelfth aspect, an embodiment of the present invention provides a non-temporary machine-readable storage medium, on which executable code is stored. When the executable code is executed by a processor of an electronic device, the processor can at least implement the clothing pattern making method described in the ninth aspect.

[0035] In an embodiment of the present invention, for a preset object (such as clothing), after obtaining a graphic file (such as a clothing pattern) corresponding to the object, the graphic file can be automatically detected for accuracy. In fact, an object may contain multiple components, and each component may contain multiple parts. Based on this, for the obtained graphic file, first, the category identification of each of the multiple components in the graphic file and the multiple part information contained in each of the multiple components can be determined according to the structural characteristics of each of the multiple components contained therein, and then, according to the category identification of each of the multiple components and the multiple part information contained in each of the multiple components, it is determined whether the graphic file meets the preset detection conditions corresponding to the object. In other words, the detection conditions corresponding to the object will be set in advance to complete the automatic detection of the graphic file based on the detection conditions and the components and part information identified from the graphic file corresponding to the object. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0037] Figure 1 A flowchart of a clothing pattern detection method provided by an embodiment of the present invention;

[0038] Figure 2 A flowchart of an implementation method of step 102 provided in an embodiment of the present invention;

[0039] Figure 3 A schematic diagram of an application scenario of a detection method provided by an embodiment of the present invention;

[0040] Figure 4 A flowchart of a clothing pattern making method provided by an embodiment of the present invention;

[0041] Figure 5 A flow chart of a detection method provided by an embodiment of the present invention;

[0042] Figure 6 A schematic structural diagram of a clothing pattern detection device provided by an embodiment of the present invention;

[0043] Figure 7 For Figure 6 A schematic diagram of the structure of an electronic device corresponding to the clothing pattern detection device provided in the illustrated embodiment;

[0044] Figure 8 A schematic structural diagram of a clothing pattern making device provided by an embodiment of the present invention;

[0045] Fig. 9 For Figure 8 A schematic diagram of the structure of an electronic device corresponding to the clothing pattern making device provided in the illustrated embodiment;

[0046] Fig.10 A schematic diagram of the structure of a detection device provided by an embodiment of the present invention;

[0047] Fig.11 For Fig.10 A schematic structural diagram of an electronic device corresponding to the detection device provided in the illustrated embodiment. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms.

[0050] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0051] In addition, the step sequence in the following method embodiments is only an example and not a strict limitation.

[0052] Figure 1 A flowchart of a clothing pattern detection method provided by an embodiment of the present invention is shown in FIG. Figure 1As shown, the method may include the following steps:

[0053] 101. Obtain a clothing pattern, where the clothing pattern includes multiple parts of the clothing.

[0054] 102. Determine, according to respective structural features of the plurality of components, respective category identifiers of the plurality of components and respective plurality of part information contained in the plurality of components.

[0055] 103. Determine whether the garment pattern satisfies a preset detection condition corresponding to the garment according to the category identifications of the plurality of components and the plurality of part information contained in the plurality of components.

[0056] The garment pattern detection method provided in the embodiment of the present invention may be executed by an electronic device, which may be a terminal device such as a PC, a laptop, a mobile phone, or a server. The electronic device is hereinafter referred to as a detection device.

[0057] In actual applications, pattern makers use CAD tools to complete the making of clothing patterns so that subsequent clothing production work can be carried out based on the obtained clothing patterns.

[0058] A garment pattern contains all the parts of a garment, which are the assembly units of the garment pattern, such as the front piece, back piece, placket, collar, etc. The garment pieces cut from the sewing material according to these parts are called cut pieces. Each part contains many parts, such as the front hem, front armhole, front shoulder seam, etc. in the front piece of a garment.

[0059] However, in actual applications, there may be some errors in the clothing patterns provided by the pattern master. Therefore, it is necessary to conduct accuracy testing on the clothing patterns to promptly discover the errors. During the testing process, the main purpose is to test whether the clothing patterns meet the requirements of the industry and clothing production factories. In actual applications, the contents that need to be tested may include: whether the cuts, knife edges, seams are correct, whether the parts are complete, whether some size information (such as length, width, curvature) is correct, etc.

[0060] If manual inspection is used, the inspection time varies from several minutes to more than ten minutes depending on the complexity of the clothing style. The more parts a clothing contains, the more time it takes, and manual inspection misses and wrong inspections often occur. To this end, an embodiment of the present invention provides an automated inspection solution.

[0061] In summary, the overall idea of ​​the automated testing solution is to pre-set testing conditions in combination with some requirements put forward by the industry and clothing production factories. When a clothing pattern corresponding to a certain piece of clothing is obtained, the parts and parts related information contained in the clothing pattern are identified from the clothing pattern, and by judging whether the identification result meets the preset testing conditions, the detection of whether the clothing pattern meets the preset testing conditions is automatically completed.

[0062] Optionally, the preset detection conditions may correspond to the generator of the above-mentioned garment (i.e., the garment production factory). That is to say, if the same garment pattern is produced by different garment production factories, the detection conditions corresponding to the different garment production factories may be different, resulting in different detection results for the same garment pattern. Based on this, when testing the garment pattern, it is necessary to determine the producer corresponding to the garment to determine the preset detection conditions corresponding to the garment provided by the producer.

[0063] In actual applications, when designing a piece of clothing and requiring a clothing production factory to produce it, preset testing conditions for accuracy testing of clothing patterns can be set according to some standards established by the clothing industry and the clothing production factory.

[0064] According to different detection granularities, optionally, a preset detection condition generally applicable to various types of clothing can be set, or corresponding preset detection conditions can be set for different categories of clothing.

[0065] For example, if various types of clothing should have certain parts, a certain clothing production factory does not support a certain process, and the width of the seam is required to be no less than a certain value, then preset test conditions that are generally applicable to various types of clothing can be set according to these requirements.

[0066] For another example: for category A clothing, it may be required that the corresponding clothing pattern includes certain parts, and each part should include certain parts, and certain parts should have certain specific property requirements. For category B clothing, it may be required that the corresponding clothing pattern includes other parts, and each part should include certain parts, and certain parts should have certain specific property requirements. In addition, clothing production factories may also have corresponding production standard requirements such as processes for different categories of clothing. Based on this, corresponding preset detection conditions can be set for different categories of clothing.

[0067] When corresponding preset detection conditions are set for different categories of clothing, optionally, the correspondence between the preset detection conditions and the clothing categories can be stored in the detection device, so that when it is necessary to detect the currently acquired clothing sample, the detection personnel can select the corresponding preset detection conditions according to the clothing category corresponding to the clothing sample.

[0068] After obtaining the garment pattern, the detection device determines the category identification of each of the multiple components and the multiple part information contained in each of the multiple components according to the structural characteristics of each of the multiple components contained in the garment pattern, and then determines whether the garment pattern meets the preset detection conditions corresponding to the garment according to the category identification of each of the multiple components and the multiple part information contained in each of the multiple components. As described above, the preset detection conditions can be preset detection conditions applicable to various garments provided by a garment production factory, or can be a preset detection condition corresponding to the category corresponding to the garment in the garment pattern selected by the detection personnel.

[0069] After determining whether the garment pattern meets the preset detection conditions, the detection device can optionally output the corresponding detection results. When it is determined that the preset detection conditions are met, a prompt message similar to "pass the test" can be output. If it is determined that the garment pattern does not meet the preset detection conditions, prompt information for prompting the target parts and target parts that do not meet the preset detection conditions is output, so as to know which parts and parts of the garment pattern have errors.

[0070] In practical applications, the preset detection conditions can be provided to the pattern maker to guide the production of clothing patterns. Alternatively, the multiple part information identified from the clothing pattern can be sent to the production party so that the production party can improve its own production process.

[0071] Combine the following Figure 2 To illustrate the execution process of the above step 102, Figure 2 As shown, the following steps may be specifically included:

[0072] 201. Extract the contours of the multiple components.

[0073] 202. Determine category identifiers of the multiple components according to their respective outlines.

[0074] 203. For any component among the multiple components, determine multiple lines corresponding to multiple parts in the outline of the any component, and determine attribute information of the multiple lines as multiple part information included in the any component.

[0075] In practical applications, a garment pattern may include graphics of multiple independent parts. For each part, its contour features can be extracted, and the extracted contour can reflect the category of the part.

[0076] Optionally, a model for component category recognition, such as a convolutional neural network model, may be pre-trained, and the clothing pattern may be used as input to the model, through which the category identifiers corresponding to the various components contained therein may be output.

[0077] In the training process of the model, a supervised training method can be used. In simple terms, a large number of component graphics are collected in advance as training samples. For each training sample, the component contour and the corresponding category can be labeled. These labeled information are used as supervision information to complete the model training, so that the model has the ability to learn the contour features of the components and their corresponding categories.

[0078] Of course, the contour extraction of the component can be achieved based on other methods. Based on the correspondence between the contour of the component and the category of the component, the category identifier corresponding to each component in the clothing pattern can be determined, that is, which components are included in the clothing pattern.

[0079] After identifying the various components included in the garment pattern (ie, knowing the category identification of each component), for each component, multiple parts included in it can be identified.

[0080] In a clothing scene, a component may contain several parts, and in actual applications, more attention should be paid to some parts that need to be sewn and cut. Therefore, in an embodiment of the present invention, for any component corresponding to a type of clothing, only some key parts can be identified. These key parts are the parts that need to be sewn and cut, and these parts often correspond to the outline of the component.

[0081] Therefore, for any component identified from the garment pattern, multiple lines corresponding to multiple parts can be determined in the outline of the component, and then attribute information of the multiple lines can be determined as multiple part information included in the component.

[0082] Specifically, the corner points on the contour of the component can be identified first. The line between two adjacent corner points generally corresponds to a part. Based on this, multiple lines contained in the contour of the component can be obtained. Each line corresponds to a part. The parts can be determined based on the position, shape and other characteristics of the lines.

[0083] After obtaining the multiple parts included in the component, the attribute information of each part, that is, the attribute information of the corresponding line, is obtained. Optionally, the attribute information may include any of the following: opening information, seam information, and size information. The opening information may include, for example, the position and quantity information of the knife edge and the cut. The seam information may include, for example, the number and width of the seam. The size information may include, for example, the length and curvature.

[0084] In actual applications, in the process of making clothing patterns, knife edges, cuts, seams, etc. will be drawn using the line format required by the specifications. Therefore, the above-mentioned attribute information corresponding to each part can be measured accordingly.

[0085] In the process of part recognition, similar to the category recognition of components, a model for part recognition can also be pre-trained, such as a convolutional neural network model, and the graphics of the components can be used as the input of the model. The model can output the identification of each part contained in the component. The identification of the part can be the name of the part, such as front armhole, front hem, and so on.

[0086] During the training process of the model, a large number of component graphics are collected in advance as training samples. For each training sample, multiple parts can be marked on the outline of the component. The marked information is used as supervision information to complete the model training, so that the model has the ability to recognize multiple parts contained in the component.

[0087] In addition, in an optional embodiment, the part can also be identified in the following manner:

[0088] Determine the category corresponding to the clothing according to the category identifiers of the multiple components;

[0089] According to the category corresponding to the clothing and the position characteristics of each line in the outline of any component, a plurality of lines corresponding to a plurality of parts are determined in the outline of the any component.

[0090] Among them, clothing categories include men's T-shirts, women's T-shirts, men's jackets, women's jackets, men's jeans, women's jeans, and so on.

[0091] In the above embodiment, the category of clothing is combined to assist in the identification of parts. In summary, the role of the category of clothing is mainly: under a certain clothing category, which parts should be included is known, which parts should be included on each part is also known, and the position of each part is also fixed. Therefore, it can assist in the identification of each part contained in each part of the currently input clothing pattern. Specifically, for any part that has been identified, based on the recognition result of the clothing category, it can be known which parts should be included in the part and the position characteristics corresponding to each part. Based on this, according to the position characteristics of each line in the outline of any part, multiple lines corresponding to multiple parts can be determined, that is, the part identification corresponding to each line is determined.

[0092] The following describes how to determine the category of the corresponding garment based on the category identifiers of the multiple components identified from the garment pattern.

[0093] In fact, as mentioned above, it is known which parts each category of clothing should contain, so the correspondence between clothing categories and component sets can be pre-set. Moreover, it is worth noting that different categories of clothing may have some overlapping parts, that is, there may be parts of the same category.

[0094] For example, suppose that the component set corresponding to clothing category C1 consists of: component a, component b and component c. The component set corresponding to clothing category C2 consists of: component a, component b and component d. It can be seen that component d is the key component for distinguishing C1 from C2. Assuming that for the current clothing pattern, component a, component b and component d are identified, then the corresponding clothing category can be determined to be C2.

[0095] Based on the above examples, it can be seen that if the component category identified in the clothing pattern is completely consistent with the component set corresponding to a certain clothing category Ci, or matches the key component set in the component set, then it can be considered that the clothing category corresponding to the clothing pattern is Ci. Among them, the key component refers to a component that can be distinguished from other clothing categories, such as component d in the above example. In other words, assuming that component a and component d are identified from the clothing pattern, and component d is unique to clothing category C2, then it can be determined that the clothing category corresponding to the clothing pattern is C2.

[0096] In summary, the above scheme can obtain the category identification of each of the multiple components in the clothing pattern and the multiple part information contained in each of the multiple components. Afterwards, it can be determined whether the clothing pattern meets the preset detection conditions according to the category identification of each of the multiple components and the multiple part information contained in each of the multiple components.

[0097] As mentioned above, if the preset detection condition is commonly used for various clothing, the preset detection condition can describe the following requirements: which components should be included in the input clothing pattern at least, which parts should be included on each component at least, and what requirements the attribute information related to each part should meet.

[0098] At this time, the components and part information identified from the garment pattern are compared with the above-mentioned preset detection conditions to determine whether the garment pattern meets the preset detection conditions.

[0099] In addition, as mentioned above, optionally, considering the differences between different categories of clothing, corresponding preset detection conditions can also be set specifically for different clothing categories.

[0100] Taking the preset detection conditions corresponding to any one of the clothing categories as an example, the preset detection conditions may describe the following requirements: a set of component category identifiers (i.e., a component set) corresponding to the clothing category and a plurality of reference part information corresponding to each of the component category identifiers, wherein the description of the reference part information is to distinguish it from the part information actually obtained from the clothing pattern.

[0101] After determining the target clothing category corresponding to the clothing corresponding to the clothing pattern based on the method introduced in the aforementioned embodiment, the preset detection condition corresponding to the target clothing category can be selected from the preset detection conditions corresponding to different clothing categories.

[0102] Furthermore, it is determined whether the category identification set composed of the category identifications of the multiple components identified from the garment pattern matches a set of component category identifications set in the preset detection conditions, so that the detection of component integrity can be completed, that is, whether the garment pattern includes all the components that the target garment category should include. And it is determined whether the multiple part information contained in each of the multiple components identified from the garment pattern matches the multiple reference part information corresponding to the corresponding component category identification set in the preset detection conditions, so that the detection of part information can be completed, that is, whether each component includes all the parts that should be included, and whether the relevant attribute information of each part also meets the requirements.

[0103] In summary, by presetting a detection condition corresponding to a certain garment, the automatic detection of the garment pattern can be completed based on the detection condition and the component and part information identified from the garment pattern corresponding to the garment.

[0104] For ease of understanding, the following Figure 3 To illustrate the implementation process of the above-mentioned clothing pattern detection solution.

[0105] exist Figure 3In the figure, a component included in a garment pattern corresponding to a garment is illustrated. When the garment pattern is sent to the detection device, the detection device identifies the category identification corresponding to the component based on the structural features of the component in the garment pattern (such as the outline of the component, the position and shape of each line on the outline), namely, the front piece of the top, and identifies multiple part information contained in the component, such as the multiple part identifications illustrated in the figure: front shoulder seam, front collar, front armhole, front side seam, and front hem. Afterwards, the above recognition results are compared with the preset detection conditions corresponding to the garment. Assuming that it is determined that these recognition results match the corresponding requirements in the preset detection conditions, the detection device can finally output a prompt message of "passed the detection".

[0106] Figure 4 A flowchart of a clothing pattern making method provided by an embodiment of the present invention, such as Figure 4 As shown, the method comprises the following steps:

[0107] 401. Obtain a clothing pattern, where the clothing pattern includes multiple parts of the clothing.

[0108] 402. Determine, according to respective structural features of the plurality of components, respective category identifiers of the plurality of components and respective plurality of part information contained in the plurality of components.

[0109] 403. Acquire production process information corresponding to the garment according to the category identifiers of the plurality of components, so as to determine whether it is necessary to modify the plurality of part information respectively included in the plurality of components according to the production process information, wherein the production process information corresponds to the manufacturer used to produce the garment.

[0110] The solution provided in this embodiment can be executed by an electronic device, such as a PC, a notebook computer, and the like.

[0111] The solution provided in this embodiment can assist pattern makers in completing the task of making clothing patterns.

[0112] Specifically, the clothing pattern mentioned in step 401 can be considered as a clothing pattern initially designed by a pattern master, and then through the processing of step 402, it can be obtained which components are included in the clothing pattern (i.e., the category identification of each of the multiple components) and the multiple part information contained in each component.

[0113] Since the clothing corresponding to the clothing pattern needs to be ultimately produced by a certain manufacturer (i.e., the clothing production factory mentioned above), as mentioned above, the information of each part in the clothing pattern needs to meet the requirements of the manufacturer. Therefore, in summary, after knowing the component category identification included in the above-mentioned clothing pattern, the production process information corresponding to each category identification can be obtained from the manufacturer, so that the pattern maker can determine whether the information of each part in the clothing pattern designed by himself matches the corresponding production process information of the manufacturer. If not, timely modification is made, thereby achieving the purpose of assisting the pattern maker in making clothing patterns based on the production process information of the manufacturer.

[0114] Specifically, in the process of obtaining the production process information corresponding to the garment according to the category identifiers of the respective multiple components, the category of the garment can be determined according to the category identifiers of the respective multiple components identified from the garment pattern, and then the production process information corresponding to the garment category can be obtained from the manufacturer. The production process information describes the different part information of different components, which is the reference part information mentioned above. The pattern maker can know whether the part information he originally gave matches the corresponding reference part information.

[0115] For the contents not introduced in this embodiment, please refer to the related descriptions in other embodiments above and will not be repeated here.

[0116] Figure 5 A flow chart of a detection method provided by an embodiment of the present invention, such as Figure 5 As shown, the method comprises the following steps:

[0117] 501. Obtain a graphic file corresponding to a preset object, where the graphic file includes multiple components of the object.

[0118] 502. Determine, according to respective structural features of the plurality of components, respective category identifiers of the plurality of components and respective plurality of part information contained in the plurality of components.

[0119] 503. Determine whether the graphic file satisfies a preset detection condition corresponding to the object according to the category identifiers of the multiple components and the multiple part information contained in the multiple components.

[0120] The detection method provided in this embodiment may be executed by an electronic device, which may be a terminal device such as a PC, a laptop, a mobile phone, or a server. The electronic device is hereinafter referred to as a detection device.

[0121] The detection method provided in the embodiment of the present invention can be applied to the scene of accuracy detection of a graphic file corresponding to a preset object, wherein the graphic file is generally a CAD file obtained by a relevant person performing graphic design of the object through a tool such as CAD.

[0122] In practical applications, the preset object may be, for example, the clothing mentioned above. At this time, the relevant personnel may be a pattern maker who completes the pattern making of clothing by using CAD tools so as to carry out subsequent clothing production work based on the obtained clothing pattern.

[0123] Of course, the above-mentioned preset objects are not limited to clothing. All objects that are ultimately formed by the fusion of multiple parts can be applicable to the detection method, such as products that are ultimately formed by the fusion of multiple mechanical parts through some connection methods.

[0124] It is understandable that before these objects are finally produced, they need to be graphically designed by, for example, a designer to obtain corresponding graphic files and perform detection processing on the graphic files.

[0125] Optionally, determining the category identification of each of the multiple components according to the structural features of each of the multiple components can be implemented as follows: extracting the contours of each of the multiple components; and determining the category identification of each of the multiple components according to the contours of each of the multiple components.

[0126] Thus, optionally, determining multiple part information contained in each of the multiple components can be implemented as follows: for any one of the multiple components, determining multiple lines corresponding to the multiple parts in the outline of the any one component; and determining attribute information of the multiple lines as the multiple part information contained in the any one component.

[0127] In addition, optionally, after determining the category identifiers of the multiple components, the category corresponding to the object can also be determined according to the category identifiers of the multiple components. In this case, the above-mentioned determination of the multiple lines corresponding to the multiple parts in the outline of any component can be specifically implemented as follows: according to the category corresponding to the object and the positional features of each line in the outline of the any component, the multiple lines corresponding to the multiple parts are determined in the outline of the any component.

[0128] Optionally, the preset detection conditions can be determined in the following manner: determine the manufacturer corresponding to the object, and determine the preset detection conditions corresponding to the object provided by the manufacturer. Further, after determining the category identifications of the above-mentioned multiple components, the category corresponding to the object can also be determined based on the category identifications of the multiple components, thereby determining the preset detection conditions corresponding to the category corresponding to the object. Determining the preset detection conditions corresponding to the category corresponding to the object may refer to determining the preset detection conditions corresponding to the category of the object mentioned by the above-mentioned manufacturer.

[0129] Optionally, the preset detection condition may include: a group of component category identifiers and a plurality of reference part information corresponding to each of the component category identifiers. Thus, according to the category identifiers of the plurality of components and the plurality of part information contained in the plurality of components, it is determined whether the graphic file meets the preset detection condition corresponding to the object, which can be specifically implemented as follows: determining whether the category identifier set composed of the category identifiers of the plurality of components matches the group of component category identifiers; determining whether the plurality of part information contained in the plurality of components matches the plurality of reference part information corresponding to the corresponding component category identifiers.

[0130] Optionally, the method further comprises: if it is determined that the graphic file does not meet the preset detection condition, outputting prompt information, wherein the prompt information is used to prompt the target component and target part information that do not meet the preset detection condition.

[0131] For the contents not introduced in this embodiment, please refer to the related descriptions in other embodiments above and will not be repeated here.

[0132] The following will describe in detail the garment pattern detection device, garment pattern making device, and detection device of one or more embodiments of the present invention. Those skilled in the art will appreciate that these devices can be configured using commercially available hardware components through the steps taught in this solution.

[0133] Figure 6 A schematic diagram of the structure of a clothing pattern detection device provided by an embodiment of the present invention is shown in FIG. Figure 6 As shown, the device includes: an acquisition module 11, a determination module 12, and a detection module 13.

[0134] The acquisition module 11 is used to acquire a clothing pattern, wherein the clothing pattern includes a plurality of parts of the clothing.

[0135] The determination module 12 is used to determine the category identification of each of the multiple components and the multiple part information respectively included in the multiple components according to the structural characteristics of each of the multiple components.

[0136] The detection module 13 is used to determine whether the clothing pattern meets the preset detection conditions corresponding to the clothing according to the category identifications of the multiple components and the multiple part information contained in the multiple components.

[0137] Figure 6 The device shown can perform the aforementioned Figures 1 to 3 The method provided in the illustrated embodiment, the detailed execution process and the technical effect can be found in the description of the aforementioned embodiment and will not be repeated here.

[0138] In one possible design, the above Figure 6 The structure of the clothing pattern detection device shown can be realized as an electronic device, such as Figure 7 As shown, the electronic device may include: a first processor 21, a first memory 22, and a first communication interface 23. The first memory 22 stores executable code, and when the executable code is executed by the first processor 21, the first processor 21 can at least implement the above-mentioned Figures 1 to 3 The clothing pattern detection method provided in the illustrated embodiment.

[0139] In addition, an embodiment of the present invention provides a non-transitory machine-readable storage medium, wherein an executable code is stored on the non-transitory machine-readable storage medium. When the executable code is executed by a processor of an electronic device, the processor can at least implement the above-mentioned Figures 1 to 3 The clothing pattern detection method provided in the illustrated embodiment.

[0140] Figure 8 A schematic diagram of the structure of a clothing pattern making device provided by an embodiment of the present invention is shown in FIG. Figure 8 As shown, the device includes: a first acquisition module 31 , a determination module 32 , and a second acquisition module 33 .

[0141] The first acquisition module 31 is used to acquire a garment pattern, wherein the garment pattern includes a plurality of garment components.

[0142] The determination module 32 is used to determine the category identification of each of the multiple components and the multiple part information respectively included in the multiple components according to the structural characteristics of each of the multiple components.

[0143] The second acquisition module 33 is used to acquire the production process information of the manufacturer corresponding to the garment according to the category identifications of the multiple components and the multiple part information contained in the multiple components, so that the user can determine whether the garment pattern needs to be modified based on the generated process information.

[0144] Figure 8 The device shown can perform the aforementioned Figure 4The method provided in the illustrated embodiment, the detailed execution process and the technical effect can be found in the description of the aforementioned embodiment and will not be repeated here.

[0145] In one possible design, the above Figure 8 The structure of the clothing pattern making device shown can be realized as an electronic device, such as Fig. 9 As shown, the electronic device may include: a second processor 41, a second memory 42, and a second communication interface 43. The second memory 42 stores executable code, and when the executable code is executed by the second processor 41, the second processor 41 can at least implement the above-mentioned Figure 4 The clothing pattern making method provided in the illustrated embodiment.

[0146] In addition, an embodiment of the present invention provides a non-transitory machine-readable storage medium, wherein an executable code is stored on the non-transitory machine-readable storage medium. When the executable code is executed by a processor of an electronic device, the processor can at least implement the above-mentioned Figure 4 The clothing pattern making method provided in the illustrated embodiment.

[0147] Fig.10 A schematic diagram of a detection device provided by an embodiment of the present invention is shown in FIG. Fig.10 As shown, the device includes: an acquisition module 51, a determination module 52, and a judgment module 53.

[0148] The acquisition module 51 is used to acquire a graphic file corresponding to a preset object, wherein the graphic file includes a plurality of components of the object.

[0149] The determination module 52 is used to determine the category identification of each of the multiple components and the multiple part information respectively included in the multiple components according to the structural characteristics of each of the multiple components.

[0150] The judgment module 53 is used to determine whether the graphic file meets the preset detection condition corresponding to the object according to the category identifications of the multiple components and the multiple part information contained in the multiple components.

[0151] Optionally, the device further comprises: an output module, for outputting prompt information if it is determined that the graphic file does not meet the preset detection condition, wherein the prompt information is used to prompt the target component and target part information that do not meet the preset detection condition.

[0152] Optionally, the determination module 52 may be specifically configured to: extract the contours of each of the plurality of components; and determine the category identifiers of each of the plurality of components according to the contours of each of the plurality of components.

[0153] Optionally, the determination module 52 may be specifically configured to: determine, for any one of the multiple components, multiple lines corresponding to multiple parts in the contour of the any one component; and determine attribute information of the multiple lines as multiple part information contained in the any one component.

[0154] Optionally, the determination module 52 can also be used to: determine the category corresponding to the object based on the category identifiers of the multiple components; determine multiple lines corresponding to multiple parts in the outline of any component based on the category corresponding to the object and the position characteristics of each line in the outline of any component.

[0155] Wherein, optionally, the preset object includes: clothing; the attribute information includes any one of the following: opening information, seam information, size information.

[0156] Optionally, the determination module 52 may also be used to: determine the category corresponding to the object according to the category identifiers of the multiple components; and determine the preset detection condition corresponding to the category corresponding to the object.

[0157] Optionally, the preset detection conditions include: a group of component category identifiers and a plurality of reference part information corresponding to each of the component category identifiers. Based on this, the judgment module 53 can be specifically used to: determine whether the category identifier set consisting of the category identifiers of the plurality of components matches the group of component category identifiers; determine whether the plurality of part information contained in each of the plurality of components matches the plurality of reference part information corresponding to the corresponding component category identifiers.

[0158] Fig.10 The device shown can perform the aforementioned Figure 6 The detection method provided in the illustrated embodiment, the detailed execution process and technical effects are described in the aforementioned embodiments and will not be repeated here.

[0159] In one possible design, the above Fig.10 The structure of the detection device shown can be implemented as an electronic device, such as Fig.11 As shown, the electronic device may include: a third processor 61, a third memory 62, and a third communication interface 63. The third memory 62 stores executable code, and when the executable code is executed by the third processor 61, the third processor 61 can at least implement the above-mentioned Figure 6 The detection method provided in the illustrated embodiment.

[0160] In addition, an embodiment of the present invention provides a non-transitory machine-readable storage medium, wherein an executable code is stored on the non-transitory machine-readable storage medium. When the executable code is executed by a processor of an electronic device, the processor can at least implement the above-mentioned Figure 6 The detection method provided in the illustrated embodiment.

[0161] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. Those of ordinary skill in the art may understand and implement the present invention without creative effort.

[0162] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by adding a necessary general hardware platform, and of course can also be implemented by combining hardware and software. Based on such an understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a computer product, and the present invention can be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0163] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A clothing pattern detection method, comprising: Obtaining a garment pattern, wherein the garment pattern includes a plurality of garment components; extracting contours of each of the plurality of components; Determining the category identification of each of the plurality of components according to the respective outlines of the plurality of components; Determining the category corresponding to the garment pattern according to the category identifiers of the respective components; Determine a preset detection condition corresponding to the category corresponding to the garment paper sample, wherein the preset detection condition corresponds to the manufacturer of the garment paper sample and is set for garment paper samples of different categories; For any one of the plurality of components, determining a plurality of lines corresponding to a plurality of locations in a contour of the any one of the plurality of components; Determining the attribute information of the plurality of lines as the plurality of part information included in any one of the components; According to the category identifications of the multiple components and the multiple part information contained in the multiple components, it is determined whether the clothing pattern meets the preset detection conditions.

2. A clothing pattern making method, comprising: Obtaining a garment pattern, wherein the garment pattern includes a plurality of garment components; extracting contours of each of the plurality of components; Determining the category identification of each of the plurality of components according to the respective outlines of the plurality of components; Determining the category corresponding to the garment pattern according to the category identifiers of the respective components; Determine a preset detection condition corresponding to the category corresponding to the garment paper sample, wherein the preset detection condition corresponds to the manufacturer of the garment paper sample and is set for garment paper samples of different categories; For any one of the plurality of components, determining a plurality of lines corresponding to a plurality of locations in a contour of the any one of the plurality of components; Determining the attribute information of the plurality of lines as the plurality of part information included in any one of the components; The production process information corresponding to the garment is obtained according to the category identifications of the multiple components, so as to determine whether it is necessary to modify the multiple part information respectively included in the multiple components according to the production process information, wherein the production process information corresponds to the manufacturer used to produce the garment.

3. A detection method comprising: Acquire a graphic file corresponding to a preset object, wherein the graphic file includes a plurality of components of the object; extracting contours of each of the plurality of components; Determining the category identification of each of the plurality of components according to the respective outlines of the plurality of components; Determining a category corresponding to the object according to the category identifiers of the respective components; Determining a preset detection condition corresponding to a category corresponding to the object, wherein the preset detection condition corresponds to a manufacturer of the object and is set for objects of different categories; For any one of the plurality of components, determining a plurality of lines corresponding to a plurality of locations in a contour of the any one of the plurality of components; Determining the attribute information of the plurality of lines as the plurality of part information included in any one of the components; According to the respective category identifiers of the multiple components and the multiple location information respectively included in the multiple components, it is determined whether the graphic file meets the preset detection condition.

4. The method according to claim 3, further comprising: Determining a producer corresponding to the object; The preset detection condition corresponding to the object provided by the manufacturer is determined.

5. The method according to claim 3, further comprising: If it is determined that the graphic file does not meet the preset detection condition, a prompt message is output, where the prompt message is used to prompt the target component and target part information that do not meet the preset detection condition.

6. The method according to claim 3, after determining the category identifications of the respective components, further comprising: Determining a category corresponding to the object according to the category identifiers of the respective components; Determining a plurality of lines corresponding to a plurality of locations in the contour of any one of the components comprises: According to the category corresponding to the object and the position characteristics of each line in the outline of any one of the components, a plurality of lines corresponding to a plurality of parts are determined in the outline of any one of the components.

7. The method according to claim 3, wherein the preset object comprises: clothing; The attribute information includes any one of the following: opening information, seam information, and size information.

8. The method according to claim 3, wherein the preset detection conditions include: A set of component category identifiers and a plurality of reference location information corresponding to each of the component category identifiers; The determining whether the graphic file satisfies the preset detection condition according to the respective category identifiers of the plurality of components and the plurality of part information respectively contained in the plurality of components comprises: Determining whether a set of category identifiers consisting of the category identifiers of the plurality of components matches the set of category identifiers of the component; It is determined whether the plurality of part information respectively included in the plurality of parts matches the plurality of reference part information corresponding to the corresponding part category identifier.

9. A detection device comprising: An acquisition module, used for acquiring a graphic file corresponding to a preset object, wherein the graphic file includes a plurality of components of the object; A determination module, configured to extract contours of each of the plurality of components; Determine the category identification of each of the multiple components according to the respective contours of the multiple components; determine the category corresponding to the object according to the respective category identification of the multiple components; determine a preset detection condition corresponding to the category corresponding to the object, wherein the preset detection condition corresponds to the manufacturer of the object and is set for objects of different categories; For any one of the plurality of components, determining a plurality of lines corresponding to a plurality of locations in a contour of the any one of the plurality of components; Determining the attribute information of the plurality of lines as the plurality of part information included in any one of the components; The judgment module is used to determine whether the graphic file meets the preset detection condition corresponding to the object according to the category identifications of the multiple components and the multiple part information contained in the multiple components.

10. An electronic device comprising: A memory, a processor, and a communication interface; wherein the memory stores executable code, and when the executable code is executed by the processor, the processor executes the detection method as described in any one of claims 3 to 8.

11. A non-transitory machine-readable storage medium having executable code stored thereon, and when the executable code is executed by a processor of an electronic device, the processor is caused to execute the detection method according to any one of claims 3 to 8.

12. An electronic device comprising: A memory, a processor, and a communication interface; wherein the memory stores executable code, and when the executable code is executed by the processor, the processor executes the clothing pattern detection method according to claim 1.

13. An electronic device comprising: A memory, a processor, and a communication interface; wherein the memory stores executable code, and when the executable code is executed by the processor, the processor executes the clothing pattern making method as described in claim 2.

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