Method and device for processing cutting data, garment manufacturing apparatus and medium

Abstract

The application discloses a kind of processing method of piece data, processing device, garment manufacturing equipment, storage medium.Processing method of piece data includes: obtaining piece file;The piece file is parsed to obtain at least one first data group;At least one first data group is fitted to the data of processing, obtains at least one second data group;Based on the data of at least one second data group, obtain a plurality of pending points of piece;According to the preset direction, a plurality of pending points are sorted to obtain a plurality of feature points and one feature data group between adjacent two feature points.The processing method of piece data in the above can reduce data amount, simplify data, reduce system control burden.

Description

Technical Field

[0001] This invention relates to the field of garment manufacturing technology, and in particular to a method, processing device, garment manufacturing equipment, and storage medium for processing pattern data. Background Technology

[0002] In related technologies, clothing design requires the use of specialized software. However, the design process generates a large amount of data, and analyzing this data is complex. Furthermore, the generated data is cumbersome and intricate, which can easily burden system control. Summary of the Invention

[0003] The present invention provides a method, apparatus, garment manufacturing equipment, and storage medium for processing pattern data to solve at least one of the aforementioned technical problems.

[0004] One embodiment of the present invention provides a method for processing cut piece data, which includes:

[0005] Obtain the cut image file;

[0006] The cut file is parsed to obtain at least one first data group;

[0007] The data from the at least one first data group are fitted to obtain at least one second data group;

[0008] Based on the data from the at least one second data group, multiple undetermined points of the cut piece are obtained;

[0009] The multiple undetermined points are sorted according to a preset direction to obtain multiple feature points and a feature data group between two adjacent feature points.

[0010] In the above-mentioned method for processing pattern data, fitting the first data set can reduce the amount of data, simplify the data, reduce the system control burden, and the resulting multiple feature points and multiple feature data sets can be used as template data or reference data for pattern pieces for subsequent sewing and other operations.

[0011] In some implementations, the first data group includes one or more polylines, each of which includes multiple data points;

[0012] The step of fitting the data of the at least one first data set to obtain at least one second data set includes:

[0013] The second data group is formed by fitting multiple data points of the polyline in the first data group.

[0014] In some implementations, the process of fitting multiple data points of the polyline in the first data set to form the second data set includes:

[0015] Calculate the first included angle between two line segments formed by sequentially connecting every three adjacent data points within each of the polyline segments;

[0016] When the first included angle is within a preset angle range, the data points located in the middle are removed and the data points located at both ends are retained.

[0017] In some implementations, obtaining multiple undetermined points of the cut piece based on the data from the at least one second data set includes:

[0018] Based on the data in the second data group, calculate the second included angle between the two line segments formed by connecting every three adjacent data points in the second data group in sequence;

[0019] When the second included angle is less than the preset angle, the middle data point of the three adjacent data points is taken as the cutoff point, and the cutoff point is taken as the undetermined point.

[0020] In some embodiments, sorting the plurality of undetermined points according to a preset direction to obtain a plurality of feature points and a feature data set between two adjacent feature points includes:

[0021] Based on the coordinates of the plurality of undetermined points, the first undetermined point located in a preset orientation is obtained as the first feature point;

[0022] Starting from the first undetermined point, sort the other undetermined points according to the preset direction to obtain other feature points, and then obtain a feature data group between two adjacent feature points.

[0023] In some embodiments, the method for processing the cut piece data further includes: outputting the plurality of feature points and the plurality of feature data groups.

[0024] In some implementations, the cutout file includes layers and tiles;

[0025] The step of parsing the cut-out file to obtain at least one first data set includes:

[0026] The layer is parsed to obtain at least one size type;

[0027] The image is parsed to obtain at least one piece type.

[0028] The at least one size type and the at least one piece type are grouped to obtain the at least one first data group, each first data group including a combination of a piece type and a size type.

[0029] An apparatus for processing fabricated piece data according to an embodiment of the present invention includes a processor and a memory. The memory stores a computer program, which, when executed by the processor, implements the steps of the fabricated piece data processing method of any of the above embodiments.

[0030] An embodiment of the present invention provides a garment manufacturing equipment including the fabric pattern data processing device described in the above embodiment.

[0031] This invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for processing cut piece data according to any of the above embodiments.

[0032] In the aforementioned processing device for pattern data, garment manufacturing equipment, and computer-readable storage medium, fitting the first data set can reduce the amount of data, simplify the data, and reduce the system control burden. Moreover, the multiple feature points and multiple feature data sets obtained can be used as template data or reference data for pattern pieces for subsequent sewing and other operations.

[0033] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0034] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, wherein:

[0035] Figure 1 This is a flowchart illustrating the method for processing cut piece data according to an embodiment of the present invention;

[0036] Figure 2 This is a graphic schematic diagram of the cut piece file of the front piece according to an embodiment of the present invention;

[0037] Figure 3 This is a graphic schematic diagram of the cut piece file of the back piece according to an embodiment of the present invention;

[0038] Figure 4 This is a schematic diagram showing the distribution of feature points of the rear piece in an embodiment of the present invention;

[0039] Figure 5 This is a flowchart illustrating the method for processing cut piece data according to an embodiment of the present invention;

[0040] Figure 6 This is a schematic diagram showing the distribution of three adjacent data points of a polyline according to an embodiment of the present invention;

[0041] Figure 7This is a flowchart illustrating the method for processing cut piece data according to an embodiment of the present invention;

[0042] Figure 8 This is a schematic diagram showing the distribution of three adjacent data points in the fitted data according to an embodiment of the present invention.

[0043] Figure 9 This is a flowchart illustrating the method for processing cut piece data according to an embodiment of the present invention;

[0044] Figure 10 This is a schematic diagram of the modules of the garment manufacturing equipment according to an embodiment of the present invention.

[0045] Explanation of key component symbols:

[0046] The garment includes a pattern data processing device 100, a garment manufacturing equipment 200, a pattern assembly device 300, a sewing device 400, a front piece 12, a back piece 14, a processor 16, a memory 18, a left hem 141, a left armpit 142, a left shoulder 143, a left collar 144, a right collar 145, a right shoulder 146, a right armpit 147, and a right hem 148. Detailed Implementation

[0047] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the embodiments of the present invention, and should not be construed as limiting the embodiments of the present invention.

[0048] Please refer to Figure 1 The present invention provides a method for processing cut piece data, comprising:

[0049] Step 101: Obtain the cut image file;

[0050] Step 103: Parse the cut-out file to obtain at least one first data group;

[0051] Step 105: Fit the data from at least one first data set to obtain at least one second data set;

[0052] Step 107: Based on data from at least one second data set, obtain multiple undetermined points for the cut piece;

[0053] Step 109: Sort multiple undetermined points according to a preset direction to obtain multiple feature points and a feature data group between two adjacent feature points.

[0054] In the above-mentioned method for processing pattern data, fitting the first data set can reduce the amount of data, simplify the data, reduce the system control burden, and the resulting multiple feature points and multiple feature data sets can be used as template data or reference data for pattern pieces for subsequent sewing and other operations.

[0055] Specifically, this invention does not specifically limit the format of the pattern file. In one embodiment, the pattern file can be a DXF (Drawing Exchange Format) file. The pattern file can be provided by relevant engineers of the garment company and can be uploaded to a personal computer, server, or database. The required pattern file can be obtained from a personal computer, server, or database. The pattern file includes data on the pattern pieces required for garment production, such as pattern type and size type. Pattern types may include, but are not limited to, front piece 12, back piece 14, back neck extension, collar, sleeve, etc. Size types include, but are not limited to, 2XS, XS, S, M, L, XL, 2XL, 3XL, 4XL. One or more pattern files can be obtained, and the pattern data of multiple pattern files can be processed simultaneously or at different times.

[0056] In one implementation, a pattern file may include multiple pattern types and multiple size types. Parsing the pattern file yields data for each pattern type and size type. The pattern types and size types are then grouped to obtain multiple first data groups, each containing a combination of each pattern type and each size type. For example, the pattern types may include front piece 12, back piece 14, back neck extension, collar, and sleeves. The size types may include 2XS, XS, S, M, L, XL, 2XL, 3XL, and 4XL. The front pieces are combined with each size type individually, starting with 2XS, then XS, S, M, L, XL, 2XL, 3XL, and 4XL, resulting in 9 first data groups. This process is repeated until a total of 45 first data groups are obtained. The obtained first data groups can then be populated into corresponding data containers.

[0057] Figure 2 The image shown is the cut file for front panel 12. The cut file for front panel 12 includes S front panel, M front panel, L front panel, and XL front panel. Figure 3 The cut file for back piece 14 is shown. The cut file for back piece 14 includes S back piece, M back piece, L back piece, and XL back piece.

[0058] In one implementation, a pattern file may include a pattern type and a size type. Parsing the pattern file yields data for a pattern type and data for a size type. The pattern type and size type are grouped to obtain a first data group, which includes combinations of a pattern type and a size type. For example, a pattern type may include one of front piece 12, back piece 14, back neckline, collar, and sleeve. A size type may include one of 2XS, XS, S, M, L, XL, 2XL, 3XL, and 4XL. Combining a size type with a pattern type yields a first data group, for example, the first data group may include one of 2XS front piece, XS front piece, S front piece, M front piece, L front piece, XL front piece, 2XL front piece, 3XL front piece, and 4XL front piece.

[0059] Fit the data from one or more first data sets to obtain one or more second data sets.

[0060] The characteristic points of the cut pieces can serve as reference points in the garment design and manufacturing process. For example, both the front piece 12 and the back piece 14 include 8 characteristic points. Please refer to... Figure 4 Taking the back piece 14 as an example, its eight feature points are: left lower hem 141, left armpit 142, left shoulder 143, left collar 144, right collar 145, right shoulder 146, right armpit 147, and right lower hem 148. When joining the front piece 12 and the back piece 14, visual positioning technology can be used to align the feature points of the front piece 12 with those of the back piece 14. Then, the front piece 12 and the back piece 14 are overlapped and sewn together.

[0061] In one implementation, please refer to Figure 4 The preset direction can be clockwise. After obtaining 8 undetermined points, the 8 undetermined points are sorted in a clockwise direction. The 8 sorted feature points are: left lower hem 141, left armpit 142, left shoulder 143, left collar 144, right collar 145, right shoulder 146, right armpit 147, and right lower hem 148.

[0062] A feature data set between two adjacent feature points includes data points located between two adjacent feature points in the second data set. These data points include coordinate positions. Multiple feature points and multiple feature data sets can determine the size of the outer contour of the fabric piece. For example, after fitting the data from the first data set of the 2XS front piece, the second data set of the 2XS front piece is obtained. Based on the second data set of the 2XS front piece, eight undetermined points of the 2XS front piece are obtained. These eight undetermined points are then sorted clockwise to obtain eight feature points of the 2XS front piece: left lower hem, left armpit, left shoulder, left collar, right collar, right shoulder, right armpit, and right lower hem, as well as a feature data set between each pair of adjacent feature points, thus obtaining multiple feature data sets.

[0063] The outer contour dimensions of the 2XS front piece can be determined by eight feature points and a set of feature data between each pair of adjacent feature points, corresponding to size 2XS. These eight feature points and the set of feature data between each pair of adjacent feature points can serve as reference or standard template data for front piece 12. This data can be subsequently used for piece assembly, determining the sewing path, judging the usability and anomalies of the cut pieces, and filtering out abnormal cut pieces, such as those with missing corners, incomplete cut pieces, or incorrect sizes.

[0064] In some implementations, the cut-out file includes layers and tiles; please refer to... Figure 5 Step 103 includes:

[0065] Step 1031: parse the layer to obtain at least one size type;

[0066] Step 1033: Parse the image to obtain at least one piece type;

[0067] Step 1035: Group at least one size type and at least one piece type to obtain at least one first data group, each first data group including a combination of a piece type and a size type.

[0068] In this way, the pattern file can be parsed to obtain the size type and pattern type.

[0069] Specifically, in one implementation, the pattern file may include multiple layers, each layer comprising multiple tiles. A layer can be defined as a size type, and a tile as a pattern type within the pattern file.

[0070] For example, the pattern file includes 9 layers: 2XS, XS, S, M, L, XL, 2XL, 3XL, and 4XL. Each layer contains 5 patterns: front piece pattern, back piece pattern, back neckline overlay pattern, collar pattern, and sleeve pattern. Parsing the layers yields the 9 layers: 2XS, XS, S, M, L, XL, and 2XL. Parsing the patterns in each layer yields the 5 patterns: front piece pattern, back piece pattern, back neckline overlay pattern, collar pattern, and sleeve pattern.

[0071] The obtained 9 size types and 5 pattern piece types were grouped to obtain 45 first data groups.

[0072] In some implementations, the first data group is one or more polylines, each polyline including multiple data points;

[0073] Step 105 includes:

[0074] The second data set is formed by fitting multiple data points of the polyline in the first data set.

[0075] In this way, the data points of the multi-segment line can be fitted to obtain the second data set.

[0076] Specifically, the pattern file can be provided by the relevant engineers at the garment company. Due to various reasons, such as requirements for certain garment details, the pattern file is drawn using polylines, for example, in... Figure 3 If you zoom in on the "vertical line" on the left, it is drawn from multiple polylines. A polyline is made up of two or more lines connected together. A polyline may contain multiple points or an infinite number of points. A polyline is defined by the pattern file. When parsing the pattern file, all polylines can be obtained. Each polyline includes multiple data points.

[0077] By fitting multiple data points within each polyline, a second data set can be obtained.

[0078] In some implementations, fitting multiple data points of the polyline in the first data set to form the second data set includes:

[0079] Calculate the first included angle between the two line segments formed by connecting every three adjacent data points within each polyline;

[0080] When the first included angle is within the preset angle range, the data points located in the middle are removed and the data points located at both ends are retained.

[0081] In this way, specific fitting processing can be performed.

[0082] Specifically, in one implementation, the preset angle range can be [175°, 185°], which can be understood as the line segment formed by three adjacent data points tending towards 180 degrees. Please refer to... Figure 6 Let E, F, and G be three adjacent data points. Connecting them sequentially forms two line segments, EF and FG, respectively. The first angle between line segments EF and FG is H. When the first angle H is within a preset angle range [175°, 185°], it can be determined that the three adjacent data points E, F, and G are approximately arranged along a straight line, tending towards a 180-degree arrangement. The three adjacent data points E, F, and G can be fitted, specifically by removing the middle data point F and retaining the data points E and G at both ends, thereby reducing the amount of data. It is understood that in other embodiments, the preset angle range can also be other angle ranges, and is not limited to [175°, 185°].

[0083] In one embodiment, the above processing can be performed on all polyline data points to obtain a second data set. In another embodiment, the above processing can be performed on a subset of polyline data points to obtain a second data set, for example, in... Figure 4 In this process, the data points of one or more polylines between the left lower hem 141 and the left armpit 142, one or more polylines between the left shoulder 143 and the left collar 144, one or more polylines between the right collar 145 and the right shoulder 146, and one or more polylines between the right armpit 147 and the right lower hem 148 can be processed as described above to obtain the second data group. It should be noted that although the data points of the polylines between the left armpit 142 and the left shoulder 143, the left collar 144 and the right collar 145, and the right shoulder 146 and the right armpit 147 are not processed as described above, the second data group still includes the data points of these polylines.

[0084] In some implementations, please refer to Figure 7 Step 107 includes:

[0085] Step 1071: Based on the data of the second data group, calculate the second included angle between the two line segments formed by connecting every three adjacent data points in the second data group in sequence;

[0086] Step 1073: When the second included angle is less than the preset angle, the middle data point of three adjacent data points is taken as the cutoff point, and the cutoff point is taken as the point to be determined.

[0087] In this way, multiple points can be obtained.

[0088] Specifically, the data in the second data group is the data after fitting the data in the first data group. For example, in the first data group, a polyline has multiple data points. After fitting, the number of data points for that polyline can be reduced, and some data points of that polyline can be retained to form the second data group. This can reduce the amount of data and prevent the data to be sent out from being too bloated.

[0089] In one implementation, during the design phase, feature points of the cut pieces can be determined to facilitate identification and sewing. Therefore, in the second data set, when the second included angle between two line segments formed by connecting three adjacent data points sequentially is less than a preset angle, the intermediate data point can be used as a cutoff point for truncation, thereby obtaining multiple cutoff points, which can be used as points to be determined.

[0090] For example, please refer to Figure 8 The fitted second data set includes multiple data points, each consisting of three adjacent data points A, B, and C. These three data points A, B, and C are connected sequentially to form two line segments AB and BC. The second included angle P between line segments AB and BC is calculated. When the second included angle P is less than a preset angle, it can be determined that a feature point appears among the three adjacent data points on the fabric piece. Furthermore, the feature point is the middle data point B, which can be used as a cutoff point and thus one of the undetermined points. By performing the above processing on every three adjacent data points, eight cutoff points can be obtained, resulting in eight undetermined points.

[0091] In one example, the preset angle can be 165°. When the second included angle P is less than 165°, it can be determined that a feature point appears among three adjacent data points on the cut piece, and the feature point is the middle data point B. The middle data point B can be used as the cut-off point. It is understood that in other embodiments, the second included angle can be other angles, and is not limited to 165°.

[0092] In some implementations, please refer to Figure 9 Step 109 includes:

[0093] Step 1091: Based on the coordinates of multiple undetermined points, obtain the first undetermined point located in a preset orientation as the first feature point;

[0094] Step 1093: Starting from the first undetermined point, sort the other undetermined points in the preset direction to obtain other feature points, and then obtain a feature data group between two adjacent feature points.

[0095] In this way, multiple undetermined points can be sorted to obtain multiple feature points and multiple feature data sets.

[0096] Specifically, through the truncation operation described above, multiple cutoff points can be obtained as multiple undetermined points, the positions of which on the cut piece have not yet been determined. In the example above, after obtaining cutoff point B as one of the undetermined points, it is still necessary to further determine which feature point B is among the left lower hem, left armpit, left shoulder, left collar, right collar, right shoulder, right armpit, and right lower hem.

[0097] In this embodiment, the location of the undetermined point can be determined using its coordinates within the coordinate system of the cut-out file itself. Based on the coordinates of multiple undetermined points, a first undetermined point located at a preset orientation is selected as the first feature point. Specifically, the first undetermined point located at the preset orientation can be determined by comparing the X and Y coordinates of multiple undetermined points. It is understood that the first undetermined point is related to the selected preset orientation.

[0098] In one example, the preset orientation can be the lower left corner, and the preset direction is clockwise. Taking the back piece 14 as an example, find the lower left corner among the eight undetermined points of the back piece 14 as the first feature point. Specifically, among the multiple undetermined points in the current second data group, the undetermined point with the leftmost X coordinate and the lowest Y coordinate is taken as the first feature point of the lower left corner. This first feature point is the lower left hem 141 feature point. Then, starting from the first undetermined point, the other 7 undetermined points are sorted clockwise to obtain the other 7 feature points: left armpit 142, left shoulder 143, left collar 144, right collar 145, right shoulder 146, right armpit 147, and right hem 148. Finally, 8 feature points are obtained: left hem 141, left armpit 142, left shoulder 143, left collar 144, right collar 145, right shoulder 146, right armpit 147, and right hem 148. The data between two adjacent feature points are used as feature data groups.

[0099] It is understandable that in other examples, the preset location can also be other locations, such as the bottom right corner, the top left corner, etc., and is not limited to the bottom left corner. The preset direction can also be other directions, such as counterclockwise, etc., and is not limited to clockwise; no specific limitation is made here.

[0100] In some implementations, the method for processing the cut piece data further includes: outputting multiple feature points and multiple feature data groups.

[0101] In this way, multiple feature points and multiple feature data sets can be used for other operations.

[0102] Specifically, the obtained feature points and feature data sets can be output to other devices, equipment, or components, such as lamination devices or sewing devices, for use in subsequent lamination and sewing operations. Since the feature data sets are fitted data, the amount of data can be reduced, the system's data processing burden can be lessened, and production efficiency can be improved. Additionally, it can also address the "labor shortage" problem by replacing some repetitive labor.

[0103] Please refer to Figure 10 An embodiment of the present invention provides a fabrication data processing apparatus 100, which includes a processor 16 and a memory 18. The memory 18 stores a computer program, and when the computer program is executed by the processor 16, it implements the steps of the fabrication data processing method of any of the above embodiments.

[0104] A garment manufacturing equipment 200 according to an embodiment of the present invention includes the fabric pattern data processing device 100 of the above embodiment.

[0105] Specifically, in one embodiment, the fabric piece data processing device 100 may include at least one of a personal computer and a server. The service manufacturing equipment 200 also includes a fabric assembly device 300 and a sewing device 400. The fabric piece data processing device 100 is electrically connected to the fabric assembly device 300 and the sewing device 400. The fabric piece data processing device 100 outputs processed fabric piece data to the fabric assembly device 300 and the sewing device 400. The fabric assembly device 300 can perform fabric assembly operations using the fabric piece data output by the fabric piece data processing device 100, and the sewing device 400 can perform sewing operations using the fabric piece data output by the fabric piece data processing device 100. The fabric assembly device 300 can also use the fabric piece data output by the fabric piece data processing device 100 to determine whether the fabric pieces are abnormal in order to filter out abnormal fabric pieces, such as fabric pieces with missing corners, incomplete pieces, or incorrect sizes.

[0106] The present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor 16, implements the steps of the method for processing cut piece data according to any of the above embodiments.

[0107] In one embodiment, the method for processing cut piece data implemented when the computer program is executed by the processor 16 includes:

[0108] Step 101: Obtain the cut image file;

[0109] Step 103: Parse the cut-out file to obtain at least one first data group;

[0110] Step 105: Fit the data from at least one first data set to obtain at least one second data set;

[0111] Step 107: Based on data from at least one second data set, obtain multiple undetermined points for the cut piece;

[0112] Step 109: Sort multiple undetermined points according to a preset direction to obtain multiple feature points and a feature data group between two adjacent feature points.

[0113] In the above-mentioned fabric data processing device 100, garment manufacturing equipment 200 and computer-readable storage medium, the first data group is fitted, which can reduce the amount of data, simplify the data, reduce the system control burden, and the obtained multiple feature points and multiple feature data groups can be used as template data or reference data for the fabric pieces for subsequent sewing and other operations.

[0114] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0115] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more steps for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0116] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, combinations, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for processing cut piece data, characterized in that, include: Obtain the cut image file; The cut file is parsed to obtain at least one first data group; The data from the at least one first data group are fitted to obtain at least one second data group; Based on the data from the at least one second data group, multiple undetermined points of the cut piece are obtained; The multiple undetermined points are sorted according to a preset direction to obtain multiple feature points and a feature data group between two adjacent feature points; The first data group includes one or more polylines, and each polyline includes multiple data points; The step of fitting the data of the at least one first data set to obtain at least one second data set includes: The second data group is formed by fitting multiple data points of the polyline in the first data group; The step of fitting multiple data points of the polyline in the first data set to form the second data set includes: Calculate the first included angle between two line segments formed by sequentially connecting every three adjacent data points within each of the polyline segments; When the first included angle is within a preset angle range, the data points located in the middle are removed and the data points located at both ends are retained.

2. The method for processing cut piece data according to claim 1, characterized in that, The step of obtaining multiple undetermined points of the cut piece based on the data from the at least one second data group includes: Based on the data in the second data group, calculate the second included angle between the two line segments formed by connecting every three adjacent data points in the second data group in sequence; When the second included angle is less than the preset angle, the middle data point of the three adjacent data points is taken as the cutoff point, and the cutoff point is taken as the undetermined point.

3. The method for processing cut piece data according to claim 1, characterized in that, The step of sorting the plurality of undetermined points according to a preset direction to obtain a plurality of feature points and a feature data group between two adjacent feature points includes: Based on the coordinates of the plurality of undetermined points, the first undetermined point located in a preset orientation is obtained as the first feature point; Starting from the first undetermined point, sort the other undetermined points according to the preset direction to obtain other feature points, and then obtain a feature data group between two adjacent feature points.

4. The method for processing cut piece data according to claim 1, characterized in that, The method for processing the cut piece data further includes: outputting the plurality of feature points and the plurality of feature data groups.

5. The method for processing cut piece data according to claim 1, characterized in that, The cut-out file includes layers and tiles; The step of parsing the cut-out file to obtain at least one first data set includes: The layer is parsed to obtain at least one size type; The image is parsed to obtain at least one piece type. The at least one size type and the at least one piece type are grouped to obtain the at least one first data group, each first data group including a combination of a piece type and a size type.

6. A device for processing cut piece data, characterized in that, The device includes a processor and a memory, the memory storing a computer program that, when executed by the processor, implements the steps of the method for processing cut piece data according to any one of claims 1-5.

7. A garment manufacturing equipment, characterized in that, The device includes the fabricated piece data processing apparatus as described in claim 6.

8. A computer-readable storage medium storing a computer program thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for processing cut piece data according to any one of claims 1-5.

Images