CN118277600B - Automatic size matching method for drawing software - Google Patents
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Abstract
The invention provides a size automatic matching method for drawing software, which relates to the technical field of data processing, and comprises the following steps: the method comprises the steps of receiving a dimension automatic matching instruction, adjusting a configuration unit to be in an activated state, restraining the configuration unit in the activated state based on input features of a user, completing initial response of the configuration unit, carrying out layer identification on a target drawing, positioning a calibration layer, carrying out marking isolation to generate marking and marking mapping of line segments in the layer, carrying out marking isolation to the calibration layer feature traversal through the configuration unit, obtaining a feature traversal result, carrying out traversal sequence marking update through the marking mapping, and carrying out automatic marking through the update result.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an automatic size matching method for drawing software.
Background
With the rapid development of social economy, the evolution of scientific technology makes computer technology increasingly perfect and popular. In such an age background, conventional hand-drawn designs have not been adaptable to the development of the age for designers working with flat designs. Therefore, in the process of designing planar works, hand-drawn design is changed into planar design by using a computer, and CAD can be contained in drawing software, which is design software widely applied to the engineering field and can be used for drawing various drawings quickly and efficiently. The dimension association is a very important ring in CAD design, and can ensure the accuracy and editability of the drawing, but in the prior art, the adaptability of automatically matching the dimension of the drawing is poor, so that the technical problem of poor dimension matching accuracy is caused.
Disclosure of Invention
The application provides an automatic size matching method for drawing software, which is used for solving the technical problem of poor size matching accuracy caused by poor adaptability of automatic size matching of drawings in the prior art.
In view of the above, the present application provides an automatic size matching method for drawing software.
In a first aspect, the present application provides a method for automatically matching dimensions of drawing software, the method comprising: receiving an automatic size matching instruction, and adjusting the configuration unit to an activated state; acquiring input features of a user, wherein the input features comprise size features, type features to be marked and marking constraint features; performing configuration unit constraint of an activation state based on the input characteristics, and completing initial response of the configuration unit; carrying out layer identification on the target drawing, and positioning and calibrating the layer; marking and isolating the calibration layer, and generating mark mapping of marking and line segments in the layer; marking the isolated calibration layer feature traversal through the configuration unit to obtain a feature traversal result, wherein the feature traversal result has traversal sequence identifiers; and performing traversal sequence identification updating through the identification mapping, and executing automatic labeling through an updating result.
In a second aspect, the present application provides an automatic size matching system for drawing software, the system comprising: the instruction receiving module is used for receiving the automatic size matching instruction and adjusting the configuration unit to be in an activated state; the device comprises a first feature module, a second feature module and a third feature module, wherein the first feature module is used for acquiring input features of a user, and the input features comprise size features, type features to be marked and marking constraint features; the constraint module is used for performing configuration unit constraint of an activation state based on the input characteristics and completing initial response of the configuration unit; the layer identification module is used for carrying out layer identification on the target drawing and positioning and calibrating the layer; the marking isolation module is used for marking and isolating the calibration layer and generating marking and marking mapping of the marking and the line segments in the layer; the feature traversing module is used for performing feature traversing of the marked and isolated calibration layer through the configuration unit to obtain a feature traversing result, wherein the feature traversing result is provided with a traversing sequence identifier; and the automatic labeling module is used for updating the traversal sequence identifiers through the identifier mapping and executing automatic labeling through the updating result.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
The automatic size matching method for drawing software provided by the application relates to the technical field of data processing, solves the technical problem of poor size matching accuracy caused by poor adaptability of automatic size matching of drawings in the prior art, realizes reasonable and accurate management and control of automatic size matching of the drawings, and further improves the size matching accuracy.
Drawings
FIG. 1 is a schematic flow chart of an automatic size matching method for drawing software;
fig. 2 is a schematic diagram of a dimension automatic matching system for drawing software according to the present application.
Reference numerals illustrate: the system comprises an instruction receiving module 1, a first characteristic module 2, a constraint module 3, a layer identification module 4, a labeling isolation module 5, a characteristic traversing module 6 and an automatic labeling module 7.
Detailed Description
The application provides the automatic size matching method for the drawing software, which is used for solving the technical problem of poor size matching accuracy caused by poor adaptability of automatic size matching of drawings in the prior art.
Example 1
As shown in fig. 1, an embodiment of the present application provides a method for automatically matching dimensions of drawing software, the method including:
step A100: receiving an automatic size matching instruction, and adjusting the configuration unit to an activated state;
In the application, the automatic size matching method for drawing software provided by the embodiment of the application is applied to an automatic size matching system of drawing software,
In order to more accurately automatically match the dimensions of the target drawing, the automatic dimension matching instruction is received through drawing software, the drawing software can be CAD, the CAD is mainly used for specially designing engineering software, drawing machinery, construction drawing such as building and the like, two-dimensional drawing and three-dimensional drawing can be performed, the automatic dimension matching instruction refers to an instruction for inputting the target drawing into the drawing software to automatically mark partial characteristics of the target drawing, meanwhile, the configuration unit is adjusted to be in an activated state, the automatic dimension matching module in the configuration unit is activated, and the automatic dimension matching module is used for carrying out dimension matching on graphics in each drawing layer contained in the target drawing and is used as an important reference basis for realizing automatic dimension matching through drawing software in the later stage.
Step A200: acquiring input features of a user, wherein the input features comprise size features, type features to be marked and marking constraint features;
In the application, in order to automatically match the size of the target drawing through the drawing software in a later more accurate mode, firstly, the content input into the drawing software by a user is extracted based on the target drawing, the input characteristics can comprise size characteristics, type characteristics to be marked and marking constraint characteristics, the size characteristics refer to the data such as the length, the angle size, the length of a circle diameter, the coaxiality and the like of a line segment contained in the target drawing, the feature of the type to be marked refers to the dimension feature which is not automatically matched and marked in the target drawing after the target drawing is input into drawing software and is marked by the dimension automatic matching instruction, the marking constraint feature refers to the feature which is used for limiting the marked dimension in the target drawing, the marking constraint feature can be accurately marked on the target drawing through the drawing software so as to ensure that the position of the marking constraint feature is consistent with the actual situation, and if a plurality of marking constraint features exist on the target drawing, different symbols or colors can be used for distinguishing, for example: for marking the size and limiting conditions of constraint features, standard size marks such as diameters, lengths, angles and the like can be used, specific numerical values or tolerance ranges are noted, and further automatic size matching through drawing software is guaranteed.
Step A300: performing configuration unit constraint of an activation state based on the input characteristics, and completing initial response of the configuration unit;
further, the step a300 of the present application further includes:
Step a310: analyzing the input features, determining the number of key feature points according to the features of the type to be marked, and finishing initial point fixing of the key feature points;
Step A320: fixing the residual key feature points through the size features, and rotating to establish a matching feature set by taking the initial points as rotation centers;
Step a330: and completing configuration unit constraint by the matched feature set.
In the application, in order to ensure configuration response data in a configuration unit, configuration unit constraint of the activation state is needed by the obtained input features, namely, the input features are analyzed, namely, the input features are searched, processed, analyzed and valuable data are mined, meanwhile, relations among all components in the data are analyzed, further, the number of key feature points in a target drawing is determined according to the feature of the type to be marked, the point corresponding to the feature of the type to be marked is marked as the key feature point, the number of the feature of the type to be marked in the target drawing is calculated and is marked as the number of the key feature points, because the key feature points do not contain distance features, only a single point is subjected to point location, the fixed position of the initial point of the key feature point is determined on the basis, the method comprises fixing the rest key feature points except key feature points by size features, and rotating to establish a matching feature set by taking an initial point as a rotation center, wherein, for example, if the key feature points are single line segments, the rest key feature points are all line segment positions except single line segment positions after 360-degree rotation is carried out on the single line segments, the initial point is any point in the line segments, iterating all key feature points on the basis, integrating and integrating the matched features of all rest key features, and finally limiting the feature constraint of the configuration unit in an activated state according to the matching feature set, thereby completing the initial response of the configuration unit, wherein, the initial response means that the output of the configuration unit is gradually increased from zero time until the configuration unit is stabilized at a specific value in the initial state of the configuration unit, and (3) carrying out automatic size matching tamping foundation through drawing software for subsequent realization.
Step A400: carrying out layer identification on the target drawing, and positioning and calibrating the layer;
in the application, in order to improve the accuracy of automatic size matching of a target drawing by drawing software, the drawing layer of the target drawing is required to be identified, the drawing layer of the target drawing is the drawing layer of an edited target drawing object, which is used for distinguishing different editing objects or different image blocks in the same drawing, and the calibration drawing layer is positioned on the basis of the drawing layer, namely, the calibration drawing layer does not contain the characteristic of marking constraint features, namely, the basic drawing layer does not contain the characteristic of line segment width, color and the like, so that the positioning and identification of the calibration drawing layer are completed in the target drawing, and the automatic size matching by the drawing software is realized.
Step A500: marking and isolating the calibration layer, and generating mark mapping of marking and line segments in the layer;
According to the method, marking information in the marking image layer and image information in the target drawing are segmented, marking isolation of the marking image layer is achieved, meanwhile, according to the association mapping relation between the marking information after marking isolation and the image information in the target drawing, identification mapping between the marking information and line segments in the image layer where the target drawing is located is correspondingly generated, namely, one value is taken in the marking information, one value is taken in the line segments in the image layer, the marking information can be corresponding to a plurality of values, and identification mapping between the line segments in the image layer and the marking information is achieved on the basis, so that the line segments can be used as reference data when size automatic matching is conducted through drawing software in the later period.
Step A600: marking the isolated calibration layer feature traversal through the configuration unit to obtain a feature traversal result, wherein the feature traversal result has traversal sequence identifiers;
In the application, in order to realize the operation of automatically matching the size of a target drawing in a quick and accurate way, firstly, marking feature information and image information in the target drawing are required to be traversed by a configuration unit on a marked layer after marking isolation, namely, marking feature information and image information in each layer contained in the marked layer are sequentially accessed and identified one by one, namely, the traversing time sequence corresponding to the marking feature information and the image information is indicated, the marking feature information can comprise line segment feature information, angle feature information, circle feature information, coaxiality feature information and the like, the image information in the target drawing can comprise axis information, graphic information and the like, a feature traversing result is generated according to the marked layer after finishing feature traversing on the basis, and meanwhile, each feature data in the feature traversing result correspondingly comprises an identifier of traversing sequence, so that the accuracy of automatically matching the size through the drawing software is improved in the later stage.
Step A700: and performing traversal sequence identification updating through the identification mapping, and executing automatic labeling through an updating result.
Further, the step a700 of the present application further includes:
step a710: carrying out layer identification on the target drawing and positioning a complete layer;
step A720: positioning the point to be marked based on the updated result to generate a positioning result;
step a730: inputting the positioning result and the complete layer into a distribution constraint network to determine a pre-distribution space;
Step a740: and completing automatic labeling control through the pre-distribution space.
Further, the step a700 of the present application further includes:
step a750: judging whether the configuration unit is continuously in an activated state or not;
step a760: if the configuration unit is continuously in an activated state, continuous identification of the configuration unit is executed;
step a770: when the node identifies the newly added matching feature at any time, a corresponding response label is generated;
step A780: and carrying out automatic annotation management according to the response annotation.
In the method, firstly, mapping identifiers are used as reference data to update the obtained traversal sequence identifiers to obtain an update result, namely, image layer identification is carried out based on image information, labeling information and labeling constraint information in a target drawing, namely, at least each image layer corresponds to one information, a plurality of image layers can be corresponding to the image information, the labeling information and the labeling constraint information, then all the image layers are integrated and then output as complete image layers, meanwhile, the updated traversal sequence identifiers are used as the basis to position points to be marked in the target drawing, namely, labeling information contained in the update result is removed from the target drawing based on all the markable points in the target drawing, and the rest points are marked as points to be marked, so that a positioning result is generated, further, the positioning result and the complete image layers are input into a distribution constraint network, and the distribution constraint network is an artificial neural network model for processing unstructured data, namely, the data structure is irregular or incomplete, a predefined data model is not convenient to use, and the data represented by a database two-dimensional logic table is not convenient. The method is mainly used for processing data such as images, voice, natural language and the like, and can realize geometric transformation of input data by introducing a space transformer network, so that the constraint capability of a distributed constraint network on positioning results and complete layers under abnormal and dangerous conditions is improved. In addition, the distribution constraint network can also effectively capture the local correlation of the input data, so that the pre-distribution space is determined, wherein the pre-distribution space is the characteristic space obtained by processing a positioning result and a complete image layer through a multi-layer neural network in deep learning. In this space, the positioning results of different categories and the complete layer are distributed in different areas, so that a classifier can be used to classify the new positioning results as well as the complete layer. The pre-distribution space is mainly used for mapping the positioning result and the complete image layer to a low-dimensional vector space, so that the relation between the positioning result and the complete image layer is more clear and easy to process. In the space, similar samples are mapped to similar positions, so that the similarity judgment is easier, and finally, the automatic labeling control of the target drawing size is finished through the pre-distribution space.
Furthermore, in order to improve the accuracy of automatic labeling control, reasonable control needs to be performed on the target drawing in the automatic labeling process, whether the configuration unit is continuously in an activated state is judged, and the configuration unit can calculate an output value through an activation function. Common activation functions include sigmoid functions, reLU functions, and the like. By passing the input data to the configuration unit and applying the activation function, a corresponding output value can be obtained. Once the output value of the configuration unit is obtained, it can be compared with a preset threshold value. If the output value exceeds the threshold value, the configuration unit may be considered to be in an active state; otherwise, it can be considered to be in an inactive state. By observing whether the output value of the configuration unit exceeds a preset threshold. Specifically, if the output value of the configuration unit exceeds a set threshold value, it can be considered to be in an activated state; conversely, if the output value is below the threshold value, it may be considered to be in an inactive state.
If the configuration unit is continuously in the activated state, the continuous identification of the configuration unit is performed, and the continuous identification of the configuration unit refers to judging whether any specific configuration unit is continuously in the activated state in a period of time in the neural network. It means that the configuration unit can be observed through time windows, i.e. first a time window is set, and the output state of the configuration unit is observed in each time window. A configuration unit is considered to be in a continuously active state if it is in an active state for a plurality of consecutive time windows. Further, when the node at any time identifies the newly added matching feature, a corresponding response label is generated, and the response label is used for automatically updating to reflect the changes when the identified newly added matching feature changes, and finally updating management is carried out on the target drawing in the process of automatic labeling according to the response label.
Further, step a730 of the present application includes:
step A741: generating alignment constraint of the label based on the label isolation result;
step A742: space positioning of the pre-distributed space is performed through the alignment constraint;
step a743: judging whether a positioning result of space conflict exists, if so, executing neighborhood space optimization of corresponding labels;
Step a744: and performing space positioning optimization according to the neighborhood space optimizing result, and completing automatic labeling control based on the optimized space positioning.
Further, step a730 of the present application includes:
Step A745: generating a new added labeling result through the optimized space positioning and updating result, wherein the new added labeling result is stored in a new added labeling layer;
Step a746: placing the newly added labeling layer in a selected state, and performing labeling grid segmentation according to the optimized space positioning to create a grid selected space;
step a747: establishing a one-to-one connection relation between the grid selected space and the newly added labeling result, and placing the grid selected space in a dynamic state;
Step a748: and acquiring a selection confirmation result of the user, and managing the dynamic newly-added labeling result according to the selection confirmation result.
Further, step a730 of the present application includes:
step a749: when receiving a confirmation instruction of a user, synchronously generating a layer locking instruction;
Step a7410: and performing layer locking management of the newly added marked layers based on the layer locking instruction.
In the method, firstly, a marked alignment constraint is generated through a marked isolation result, the marked alignment constraint is used for constraining marked information, namely, constraining the distance of marked information, namely, constraining horizontal distance, vertical size or inclined size and the like, and then the marked information is quantized in space through the alignment constraint in a pre-distribution space, namely, the marked information is mapped into a vector space under the size constraint in the alignment constraint to finish the space positioning of the marked information in the pre-distribution space, further, judging whether a positioning result of space conflict exists in the pre-distribution space, if so, considering that the position of the marked information exists and the image information overlap, and simultaneously executing neighborhood space optimizing corresponding to the marked, namely, searching and evaluating candidate solutions in the neighborhood space to find an optimal solution. In any one of the neighborhood spaces, a set of possible candidate solutions may be generated by making minor changes or modifications to the labeling information. Then, by evaluating the performance or objective function value of the candidate solutions, selecting the optimal solution as the current solution, and continuing to search in the neighborhood space of the new solution until the stopping condition is met, further, optimizing the space positioning according to the neighborhood space optimizing result, namely updating the space positioning through the optimal solution in the neighborhood space optimizing result, and finally, automatically labeling the objective drawing according to the optimized space positioning.
Further, generating a new labeling result through the optimized space positioning and updating result means that labeling information in the optimized space positioning and updating result is extracted to label a complete layer, the new labeling is used as the new labeling result, the new labeling result is stored in one layer, namely, the new labeling result is stored in the new labeling layer, then the new labeling layer is placed in a selected state, and labeling grids are segmented according to the optimized space positioning, a grid selected space is created, in order to conveniently select the new labeling result, uniform grid segmentation is needed to be carried out on the whole target drawing according to the region where the new labeling information is located, each segmented grid is set as a grid selected region, all grid selected regions are summarized to complete the creation of the grid selected space, further, establishing connection relation between the grid selected space and the newly added labeling result, wherein the connection relation between the grid selected space and the newly added labeling result is in one-to-one correspondence, and the network selected space is placed in active state, which means that operations such as selecting, deleting, moving and the like can be performed on the network selected space, then selection confirmation results of users are extracted, the selection confirmation results of the users are used for carrying out selection confirmation on data required by the users in the target picture paper, labeling management is performed on the newly added labeling result under the active state through the selection confirmation results, further, when the system receives a confirmation instruction of the users, a layer locking instruction is synchronously generated, the layer locking instruction is a function of protecting the content of a layer from being accidentally modified, and accidental drawing or editing operation on the newly added labeling layer can be avoided through locking the layer, therefore, the integrity and stability of the image are ensured, the image is used for carrying out temporary locking operation on the newly added marked image layer, and the image layer of the newly added marked image layer is subjected to locking management through an image layer locking instruction, so that the data in the newly added marked image layer are protected from being influenced by accidental modification, the working efficiency is improved, and the automatic matching of the size with the target drawing is better ensured in the later stage through drawing software.
In summary, the method for automatically matching the dimensions of the drawing software provided by the embodiment of the application at least has the following technical effects that rationalized and precise management and control of automatically matching the dimensions of the drawing is realized, and further, the accuracy of matching the dimensions is improved.
Example two
Based on the same inventive concept as the size automatic matching method for drawing software in the foregoing embodiment, as shown in fig. 2, the present application provides a size automatic matching system for drawing software, the system comprising:
The instruction receiving module 1 is used for receiving an automatic size matching instruction and adjusting the configuration unit to an activated state;
The first feature module 2 is used for acquiring input features of a user, wherein the input features comprise size features, type features to be marked and marking constraint features;
the constraint module 3 is used for performing configuration unit constraint of an activation state based on the input characteristics, and completing initial response of the configuration unit;
the layer identification module 4 is used for carrying out layer identification on the target drawing and positioning and calibrating the layer;
the marking isolation module 5 is used for marking and isolating the calibration layer and generating marking and marking mapping of line segments in the marking layer;
The feature traversing module 6 is used for performing feature traversing of the marked and isolated calibration layer through the configuration unit to obtain a feature traversing result, wherein the feature traversing result is provided with a traversing sequence identifier;
And the automatic labeling module 7 is used for updating the traversal sequence identifiers through the identifier mapping and executing automatic labeling through the updating result.
Further, the system further comprises:
the identification module is used for carrying out layer identification on the target drawing and positioning a complete layer;
The first positioning module is used for positioning the point to be marked based on the updating result and generating a positioning result;
The space presetting module is used for inputting the positioning result and the complete image layer into a distribution constraint network to determine a pre-distribution space;
and the first control module is used for completing automatic labeling control through the pre-distribution space.
Further, the system further comprises:
The constraint module is used for generating alignment constraint of the label based on the label isolation result;
the second positioning module is used for performing space positioning of the pre-distributed space through the alignment constraint;
The first optimizing module is used for judging whether a positioning result of space conflict exists or not, and if so, neighborhood space optimizing corresponding to the label is executed;
The second optimizing module is used for performing space positioning optimization according to the neighborhood space optimizing result and completing automatic labeling control based on the optimized space positioning.
Further, the system further comprises:
The new adding module is used for generating a new adding annotation result through the optimized space positioning and updating result, wherein the new adding annotation result is stored in a new adding annotation layer;
The grid segmentation module is used for placing the newly added labeling layer in a selected state, and performing labeled grid segmentation according to the optimized space positioning to create a grid selected space;
the connection establishment module is used for establishing a one-to-one connection relation between the grid selected space and the newly added labeling result and placing the grid selected space in a dynamic state;
The first management module is used for acquiring a selection confirmation result of a user and managing the dynamic newly-added labeling result according to the selection confirmation result.
Further, the system further comprises:
The instruction module is used for synchronously generating a layer locking instruction when receiving a confirmation instruction of a user;
And the second management module is used for carrying out layer locking management of the newly added marked layer based on the layer locking instruction.
Further, the system further comprises:
The analysis module is used for analyzing the input features, determining the number of key feature points according to the features of the type to be marked, and finishing initial point fixing of the key feature points;
The feature matching module is used for fixing the residual key feature points through the size features and rotating by taking the initial point as a rotation center to establish a matching feature set;
And the constraint configuration module is used for completing configuration unit constraint by the matched feature set.
Further, the system further comprises:
The first judging module is used for judging whether the configuration unit is continuously in an activated state or not;
the second judging module is used for executing continuous identification of the configuration unit if the configuration unit is in an activated state continuously;
The response labeling module is used for generating corresponding response labels when the node at any time identifies the newly added matching characteristics;
and the third management module is used for carrying out automatic annotation management according to the response annotation.
The foregoing detailed description of the automatic size matching method for drawing software will be clear to those skilled in the art, and the automatic size matching system for drawing software in this embodiment is relatively simple for the device disclosed in the embodiments, and the relevant points refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. The automatic size matching method for drawing software is characterized by comprising the following steps:
Receiving an automatic size matching instruction, and adjusting the configuration unit to an activated state;
Acquiring input features of a user, wherein the input features comprise size features, type features to be marked and marking constraint features;
Performing configuration unit constraint of an activation state based on the input characteristics, and completing initial response of the configuration unit;
carrying out layer identification on the target drawing, and positioning and calibrating the layer;
Marking and isolating the calibration layer, and generating mark mapping of marking and line segments in the layer;
marking the isolated calibration layer feature traversal through the configuration unit to obtain a feature traversal result, wherein the feature traversal result has traversal sequence identifiers;
Performing traversal sequence identification updating through the identification mapping, and executing automatic labeling through an updating result;
the method further comprises the steps of:
carrying out layer identification on the target drawing and positioning a complete layer;
positioning the point to be marked based on the updated result to generate a positioning result;
Inputting the positioning result and the complete layer into a distribution constraint network to determine a pre-distribution space;
completing automatic labeling control through the pre-distribution space;
the method further comprises the steps of:
generating alignment constraint of the label based on the label isolation result;
space positioning of the pre-distributed space is performed through the alignment constraint;
judging whether a positioning result of space conflict exists, if so, executing neighborhood space optimization of corresponding labels;
and performing space positioning optimization according to the neighborhood space optimizing result, and completing automatic labeling control based on the optimized space positioning.
2. The method of claim 1, wherein the method further comprises:
Generating a new added labeling result through the optimized space positioning and updating result, wherein the new added labeling result is stored in a new added labeling layer;
Placing the newly added labeling layer in a selected state, and performing labeling grid segmentation according to the optimized space positioning to create a grid selected space;
Establishing a one-to-one connection relation between the grid selected space and the newly added labeling result, and placing the grid selected space in a dynamic state;
and acquiring a selection confirmation result of the user, and managing the dynamic newly-added labeling result according to the selection confirmation result.
3. The method of claim 1, wherein the method further comprises:
when receiving a confirmation instruction of a user, synchronously generating a layer locking instruction;
and performing layer locking management of the newly added marked layers based on the layer locking instruction.
4. The method of claim 1, wherein the configuring unit constraint for the activation state based on the input feature completes an initial response of the configuring unit, further comprising:
analyzing the input features, determining the number of key feature points according to the features of the type to be marked, and finishing initial point fixing of the key feature points;
Fixing the residual key feature points through the size features, and rotating to establish a matching feature set by taking the initial points as rotation centers;
and completing configuration unit constraint by the matched feature set.
5. The method of claim 1, wherein the method further comprises:
Judging whether the configuration unit is continuously in an activated state or not;
if the configuration unit is continuously in an activated state, continuous identification of the configuration unit is executed;
When the node identifies the newly added matching feature at any time, a corresponding response label is generated;
and carrying out automatic annotation management according to the response annotation.
6. An automatic size matching system for drawing software, the system comprising:
the instruction receiving module is used for receiving the automatic size matching instruction and adjusting the configuration unit to be in an activated state;
The device comprises a first feature module, a second feature module and a third feature module, wherein the first feature module is used for acquiring input features of a user, and the input features comprise size features, type features to be marked and marking constraint features;
The constraint module is used for performing configuration unit constraint of an activation state based on the input characteristics and completing initial response of the configuration unit;
The layer identification module is used for carrying out layer identification on the target drawing and positioning and calibrating the layer;
the marking isolation module is used for marking and isolating the calibration layer and generating marking and marking mapping of the marking and the line segments in the layer;
the feature traversing module is used for performing feature traversing of the marked and isolated calibration layer through the configuration unit to obtain a feature traversing result, wherein the feature traversing result is provided with a traversing sequence identifier;
the automatic labeling module is used for updating the traversal sequence identifiers through the identifier mapping and executing automatic labeling through the updating result;
the identification module is used for carrying out layer identification on the target drawing and positioning a complete layer;
The first positioning module is used for positioning the point to be marked based on the updating result and generating a positioning result;
The space presetting module is used for inputting the positioning result and the complete image layer into a distribution constraint network to determine a pre-distribution space;
The first control module is used for completing automatic labeling control through the pre-distribution space;
The constraint module is used for generating alignment constraint of the label based on the label isolation result;
the second positioning module is used for performing space positioning of the pre-distributed space through the alignment constraint;
The first optimizing module is used for judging whether a positioning result of space conflict exists or not, and if so, neighborhood space optimizing corresponding to the label is executed;
The second optimizing module is used for performing space positioning optimization according to the neighborhood space optimizing result and completing automatic labeling control based on the optimized space positioning.
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