Methods and systems for feature recognition of two-dimensional prints for manufacture
An apparatus for feature recognition of two-dimensional prints is illustrated. The apparatus comprise a processor and a memory communicatively connected to the processor. The memory contains instructions configuring the processor to receive a two-dimensional print of a part for manufacture, scale two-dimensional print so that the two-dimensional print is within a predetermined area, identify a curve feature of the two-dimensional print as a function of scaling of the two-dimensional print, wherein the curve feature comprises a plurality of line segments, and classify a line type of the curve feature using line observations as a function of the curve feature identification.
1. An apparatus for feature recognition of two-dimensional prints, wherein the apparatus comprises:
a processor; and
a memory communicatively connected to the processor, the memory containing instructions configuring the processor to:
receive a two-dimensional print of a part for manufacture;
scale the two-dimensional print to fit a predetermined area, wherein scaling the two-dimensional print includes:
determining an original size of the part; and
resizing the two-dimensional print to the original size of the part;
identify a curve feature of the two-dimensional print as a function of scaling the two-dimensional print, wherein the curve feature comprises a plurality of line segments; and
classify the curve feature to a line type of as a function of the curve feature identification and at least a line observation.
2. The apparatus of claim 1 , wherein receiving the two-dimensional print further comprises receiving the two-dimensional print through a web application.
3. The apparatus of claim 1 , wherein the two-dimensional print includes an object line and scaling the two-dimensional print includes:
comparing a length of the object line to a length stated in an annotation of the two-dimensional print; and
validating scale and dimensions of the two-dimensional print as a function of the comparison.
4. The apparatus of claim 1 , wherein identifying the curve feature further comprises:
determining that the curve feature strays from a perfectly circular circle by less than a preconfigured threshold; and
identifying the curve as a circle as a function of the determination.
5. The apparatus of claim 1 , wherein identifying the curve feature further comprises:
determining that the curve feature strays from a perfectly circular arc by less than a preconfigured threshold; and
identifying the curve as an arc as a function of the determination.
6. The apparatus of claim 1 , wherein classifying includes classifying the line type as a function of a probabilistic machine learning model.
7. The apparatus of claim 1 , wherein the at least a line observation includes a superimposition of object lines on hidden lines.
8. The apparatus of claim 1 , wherein the at least a line observation includes a positioning of center lines.
9. The apparatus of claim 1 , wherein the at least a line observation includes at least a diameter annotation.
10. A method for feature recognition of two-dimensional prints, wherein the method is performed by a processor and comprises:
receiving a two-dimensional print of a part for manufacture;
scaling the two-dimensional print to fit a predetermined area, wherein scaling the two-dimensional print includes:
determining an original size of the part; and
resizing the two-dimensional print to the original size of the part;
identifying a curve feature of the two-dimensional print as a function of scaling the two-dimensional print, wherein the curve feature comprises a plurality of line segments; and
classifying curve feature to a line type as a function of the curve feature identification and at least a line observation.
11. The method of claim 10 , wherein receiving the two-dimensional print further comprises receiving the two-dimensional print through a web application.
12. The method of claim 10 , wherein the two-dimensional print includes an object line and scaling the two-dimensional print includes:
comparing a length of the object line to a length stated in an annotation of the two-dimensional print; and
validating scale and dimensions of the two-dimensional print as a function of the comparison.
13. The method of claim 10 , wherein identifying the curve feature further comprises:
determining that the curve feature deviates from a perfectly circular circle by less than a preconfigured threshold; and
identifying the curve as a circle as a function of the determination.
14. The method of claim 10 , wherein identifying the curve feature further comprises:
determining that the curve feature deviates from a perfectly circular arc by less than a preconfigured threshold; and
identifying the curve as an arc as a function of the determination.
15. The method of claim 10 , wherein classifying includes classifying the line type as a function of a probabilistic machine learning model.
16. The method of claim 10 , wherein the at least a line observation includes a superimposition of object lines on hidden lines.
17. The method of claim 10 , wherein the at least a line observation includes a positioning of center lines.
18. The method of claim 10 , wherein the at least a line observation includes at least a diameter annotation.