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A short "starter project" with the goal of generating a small 2D image dataset of abstract shapes (formed using Bezier curves) and then training a model to classify them.

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genClassBezier2D

A short "starter project" with the goal of generating a small 2D image dataset of abstract shapes (formed using Bezier curves) and then training a model to classify them.

What is this?

SEE writeup.pdf IN RESULTS DIRECTORY.

How to run

To generate datasets

python3 main.py --generate

To utilize Holistically-Nested Edge Detection data augmentation

python3 main.py --hed

To train (on default dataset)

python3 main.py --train --epochs 50

To train (on specific dataset)

python3 main.py --train --epochs 50 --dataset colors

To test (on default dataset)

python3 main.py --test --weights "./path/to/weights"

To test (on specific dataset)

python3 main.py --test --weights "./path/to/weights" --dataset colors

References

[1] Habibollah Agh Atabay. “Binary shape classification using Convolutional Neu- ral Networks”. In: IIOAB Journal 7 (Oct. 2016), pp. 332–336.

[2] John Canny. “A Computational Ap- proach to Edge Detection”. In: IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-8.6 (1986), pp. 679–698. DOI: 10.1109/TPAMI. 1986.4767851.

[3] Jonathan Viquerat and Elie Hachem. “A supervised neural network for drag prediction of arbitrary 2D shapes in laminar flows at low Reynolds num- ber”. In: Computers Fluids 210 (2020), p. 104645. ISSN: 0045-7930. DOI: https: //doi.org/10.1016/j.compfluid. 2020.104645. URL: https:// www.sciencedirect.com/science/ article/pii/S0045793020302164.

[4] S. Xie and Z. Tu, “Holistically-nested edge detection,” 2015 IEEE International Conference on Computer Vision (ICCV), 2015.

[5] Chaoyan Zhang et al. “SCN: A Novel Shape Classification Algorithm Based on Convolutional Neural Network”. In: Symmetry 13.3 (2021). ISSN: 2073- 8994. DOI: 10.3390/sym13030499. URL: https://www.mdpi.com/ 2073-8994/13/3/499.

Credits

This application uses Open Source components. You can find the source code of their open source projects along with license information below. We acknowledge and are grateful to these developers for their contributions to open source.

Project: bezier_shapes https://github.com/jviquerat/bezier_shapes Copyright (c) 2019 Jonathan Viquerat ([email protected]) License (MIT) https://github.com/jviquerat/bezier_shapes/blob/master/LICENSE

Project: hed https://github.com/s9xie/hed Copyright (c) 2014, 2015, The Regents of the University of California (Regents) License https://github.com/s9xie/hed/blob/master/LICENSE

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A short "starter project" with the goal of generating a small 2D image dataset of abstract shapes (formed using Bezier curves) and then training a model to classify them.

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