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util.py
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util.py
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import matplotlib.colors as mcolors
def get_jabbr(entry):
if entry['ENTRYTYPE'].lower()=='article':
return _jabbr_mapping(entry['journal'])
if entry['ENTRYTYPE'].lower()=='inproceedings':
return _jabbr_mapping(entry['booktitle'])
if entry['ENTRYTYPE'].lower()=='misc':
return ''
colors=list(mcolors.TABLEAU_COLORS.values())
def get_label_badge_link(label):
color_code=colors[ord(label[0])%len(colors)][1:]
return f"https://img.shields.io/badge/-{label}-{color_code}.svg"
def get_markdown_header():
return ("# Awesome Neural Physics\n\n"
"[This repository](https://github.com/awesome-physics/awesome-neural-physics) hosts a curated list of papers on **AI techniques for physics simulation** in computer graphics.\n\n"
"If you find this list useful, please consider citing it and giving it a :star:. Feel free to share it with others!\n\n")
def get_markdown_footer():
return ("## Citation\n\n"
"If you find this repository helpful, please consider citing it!\n\n"
"```\n"
"@misc{wang2024awesomelist,\n"
" title = {Awesome Neural Physics - A Curated List of Papers on AI Techniques for Physics Simulation in Computer Graphics},\n"
" author = {Hui Wang},\n"
" journal = {GitHub repository},\n"
" url = {https://github.com/awesome-physics/awesome-neural-physics},\n"
" year = {2023},\n"
"}\n"
"```\n")
jabbr_map={
'ACM Transactions on Graphics (TOG)'.casefold():'TOG',
'ACM Transactions on Graphics'.casefold():'TOG',
'ACM Trans. Graph.'.casefold():'TOG',
'IEEE Transactions on Visualization and Computer Graphics'.casefold():'TVCG',
'Computer Graphics Forum'.casefold():'CGF',
'Proceedings of the ACM on Computer Graphics and Interactive Techniques'.casefold():'PACMCGIT',
'Proc. ACM Comput. Graph. Interact. Tech.'.casefold():'PACMCGIT',
'Computational Visual Media'.casefold():'CVM',
'Computer Animation and Virtual Worlds'.casefold():'CAVW',
'Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)'.casefold():'CVPR',
'Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition'.casefold():'CVPR',
'The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)'.casefold():'CVPR',
'The IEEE/CVF Conference on Computer Vision and Pattern Recognition'.casefold():'CVPR',
'Advances in Neural Information Processing Systems'.casefold():'NeurIPS',
'Conference on Neural Information Processing Systems'.casefold():'NeurIPS',
'Proceedings of the International Conference on Learning Representations'.casefold():'ICLR',
'International Conference on Learning Representations'.casefold():'ICLR',
'ICML'.casefold():'ICML',
'International Conference on Machine Learning'.casefold():'ICML',
'Proceedings of the AAAI Conference on Artificial Intelligence'.casefold():'AAAI',
'Proceedings of the european conference on computer vision (eccv)'.casefold():'ECCV',
'European Conference on Computer Vision'.casefold():'ECCV',
'Proceedings of the IEEE/CVF International Conference on Computer Vision'.casefold():'ICCV',
'Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)'.casefold():'ICRA',
'IEEE International Conference on Robotics and Automation (ICRA)'.casefold():'ICRA',
'International Conference on Robotics and Automation (ICRA)'.casefold():'ICRA'
}
def _jabbr_mapping(j):
if j.casefold() in jabbr_map:
return jabbr_map[j.casefold()]
elif j.casefold().startswith('arxiv'):
return 'Arxiv'
elif 'siggraph asia' in j.casefold():
return 'Siggraph Asia'
elif 'siggraph' in j.casefold():
return 'Siggraph'
else:
return ''
print('find no ',j,'in our mapping')