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| import os | |
| path = '/path/to/folder' | |
| # Get all the .png files in the folder | |
| files = [file for file in os.listdir(path) if file.endswith('.png')] | |
| # Sort the files | |
| files.sort() |
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| https://github.com/tianyu0207/RTFM | |
| https://github.com/seominseok0429/Real-world-Anomaly-Detection-in-Surveillance-Videos-pytorch --> | |
| https://github.com/fjchange/MIST_VAD--> | |
| https://github.com/OmRajpurkar/Alert-Generation-on-Detection-of-Suspicious-Activity-using-Transfer-Learning | |
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| https://www.kaggle.com/mlwhiz/multiclass-text-classification-pytorch | |
| https://towardsdatascience.com/text-classification-with-state-of-the-art-nlp-library-flair-b541d7add21f | |
| https://towardsdatascience.com/how-to-beat-automl-hyperparameter-optimisation-with-flair-3b2f5092d9f5 | |
| https://github.com/pytorch/text/blob/master/torchtext/experimental/datasets/text_classification.py |
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| https://www.math.utk.edu/~finotti/files/latex/LaTeX_Symbols.pdf --- symbol pdf... | |
| https://tex.stackexchange.com/questions/345379/table-in-two-column | |
| Latex_tables - two column width... | |
| \begin{table*}[!hbt] | |
| \caption{Comparison of our evaluation scores with other references}\label{tab:apis} | |
| \small | |
| \begin{center} | |
| \begin{tabular}{|l|l|l|l|l|l|} |
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| The Python code to convert refs.bib file to bibitem file | |
| python2 bibtex2item.py < refs.bib > bibitem.txt | |
| https://tex.stackexchange.com/questions/124874/converting-to-bibitem-in-latex | |
| # filename: bibtex2item.py | |
| import sys | |
| bibtex = sys.stdin.read() |
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| https://machinelearningmastery.com/precision-recall-and-f-measure-for-imbalanced-classification/ -- Calculate Recall With Scikit-Learn |
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| """ | |
| # https://github.com/bentrevett/pytorch-seq2seq/issues/129 | |
| # https://github.com/bentrevett/pytorch-seq2seq/blob/master/6%20-%20Attention%20is%20All%20You%20Need.ipynb | |
| """ | |
| import torch | |
| import torch.nn as nn | |
| import torch.optim as optim | |
| import torchtext | |
| from torchtext.datasets import Multi30k |
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| > /content/trans-vsumm/seq_sum.py(78)forward() | |
| -> src = layer(src, src_mask) | |
| (Pdb) src.shape | |
| torch.Size([461, 1024, 256]) | |
| (Pdb) src_mask.shape | |
| torch.Size([461, 1, 1, 1024]) | |
| > /content/trans-vsumm/seq_sum.py(78)forward() | |
| -> src = layer(src, src_mask) |
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| %xmode Verbose | |
| %pdb on | |
| from IPython.core.debugger import set_trace #set_trace() |
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| https://www.youtube.com/watch?v=UY7sVKJPTMA | |
| > resist the temptation of procrastination | |
| > review the latest happenings in your research area | |
| > Have a outline of the paper so that you can start from where you have left | |
| Tables of data , Figures.. put them in order... Logical sequence..like you arrange for a talk.. | |
| Don't write the introduction/Abstract.. at this time.. |
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