transformer 재설치 pytorch version이랑 뭔가 안맞는듯 아래 참고했을 떄 transformers 4.10.x 부터 해결되는 것 같아서 기존 4.5.1버전을 uninstall 로 삭제하고 재설치함 +) https://github.com/huggingface/transformers/issues/12904 transformers.__spec__ returning None. Causing downstream import errors · Issue #12904 · huggingface/transformers Environment info transformers version: Tried on 4.6.1(current default kaggle version)/4.8.1/4.8.2 and 4.9..
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https://ssaru.github.io/2021/05/05/20210505-til_install_rtx3090_supported_pytorch/ (TIL) RTX 3090을 지원하는 PyTorch 버전설치 2021.05.05 현재 RTX3090은 CUDA11 이상을 지원하는 딥러닝 프레임워크에 버전에서만 사용할 수 있습니다. 하지만 단순하게 pip install torch==1.7.1 torchvision==0.8.2 형태로 설치하면 CUDA error: no kernel image is ava ssaru.github.io pip install torch==[버전] 이런식으로 설치하면 CUDA error: no kernel image is available for execution on the dev..
pip install setuptools==59.5.0 이유는 모르겠지만 이게 도움이 되는 것 같다. +) 참고자료 : https://stackoverflow.com/questions/70520120/attributeerror-module-setuptools-distutils-has-no-attribute-version AttributeError: module 'setuptools._distutils' has no attribute 'version' I was trying to train a model using tensorboard. While executing, I got this error: $ python train.py Traceback (most recent call last): File "t..
https://arxiv.org/abs/2103.06495 Read Like Humans: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Recognition Linguistic knowledge is of great benefit to scene text recognition. However, how to effectively model linguistic rules in end-to-end deep networks remains a research challenge. In this paper, we argue that the limited capacity of language models comes from arxiv..
PAPER : https://arxiv.org/abs/2106.10598 TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition A table arranging data in rows and columns is a very effective data structure, which has been widely used in business and scientific research. Considering large-scale tabular data in online and offline documents, automatic table recognition has attracted i arxiv.org GITHUB: https..
PAPER DocFormer: End-to-End Transformer for Document Understanding We present DocFormer -- a multi-modal transformer based architecture for the task of Visual Document Understanding (VDU). VDU is a challenging problem which aims to understand documents in their varied formats (forms, receipts etc.) and layouts. In additio arxiv.org GitHub GitHub - shabie/docformer: Implementation of DocFormer: E..
PIL Image.open함수로 png를 열었는데 아래와 같이 배경그림이 다 검게 변해버렸다. 알고보니, open 과정에서 RGBA 옵션으로 투명도를 적용해줘야 정상적으로 이미지가 열린다. When, I opened the PNG Files by (PIL.open()), the background is returned as black images like below. => Solution Image.open($IMAGE_NAME).convert("RGBA")
https://www.tablesgenerator.com/markdown_tables
from PIL import Image, ImageDraw, ImageFont, ImageOps, ImageFilter def _random_filter(bg_image): filter_dict = { '0':ImageFilter.BLUR, '1':ImageFilter.CONTOUR, '2':ImageFilter.DETAIL, '3':ImageFilter.EDGE_ENHANCE, '4':ImageFilter.EDGE_ENHANCE_MORE, '5':ImageFilter.EMBOSS, '6':ImageFilter.FIND_EDGES, '7':ImageFilter.SMOOTH, '8':ImageFilter.SMOOTH_MORE, '9':ImageFilter.SHARPEN, '10':None } for num..
file("gt_%d.txt") : GT bounding box 정보를 담고 있음, 각 polygon 좌표값은 tab('\t')으로 구분했다고 가정 [x1 y1 x2 y2 x3 y3 x4 y4 label] import cv2; import numpy as np input_id = 1 # Reading polygon txt file file = './gt_%d.txt'%input_id f = open(file,'r') lines = f.readlines() # Reading Image image_file = './images/0/%d.jpg'%input_id image = cv2.imread(image_file) # Draw for line in lines: polygon = line.split('\t')..
