This commit is contained in:
Shuguang Dou 2024-04-21 17:28:06 -04:00 коммит произвёл GitHub
Родитель 515ae12d86
Коммит acf8c18cfa
Не найден ключ, соответствующий данной подписи
Идентификатор ключа GPG: B5690EEEBB952194
1 изменённых файлов: 4 добавлений и 3 удалений

Просмотреть файл

@ -10,7 +10,7 @@ This repository is the official PyTorch implementation of our two powerful vecto
<p align="center">
<img alt="img-name" src="misc/RGvsVG.png" width="900">
Rendering vector graphics into pixel arrays can result in significant memory costs or loss of information, as demonstrated in Figure 1. Additionally, this process discards high-level structural information within the primitives, which is critical for recognition tasks such as identifying corners and contours.
Rendering vector graphics into pixel arrays can result in significant memory costs or loss of information, as demonstrated in above Figure 1. Additionally, this process discards high-level structural information within the primitives, which is critical for recognition tasks such as identifying corners and contours.
To summarize, we propose You Only Look at Text series (YOLaT & YOLaT++) which addresses issues with raster graphics by taking in textual documents of vector graphics as input.
## Environments
```sh
@ -53,8 +53,9 @@ CUDA_VISIBLE_DEVICES=0 python -u train.py --batch_size 4 --data_dir data/diagram
```
## YOLaT++
<p align="center">
<img alt="img-name" src="misc/Yolat%2B%2B.png" width="900">
YOLaT++ is introduced, characterized by a hierarchical structure designed for VGs, spanning three levels: **Primitive, Curve, and Point**. Additionally, YOLaT++ employs a position-aware enhancement strategy to effectively differentiate similar primitives.
## Citation
BibTex: