WTW-Dataset icon indicating copy to clipboard operation
WTW-Dataset copied to clipboard

This is an official implementation for the WTW Dataset in "Parsing Table Structures in the Wild " on table detection and table structure recognition.

Results 15 WTW-Dataset issues
Sort by recently updated
recently updated
newest added

文中您提到的是采用ICDAR2013比赛指标(P, R, F1)进行计算,对此我有两个疑问: 1、该指标需要text content进行比较,而WTW数据集没有内容的标注,这里您是怎么计算指标的呢? 2、该指标是不计算空单元格之间的匹配的,而WTW数据集同样没有标注单元格是否为空,请问这里是怎么处理的? (个人猜测:您是否使用的是ICDAR2019的比赛指标?是否将所有单元格均当做非空单元格?)

for info in root: for table in info: for cell in table: if cell.tag!='tablecell': continue 官网下载的数据tablecell都没有,xmltohtml代码转不了

Thank you for this awesome paper and dataset. I am trying to understand this paper. It would be great to get a clarification ![image](https://user-images.githubusercontent.com/44224387/227084322-f193cc84-e028-48f9-b2a8-db0fb5468aa6.png) I understand how to calculate the...

在使用过程中,发现训练集中存在大量的错误标注,可用性受到了很大的影响

在使用centernet的代码复现其physical structure中的P,R,F指标时,发现自己的结果为 ![1](https://user-images.githubusercontent.com/65839993/180694560-c198e1e3-1ce2-41b1-b8bf-d8c3e3effde4.JPG) 在iou=0.9时检测结果为0 并可视化了一些结果,发现其大概是正常的 ![2](https://user-images.githubusercontent.com/65839993/180694877-560e816e-ba1a-43e5-ad54-4f9693e7fe9a.png) 所以对您iou=0.9的指标有些疑惑 我使用了3090x4来复现您的结果其opt如下 ==> torch version: 1.7.0+cu110 ==> cudnn version: 8004 ==> Cmd: ['src/main.py', 'ctdet', '--exp_id', 'wtw_lr_1024', '--dataset', 'wtw', '--batch_size', '32', '--master_batch', '9', '--lr', '1.25e-4',...

Thank you for your excellent paper and the dataset. Could you please share the dataset annotation tool? cause I found it is hard to label the table with normal annotation...

``` All the experiments are performed on a workstation with 8 NVIDIA GTX 1080Ti GPUs. During the training, we set the batch size to 32 per GPU in parallel ```...

When I do my sub-category experiment in the sub-categories in WTW, because there may be more than one table in a single image, I tried to assemble the sub-cate result...