Comments (3)
Have already solved by CSDN BLOG
from east.
Hi, This repo is for ICDAR2015, so there are some details which could be changed according to your own dataset. Here is an example:
The training batch is cropped from image, which would change the distance GT. I was lazy to handle such case, so I just repeat 1000 times to crop image to avoid split text region. The text regions in ICDAR2015 are often sparse and this takes little time. However, the time consumption would increase when dense texts exist. This may be the reason of low speed. ( I guess...
from east.
"The training batch is cropped from image, which would change the distance GT"
I have a question:
In your code, you had cropped image before getting ground truth distance, so it is not affect the result of ground truth distance, right?
from east.
Related Issues (20)
- According to find_min_rect_angle HOT 3
- According to crop_img HOT 1
- 直接加载训练好的模型,也不能复现性能 HOT 1
- ZIP entry not valid HOT 1
- How many epochs were trained for the pretrained model?
- Question: Saving checkpoints
- what is submit.zip HOT 1
- 无法得到作者的精度 HOT 3
- ZeroDivisionError: float division by zero
- 请帮忙看看,测试不了是什么情况 HOT 2
- 执行python train.py 遇到以下问题。望回复 HOT 1
- The sample not present in GT
- add languages
- RGBA support with png images
- Error loading the ZIP archive HOT 1
- Windows运行EAST
- CUDA out of memory on eval.py
- In dataset.py crop_img function sometimes returning negative vertices
- 有没有中文权重文件
- AP
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from east.