mhliao / db Goto Github PK

Hi, thanks for the awesome job. Could you provide the pretrained synthtext model on resnet-18?

Hi, Minghui, thanks to your nice work, here are some question to ask you:

1. "where the label of the threshold map can be generated by computing the distance
   to the closest segment in G."
   I think the distance is distanceTransform of pixels in border, however I add it into loss cannot be converged.
2. "Lt is computed as the sum of L1 distances between the prediction and label inside the dilated text polygon Gd"
   I think the loss for threshold map is calculated for region in border.
3. Pixels in threshold map are in [0, 1]? If so, the threshold map network predicted should process by sigmoid.

Above all are my question and my thoughs.

/usr/local/cuda:/usr/local/cuda:/usr/local/cuda-9.0/bin/nvcc -I/home/nmt/anaconda3/envs/pytorch1_2/lib/python3.6/site-packages/torch/include -I/home/nmt/anaconda3/envs/pytorch1_2/lib/python3.6/site-packages/torch/include/torch/csrc/api/include -I/home/nmt/anaconda3/envs/pytorch1_2/lib/python3.6/site-packages/torch/include/TH -I/home/nmt/anaconda3/envs/pytorch1_2/lib/python3.6/site-packages/torch/include/THC -I/usr/local/cuda:/usr/local/cuda:/usr/local/cuda-9.0/include -I/home/nmt/anaconda3/envs/pytorch1_2/include/python3.6m -c src/deform_conv_cuda_kernel.cu -o build/temp.linux-x86_64-3.6/src/deform_conv_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=deform_conv_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11
unable to execute '/usr/local/cuda:/usr/local/cuda:/usr/local/cuda-9.0/bin/nvcc': No such file or directory
error: command '/usr/local/cuda:/usr/local/cuda:/usr/local/cuda-9.0/bin/nvcc' failed with exit status 1

试过更改.brashrc的CUDA的环境变量，但是不行，这个问题要怎么解决?

这一行为什么要设置canvas 的最小值是0.3？
https://github.com/MhLiao/DB/blob/master/data/processes/make_border_map.py#L41

python train.py ./experiments/seg_detector/base_totaltext.yaml --num_gpus 2

Traceback (most recent call last):
File "train.py", line 70, in
main()
File "train.py", line 60, in main
experiment_args = conf.compile(conf.load(args['exp']))['Experiment']
KeyError: 'Experiment'

Traceback (most recent call last):
File "train.py", line 70, in
main()
File "train.py", line 60, in main
experiment_args = conf.compile(conf.load(args['exp']))['Experiment']
KeyError: 'Experiment'

could you please upload weight on google drive

When I run python3 eval.py, raise NotImplementedError. why? how to slove it?

请问训练自己的数据集时，除了数据路径外，其他参数还有哪些需要注意的，涉及到哪些参数，谢谢

支持！

请问为什么使用参数--visualize后得到的可视化图很模糊？

我用的redhat7.4，python3.6.2, gcc 4.9.2, Cython 0.28, torch 1.3，cuda 10.1，
deformable convolution编译的时候没问题，已经生成文件了。
但是在运行eval.py进行测试时，报了图中的错误。我怀疑是哪个库版本不一致导致的，麻烦您有空看一下，谢谢

dcn模块是否可以运行在CPU上？？

python train.py experiments/seg_detector/ic15_resnet50_deform_thre.yaml --num_gpus 4
[INFO] [2019-12-05 05:32:38,907] Training epoch 0
error in modulated_deformable_col2im_coord_cuda: invalid device function
error in modulated_deformable_col2im_cuda: invalid device function

你好，我看到yaml文件里有很多参数，不太清楚某些参数的具体意义，请问你什么时候有时间可以给我们解释一下这些参数的用处吗

D:/STL/software/Anaconda/Anaconda33/envs/DB/lib/site-packages/torch/include\c10/util/order_preserving_flat_hash_map.h(1502): error C3203: “templated_iterator”: 未专用化的 类 模板 不能用作 模板 变量，该变量属于 模板 参数“_Ty1”，应为 real 类型
D:/STL/software/Anaconda/Anaconda33/envs/DB/lib/site-packages/torch/include\c10/util/order_preserving_flat_hash_map.h(1560): note: 参见对正在编译的类 模板 实例化“ska_ordered::order_preserving_flat_hash_map<K,V,H,E,A>”的引用
D:/STL/software/Anaconda/Anaconda33/envs/DB/lib/site-packages/torch/include\c10/util/order_preserving_flat_hash_map.h(1506): error C3203: “templated_iterator”: 未专用化的 类 模板 不能用作 模板 变量，该变量属于 模板 参数“_Ty1”，应为 real 类型
D:/STL/software/Anaconda/Anaconda33/envs/DB/lib/site-packages/torch/include\c10/util/order_preserving_flat_hash_map.h(1514): error C3203: “templated_iterator”: 未专用化的 类 模板 不能用作 模板 变量，该变量属于 模板 参数“_Ty1”，应为 real 类型
D:/STL/software/Anaconda/Anaconda33/envs/DB/lib/site-packages/torch/include\c10/util/order_preserving_flat_hash_map.h(1596): error C3203: “templated_iterator”: 未专用化的 类 模板 不能用作 模板 变量，该变量属于 模板 参数“_Ty1”，应为 real 类型
D:/STL/software/Anaconda/Anaconda33/envs/DB/lib/site-packages/torch/include\c10/util/order_preserving_flat_hash_map.h(1633): note: 参见对正在编译的类 模板 实例化“ska_ordered::flat_hash_set<T,H,E,A>”的引用
D:/STL/software/Anaconda/Anaconda33/envs/DB/lib/site-packages/torch/include\c10/util/order_preserving_flat_hash_map.h(1601): error C3203: “templated_iterator”: 未专用化的 类 模板 不能用作 模板 变量，该变量属于 模板 参数“_Ty1”，应为 real 类型
D:/STL/software/Anaconda/Anaconda33/envs/DB/lib/site-packages/torch/include\c10/util/order_preserving_flat_hash_map.h(1605): error C3203: “templated_iterator”: 未专用化的 类 模板 不能用作 模板 变量，该变量属于 模板 参数“_Ty1”，应为 real 类型
D:/STL/software/Anaconda/Anaconda33/envs/DB/lib/site-packages/torch/include\c10/util/order_preserving_flat_hash_map.h(1609): error C3203: “templated_iterator”: 未专用化的 类 模板 不能用作 模板 变量，该变量属于 模板 参数“_Ty1”，应为 real 类型
D:/STL/software/Anaconda/Anaconda33/envs/DB/lib/site-packages/torch/include\c10/util/order_preserving_flat_hash_map.h(1613): error C3203: “templated_iterator”: 未专用化的 类 模板 不能用作 模板 变量，该变量属于 模板 参数“_Ty1”，应为 real 类型

Please check the trained model link, I just find some ground truth files?

Thanks for your excellent work! But I have a question, why I get the inconsistent results with the ones reported in paper when testing the fintuned resnet-18 backbone on TotalText?

Hi Minghui, thanks for your awesome work!

I found that adding --visulize after the evaluation command will generate the visualization results for only the threshold map. I'm wondering how can I generate or obtain the visualization result for predicted characters?

Thank you!

When running:

python eval.py ./experiments/seg_detector/base.yaml --resume ./modelz/totaltext_resnet50 --polygon --box_thresh 0.6

I get error:

Traceback (most recent call last):
  File "eval.py", line 8, in <module>
    from trainer import Trainer
  File "/home/home/p9/DB/trainer.py", line 6, in <module>
    from experiment import Experiment
  File "/home/home/p9/DB/experiment.py", line 4, in <module>
    from structure.representers import *
  File "/home/home/p9/DB/structure/representers/__init__.py", line 2, in <module>
    from .boxes_from_map import boxes_from_map
ModuleNotFoundError: No module named 'structure.representers.boxes_from_map'

When mask.sum() ==0 in this line https://github.com/MhLiao/DB/blob/master/decoders/l1_loss.py#L10,the l1loss will get nan

How to use the pre-trained model of SynthDat for finetuning? How to add this weight to train.py script?

pip install -r requirement.txt

ERROR: Failed building wheel for geventwebsocket

Maybe you want to replace geventwebsocket, because it is failing to build.

Dear author, I wanted to train the model with command "python train.py experiments/seg_detector/base_totaltext.yaml --num_gpus 8", and the error raise that
File "train.py", line 72, in
main()
File "train.py", line 62, in main
experiment_args = conf.compile(conf.load(args['exp']))['Experiment']
KeyError: 'Experiment'

How can I solve these problem?

Any scripts test on a single image?

代码中，没有找到 dilated 的操作？？？是省去了吗？为啥啊

pip install -r requirements.txt
没有 requirements.txt 没有 s
pip install -r requirement.txt

When training the model with totaltext, I got this error when running the command
python mytrain.py experiments/seg_detector/totaltext_resnet18_deform_thre.yaml --num_gpus 4. Can you help me? Thank you!

libibverbs: Warning: no userspace device-specific driver found for /sys/class/infiniband_verbs/uverbs0
Traceback (most recent call last): File "train.py", line 72, in <module> main() File "train.py", line 69, in main trainer.train() File "/DB/trainer.py", line 86, in train epoch=epoch, step=self.steps) File "/DB/trainer.py", line 127, in train_step if step % self.experiment.logger.log_interval == 0: TypeError: unsupported operand type(s) for %: 'int' and 'NoneType'

Dear author, Could you give me the information about your training time and your computing resource?
I found it cost about 50min with 4 Titian Xp GPUs to train one epoch. Is it normal ?

After inputting the probability map and threshold map into eq.2, what post processing should we do for the fianl results? Particularly, if P equal to T, the output is a median value (1/2). It seems that there are many noises in the final binary map, so can you tell us the detailed inference?
Thank you~

page 7 table 5: CDAFT (Baek et al. 2019) 89.8 84.3 86.9 may be CRAFT

你好，感谢你的工作，我在试图评估时报错
IndexError: list index out of range
具体如下：
python eval.py experiments/seg_detector/totaltext_resnet50_deform_thre.yaml --resume models/totaltext_resnet50 --polygon --box_thresh 0.6
Traceback (most recent call last):
File "eval.py", line 193, in
main()
File "eval.py", line 77, in main
experiment = Configurable.construct_class_from_config(experiment_args)
File "./DB/concern/config.py", line 130, in construct_class_from_config
return cls(**args)
File "./DB/experiment.py", line 96, in init
self.load_all(**kwargs)
File "./DB/concern/config.py", line 143, in load_all
self.load(name, **kwargs)
File "./DB/concern/config.py", line 151, in load
(kwargs[state_name], cmd)))
File "./DB/concern/config.py", line 164, in create_member_from_config
return cls(**args, cmd=cmd)
File "./DB/experiment.py", line 37, in init
self.load_all(**kwargs)
File "./DB/concern/config.py", line 143, in load_all
self.load(name, **kwargs)
File "./DB/concern/config.py", line 151, in load
(kwargs[state_name], cmd)))
File "./DB/concern/config.py", line 164, in create_member_from_config
return cls(**args, cmd=cmd)
File "./DB/data/data_loader.py", line 29, in init
self.load_all(**kwargs)
File "./DB/concern/config.py", line 143, in load_all
self.load(name, **kwargs)
File "./DB/concern/config.py", line 151, in load
(kwargs[state_name], cmd)))
File "./DB/concern/config.py", line 164, in create_member_from_config
return cls(**args, cmd=cmd)
File "./DB/data/image_dataset.py", line 33, in init
self.get_all_samples()
File "./DB/data/image_dataset.py", line 37, in get_all_samples
with open(self.data_list[i], 'r') as fid:
IndexError: list index out of range

我使用的是python 3.7.5 pytorch 1.3.1 cuda 10.1
请问我该怎么做？

I find this error when I run eval.py and demo.py, it seemed something went wrong with the data input?
File "eval.py", line 194, in
main()
File "eval.py", line 80, in main
Eval(experiment, experiment_args, cmd=args, verbose=args['verbose']).eval(args['visualize'])
File "eval.py", line 177, in eval
pred = model.forward(batch, training=False)
File "/ssd/xmzhang/TextDetection/lab1/DB/structure/model.py", line 56, in forward
pred = self.model(data, training=self.training)

TypeError: forward() missing 1 required positional argument: 'data'

提供的datasets百度网盘链接里的total_text文件夹中没有train_images和test_images文件

当然我们相信各位的工作，相信速度很快，我们不需要再去测试速度，我觉得没什么意义，我们需要的是简单的加载模型，进行预测。现在的代码是各种类，各种跳转，各种参数还不知道啥意思。。。。好南。。。。。。。。

您好 请问这个参数是什么意思 训练的时候需要开着吗

(db) home@home-desktop:~/p9/DB$ python eval.py ./experiments/seg_detector/base.yaml --resume ./modelz/totaltext_resnet50 --polygon --box_thresh 0.6
Traceback (most recent call last):
  File "eval.py", line 193, in <module>
    main()
  File "eval.py", line 75, in main
    experiment_args = conf.compile(conf.load(args['exp']))['Experiment']
KeyError: 'Experiment'

@MhLiao test the code, both train.py and eval.py

请问博主，模型对中文检测是不是效果比较差，而且容易把二维码的纹理识别成字，我用demo.py测试一些电商图片效果很差

In concern.config there is no class name State,but this class is import in many files

之前一直在用tensorflow，所以synthtext这个数据集的图片和标注都是处理成tfrecord的格式。这边用syntntext数据集进行训练的时候需要怎么处理呢？处理成一张图片img_name.jpg对应标注img_name.txt的形式吗？

还有一个问题就是，对于只有四个坐标点的数据怎么转换到和你这个一样的标签上

Dear author:
When I trained the model, I found the Volatile GPU-Util equal to 0%. Is anything wrong with my method?
+-------------------------------+----------------------+----------------------+
| 8 TITAN Xp On | 00000000:8E:00.0 Off | N/A |
| 23% 32C P2 65W / 250W | 1683MiB / 12196MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 9 TITAN Xp On | 00000000:8F:00.0 Off | N/A |
| 23% 34C P2 60W / 250W | 1685MiB / 12196MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 10 TITAN Xp On | 00000000:90:00.0 Off | N/A |
| 23% 31C P2 61W / 250W | 1685MiB / 12196MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 11 TITAN Xp On | 00000000:91:00.0 Off | N/A |
| 23% 31C P2 60W / 250W | 1693MiB / 12196MiB | 0% Default |
+-------------------------------+----------------------+----------------------+