astarlight/lets_ocr

A repository for OCR, which inlcudes some classical OCR algorithms Pytorch implementation such as CTPN, EAST and CRNN.

lets_ocr's Issues

draw_image模块问题

你好，请问generate_gt_anchor.py这个文件中的draw_image是什么模块呀，我用的Python3.

训练不收敛

作者您好，请问一下，您训练多少个epoch开始收敛呢？我用您提供的数据集训练2个epoch还是震荡的，用您的代码转换了ICDAR2017的数据集训练，训练了7个epoch也不收敛。想问下您除了调整学习速率还有什么解决办法吗？谢谢～

ModuleNotFoundError: No module named 'lib.nms'

你好， 我想直接使用Inference，下载好pretrain model和数据以后 执行test.sh
但是报错ModuleNotFoundError: No module named 'lib.nms'，然后我看了下lib目录下确实也没有nms这个文件，请问下怎么办的？

是因为我cd ctpn 后没有make吗？
我尝试了一下make但是报错信息如下：
cython ../common/nms.pyx
gcc -shared -pthread -fPIC -fwrapv -O2 -Wall -fno-strict-aliasing -I/usr/include/python2.7 -o ./lib/nms.so ../common/nms.c
../common/nms.c:4:20: fatal error: Python.h: No such file or directory
compilation terminated.
Makefile:3: recipe for target 'all' failed
make: *** [all] Error 1

请问下是什么问题呢？我用的是anaconda python 3.6

train.py 中TypeError: can't pickle Environment objects错误？

Traceback (most recent call last):
File "train.py", line 322, in
train_iter = iter(train_loader)
File "D:\Anaconda\AnacondaRunning\lib\site-packages\torch\utils\data\dataloader.py", line 193, in iter
return _DataLoaderIter(self)
File "D:\Anaconda\AnacondaRunning\lib\site-packages\torch\utils\data\dataloader.py", line 469, in init
w.start()
File "D:\Anaconda\AnacondaRunning\lib\multiprocessing\process.py", line 105, in start
self._popen = self._Popen(self)
File "D:\Anaconda\AnacondaRunning\lib\multiprocessing\context.py", line 223, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "D:\Anaconda\AnacondaRunning\lib\multiprocessing\context.py", line 322, in _Popen
return Popen(process_obj)
File "D:\Anaconda\AnacondaRunning\lib\multiprocessing\popen_spawn_win32.py", line 65, in init
reduction.dump(process_obj, to_child)
File "D:\Anaconda\AnacondaRunning\lib\multiprocessing\reduction.py", line 60, in dump
ForkingPickler(file, protocol).dump(obj)
TypeError: can't pickle Environment objects
Traceback (most recent call last):
File "", line 1, in
File "D:\Anaconda\AnacondaRunning\lib\multiprocessing\spawn.py", line 99, in spawn_main
new_handle = reduction.steal_handle(parent_pid, pipe_handle)
File "D:\Anaconda\AnacondaRunning\lib\multiprocessing\reduction.py", line 87, in steal_handle
_winapi.DUPLICATE_SAME_ACCESS | _winapi.DUPLICATE_CLOSE_SOURCE)
PermissionError: [WinError 5] ▒ܾ▒▒▒▒ʡ▒

TypeError: can't pickle Environment objects 不知道是什么原因导致的？求讨论

训练数据

请问一下，您是怎样切分数据集的呢？代码描述上您是使用俩个数据集，但是从csdn您的训练截图来看，您好像只使用了msra数据集？

原程序使用ConfigParser，在python3.6中使用configparser

安装命令：
pip install configparser

我用自己的训练集转lmdb，CRNN训练时loss都是20多，不收敛。我只识别数字和字母

tag_anchor 中的疑问

gt_anchor 来自 generate_gt_anchor
result.append((position, cy, h))

那么
if a[0] >= int(width - 1):

似乎应该改成
if a[0]*16 >= int(width - 1):

训练时torch.cuda.is_available()=False,我自己建一个python文件导入torch之后torch.cuda.is_available()=True

运行infar检测一张图像过程CPU会爆掉

运行infar检测（running_mode = "cpu"或者“gpu”）一张图像中的OCR，CPU都会瞬间达到99%卡住几秒后恢复正常，但检测结果正常，请问这可能会是神马原因？

运行train.py出现Corrupted image for 5372问题，求各位大神指教

你好，我运行train.py出现一下问题，请问是怎么回事啊
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raise RuntimeError('DataLoader worker (pid(s) {}) exited unexpectedly'.format(pids_str))
RuntimeError: DataLoader worker (pid(s) 128326) exited unexpectedly
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[root@localhost crnn]#

warning: img ./train_data/data_ready/MSRA_TD500/train_im/img_1756.jpg raise error!

大神您好，请问ctpn训练data_ready时出现这个问题，怎么解决？

train 数据集时候，未收敛便提前终止了，并且和题主给的训练图片也不太一样，len(train_loader)输出的是7，不知道哪里出错了

python3 infer.py error:

python3 infer.py error:
Traceback (most recent call last):
File "infer.py", line 58, in
model.load_state_dict(torch.load(crnn_model_path))
File "/usr/local/lib/python3.5/dist-packages/torch/nn/modules/module.py", line 721, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for CRNN:
Unexpected key(s) in state_dict: "cnn.vgg_16.BatchNorm1.num_batches_tracked", "cnn.vgg_16.BatchNorm2.num_batches_tracked".

my model for ./w160_bs64_model/netCRNN_4_48000.pth'

thank you for your help!

doceker中lets

训练自己的数据集

你好，看了一下您训练用的数据集，里面label的长度都是定长的，如果我自己的数据集不是定长的，需要额外处理么？

编码问题，求解答

为什么我按照博客上说的运行这个文件 python3 ./lib/create_lmdb_dataset.py
会报下面的错误
Traceback (most recent call last):
File "./lib/create_lmdb_dataset.py", line 87, in
imagePathList = list(imgdata)
File "/usr/local/lib/python3.6/codecs.py", line 321, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xd0 in position 6: invalid continuation byte

请教：为什么运行train.py 在lmdb.open()时，总是说 not such a file or directory. 我确定目录存在的。

Exception has occurred: Error
/home/leon/ocr/LetsOCR/data/train_lmdb: No such file or directory
File "/home/leon/ocr/LetsOCR/lib/dataset.py", line 25, in init
meminit=False)

配置文件：
raw_folder = ''
train_data = "/home/leon/ocr/LetsOCR/data/train_lmdb"
test_data = "/home/leon/ocr/LetsOCR/data/test_lmdb"

训练时Corrupted image errror，字节对象进lmdb，lmdb读出来的不一样，请高手帮解决，急。

Corrupted image for 1
Traceback (most recent call last):
File "/home/wdj/mycode3/Lets_OCR/recognizer/crnn/lib/dataset.py", line 132, in getitem
img = Image.open(buf).convert('L')
File "/root/anaconda3/envs/Pytorch_CRNN3/lib/python3.6/site-packages/PIL/Image.py", line 2821, in open
raise IOError("cannot identify image file %r" % (filename if filename else fp))
OSError: cannot identify image file <_io.BytesIO object at 0x7f6110132308>

Use my own dataset ,but loss is always larger than 1

plz...i use my own dataset which contains handwriting English text.

关于运行内存的问题

我在训练模型的时候，使用gpu进行训练，但是还没开始输出loss数据，训练机的内存(16G)就全部给吃掉了，最后报“OSError: [Errno 12] Cannot allocate memory”的错误，请问训练这个模型的时候需要用多大的内存呢？

编译错误

感谢作者的分享 但是我在编译的时候会遇到这个问题 想问一下要怎么解决呢 谢谢

Corrupted image errror

Hello, I got Corrupted image error while training. Anyone could help? Thanks at advance.

x@x:~/Deep_Learning/NLP/Chinese_OCR/Lets_OCR/recognizer/crnn$ python3 train.py 
image scale: [32,160]
model_save_path: ./w160_bs64_model
gpu_id: 5
batch_size: 64
Using cpu mode
alphabet class num is 6736
CRNN(
  (cnn): Sequential(
    (vgg_16): Vgg_16(
      (convolution1): Conv2d(1, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
      (pooling1): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
      (convolution2): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
      (pooling2): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
      (convolution3): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
      (convolution4): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
      (pooling3): MaxPool2d(kernel_size=(1, 2), stride=(2, 1), padding=0, dilation=1, ceil_mode=False)
      (convolution5): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
      (BatchNorm1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (convolution6): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
      (BatchNorm2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (pooling4): MaxPool2d(kernel_size=(1, 2), stride=(2, 1), padding=0, dilation=1, ceil_mode=False)
      (convolution7): Conv2d(512, 512, kernel_size=(2, 2), stride=(1, 1))
    )
  )
  (rnn): Sequential(
    (rnn): RNN(
      (Bidirectional_LSTM1): LSTM(512, 256, bidirectional=True)
      (embedding1): Linear(in_features=512, out_features=512, bias=True)
      (Bidirectional_LSTM2): LSTM(512, 256, bidirectional=True)
      (embedding2): Linear(in_features=512, out_features=6736, bias=True)
    )
  )
)
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Process Process-4:
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Traceback (most recent call last):
  File "/home/x/.local/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 511, in _try_get_batch
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    data = self.data_queue.get(timeout=timeout)
  File "/usr/lib/python3.7/multiprocessing/queues.py", line 104, in get
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    if not self._poll(timeout):
  File "/usr/lib/python3.7/multiprocessing/connection.py", line 257, in poll
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    return self._poll(timeout)
  File "/usr/lib/python3.7/multiprocessing/connection.py", line 414, in _poll
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    r = wait([self], timeout)
  File "/usr/lib/python3.7/multiprocessing/connection.py", line 920, in wait
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    ready = selector.select(timeout)
  File "/usr/lib/python3.7/selectors.py", line 415, in select
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    fd_event_list = self._selector.poll(timeout)
  File "/home/x/.local/lib/python3.7/site-packages/torch/utils/data/_utils/signal_handling.py", line 63, in handler
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    _error_if_any_worker_fails()
RuntimeError: DataLoader worker (pid 13899) exited unexpectedly with exit code 1. Details are lost due to multiprocessing. Rerunning with num_workers=0 may give better error trace.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "train.py", line 163, in <module>
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    cost = trainBatch(net, criterion, optimizer, train_iter)
  File "train.py", line 70, in trainBatch
    data = train_iter.next()
  File "/home/x/.local/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 576, in __next__
    idx, batch = self._get_batch()
  File "/home/x/.local/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 553, in _get_batch
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    success, data = self._try_get_batch()
  File "/home/x/.local/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 519, in _try_get_batch
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    raise RuntimeError('DataLoader worker (pid(s) {}) exited unexpectedly'.format(pids_str))
RuntimeError: DataLoader worker (pid(s) 13899) exited unexpectedly
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ctpn项目中，为什么所有anchor的bottom坐标都比top坐标要大

您好，我最近在研读你的ctpn项目代码，有一个小小的疑问，为什么所有anchor的bottom坐标都比
top坐标要大？比如./lib/generate_gt_anchor.py 第37行，
h = y_bottom[i] - y_top[i] + 1 # the height of anchor box
高度的计算默认bottom比top大，下面的cal_y_top_and_bottom()函数中，y_top明显是从下往上找到的，而y_bottom是从上往下找到的。
相同的情况在./lib/tag_anchor.py文件的cal_y()函数中也出现了。
我对cv领域不太了解，想请问一下这个是后面训练有要求还是cv领域特有的讲究？

math.ceil改为math.floor会更好

Lets_OCR/detector/ctpn/lib/generate_gt_anchor.py

Line 23 in cce8f8b

right_anchor_num = int(math.ceil(min(max(box[2], box[4]), img.shape[1]) / anchor_width)) # the right side anchor of the text box, upwards

这样会减少下一步筛选的量，因为right_anchor_num的值应该是math.floor而不是ceil定位到的值

CTC计算出来的loss非常大，大于60的loss, 不知道哪里出了问题

train 数据集时候，未收敛便提前终止了，并且和题主给的训练图片也不太一样，len(train_loader)输出的是7，不知道哪里出错了

关于文本中的空格如何识别

作者您好，请教一下在英文字符串中，我如何去学习其中的空格。例如假设有一段文字：“wath your name”，我希望识别到的是:wath空格your空格name，而不是wathyouname。

识别问题

利用已有的模型，识别图片，识别率很低

RuntimeError: set_sizes_contiguous is not allowed on Tensor created from .data or .detach()

Traceback (most recent call last):
File "/home/ayg/Downloads/pycharm-2019.1.1/helpers/pydev/pydevd.py", line 1741, in
main()
File "/home/ayg/Downloads/pycharm-2019.1.1/helpers/pydev/pydevd.py", line 1735, in main
globals = debugger.run(setup['file'], None, None, is_module)
File "/home/ayg/Downloads/pycharm-2019.1.1/helpers/pydev/pydevd.py", line 1135, in run
pydev_imports.execfile(file, globals, locals) # execute the script
File "/home/ayg/Downloads/pycharm-2019.1.1/helpers/pydev/pydev_imps/pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "/home/ayg/workspace/crnn/train.py", line 163, in
cost = trainBatch(net, criterion, optimizer, train_iter)
File "/home/ayg/workspace/crnn/train.py", line 73, in trainBatch
lib.dataset.loadData(image, cpu_images)
File "/home/ayg/workspace/crnn/lib/dataset.py", line 144, in loadData
v.data.resize(data.size()).copy(data)
RuntimeError: set_sizes_contiguous is not allowed on Tensor created from .data or .detach()

程序运行到这里出错：
def loadData(v, data):
v.data.resize_(data.size()).copy_(data)

相同文字的不同图片识别问题

感谢作者的分享，我在识别的时候发现一个很奇怪的问题，同一个文字，图片的大小不一样，识别效果居然会不一样。
效果如下：

另外，我修改了这个图片里面蓝色框内的文件的名字，因为不修改运行时会报错。

这里面demo5的大小280和32，test的大小491和76。
下面是俩个图片的原图：

希望作者能解答一下，谢谢

open(image,"r“).read()报错

提示gbk错误，一定要用"rb"才能打开，而"rb”打开的是二进制格式，而非字符串？请教^——^

请问文本识别的数据集有数据集的描述吗？比如数据集用了哪些字体之类的

关于CRNN和CTPN之间的连接问题

感谢作者的分享，请问一下我们用CTPN或者EAST进行文体提取之后，需要进行仿射变换后再输入进CRNN进行文本识别吗？如果是一些弧形的字体的话需要什么其他方法吗？谢谢

关于ctpn的源码的一些问题集中提问

1. 对于lib/draw_image.py和lib/utils.py这两个文件，除了bi_range()和draw_ploy_4pt()两个方法以外完全相同，请问这样设置是有什么深意吗。
2. 在infer文件中开头引用了 lib.nms可是我查看源码并没找到这个文件，是需要自己去网上下载吗？

想看下博主的安装cpython版本

AssertionError: index range error

Traceback (most recent call last):
File "/home/ayg/anaconda3/lib/python3.6/site-packages/torch/utils/data/_utils/worker.py", line 99, in _worker_loop
samples = collate_fn([dataset[i] for i in batch_indices])
File "/home/ayg/anaconda3/lib/python3.6/site-packages/torch/utils/data/_utils/worker.py", line 99, in
samples = collate_fn([dataset[i] for i in batch_indices])
File "/home/ayg/workspace/crnn/lib/dataset.py", line 59, in getitem
return self[index + 1]
File "/home/ayg/workspace/crnn/lib/dataset.py", line 59, in getitem
return self[index + 1]
File "/home/ayg/workspace/crnn/lib/dataset.py", line 59, in getitem
return self[index + 1]
[Previous line repeated 184 more times]
File "/home/ayg/workspace/crnn/lib/dataset.py", line 44, in getitem
assert index <= len(self), 'index range error'
AssertionError: index range error

在报错之前出现很多错误的图片：
Corrupted image for 1628
Corrupted image for 1630
Corrupted image for 1632
Corrupted image for 1634
...

错误信息来源：
def _process_next_batch(self, batch):
self.rcvd_idx += 1
self._put_indices()
if isinstance(batch, _utils.ExceptionWrapper):
# make multiline KeyError msg readable by working around
# a python bug https://bugs.python.org/issue2651
if batch.exc_type == KeyError and "\n" in batch.exc_msg:
raise Exception("KeyError:" + batch.exc_msg)
else:
raise batch.exc_type(batch.exc_msg)
return batch

有人遇到这个问题吗？是否和Corrupted image 的出现有关？

在CRNN 中训练数据时 RuntimeError: DataLoader worker (pid 2918) exited unexpectedly with exit code 1

Traceback (most recent call last):
File "train.py", line 163, in
cost = trainBatch(net, criterion, optimizer, train_iter)
File "train.py", line 70, in trainBatch
data = train_iter.next()
File "/usr/local/lib/python3.5/dist-packages/torch/utils/data/dataloader.py", line 280, in next
idx, batch = self._get_batch()
File "/usr/local/lib/python3.5/dist-packages/torch/utils/data/dataloader.py", line 259, in _get_batch
return self.data_queue.get()
File "/usr/lib/python3.5/multiprocessing/queues.py", line 343, in get
res = self._reader.recv_bytes()
File "/usr/lib/python3.5/multiprocessing/connection.py", line 216, in recv_bytes
buf = self._recv_bytes(maxlength)
File "/usr/lib/python3.5/multiprocessing/connection.py", line 407, in _recv_bytes
buf = self._recv(4)
File "/usr/lib/python3.5/multiprocessing/connection.py", line 379, in _recv
chunk = read(handle, remaining)
File "/usr/local/lib/python3.5/dist-packages/torch/utils/data/dataloader.py", line 178, in handler
_error_if_any_worker_fails()
RuntimeError: DataLoader worker (pid 2918) exited unexpectedly with exit code 1.
这种错 如何解决呢

数据集标签

数据及的标签是数字啊，数字对应的也不是alphabets文件中的汉字，是不是有别的标签文件呀

运行 infer.py 时提示 No module named 'lib.nms'

Traceback (most recent call last):
File "infer.py", line 11, in
import lib.nms
ModuleNotFoundError: No module named 'lib.nms'

代码中没有找到lib.nms，不知道去哪儿找？

请问长文本图片是先切好再做inference再考虑整合吗？

比如训练尺寸是100x32，需要inference 500x32 的长文本图片。
正确的做法是把500x32 切成5张 100x32 然后做inference。然后将答案按照一定逻辑组合起来，对吧？
尺寸上不定长文本图片的识别我一直没想通，请指点！多谢！

Hi, Could you upload your test model? I want to have a quick test. Thanks!

Hi, Could you upload your test model? I want to have a quick test. Thanks!

make compile Error

hi, thank you for your great job! But I met this problem when I tried to implement your code, do you know how to solve it?

付费向学霸哥哥请教

大神，我是你的忠实读者，希望能付费得到您的指导。我是一家上市公司的研发带头人，从业多年。我折服于你的学识，以及你在各blog上严谨的文字，精美的示意图，治学的态度。希望能付费得到你的指教。
我的qq:37580100,我的微信号：zaozaowang1
三生有幸！

训练数据

训练数据中inpath文件可否开源给我们呢

请问一下楼主，文本检测的优化算法都是使用SGD吗？那GPU的作用是不是很小，训练的很慢？

docker中lets_ocr中没有任何东西

博主您好，我用docker cd lets_ocr/detector/ctpn/ 报没有这个目录错误，lets_ocr目录下好像没有任何东西

请问可以训练英文训练集吗？

感谢博主大大奉献的源码，请问这个可以直接训练英文数据集吗？

运行环境

请问这个运行环境是windows还是linux的？因为我看你这个涉及到ctc的安装

这个问题你解决了吗

把 Makefile 改一下
改成 -I/usr/include/python3.6
先查一下有没有这个目录 /usr/include/python3.6
如果没有，要走 apt-get 安装 python3 develop

你好，我还是编译不成功，我对c和 cython或者make不熟，您可以直接把lib.nms 这个文件发给我看看吗，因为只是想用一下inference，它只是import而已，我不需要再去处理数据或者训练。
或者是说必须经过make步骤之后才能运行
[email protected] 这是我的邮箱，万分感谢～

Originally posted by @nicegdhj in #18 (comment)