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crnn's Issues

输入图片尺寸

你的输入图片尺寸高度为32,宽度时根据高度缩放的,是在脚本中将keep ratio设置为true吗

there are two bugs in the code

first :
preds = preds.squeeze(2) -> preds = preds.squeeze(1)
second:
preds = preds.transpose(1, 0).contiguous().view(-1) -> preds = preds.transpose(-1, 0).contiguous().view(-1)
to change the two lines then get the result

精确度为0,验证集没输出

你好,我自己用您给的生成数据工程synthdata-zh做数据集,其中word.txt是26个小写字母,每个字母生成550训练样本,50的验证样本,共600张。
然后在CRNN工程里的tool里面,用tolmdb.py产生相关训练与验证集合文件,再把key.py里面的alphabet也改成26个小写字母,开始训练,但是出现这样的结果,不知道哪里有问题?
_20180920154344

ncalss

我使用中文字符时,一个字符的len是3,当我使用100时,len为300,nclass为301,但是我看你使用了中文字符,类别数就是比字符数多1,所以我觉得有些疑问。还有一个问题就是我用合成的样本进行训练和测试,效果比较好,但是我用自然场景下扣出来的文本进行测试,如果只是效果不好那我觉得是合理的,但是我预测出来的标签序列有alphabet中不包含的字符,这让我觉得很奇怪。请问你有遇到过这个问题吗,或者你的看法是什么呢?

多GPU训练loss不对,单GPU训练没有问题

麻烦问一下,我用多个gpu训练的loss感觉不对,与单gpu训练相同Loss值的模型,预测结果非常差,单gpu训练的模型预测是正确的。@ wulivicte,请问您遇到过这种问题吗,怎么解决的,非常感谢。

crnn_main.py

max_iter = min(max_iter, len(data_loader))

accuracy = n_correct / float(max_iter * opt.batchSize)

请问这两句该怎么理解?

Corrupted image?

用synthdata-zh这个项目生成的图片,训练时一直有Corrupted image的错误

dimenson mismatch problem

There is something wrong (dimenson mismatch) when fine tune with your code.
for k,v in model_dict.items(): if (k != weig1 or k != bias1): model_dict[k] = pre_trainmodel[k] crnn.load_state_dict(model_dict)
I fixed it by updating
if (k != weig1 or k != bias1):
to
if not (k == weig1 or k == bias1):

请问下你的训练样本是怎样的?

例如对于alphabet = 'ACIMRey万下依口哺摄次状璐癌草血运重' 的训练样本,是一个字一个字作为训练样本吗?还是词组性的,例如哺璐草?

无法使用CUDA

在编译安装warp_ctc的时候设置了CUDA_HOME,运行时依然提示no CUDA-capable device is detected
torch.cuda.is_available() 返回true

train data

您好!21类中英文大概是哪些类?

多卡训练

你好。我想问一下。这个模型可以实现多卡训练嘛?

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