Comments (16)
你好,报错可能是pycharm自身原因,我的就没有报错,那里import的是这个目录下的文件,有这些文件肯定可以运行
from crnn.
哦。我mark as source 好像也没用。
690张图,训练2轮,测试结果全是失败,是正常的吗?要怎样才能正确识别?
C:\Users\Ni\AppData\Local\Programs\Python\Python38\python.exe F:/pycharm2020.2/crnn-master/test.py
load weights/chinese_2_82.80496325595773_0.0.pt model success!
device: cpu
test_batch_loss=84.44302188648896, test_batch_acc=0.0
test_loss=84.44302188648896, test_acc=0.0
但是先不说妈妈 ------------> ❌❌❌
我绝对不想成为爸爸那样的人 ------------> ❌❌❌
我爸爸逃避着自己的问题 ------------> ❌❌❌
只替周围的人操心 ------------> ❌❌❌
有没有我能做的事呢 ------------> ❌❌❌
我想我一定无法成为那样的人 ------------> ❌❌❌
但是在这个世界上 ------------> ❌❌❌
有很多逃避自己问题的人 ------------> ❌❌❌
这样的人很轻松 ------------> ❌❌❌
from crnn.
正常,我训练了一天准确率才是96,你现在训练太少了,在训练集的准确率还是0。我训练用的是100万的数据集,训练用lr=0.0001训练的3个epoch,再lr=0.00001训练2个epoch
from crnn.
lr=0.0001 在哪里设置?
您训练的模型可以分享吗?我想测试看看准确率。
from crnn.
模型:https://cloud.189.cn/web/share?code=U7NV3iNbmYvi
数据集:https://cloud.189.cn/web/share?code=eyuiiyjyEFva(访问码:4giq)
from crnn.
谢谢。自己准备的训练用的图片,要不要先用ctpn的定位把它裁边裁成只剩文字的?每张图的尺寸要统一吗?
from crnn.
from crnn.
需要裁剪成只有文字,但不需要统一尺寸,我会在读取数据集时处理成32*1000的大小。这里的1000你可以改,改源代码
from crnn.
下载了你那个chinese_4_0.4110666987350187_0.95999.pt
我用我自己的图片测试为什么报错?必须要用训练的图片才能有结果?
C:\Users\Ni\AppData\Local\Programs\Python\Python38\python.exe F:/pycharm2020.2/crnn-master/test.py
Traceback (most recent call last):
File "F:/pycharm2020.2/crnn-master/test.py", line 91, in
main(opt)
File "F:/pycharm2020.2/crnn-master/test.py", line 62, in main
crnn.load_state_dict(torch.load(opt.weights, map_location=torch.device('cpu')))
File "C:\Users\Ni\AppData\Local\Programs\Python\Python38\lib\site-packages\torch\nn\modules\module.py", line 1482, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for CRNN:
size mismatch for rnn.1.embedding.weight: copying a param with shape torch.Size([2569, 512]) from checkpoint, the shape in current model is torch.Size([776, 512]).
size mismatch for rnn.1.embedding.bias: copying a param with shape torch.Size([2569]) from checkpoint, the shape in current model is torch.Size([776]).
from crnn.
你发一张图片让我测试一下
from crnn.
识别时是一定要用二值化图?还是场景文字也可以?
下面有4张图。2张中文,2张日文。
识别时,也要用ctpn裁剪成只剩文字区域?然后二值化,再进行识别?
from crnn.
我在读取图片时就二值化了
from crnn.
我在读取图片时就二值化了
但是如果我给的是白底黑字的图,没必要二值化吧?
from crnn.
chinese_7_18.998092761142647_0.0
18.998092761142647 是代表什么?
如果我按默认设置先训练10epochs
然后可以用weights, 继续接着最后生成的pt文件,继续训练?
from crnn.
chinese_7_18.998092761142647_0.0代表的意思是 chinese_epoch_loss_acc。可以加载保存好的权重继续训练
from crnn.
你好,加你微信了,回复一下
from crnn.
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from crnn.