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sirius-ai / LPRNet_Pytorch

Pytorch Implementation For LPRNet, A High Performance And Lightweight License Plate Recognition Framework.
Apache License 2.0
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你们测试的正确率都有多少 #44

Open XieHui1995 opened 3 years ago

XieHui1995 commented 3 years ago

用预训练的模型测试所给的测试集，怎么只有0.9的正确率，再训练了自己的数据集之后就只有0.74了。。。

kingStar1006 commented 3 years ago

我也是0.74

luotianhang commented 3 years ago

请问有训练过模型吗，为啥感觉训练不好啊

kingStar1006 commented 3 years ago

训练过，测试准确率50多

------------------ 原始邮件 ------------------ 发件人: "luotianhang"<notifications@github.com>; 发送时间: 2021年2月5日(星期五) 下午3:25 收件人: "sirius-ai/LPRNet_Pytorch"; 抄送: "Comment"; 主题: Re: [sirius-ai/LPRNet_Pytorch] 你们测试的正确率都有多少 (#44)

请问有训练过模型吗，为啥感觉训练不好啊

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rawli commented 3 years ago

用预训练的模型测试所给的测试集，怎么只有0.9的正确率，再训练了自己的数据集之后就只有0.74了。。。

请教一下大神，你是什么训练出0.74的准确率的？能教我一下你修改了哪儿吗？为啥我训练出来的都是0呢。 这是我训练的过程： Successful to build network! initial net weight successful! [Info] Test Accuracy: 0.0 [0:861:99:960] [Info] Test Speed: 0.015824174165725707s 1/1000] [Info] Test Accuracy: 0.0 [0:866:94:960] [Info] Test Speed: 0.016215238094329835s 1/1000] [Info] Test Accuracy: 0.0 [0:857:103:960] [Info] Test Speed: 0.015121325016021729s 1/1000] [Info] Test Accuracy: 0.0 [0:840:120:960] [Info] Test Speed: 0.015990777015686033s 1/1000] [Info] Test Accuracy: 0.0 [0:860:100:960] [Info] Test Speed: 0.016122838973999024s 1/1000] [Info] Test Accuracy: 0.0 [0:850:110:960] [Info] Test Speed: 0.01493265199661255s 1/1000] [Info] Test Accuracy: 0.0 [0:873:87:960] [Info] Test Speed: 0.01611969208717346s 1/1000]

kingStar1006 commented 3 years ago

我的数据集是ccpd加生成的数据，我主要修改了dataset，其他没动，你这好像不是最终训好模型的测试结果。

------------------ 原始邮件 ------------------ 发件人: "sirius-ai/LPRNet_Pytorch" <notifications@github.com>; 发送时间: 2021年2月25日(星期四) 中午11:18 收件人: "sirius-ai/LPRNet_Pytorch"<LPRNet_Pytorch@noreply.github.com>; 抄送: "四月的谎言"<1065205459@qq.com>;"Comment"<comment@noreply.github.com>; 主题: Re: [sirius-ai/LPRNet_Pytorch] 你们测试的正确率都有多少 (#44)

用预训练的模型测试所给的测试集，怎么只有0.9的正确率，再训练了自己的数据集之后就只有0.74了。。。

请教一下大神，你是什么训练出0.74的准确率的？能教我一下你修改了哪儿吗？为啥我训练出来的都是0呢。 这是我训练的过程： Successful to build network! initial net weight successful! [Info] Test Accuracy: 0.0 [0:861:99:960] [Info] Test Speed: 0.015824174165725707s 1/1000] [Info] Test Accuracy: 0.0 [0:866:94:960] [Info] Test Speed: 0.016215238094329835s 1/1000] [Info] Test Accuracy: 0.0 [0:857:103:960] [Info] Test Speed: 0.015121325016021729s 1/1000] [Info] Test Accuracy: 0.0 [0:840:120:960] [Info] Test Speed: 0.015990777015686033s 1/1000] [Info] Test Accuracy: 0.0 [0:860�9�9960] [Info] Test Speed: 0.016122838973999024s 1/1000] [Info] Test Accuracy: 0.0 [0:850:110:960] [Info] Test Speed: 0.01493265199661255s 1/1000] [Info] Test Accuracy: 0.0 [0:873:87:960] [Info] Test Speed: 0.01611969208717346s 1/1000]

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litingting1111 commented 3 years ago

我的是数据集是ccpd，现在测试结果正确率82%，还在训练

zhangjianying commented 3 years ago

CCPD的数据 [2021-05-03 22:51:18,529][train_LPRNet.py][line:311][INFO] Epoch:116 || epochiter: 45/277|| Totel iter 31900 || Loss: 0. 0347||Batch time: 0.2164 sec. ||LR: 0.00010000 [2021-05-03 22:51:41,751][train_LPRNet.py][line:417][INFO] [Info] Test Accuracy: 0.9659668508287292 [4371:73:81:4525] [2021-05-03 22:51:41,751][train_LPRNet.py][line:418][INFO] [Info] 75%+ Accuracy: 0.9807734806629834 [4438/4525] [2021-05-03 22:51:41,753][train_LPRNet.py][line:429][INFO] [Info] Test Speed: 0.00043868047880454803s 1/4544] [2021-05-03 22:51:42,188][train_LPRNet.py][line:311][INFO] Epoch:116 || epochiter: 145/277|| Totel iter 32000 || Loss: 0

[2021-05-03 22:58:56,468][train_LPRNet.py][line:417][INFO] [Info] Test Accuracy: 0.9646408839779006 [4365:76:84:4525] [2021-05-03 22:58:56,469][train_LPRNet.py][line:418][INFO] [Info] 75%+ Accuracy: 0.9812154696132597 [4440/4525] [2021-05-03 22:58:56,471][train_LPRNet.py][line:429][INFO] [Info] Test Speed: 0.00045087188482284546s 1/4544] [2021-05-03 22:58:56,908][train_LPRNet.py][line:311][INFO] Epoch:123 || epochiter: 206/277|| Totel iter 34000 || Loss: .0097||Batch time: 0.2157 sec. ||LR: 0.00010000

参数: parser.add_argument('--learning_rate', default=0.01, help='base value of learning rate.') parser.add_argument('--lr_schedule', default=[20, 95, 135, 142, 148], help='schedule for learning rate.')

littlePrince126 commented 3 years ago

You should add Net.eval() for BN and dropout

CherishSmile commented 2 years ago

CCPD的数据 [2021-05-03 22:51:18,529][train_LPRNet.py][line:311][INFO] Epoch:116 || epochiter: 45/277|| Totel iter 31900 || Loss: 0. 0347||Batch time: 0.2164 sec. ||LR: 0.00010000 [2021-05-03 22:51:41,751][train_LPRNet.py][line:417][INFO] [Info] Test Accuracy: 0.9659668508287292 [4371:73:81:4525] [2021-05-03 22:51:41,751][train_LPRNet.py][line:418][INFO] [Info] 75%+ Accuracy: 0.9807734806629834 [4438/4525] [2021-05-03 22:51:41,753][train_LPRNet.py][line:429][INFO] [Info] Test Speed: 0.00043868047880454803s 1/4544] [2021-05-03 22:51:42,188][train_LPRNet.py][line:311][INFO] Epoch:116 || epochiter: 145/277|| Totel iter 32000 || Loss: 0

[2021-05-03 22:58:56,468][train_LPRNet.py][line:417][INFO] [Info] Test Accuracy: 0.9646408839779006 [4365:76:84:4525] [2021-05-03 22:58:56,469][train_LPRNet.py][line:418][INFO] [Info] 75%+ Accuracy: 0.9812154696132597 [4440/4525] [2021-05-03 22:58:56,471][train_LPRNet.py][line:429][INFO] [Info] Test Speed: 0.00045087188482284546s 1/4544] [2021-05-03 22:58:56,908][train_LPRNet.py][line:311][INFO] Epoch:123 || epochiter: 206/277|| Totel iter 34000 || Loss: .0097||Batch time: 0.2157 sec. ||LR: 0.00010000

参数: parser.add_argument('--learning_rate', default=0.01, help='base value of learning rate.') parser.add_argument('--lr_schedule', default=[20, 95, 135, 142, 148], help='schedule for learning rate.')

我的准确率也一直是0.0，不知道哪里出问题了

wang-TJ-20 commented 2 years ago

您好，你找到准确率为0.0的原因了嘛 @CherishSmile

123Vincent2018 commented 2 years ago

@wang-TJ-20 我也是准确率一直为0，你找到原因了么

123Vincent2018 commented 2 years ago

倒入预训练模型后，使用他给的data/test里的数据做测试，准确率有0.896 image

wang-TJ-20 commented 2 years ago

后面没看这个了，我记得我当时主要是训练不成功，就是用数据训练完后生成的权重进行测试，准确率为0，不懂为什么😂

---原始邮件--- 发件人: @.> 发送时间: 2022年3月16日(周三) 下午3:02 收件人: @.>; 抄送: @.**@.>; 主题: Re: [sirius-ai/LPRNet_Pytorch] 你们测试的正确率都有多少 (#44)

倒入鱼训练模型后，使用他给的data/test里的数据做测试，准确率有0.896

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123Vincent2018 commented 2 years ago

@wang-TJ-20 @CherishSmile 问题解决了！是预训练模型加载错误以及学习率设置不合理造成的。

wang-TJ-20 commented 2 years ago

您指的是训练时学习率设置不对和预训练模型不对吗，那方便分享一下您的设置和预训练模型吗，我当时因为找不到原因都放弃了😂

---原始邮件--- 发件人: @.> 发送时间: 2022年3月17日(周四) 上午9:26 收件人: @.>; 抄送: @.**@.>; 主题: Re: [sirius-ai/LPRNet_Pytorch] 你们测试的正确率都有多少 (#44)

@wang-TJ-20 @CherishSmile 问题解决了！是预训练模型加载以及学习率设置不合理造成的。

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123Vincent2018 commented 2 years ago

这个是根据你自己的数据量来设置的，不能太大0.1，最好是1e-3,同时你加载预训练模型参数时，要在model.eval()模式下加载才可以，我使用的是自己的数据集30w张进行再训练，测试准确率来到了接近95%，还在训练

------------------ 原始邮件 ------------------ 发件人: "sirius-ai/LPRNet_Pytorch" @.>; 发送时间: 2022年3月17日(星期四) 下午4:43 @.>; @.**@.>; 主题: Re: [sirius-ai/LPRNet_Pytorch] 你们测试的正确率都有多少 (#44)

您指的是训练时学习率设置不对和预训练模型不对吗，那方便分享一下您的设置和预训练模型吗，我当时因为找不到原因都放弃了😂

---原始邮件--- 发件人: @.&gt; 发送时间: 2022年3月17日(周四) 上午9:26 收件人: @.&gt;; 抄送: @.**@.&gt;; 主题: Re: [sirius-ai/LPRNet_Pytorch] 你们测试的正确率都有多少 (#44)

@wang-TJ-20 @CherishSmile 问题解决了！是预训练模型加载以及学习率设置不合理造成的。

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wang-TJ-20 commented 2 years ago

可以的哦，准确率不错，感谢感谢，让我重拾信心，之后再试试✌🏻

---原始邮件--- 发件人: @.> 发送时间: 2022年3月17日(周四) 下午4:53 收件人: @.>; 抄送: @.**@.>; 主题: Re: [sirius-ai/LPRNet_Pytorch] 你们测试的正确率都有多少 (#44)

这个是根据你自己的数据量来设置的，不能太大0.1，最好是1e-3,同时你加载预训练模型参数时，要在model.eval()模式下加载才可以，我使用的是自己的数据集30w张进行再训练，测试准确率来到了接近95%，还在训练

------------------&nbsp;原始邮件&nbsp;------------------ 发件人: "sirius-ai/LPRNet_Pytorch" @.&gt;; 发送时间:&nbsp;2022年3月17日(星期四) 下午4:43 @.&gt;; @.**@.&gt;; 主题:&nbsp;Re: [sirius-ai/LPRNet_Pytorch] 你们测试的正确率都有多少 (#44)

您指的是训练时学习率设置不对和预训练模型不对吗，那方便分享一下您的设置和预训练模型吗，我当时因为找不到原因都放弃了😂

---原始邮件---
发件人: @.&amp;gt;
发送时间: 2022年3月17日(周四) 上午9:26
收件人: @.&amp;gt;;
抄送: @.**@.&amp;gt;;
主题: Re: [sirius-ai/LPRNet_Pytorch] 你们测试的正确率都有多少 (#44)

@wang-TJ-20 @CherishSmile 问题解决了！是预训练模型加载以及学习率设置不合理造成的。

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123Vincent2018 commented 2 years ago

目前在结合分布式策略进行大批次训练

balancedZhi commented 2 years ago

能太大0.1，最好是1e-3,同 您好，请问一般训练多少epoch呢？model.eval()模式下加载，这个可以再详细一点吗，不是很理解，感谢~

123Vincent2018 commented 2 years ago

这个看你模型的拟合情况，训练精度下降前停就行。 模型加载不了？你遇到的是啥问题？

balancedZhi commented 2 years ago

image 调整了学习率，精度是0.测试的时候，model.eval()模式下加载，是在Greedy_Decode_Eval（）中修改吗，非常感谢您的耐心回答~ image

123Vincent2018 commented 2 years ago

训练情况呢？应该是你没把模型参数加载进去

balancedZhi commented 2 years ago

image 这是一部分训练情况，是把test文件中的数据分一部分到train中。

balancedZhi commented 2 years ago

image 也显示加载成功了

123Vincent2018 commented 2 years ago

训练精度呢，可能是数据太少，训练不收敛，这个测试loss这么高

balancedZhi commented 2 years ago

好的我换用大数据集试一试，谢谢。

gubei528 commented 2 years ago

为啥我的加载他的权重之后，测试的ACC是0呢

Vergissmeinnic commented 2 years ago

为啥我的加载他的权重之后，测试的ACC是0呢 Learning_rate调小，我设置的0.001

Vergissmeinnic commented 2 years ago

我用CCPD数据集，训练结果是0.8-0.85之间，测试也是0.8-0.85之间

yangh-zzf-itcast commented 1 year ago

CCPD的数据 [2021-05-03 22:51:18,529][train_LPRNet.py][line:311][INFO] Epoch:116 || epochiter: 45/277|| Totel iter 31900 || Loss: 0. 0347||Batch time: 0.2164 sec. ||LR: 0.00010000 [2021-05-03 22:51:41,751][train_LPRNet.py][line:417][INFO] [Info] Test Accuracy: 0.9659668508287292 [4371:73:81:4525] [2021-05-03 22:51:41,751][train_LPRNet.py][line:418][INFO] [Info] 75%+ Accuracy: 0.9807734806629834 [4438/4525] [2021-05-03 22:51:41,753][train_LPRNet.py][line:429][INFO] [Info] Test Speed: 0.00043868047880454803s 1/4544] [2021-05-03 22:51:42,188][train_LPRNet.py][line:311][INFO] Epoch:116 || epochiter: 145/277|| Totel iter 32000 || Loss: 0

[2021-05-03 22:58:56,468][train_LPRNet.py][line:417][INFO] [Info] Test Accuracy: 0.9646408839779006 [4365:76:84:4525] [2021-05-03 22:58:56,469][train_LPRNet.py][line:418][INFO] [Info] 75%+ Accuracy: 0.9812154696132597 [4440/4525] [2021-05-03 22:58:56,471][train_LPRNet.py][line:429][INFO] [Info] Test Speed: 0.00045087188482284546s 1/4544] [2021-05-03 22:58:56,908][train_LPRNet.py][line:311][INFO] Epoch:123 || epochiter: 206/277|| Totel iter 34000 || Loss: .0097||Batch time: 0.2157 sec. ||LR: 0.00010000

参数: parser.add_argument('--learning_rate', default=0.01, help='base value of learning rate.') parser.add_argument('--lr_schedule', default=[20, 95, 135, 142, 148], help='schedule for learning rate.')

您好，你是用了CCPD所有数据集还是用了base子集，其他的没用呢？我是每个子集抽样10%来训练，无法测试达到这么高的准确率

wirsnow commented 8 months ago

您好，你是用了CCPD所有数据集还是用了base子集，其他的没用呢？我是每个子集抽样10%来训练，无法测试达到这么高的准确率

刚学几天，我用的CCPD的base+green，并且和CBLPRD混合起来，一共有305409张，7:1.5:1.5，准确率有0.932。 但是不知道为什么，到第15个epoch之后loss就会突然增大然后准确率降到0 XWIT%KYL QR5O($CRQ13W36