Missing key(s) in state_dict ,the weigh are mismatch for crnn.py

[HuangGuoHui110]

Hi, I use the weight file you provided, and modify only the 100th line of the crnn_recognizer.py file to def init(self, model_path='checkpoints/CRNN.pth'). When I execute ' python demo.py' command is an error, the display is as follows

Traceback (most recent call last):
File "demo.py", line 2, in
from ocr import ocr
File "/media/hgh/HGH_30/plate/ocr.pytorch-master/ocr.py", line 6, in
recognizer = PytorchOcr()
File "/media/hgh/HGH_30/plate/ocr.pytorch-master/recognize/crnn_recognizer.py", line 111, in init
self.model.load_state_dict(torch.load(model_path))
File "/mnt/home/hgh/anaconda2/envs/py3_torch4.1/lib/python3.6/site-packages/torch/nn/modules/module.py", line 719, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for CRNN_v2:
Missing key(s) in state_dict: "conv1_1.weight", "conv1_1.bias", "bn1_1.weight", "bn1_1.bias", "bn1_1.running_mean", "bn1_1.running_var", "conv1_2.weight", "conv1_2.bias", "bn1_2.weight", "bn1_2.bias", "bn1_2.running_mean", "bn1_2.running_var", "conv2_1.weight", "conv2_1.bias", "bn2_1.weight", "bn2_1.bias", "bn2_1.running_mean", "bn2_1.running_var", "conv2_2.weight", "conv2_2.bias", "bn2_2.weight", "bn2_2.bias", "bn2_2.running_mean", "bn2_2.running_var", "conv3_1.weight", "conv3_1.bias", "bn3_1.weight", "bn3_1.bias", "bn3_1.running_mean", "bn3_1.running_var", "conv3_2.weight", "conv3_2.bias", "bn3_2.weight", "bn3_2.bias", "bn3_2.running_mean", "bn3_2.running_var", "conv4_1.weight", "conv4_1.bias", "bn4_1.weight", "bn4_1.bias", "bn4_1.running_mean", "bn4_1.running_var", "conv4_2.weight", "conv4_2.bias", "bn4_2.weight", "bn4_2.bias", "bn4_2.running_mean", "bn4_2.running_var", "bn5.weight", "bn5.bias", "bn5.running_mean", "bn5.running_var".
Unexpected key(s) in state_dict: "cnn.conv0.weight", "cnn.conv0.bias", "cnn.conv1.weight", "cnn.conv1.bias", "cnn.conv2.weight", "cnn.conv2.bias", "cnn.batchnorm2.weight", "cnn.batchnorm2.bias", "cnn.batchnorm2.running_mean", "cnn.batchnorm2.running_var", "cnn.batchnorm2.num_batches_tracked", "cnn.conv3.weight", "cnn.conv3.bias", "cnn.conv4.weight", "cnn.conv4.bias", "cnn.batchnorm4.weight", "cnn.batchnorm4.bias", "cnn.batchnorm4.running_mean", "cnn.batchnorm4.running_var", "cnn.batchnorm4.num_batches_tracked", "cnn.conv5.weight", "cnn.conv5.bias", "cnn.conv6.weight", "cnn.conv6.bias", "cnn.batchnorm6.weight", "cnn.batchnorm6.bias", "cnn.batchnorm6.running_mean", "cnn.batchnorm6.running_var", "cnn.batchnorm6.num_batches_tracked".
size mismatch for rnn.1.embedding.weight: copying a param of torch.Size([5835, 512]) from checkpoint, where the shape is torch.Size([5997, 512]) in current model.
size mismatch for rnn.1.embedding.bias: copying a param of torch.Size([5835]) from checkpoint, where the shape is torch.Size([5997]) in current model.

Does the weight file you provide correspond to the network? Thanks!

[qingqing625]

I have encountered the same problem. Have you solved it?

[courao]

Hi, I'm so sorry that I update the recognition api, and forgot update the recognition model.
And now, the newest model is updated!

[qingqing625]

Hi, I'm so sorry that I update the recognition api, and forgot update the recognition model.
And now, the newest model is updated!

thank you ！ i can run demo。

[HuangGuoHui110]

Hi, I'm so sorry that I update the recognition api, and forgot update the recognition model.
And now, the newest model is updated!

Thanks!