• <legend id='spmCm'><style id='spmCm'><dir id='spmCm'><q id='spmCm'></q></dir></style></legend>
    <i id='spmCm'><tr id='spmCm'><dt id='spmCm'><q id='spmCm'><span id='spmCm'><b id='spmCm'><form id='spmCm'><ins id='spmCm'></ins><ul id='spmCm'></ul><sub id='spmCm'></sub></form><legend id='spmCm'></legend><bdo id='spmCm'><pre id='spmCm'><center id='spmCm'></center></pre></bdo></b><th id='spmCm'></th></span></q></dt></tr></i><div id='spmCm'><tfoot id='spmCm'></tfoot><dl id='spmCm'><fieldset id='spmCm'></fieldset></dl></div>
  • <tfoot id='spmCm'></tfoot>
      <bdo id='spmCm'></bdo><ul id='spmCm'></ul>

        <small id='spmCm'></small><noframes id='spmCm'>

      1. 如果我想让 OpenCV dnn 模块加载它,我应该如何保存 PyTorch 的模型

        时间:2023-12-02

              • <bdo id='xXMH5'></bdo><ul id='xXMH5'></ul>

                <small id='xXMH5'></small><noframes id='xXMH5'>

                  <i id='xXMH5'><tr id='xXMH5'><dt id='xXMH5'><q id='xXMH5'><span id='xXMH5'><b id='xXMH5'><form id='xXMH5'><ins id='xXMH5'></ins><ul id='xXMH5'></ul><sub id='xXMH5'></sub></form><legend id='xXMH5'></legend><bdo id='xXMH5'><pre id='xXMH5'><center id='xXMH5'></center></pre></bdo></b><th id='xXMH5'></th></span></q></dt></tr></i><div id='xXMH5'><tfoot id='xXMH5'></tfoot><dl id='xXMH5'><fieldset id='xXMH5'></fieldset></dl></div>

                    <tbody id='xXMH5'></tbody>

                • <legend id='xXMH5'><style id='xXMH5'><dir id='xXMH5'><q id='xXMH5'></q></dir></style></legend><tfoot id='xXMH5'></tfoot>

                • 本文介绍了如果我想让 OpenCV dnn 模块加载它,我应该如何保存 PyTorch 的模型的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着跟版网的小编来一起学习吧!

                  问题描述

                  我通过 PyTorch 训练了一个简单的分类模型并通过 opencv3.3 加载它,但它抛出异常并说

                  I train a simple classification model by PyTorch and load it by opencv3.3, but it throw exception and say

                  OpenCV 错误:函数/特性未在 readObject、file 中实现(不支持的 Lua 类型)/home/ramsus/Qt/3rdLibs/opencv/modules/dnn/src/torch/torch_importer.cpp,第 797 行/home/ramsus/Qt/3rdLibs/opencv/modules/dnn/src/torch/torch_importer.cpp:797:错误:(-213) 函数 readObject 中不支持 Lua 类型

                  模型定义

                  class conv_block(nn.Module):
                      def __init__(self, in_filter, out_filter, kernel):
                          super(conv_block, self).__init__()
                  
                          self.conv1 = nn.Conv2d(in_filter, out_filter, kernel, 1, (kernel - 1)//2)
                          self.batchnorm = nn.BatchNorm2d(out_filter)
                          self.maxpool = nn.MaxPool2d(2, 2)
                  
                      def forward(self, x):
                          x = self.conv1(x)
                          x = self.batchnorm(x)
                          x = F.relu(x)
                          x = self.maxpool(x)
                  
                          return x
                  
                  class Net(nn.Module):
                      def __init__(self):
                          super(Net, self).__init__()
                  
                          self.conv1 = conv_block(3, 6, 3)
                          self.conv2 = conv_block(6, 16, 3)
                          self.fc1 = nn.Linear(16 * 8 * 8, 120)
                          self.bn1 = nn.BatchNorm1d(120)
                          self.fc2 = nn.Linear(120, 84)
                          self.bn2 = nn.BatchNorm1d(84)
                          self.fc3 = nn.Linear(84, 10)
                  
                      def forward(self, x):
                          x = self.conv1(x)
                          x = self.conv2(x)
                          x = x.view(x.size()[0], -1)
                          x = F.relu(self.bn1(self.fc1(x)))
                          x = F.relu(self.bn2(self.fc2(x)))
                          x = self.fc3(x)
                          return x
                  

                  该模型仅使用 Conv2d、ReLU、BatchNorm2d、MaxPool2d 和 Linear 层,opencv3.3 支持每一层

                  This model use Conv2d, ReLU, BatchNorm2d, MaxPool2d and Linear layer only, every layers are supported by opencv3.3

                  我用 state_dict 保存

                  I save it by state_dict

                  torch.save(net.state_dict(), 'cifar10_model')
                  

                  通过 C++ 加载它

                  std::string const model_file("/home/some_folder/cifar10_model");
                  
                  std::cout<<"read net from torch"<<std::endl;
                  dnn::Net net = dnn::readNetFromTorch(model_file);
                  

                  我想我用错误的方式保存模型,为了使用 OpenCV 加载,保存 PyTorch 模型的正确方法是什么?谢谢

                  I guess I save the model with the wrong way, what is the proper way to save the model of PyTorch in order to load using OpenCV? Thanks

                  我用另一种方式保存模型,但也无法加载

                  I use another way to save the model, but it cannot be loaded either

                  torch.save(net, 'cifar10_model.net')
                  

                  这是一个错误吗?还是我做错了什么?

                  Is this a bug?Or I am doing something wrong?

                  推荐答案

                  我找到了答案,opencv3.3 不支持 PyTorch (https://github.com/pytorch/pytorch) 但 pytorch (https:///github.com/hughperkins/pytorch),真是个大惊喜,我不知道还有其他版本的pytorch存在(看起来像一个死项目,好久没有更新了),希望他们能提一下他们在 wiki 上支持哪些 pytorch.

                  I found the answer, opencv3.3 do not support PyTorch (https://github.com/pytorch/pytorch) but pytorch (https://github.com/hughperkins/pytorch), it is a big surprise, I never know there are another version of pytorch exist(looks like a dead project, long time haven't updated), I hope they could mention which pytorch they support on wiki.

                  这篇关于如果我想让 OpenCV dnn 模块加载它,我应该如何保存 PyTorch 的模型的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持跟版网!

                  上一篇:使用来自桌面应用程序的 Windows 8 Toast 通知 下一篇:你在 C++ 中使用 NULL 还是 0(零)作为指针?

                  相关文章

                  1. <small id='fQmHv'></small><noframes id='fQmHv'>

                    1. <tfoot id='fQmHv'></tfoot>
                    2. <i id='fQmHv'><tr id='fQmHv'><dt id='fQmHv'><q id='fQmHv'><span id='fQmHv'><b id='fQmHv'><form id='fQmHv'><ins id='fQmHv'></ins><ul id='fQmHv'></ul><sub id='fQmHv'></sub></form><legend id='fQmHv'></legend><bdo id='fQmHv'><pre id='fQmHv'><center id='fQmHv'></center></pre></bdo></b><th id='fQmHv'></th></span></q></dt></tr></i><div id='fQmHv'><tfoot id='fQmHv'></tfoot><dl id='fQmHv'><fieldset id='fQmHv'></fieldset></dl></div>

                        <bdo id='fQmHv'></bdo><ul id='fQmHv'></ul>
                    3. <legend id='fQmHv'><style id='fQmHv'><dir id='fQmHv'><q id='fQmHv'></q></dir></style></legend>