Convolutional neural network for machine learning uses cifar10 data set and alexnet network model to train classification model, install labelimg, and report error

Use cifar10 Data set and alexnet Network model training classification model

download cifar10 Data sets

Code ：

import torchvisionimport torchtransform = torchvision.transforms.Compose(    [torchvision.transforms.ToTensor(),     torchvision.transforms.Resize(224)])train_set = torchvision.datasets.CIFAR10(root='./',download=False,train=True,transform=transform)test_set = torchvision.datasets.CIFAR10(root='./',download=False,train=False,transform=transform)train_loader = torch.utils.data.DataLoader(train_set,batch_size=8,shuffle=True)test_loader = torch.utils.data.DataLoader(test_set,batch_size=8,shuffle=True)class Alexnet(torch.nn.Module):  #1080 2080    def __init__(self,num_classes=10):        super(Alexnet,self).__init__()        net = torchvision.models.alexnet(pretrained=False)  # The migration study         net.classifier = torch.nn.Sequential()        self.features = net        self.classifier = torch.nn.Sequential(            torch.nn.Dropout(0.3),            torch.nn.Linear(256 * 6 * 6, 4096),            torch.nn.ReLU(inplace=True),            torch.nn.Dropout(0.3),            torch.nn.Linear(4096, 4096),            torch.nn.ReLU(inplace=True),            torch.nn.Linear(4096, num_classes),        )    def forward(self,x):        x = self.features(x)        x = x.view(x.size(0),-1)        x = self.classifier(x)        return xdevice = torch.device('cpu')net = Alexnet().to(device)loss_func = torch.nn.CrossEntropyLoss().to(device)optim = torch.optim.Adam(net.parameters(),lr=0.001)net.train()for epoch in range(10):    for step,(x,y) in enumerate(train_loader):  # 28*28*1 32*32*3        x,y = x.to(device),y.to(device)        output = net(x)        loss = loss_func(output,y)        optim.zero_grad()        loss.backward()        optim.step()    print("epoch:",epoch,'loss:',loss)

install labelimg, And reporting errors

Target detection and labeling tool ：labelimg
install pip install labelimg
Use labelimg

Report errors

ERROR: spyder 4.1.4 requires pyqtwebengine<5.13; python_version >= “3”, which is not installed. ERROR: spyder 4.1.4 has requirement pyqt5<5.13; python_version >= “3”, but you’ll have pyqt5 5.15.6 which is incompatible

Version mismatch problem

open Anaconda Prompt

Install with command Spyder

pip install spyder==4.1.4

perhaps

pip install -i https://pypi.tuna.tsinghua.edu.cn/simple/ spyder==4.1.4

Use labelimg

Found in the installation environment labelimg.exe Copy to desktop

open

Open a picture