AI基础之展示

  在训练完网络后，我们需要将需要识别的图片输入模型中并输出结果，下面是具体代码。

import torchfrom PIL import Imageimport torchvision.transforms as transdef testImage():    net = torch.load("models/net.pth")    img = Image.open("images/car.jpg")    transform = trans.Compose([        trans.Resize(32),        trans.CenterCrop(32),        trans.ToTensor(),        trans.Normalize((0.4914, 0.4822, 0.4465),(0.2023, 0.1994, 0.2010))    ])    img = transform(img).unsqueeze(0)    output = net(img.cuda())    classes = ('plane','car', 'bird','cat','deer','dog','frog','horse','ship','truck')    index = output.argmax(1)    print("预测结果是：{0}".format(classes[index]))testImage()

来源：https://www.cnblogs.com/wangyueyyy/p/11967376.html