"""
    测试（使用）训练好的网络
"""
import torch
import torchvision
from PIL import Image
from torch import nn

# 网上随便下载一个图片
image_path = "./images/dogg.png"
image = Image.open(image_path)
image = image.convert("RGB")
print(image)

transform = torchvision.transforms.Compose([torchvision.transforms.Resize((32, 32)),
                                            torchvision.transforms.ToTensor()])

image = transform(image)
print(image.shape)


# 搭建神经网络
class Gisleung(nn.Module):
    def __init__(self):
        super(Gisleung, self).__init__()
        self.model = nn.Sequential(
            nn.Conv2d(3, 32, 5, 1, 2),
            nn.MaxPool2d(2),
            nn.Conv2d(32, 32, 5, 1, 2),
            nn.MaxPool2d(2),
            nn.Conv2d(32, 64, 5, 1, 2),
            nn.MaxPool2d(2),
            nn.Flatten(),
            nn.Linear(64 * 4 * 4, 64),
            nn.Linear(64, 10)
        )

    def forward(self, x):
        x = self.model(x)
        return x


# 注意：模型保存时是采用GPU训练的，当需要在cpu测试时
# 1 在gpu测试
# model = torch.load("./model_save/gis_9.pth")
# image = torch.reshape(image, (1, 3, 32, 32)).cuda()

# 2 在cpu测试
model = torch.load("./model_save/gis_9.pth", map_location=torch.device("cpu"))
image = torch.reshape(image, (1, 3, 32, 32))

model.eval()
with torch.no_grad():
    output = model(image)

print(output)
print(output.argmax(1))
# 最后输出的是5，训练集中第5个类别是狗dog
# 如果输出的不是5，两种可能①图片找的不太对；②模型没训练好