双十一行人重识别推荐

import torch
import torchvision.transforms as transforms
from torch.utils.data import DataLoader
from torchvision.datasets import ImageFolder
from model import ReIDModel

# 数据预处理
transform = transforms.Compose([
    transforms.Resize((256, 128)),
    transforms.ToTensor(),
    transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
])

# 加载数据集
train_dataset = ImageFolder(root='path_to_train_data', transform=transform)
train_loader = DataLoader(train_dataset, batch_size=32, shuffle=True)

# 定义模型
model = ReIDModel()
criterion = torch.nn.CrossEntropyLoss()
optimizer = torch.optim.Adam(model.parameters(), lr=0.001)

# 训练模型
for epoch in range(10):
    for images, labels in train_loader:
        optimizer.zero_grad()
        outputs = model(images)
        loss = criterion(outputs, labels)
        loss.backward()
        optimizer.step()
    print(f'Epoch {epoch+1}, Loss: {loss.item()}')