import torch import torchvision import torchvision.transforms as transforms
# Load pre-trained model model = torchvision.models.resnet50(pretrained=True)
# Load your image and transform it img = ... # Load your image here img = transform(img)
# Extract features with torch.no_grad(): features = model(img.unsqueeze(0)) # Add batch dimension
# Freeze the model for param in model.parameters(): param.requires_grad = False
import torch import torchvision import torchvision.transforms as transforms
# Load pre-trained model model = torchvision.models.resnet50(pretrained=True)
# Load your image and transform it img = ... # Load your image here img = transform(img)
# Extract features with torch.no_grad(): features = model(img.unsqueeze(0)) # Add batch dimension
# Freeze the model for param in model.parameters(): param.requires_grad = False