Slike_slovenke_socialmediarip_vol.1.rar

# Define transformations for images transform = transforms.Compose([ transforms.Resize((224, 224)), transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) ])

# Move model to GPU if available device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") model.to(device) model.eval() slike_SLOVENKE_socialMEDIArip_vol.1.rar

# Now 'features' is a list of feature vectors, you can convert it to a numpy array features = np.array(features) # Define transformations for images transform = transforms

# Load pre-trained ResNet50 and remove the last layer model = resnet50(pretrained=True) model.fc = torch.nn.Identity() slike_SLOVENKE_socialMEDIArip_vol.1.rar

# Save or use the features np.save('image_features.npy', features) Please adjust paths and details according to your specific situation. This example assumes you have PyTorch installed and have extracted the images from the .rar file.