features = [] for filename in os.listdir(images_dir): img_path = os.path.join(images_dir, filename) image = Image.open(img_path) image = transform(image) image = image.unsqueeze(0).to(device) feature = model(image) feature = feature.detach().cpu().numpy().squeeze() features.append(feature)
import torch import torchvision import torchvision.transforms as transforms from torchvision.models import resnet50 from PIL import Image import os import numpy as np slike_SLOVENKE_socialMEDIArip_vol.1.rar
# Load pre-trained ResNet50 and remove the last layer model = resnet50(pretrained=True) model.fc = torch.nn.Identity() features = [] for filename in os
# 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. slike_SLOVENKE_socialMEDIArip_vol.1.rar