def generate_basic_features(image_path): try: img = Image.open(image_path) features = { 'width': img.width, 'height': img.height, 'mode': img.mode, 'file_size': os.path.getsize(image_path) } return features except Exception as e: print(f"An error occurred: {e}") return None
return features
# Generate features with torch.no_grad(): features = model(img) Ilovecphfjziywno Onion 005 jpg %28%28NEW%29%29
import torch import torchvision import torchvision.transforms as transforms def generate_basic_features(image_path): try: img = Image
# Usage image_path = 'Ilovecphfjziywno Onion 005 jpg (NEW).jpg' features = generate_cnn_features(image_path) print(features.shape) These examples are quite basic. The kind of features you generate will heavily depend on your specific requirements and the nature of your project. Ilovecphfjziywno Onion 005 jpg %28%28NEW%29%29