# Load a pre-trained model model = VGG16(weights='imagenet', include_top=False, input_shape=(224, 224, 3))
# You might visualize the output of certain layers to understand learned features This example uses a pre-trained VGG16 model to extract features from an image. Adjustments would be necessary based on your actual model and goals. emloadal hot
# Load an image img_path = "path/to/your/image.jpg" img = image.load_img(img_path, target_size=(224, 224)) x = image.img_to_array(img) x = np.expand_dims(x, axis=0) # Load a pre-trained model model = VGG16(weights='imagenet',
# Get the features features = model.predict(x) emloadal hot