image_tagging.py

from keras.applications.resnet50 import ResNet50
from keras.preprocessing import image
from keras.applications.resnet50 import preprocess_input, decode_predictions
import numpy as np

model = ResNet50(weights='imagenet')

def save_tags(filename):
    img = image.load_img(filename, target_size=(224, 224))
    x = image.img_to_array(img)
    x = np.expand_dims(x, axis=0)
    x = preprocess_input(x)

    preds = model.predict(x)
    # decode the results into a list of tuples (class, description, probability)
    # (one such list for each sample in the batch)
    tags = [x[1] for x in decode_predictions(preds, top=3)[0]]
    
    with open(filename + '_tags.txt', 'w') as f:
        f.write(','.join(tags))