自学教程：利用ResNet50网络进行ImageNet分类

利用ResNet50网络进行ImageNet分类

1. from keras.applications.resnet50 import ResNet50
2. from keras.preprocessing import image
3. from keras.applications.resnet50 import preprocess_input, decode_predictions
4. import numpy as np
5.  
6. model = ResNet50(weights='imagenet')
7. #仅仅这样就可以
8. img_path = 'elephant.jpg'
9. img = image.load_img(img_path, target_size=(224, 224))
10. x = image.img_to_array(img)
11. x = np.expand_dims(x, axis=0)
12. x = preprocess_input(x)
13.  
14. preds = model.predict(x)
15. # decode the results into a list of tuples (class, description, probability)
16. # (one such list for each sample in the batch)
17. print('Predicted:', decode_predictions(preds, top=3)[0])
18. # Predicted: [(u'n02504013', u'Indian_elephant', 0.82658225), (u'n01871265', u'tusker', 0.1122357), (u'n02504458