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代码:
- from keras.applications.vgg16 import VGG16
- from keras.preprocessing import image
- from keras.applications.vgg16 import preprocess_input
- from keras.applications import imagenet_utils
- import numpy as np
-
- model = VGG16(weights='imagenet')
-
- img_path = 'E:\\timg.jpg'
- img = image.load_img(img_path, target_size=(224, 224))
- x = image.img_to_array(img)
- x = np.expand_dims(x, axis=0)
-
- x = preprocess_input(x)
-
- features = model.predict(x)
- print('Predicted:', imagenet_utils.decode_predictions(features, top=3)[0])
输出结果:预测结果是pizza,82%的概率
- E:\phthon35\python.exe I:/catsVSdogs1-master/catsVSdogs1-master/file01/ImagesPredict.py
-
- Predicted: [('n07873807', 'pizza', 0.82579499), ('n07583066', 'guacamole', 0.029104929), ('n07880968', 'burrito', 0.018119223)]
-
- Process finished with exit code 0
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