TensorFlow keras vgg16net的使用
作者:互联网
from tensorflow.python.keras.applications.vgg16 import VGG16,preprocess_input,decode_predictions from tensorflow.python.keras.preprocessing.image import load_img,img_to_array def predict(): model = VGG16() print(model.summary()) #预测一张图片的类别 #加载图片并输入到模型当中 #(224,224)是VGG的输入要求 image = load_img("./tiger.png",target_size=(224,224)) image = img_to_array(image) #输入到卷积神经网络当中,需要四维结构 image = image.reshape((1,image.shape[0],image.shape[1],image.shape[2])) print(image.shape) #预测之前做图片的数据处理,归一化处理等 image = preprocess_input(image) y_predictions = model.predict(image) label = decode_predictions(y_predictions) print(label) if __name__ == '__main__': predict()
标签:__,vgg16net,img,keras,image,predictions,shape,TensorFlow,224 来源: https://www.cnblogs.com/LiuXinyu12378/p/12257317.html