本文介绍了如何保存经过训练的FCN模型并在经过训练的FCN模型上测试新图像?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我正在使用此代码来训练FCN,我已成功运行了此代码.但是,我想在这种训练有素的模型上测试新图像,有人可以帮助我吗?
I am using this code to train FCN, I have succssfully run this code. However, I want to test new images on this trained model, can anyone help me?
#Training from keras import optimizers sgd = optimizers.SGD(lr=1E-2, decay=5**(-4), momentum=0.9, nesterov=True) modelpile(loss='categorical_crossentropy', optimizer=sgd, metrics=['accuracy']) hist1 = model.fit(X_train,y_train, validation_data=(X_test,y_test), batch_size=2,epochs=20,verbose=1) for key in ['loss', 'acc', 'val_loss', 'val_acc']: plt.plot(hist1.history[key],label=key) plt.legend() plt.show() y_pred = model.predict(X_test) y_predi = np.argmax(y_pred, axis=3) y_testi = np.argmax(y_test, axis=3) print(y_testi.shape,y_predi.shape)推荐答案
如keras常见问题解答( keras.io/getting-started/faq/#how-can-i-save-a-keras-model ):
As stated in the keras FAQs (keras.io/getting-started/faq/#how-can-i-save-a-keras-model):
要将模型保存到磁盘,您可以执行以下操作:
To save your model to your disk you can do:
model.save("my_model_file.h5")并在以后再次加载它或在另一个文件中加载它以供使用:
And to load it again later or in another file for using it:
from keras.models import load_model model = load_model("my_model_file.h5") y_pred = model.predict(X_test)更多推荐
如何保存经过训练的FCN模型并在经过训练的FCN模型上测试新图像?
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