I have a hyper spectral image of 170 bands. I have used auto-encoder to reconstruct the image. Now I want to plot the FID score for 100 epochs like we can do for MSE plot.
like we do for MSE polt:
model.compile(optimizer=‘adam’, loss=‘mean_absolute_error’, metrics=[‘accuracy’])
history = model.fit(img, img,
epochs=100, batch_size=1, verbose=1,
validation_split=0.33, shuffle=True)
list all data in history
print(history.history.keys())
summarize history for accuracy
plt.plot(history.history[‘accuracy’])
plt.plot(history.history[‘val_accuracy’])
plt.title(‘model accuracy’)
plt.ylabel(‘accuracy’)
plt.xlabel(‘epoch’)
plt.legend([‘train’, ‘test’], loc=‘upper left’)
plt.show()
Is there a simple way to do that? If so can anyone assist me with a demo code is possible…
Thanks in advance…