As a complement to the accepted answer, this answer shows keras behaviors and how to achieve each picture. General Keras behavior The standard keras internal processing is always a many to many as in the following picture (where I used features=2, pressure and temperature, just as an example): In this image, I increased the number … Read more
There are at least two separate issues with your question. The first one should be clear by now from the comments by Dr. Snoopy and the other answer: accuracy is meaningless in a regression problem, such as yours; see also the comment by patyork in this Keras thread. For good or bad, the fact is … Read more
This is a very large question. And a hard task. I think, the easy way is to extract one frame by second if the source is a video stream. Then use OpenCV to make a face detection. Once you got the faces, feed a NN for recognitions. Some links for face recognition in Deep Learning: … Read more
Save your model or the weights of your model: model.save(filename) np.save(filename, model.get_weights()) For loading, in the first case: from keras.models import load_model model = load_model(filename) In the second case: #recreate the model then: model.set_weights(np.load(filename)) Then: results = model.predict(batch_of_data)