[IEEE TGRS 2020] Official Tensorflow implementation for Change Detection in Multisource VHR Images via Deep Siamese Convolutional Multiple-Layers Recurrent Neural Network
In my opinion, the SiamCRNN is trained end-to-end to classify the central pixel of a patch as change or no change. The patches are of size 5x5 pixels, and the network attempts to classify the label of the central pixel based on its neighbourhood’s values.
When generating the training samples, do you specify the label (change or no change) of a pair of patches according whether the central pixel changed or not?
Hi,
A good work. In train.py file you load file train_sample_X.pickle , but I want to know how you write the images in this pickle file and where(in which file) I have to add this code.
Hi, I want to know about the form of pikle format GF-2 dataset you use so that I can run siamCRNN on my own dataset. Or can the GF-2 dataset be provided?
Look forward to your reply. thank.
hi dear authors
your code have lots of problems. I runned it on colab but 'infer.py' and 'train.py' miss datasets. I guess you had data sets on your system so forget to upload it here. path also returns Null. you used load_data() func in 'infer_result()' of 'infer' but it doesn't have the input. unfortunately there is no 'train_sample_X and Y'.