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Deep homography network with Pytorch

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Hi mazenmel, I have a question for you. save .npy files function in DataGenerationAndPRocessing.py np.save(new_path+'%s'%i[0:12], ImagePreProcessing(i,path)) ImagePreProcessing(i,path) is a tuple. cuz return value of ImagePreProcessing is Tuple (variable is named...

TrainingData = CocoDdataset(train_path)This line of code has gone wrong.

Thanks for re-implement the model. How's the performance? Consistent with claimed in the paper?

how do I infer on a single pair of image?