Closed fabulousfeng closed 3 years ago
Hi @fabulousfeng,
Sorry about this inconvenience. Our current implementation is not very memory efficient regarding large datasets because all of the training patches are loaded into memory simultaneously. That is why it tries to allocate 112 GB of memory.
There are two solutions:
Best wishes.
@tibuch Thanks a lot for the detailed reply! I finally decided to use the second solution and it now works.
I got a memory error when I ran the denoising2D_RGB example using my own data. My own data consists of more than 700 images and they generated more than 1 million 64*64 patches. Then the error came out "MemoryError: Unable to allocate 112. GiB for an array with shape (1225317, 64, 64, 6) and data type float32". The data(RGB.zip) in the example seems to have only one image, so does it mean that it cannot support too many images?