Hi Jean-Patrick, Why do you need to load everything into RAM to resize it? This a perfect use-case for streaming data processing. Have a look at my notebook from EuroSciPy 2015 for some examples: https://github.com/jni/streaming-talk/blob/master/Big%20data%20in%20little%2... Specifically, as you generate examples, you should be writing them to disk directly. Then you are limited by disk size, instead of RAM size. I hope that helps! Juan. On 27 September 2016 at 8:27:09 pm, Jean-Patrick Pommier ( jeanpatrick.pommier@gmail.com) wrote: Dear all, I proposed on kagle an image processing/supervised classification problem <https://www.kaggle.com/jeanpat/d/jeanpat/metaphase/generating-overlapping-ch...> concerning the resolution of overlapping chromosomes.The aim is to produce a large dataset of examples. A first dataset was produced <https://www.kaggle.com/jeanpat/overlapping-chromosomes>, but it seems to be too small to yield good results for supervised classification with a neural network. As explained in the first notebook, 8Go is not enough to process, mainly to resize/crop, the images. My question how a large batch of images >>100 000 can be resized? Thanks. Jean-Patrick PS I can't hide that It would be great if some would be interrested by the problem itself and give some help on the resolution itself or some advices on the proposed code. -- You received this message because you are subscribed to the Google Groups "scikit-image" group. To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image+unsubscribe@googlegroups.com. To post to this group, send email to scikit-image@googlegroups.com. To view this discussion on the web, visit https://groups.google.com/d/msgid/scikit-image/cc5cdf4e-6847-4872-a10f-a5981... <https://groups.google.com/d/msgid/scikit-image/cc5cdf4e-6847-4872-a10f-a598148edf56%40googlegroups.com?utm_medium=email&utm_source=footer> . For more options, visit https://groups.google.com/d/optout.