Hello,
I have also had hilarious experiences with MATLAB RAM usage. I can however give a brief explanation of what is causing the RAM to be filled a lot. This is based on my personal experience and I don't have objective measures for you.
- I see this particular computer vision uses a table to read the data. It is possible that this table is being read all at once and the images are being loaded. What you need is the Image Datastore(imds)https://www.mathworks.com/help/matlab/ref/matlab.io.datastore.imagedatastore.html and the box label datastore(blds) https://www.mathworks.com/help/vision/ref/boxlabeldatastore.html. These will load in only the images which are currently being used.
- You must take a look at your network architecture and consider the convolution kernels that you're using and how much intermediate information is being used by you convolutions. If you have a 2000x2000 image with a 2x2 pixel convolution filter with a stride of 1, a lot of intermediate information is being used. If you make a 7x7 filter with a 5 pixel stride, the intermediate information will be less
- I'm not familiar with this particular object detector, but the batch size has a large effect on RAM usage. If you make the batch size smaller, it will reduce the RAM being used and once and will hopefully prevent a crash.
Hope this helps
RC
