I am working on my own set of data, I have created coco annotation file for that data I tried train with with unet_lerner with BS=1,I got CUDA memory error, It might be because of of my image size 2448*1564. If I want to resize the image to (256 x any) with Bbox is there any built-in method in fastai to correlate the Bbox coordinates.
There are BBox transforms. What CUDA memory error are you getting? Out of memory? Or something like CUDA Assist?
Also unet out of the box is for segmentation, not boxes. You’d want something like RetinaNet for that
RuntimeError: CUDA out of memory Error, I am with 2080Ti for training
Definitely image size. Just scale it down to 224. There are also examples on the forums showing how to do bounding boxes in the framework, do a quick search for RetinaNet for an example with the API
I have to scale it to 224 and manually annotate all my data set Right??
No you wouldn’t, this is why we have the API
Thank you @muellerzr I will check on it