I followed the example to load the COCO data sets as follows:
from gluoncv import data, utils
train_dataset = data.COCODetection(splits=['instances_train2017'])
val_dataset = data.COCODetection(splits=['instances_val2017'])
The train_dataset is about 117266 images and labels.
Now I am simply trying to loop through the data-set:
for i in range(len(train_dataset)):
train_image, train_label = train_dataset[i]
This loop simply eats up all of my 15Gb of RAM and I am not even 60% of data.
How can I make sure that my memory is used properly or how can i fix a batch
size etc?
---
[Visit
Topic](https://discuss.mxnet.apache.org/t/out-of-memory-when-using-gluoncv-data-cocodetection/6778/1)
or reply to this email to respond.
You are receiving this because you enabled mailing list mode.
To unsubscribe from these emails, [click
here](https://discuss.mxnet.apache.org/email/unsubscribe/6373da637b9ad7269b59f4ba0a49689df37efeacb17f0231a0cdc8669232abf4).
