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from super-gradients.
My guess that it is OOM error. In theory if the video has high resolution frames that we accumulate during processing may sum up and take all system memory. Do you mind sharing a video (or at least it's dimensions) you're trying to process?
from super-gradients.
i get the same problem on
yolo_nas_l.to(device).predict(input_video_path).save(output_video_path)
memory get all 125gb i have and crash + 2 gb of swap
i get this working ok on the same video on yolo 7 and 8 and yolox
i am infer on yolo_nas_l
from super-gradients.
Hi @sivaji123256 and @Lifeguard-alex ,
Please check out #976, does this solve your issue ?
from super-gradients.
We have implemented memory-efficient predict for video in super-gradients 3.5.0.
So you are welcome to upgrade to a new version of SG which should not have this issue.
from super-gradients.
Related Issues (20)
- Issue when training and predicting with a custom dataset and the YOLO_NAS_S model HOT 2
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from super-gradients.