inference on 4k images.

[aiwithshekhar]

how can i run inference on 4k( 3840 x 2160) images, as presently DAVIS or youtube-vos uses 480p resolution.

[z-x-yang]

Please set --max_long_edge to a number larger than 2160 during inference.

Running inference on such huge images will take a large amount of GPU memory. I'm not sure how much memory is enough.

[aiwithshekhar]

thanks for the reply, i get this error message, RuntimeError: CUDA out of memory. Tried to allocate 3.19 GiB (GPU 3; 10.92 GiB total capacity; 7.00 GiB already allocated; 3.12 GiB free; 7.16 GiB reserved in total by PyTorch). I am using GTX 1080 having RAM (11178MB).

[z-x-yang]

For reducing the memory usage, you can refer to this issue.

But, I suppose 11G memory is not enough for 4k images...

[johndpope]

you can get k80 / 32gb of VRAM on ec2 spot pricing for $0.27

[aiwithshekhar]

Thanks @z-x-yang and @johndpope for your help!

[aiwithshekhar]

For 480p, by any means is it possible for inference on CPU, below is the lowest memory usage on mobilent.

MobileNetV2-Fast-CFBI-DAVIS - 3053MiB
MobileNetV2-CFBI-DAVIS - 6971MiB

[z-x-yang]

I've not tried to infer on CPU. Maybe you can try it by removing all the .cuda() in eval_manager.py.

[aiwithshekhar]

thanks, i tried with cpu below are the values i got.
per frame time 11 sec
Fps per seq 0.1 ~ 0