Comments (5)
from binarization_2017.
My GPU is Nvidia 1050 Ti 4GB.
from binarization_2017.
Tried to run without GPU, but ran out of memory:
I1023 03:51:57.924324 1 net.cpp:259] Network initialization done.
I1023 03:51:57.924329 1 net.cpp:260] Memory required for data: 503054336
F1023 03:52:49.289590 1 syncedmem.hpp:33] Check failed: *ptr host allocation of size 5435817984 failed
*** Check failure stack trace: ***
Loading Image
Computing RD features
Concating inputs
Preprocessing
(722, 1087, 4)
Tiling input
Starting predictions for network 1/5
I have 8 GIBs of RAM and Intel Core I7-7700HQ. My system is Linux Mint 19.
When I started container, I had 6.5 GIBs of free RAM.
from binarization_2017.
Hello!
I am using docker to run with DIBCO2017 dataset but failure and got a similar issue.
I0410 07:38:22.774055 1 net.cpp:259] Network initialization done.
I0410 07:38:22.774060 1 net.cpp:260] Memory required for data: 503054336
F0410 07:38:22.959889 1 math_functions.cu:81] Check failed: error == cudaSuccess (77 vs. 0) an illegal memory access was encountered
*** Check failure stack trace: ***
Loading Image
Computing RD features
Concating inputs
Preprocessing
(1350, 2397, 4)
Tiling input
Starting predictions for network 1/5
from binarization_2017.
Hello,
I have the same problem as mentioned above.
I've changed the batch size to 8 (Issue shihenw/convolutional-pose-machines-release#6 (comment) it's working for most of the images(although giving washed out text) but it's still failing for some images.
Anyone found a solution?
from binarization_2017.
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