The nms seems not working? about pytorch-retinanet HOT 7 CLOSED

Hey, I solve this problem!
The problem lies in lib/build.sh. What I do is just to add '-gencode arch=compute_70,code=sm_70' (according to my GPU device RTX2070) to the CUDA_ARCH and recompile the NMS extension. Now everything works well!
Hope this help someone and sorry for my poor English.

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Here's a bug I found in compiling nms.. hope it is useful to someone.
The build.sh file is saying "$CUDA_ARCH" as a parameter to nvcc command which was not set inside my docker environment.
The actual nvcc command goes like the one in the link below.
https://github.com/multimodallearning/pytorch-mask-rcnn

I replaced $CUDA_ARCH with --arch=sm_52 (I have a titanx).

I was getting a "no gpu_nms" module found error before and it was gone after compiling nms properly.

Hope this helps someone.

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Hi,
I'm looking into this issue. Could you please indicate:

• Were you able to compile the NMS extension without any errors?
• Is this running in a jupyer notebook ?

Thanks.

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Thanks for your reply.

1. I think I compile the NMS extension without any errors:

root@9a42af0f41ef:/pytorch-retinanet/lib# sh build.sh
Compiling nms kernels by nvcc...
Including CUDA code.
/pytorch-retinanet/lib/nms
generating /tmp/tmpKGuPdx/_nms.c
setting the current directory to '/tmp/tmpKGuPdx'
running build_ext
building '_nms' extension
creating pytorch-retinanet
creating pytorch-retinanet/lib
creating pytorch-retinanet/lib/nms
creating pytorch-retinanet/lib/nms/src
x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fno-strict-aliasing -Wdate-time -D_FORTI
FY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security -fPIC -DWITH_CUDA -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/usr/include/python2.7 -c _nms.c -o ./_nms.o -std=c99 -std=c99x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fno-strict-aliasing -Wdate-time -D_FORTI
FY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security -fPIC -DWITH_CUDA -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/usr/include/python2.7 -c /pytorch-retinanet/lib/nms/src/nms.c -o ./pytorch-retinanet/lib/nms/src/nms.o -std=c99 -std=c99x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fno-strict-aliasing -Wdate-time -D_FORTI
FY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security -fPIC -DWITH_CUDA -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/usr/include/python2.7 -c /pytorch-retinanet/lib/nms/src/nms_cuda.c -o ./pytorch-retinanet/lib/nms/src/nms_cuda.o -std=c99 -std=c99/pytorch-retinanet/lib/nms/src/nms_cuda.c: In function ‘gpu_nms’:
/pytorch-retinanet/lib/nms/src/nms_cuda.c:29:35: warning: initialization from incompatible pointer type [-Wincompatible-p
ointer-types] unsigned long long* mask_flat = THCudaLongTensor_data(state, mask);
^
/pytorch-retinanet/lib/nms/src/nms_cuda.c:37:40: warning: initialization from incompatible pointer type [-Wincompatible-p
ointer-types] unsigned long long * mask_cpu_flat = THLongTensor_data(mask_cpu);
^
/pytorch-retinanet/lib/nms/src/nms_cuda.c:40:39: warning: initialization from incompatible pointer type [-Wincompatible-p
ointer-types] unsigned long long* remv_cpu_flat = THLongTensor_data(remv_cpu);
^
/pytorch-retinanet/lib/nms/src/nms_cuda.c:23:7: warning: unused variable ‘boxes_dim’ [-Wunused-variable]
int boxes_dim = THCudaTensor_size(state, boxes, 1);
^
x86_64-linux-gnu-gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -fno-strict-
aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -Wdate-time -D_FORTIFY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wl,-Bsymbolic-functions -Wl,-z,relro -Wdate-time -D_FORTIFY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security ./_nms.o ./pytorch-retinanet/lib/nms/src/nms.o ./pytorch-retinanet/lib/nms/src/nms_cuda.o /pytorch-retinanet/lib/nms/src/cuda/nms_kernel.cu.o -o ./_nms.so

2. I run it in docker(on a Linux machine) instread of jupyter notebook.
   Thanks.

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@yhenon Hi have you figured out the problem of nms yet?I think I confront the same problem but I run it in a jupyter notebook. Thx

Well, I've read the codes about NMS and I think there is a problem as using only one pass of nms which treated all the detected objects in the same category. Shouldn't it using nms several times over each categories?
However, I'm not quite sure that this problem related to @CPFLAME yours

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@qq184861643 HI
Agree with u.

In my experiment, although visualize works fine, there was no problem. But i think we should do nms once for each category when using NMS.

@yhenon
hope your help!!
many many thanks!!

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I come across the same problem! The NMS extension has been compiled without any errors. I don't know how to solve it. Can anyone help me?

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