Something on RoIAlign --- basic introduction and implementation

2018-10-22 22:40:09

Paper: Mask RCNN

Codehttps://github.com/longcw/RoIAlign.pytorch

Blog:

1. https://www.cnblogs.com/wangyong/p/8523814.html

2. https://blog.csdn.net/JNingWei/article/details/78822159

3. https://blog.csdn.net/Julialove102123/article/details/80567827

===========  Introduction  ===========

see this blog: https://www.cnblogs.com/wangxiaocvpr/p/9840230.html

===========  Implementation  ===========

git clone https://github.com/longcw/RoIAlign.pytorch

cd RoIAlign.pytorch

modify the script install.sh and test.sh into the following way:

#!/usr/bin/env bash

CUDA_PATH=/usr/local/cuda

echo "Compiling crop_and_resize kernels by nvcc..."
cd roi_align/src/cuda
$CUDA_PATH/bin/nvcc -c -o crop_and_resize_kernel.cu.o crop_and_resize_kernel.cu -x cu -Xcompiler -fPIC -arch=sm_30 \
-gencode=arch=compute_30,code=sm_30 \
-gencode=arch=compute_50,code=sm_50 \
-gencode=arch=compute_52,code=sm_52 \
-gencode=arch=compute_60,code=sm_60 \
-gencode=arch=compute_61,code=sm_61 \
-gencode=arch=compute_62,code=sm_62 \ cd ../../../roi_align
python3 build.py cd ..
python3 setup.py install
#find $CONDA_PREFIX -name roi_align | awk '{mkdir $0 "/_ext" }' |bash
#find $CONDA_PREFIX -name roi_align | awk '{print "cp -r roi_align/_ext/* " $0 "/_ext/" }' |bash
python3 tests/test.py
python3 tests/test2.py
python3 tests/crop_and_resize_example.py

then, run the test.sh, you can found this:

wangxiao@AHU:/media/wangxiao/b8efbc67-7ea5-476d-9631-70da75f84e2d/reference_code/RoIAlign.pytorch$ sh ./test.sh
/usr/local/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6
return f(*args, **kwds)
pytorch forward and backward start
pytorch forward and backward end
2018-10-22 22:38:28.483699: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2018-10-22 22:38:28.492705: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:892] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-10-22 22:38:28.493019: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Found device 0 with properties:
name: GeForce GTX 1080 major: 6 minor: 1 memoryClockRate(GHz): 1.898
pciBusID: 0000:02:00.0
totalMemory: 7.92GiB freeMemory: 6.29GiB
2018-10-22 22:38:28.493047: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce GTX 1080, pci bus id: 0000:02:00.0, compute capability: 6.1)
2018-10-22 22:38:28.737003: E tensorflow/stream_executor/cuda/cuda_dnn.cc:378] Loaded runtime CuDNN library: 7102 (compatibility version 7100) but source was compiled with 6021 (compatibility version 6000). If using a binary install, upgrade your CuDNN library to match. If building from sources, make sure the library loaded at runtime matches a compatible version specified during compile configuration.
2018-10-22 22:38:28.737107: F tensorflow/core/kernels/conv_ops.cc:667] Check failed: stream->parent()->GetConvolveAlgorithms( conv_parameters.ShouldIncludeWinogradNonfusedAlgo<T>(), &algorithms)
Aborted
tensor([[[[0., 1., 2.],
[0., 1., 2.],
[0., 1., 2.]]]], grad_fn=<CropAndResizeFunction>)
torch.Size([2, 3, 500, 500])


Some Bug you may meet:

1. cffi.error.VerificationError: LinkError: command 'x86_64-linux-gnu-gcc' failed with exit status 1 

==>> run the followings in the terminal before you run "sh make.sh":

export CUDA_PATH=/usr/local/cuda/
export CXXFLAGS="-std=c++11"
export CFLAGS="-std=c99"
export PATH=/usr/local/cuda-8.0/bin${PATH:+:${PATH}}
export CPATH=/usr/local/cuda-8.0/include${CPATH:+:${CPATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

then, it will shown you the followings:

wangxiao@AHU:~/Documents/Detectron.pytorch/lib$ sh make.sh
running build_ext
building 'utils.cython_bbox' extension
creating build
creating build/temp.linux-x86_64-2.7
creating build/temp.linux-x86_64-2.7/utils
x86_64-linux-gnu-gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -std=c99 -fPIC -I/usr/local/lib/python2./dist-packages/numpy/core/include -I/usr/include/python2. -c utils/cython_bbox.c -o build/temp.linux-x86_64-2.7/utils/cython_bbox.o -Wno-cpp
creating build/lib.linux-x86_64-2.7
creating build/lib.linux-x86_64-2.7/utils
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 -D_FORTIFY_SOURCE= -g -fstack-protector --param=ssp-buffer-size= -Wformat -Werror=format-security -std=c99 build/temp.linux-x86_64-2.7/utils/cython_bbox.o -o build/lib.linux-x86_64-2.7/utils/cython_bbox.so
building 'utils.cython_nms' extension
x86_64-linux-gnu-gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -std=c99 -fPIC -I/usr/local/lib/python2./dist-packages/numpy/core/include -I/usr/include/python2. -c utils/cython_nms.c -o build/temp.linux-x86_64-2.7/utils/cython_nms.o -Wno-cpp
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 -D_FORTIFY_SOURCE= -g -fstack-protector --param=ssp-buffer-size= -Wformat -Werror=format-security -std=c99 build/temp.linux-x86_64-2.7/utils/cython_nms.o -o build/lib.linux-x86_64-2.7/utils/cython_nms.so
copying build/lib.linux-x86_64-2.7/utils/cython_bbox.so -> utils
copying build/lib.linux-x86_64-2.7/utils/cython_nms.so -> utils
Compiling nms kernels by nvcc...
Including CUDA code.
/home/wangxiao/Documents/Detectron.pytorch/lib/model/nms
['/home/wangxiao/Documents/Detectron.pytorch/lib/model/nms/src/nms_cuda_kernel.cu.o']
generating /tmp/tmp1cFjY6/_nms.c
setting the current directory to '/tmp/tmp1cFjY6'
running build_ext
building '_nms' extension
creating home
creating home/wangxiao
creating home/wangxiao/Documents
creating home/wangxiao/Documents/Detectron.pytorch
creating home/wangxiao/Documents/Detectron.pytorch/lib
creating home/wangxiao/Documents/Detectron.pytorch/lib/model
creating home/wangxiao/Documents/Detectron.pytorch/lib/model/nms
creating home/wangxiao/Documents/Detectron.pytorch/lib/model/nms/src
x86_64-linux-gnu-gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -std=c99 -fPIC -DWITH_CUDA -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/usr/include/python2. -c _nms.c -o ./_nms.o
x86_64-linux-gnu-gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -std=c99 -fPIC -DWITH_CUDA -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/usr/include/python2. -c /home/wangxiao/Documents/Detectron.pytorch/lib/model/nms/src/nms_cuda.c -o ./home/wangxiao/Documents/Detectron.pytorch/lib/model/nms/src/nms_cuda.o
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 -D_FORTIFY_SOURCE= -g -fstack-protector --param=ssp-buffer-size= -Wformat -Werror=format-security -std=c99 ./_nms.o ./home/wangxiao/Documents/Detectron.pytorch/lib/model/nms/src/nms_cuda.o /home/wangxiao/Documents/Detectron.pytorch/lib/model/nms/src/nms_cuda_kernel.cu.o -o ./_nms.so
Compiling roi pooling kernels by nvcc...
Including CUDA code.
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_pooling
generating /tmp/tmpUUPhTw/_roi_pooling.c
setting the current directory to '/tmp/tmpUUPhTw'
running build_ext
building '_roi_pooling' extension
creating home
creating home/wangxiao
creating home/wangxiao/Documents
creating home/wangxiao/Documents/Detectron.pytorch
creating home/wangxiao/Documents/Detectron.pytorch/lib
creating home/wangxiao/Documents/Detectron.pytorch/lib/model
creating home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_pooling
creating home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_pooling/src
x86_64-linux-gnu-gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -std=c99 -fPIC -DWITH_CUDA -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/usr/include/python2. -c _roi_pooling.c -o ./_roi_pooling.o
x86_64-linux-gnu-gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -std=c99 -fPIC -DWITH_CUDA -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/usr/include/python2. -c /home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_pooling/src/roi_pooling.c -o ./home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_pooling/src/roi_pooling.o
x86_64-linux-gnu-gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -std=c99 -fPIC -DWITH_CUDA -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/usr/include/python2. -c /home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_pooling/src/roi_pooling_cuda.c -o ./home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_pooling/src/roi_pooling_cuda.o
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 -D_FORTIFY_SOURCE= -g -fstack-protector --param=ssp-buffer-size= -Wformat -Werror=format-security -std=c99 ./_roi_pooling.o ./home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_pooling/src/roi_pooling.o ./home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_pooling/src/roi_pooling_cuda.o /home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_pooling/src/roi_pooling.cu.o -o ./_roi_pooling.so
Compiling roi crop kernels by nvcc...
Including CUDA code.
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop
generating /tmp/tmp2NBTVb/_roi_crop.c
setting the current directory to '/tmp/tmp2NBTVb'
running build_ext
building '_roi_crop' extension
creating home
creating home/wangxiao
creating home/wangxiao/Documents
creating home/wangxiao/Documents/Detectron.pytorch
creating home/wangxiao/Documents/Detectron.pytorch/lib
creating home/wangxiao/Documents/Detectron.pytorch/lib/model
creating home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop
creating home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src
x86_64-linux-gnu-gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -std=c99 -fPIC -DWITH_CUDA -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/usr/include/python2. -c _roi_crop.c -o ./_roi_crop.o
x86_64-linux-gnu-gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -std=c99 -fPIC -DWITH_CUDA -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/usr/include/python2. -c /home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.c -o ./home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.o
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.c: In function ‘BilinearSamplerBHWD_updateGradInput’:
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.c::: warning: unused variable ‘inBottomRight’ [-Wunused-variable]
real inBottomRight=;
^
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.c::: warning: unused variable ‘inBottomLeft’ [-Wunused-variable]
real inBottomLeft=;
^
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.c::: warning: unused variable ‘inTopRight’ [-Wunused-variable]
real inTopRight=;
^
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.c::: warning: unused variable ‘inTopLeft’ [-Wunused-variable]
real inTopLeft=;
^
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.c::: warning: unused variable ‘v’ [-Wunused-variable]
real v=;
^
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.c: In function ‘BilinearSamplerBCHW_updateGradInput’:
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.c::: warning: unused variable ‘inBottomRight’ [-Wunused-variable]
real inBottomRight=;
^
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.c::: warning: unused variable ‘inBottomLeft’ [-Wunused-variable]
real inBottomLeft=;
^
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.c::: warning: unused variable ‘inTopRight’ [-Wunused-variable]
real inTopRight=;
^
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.c::: warning: unused variable ‘inTopLeft’ [-Wunused-variable]
real inTopLeft=;
^
/home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.c::: warning: unused variable ‘v’ [-Wunused-variable]
real v=;
^
x86_64-linux-gnu-gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -std=c99 -fPIC -DWITH_CUDA -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/usr/include/python2. -c /home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop_cuda.c -o ./home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop_cuda.o
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 -D_FORTIFY_SOURCE= -g -fstack-protector --param=ssp-buffer-size= -Wformat -Werror=format-security -std=c99 ./_roi_crop.o ./home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop.o ./home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop_cuda.o /home/wangxiao/Documents/Detectron.pytorch/lib/model/roi_crop/src/roi_crop_cuda_kernel.cu.o -o ./_roi_crop.so
Compiling roi align kernels by nvcc...
Including CUDA code.
/home/wangxiao/Documents/Detectron.pytorch/lib/modeling/roi_xfrom/roi_align
generating /tmp/tmptraHMG/_roi_align.c
setting the current directory to '/tmp/tmptraHMG'
running build_ext
building '_roi_align' extension
creating home
creating home/wangxiao
creating home/wangxiao/Documents
creating home/wangxiao/Documents/Detectron.pytorch
creating home/wangxiao/Documents/Detectron.pytorch/lib
creating home/wangxiao/Documents/Detectron.pytorch/lib/modeling
creating home/wangxiao/Documents/Detectron.pytorch/lib/modeling/roi_xfrom
creating home/wangxiao/Documents/Detectron.pytorch/lib/modeling/roi_xfrom/roi_align
creating home/wangxiao/Documents/Detectron.pytorch/lib/modeling/roi_xfrom/roi_align/src
x86_64-linux-gnu-gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -std=c99 -fPIC -DWITH_CUDA -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/usr/include/python2. -c _roi_align.c -o ./_roi_align.o
x86_64-linux-gnu-gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -std=c99 -fPIC -DWITH_CUDA -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2./dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/usr/include/python2. -c /home/wangxiao/Documents/Detectron.pytorch/lib/modeling/roi_xfrom/roi_align/src/roi_align_cuda.c -o ./home/wangxiao/Documents/Detectron.pytorch/lib/modeling/roi_xfrom/roi_align/src/roi_align_cuda.o
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 -D_FORTIFY_SOURCE= -g -fstack-protector --param=ssp-buffer-size= -Wformat -Werror=format-security -std=c99 ./_roi_align.o ./home/wangxiao/Documents/Detectron.pytorch/lib/modeling/roi_xfrom/roi_align/src/roi_align_cuda.o /home/wangxiao/Documents/Detectron.pytorch/lib/modeling/roi_xfrom/roi_align/src/roi_align_kernel.cu.o -o ./_roi_align.so
wangxiao@AHU:~/Documents/Detectron.pytorch/lib$

2. You may also meet the following issues: AttributeError: 'module' object has no attribute 'getLogger'

Traceback (most recent call last):
File "tools/train_net_step.py", line , in <module>
import utils.net as net_utils
File "/home/Detectron.pytorch/lib/utils/net.py", line , in <module>
logger = logging.getLogger(__name__)
AttributeError: 'module' object has no attribute 'getLogger'

you need to re-compile the lib with python3.6. i.e. change the make.sh into follows: 

#!/usr/bin/env bash

CUDA_PATH=/usr/local/cuda/

python3 setup.py build_ext --inplace
rm -rf build # Choose cuda arch as you need
CUDA_ARCH="-gencode arch=compute_30,code=sm_30 \
-gencode arch=compute_35,code=sm_35 \
-gencode arch=compute_50,code=sm_50 \
-gencode arch=compute_52,code=sm_52 \
-gencode arch=compute_60,code=sm_60 \
-gencode arch=compute_61,code=sm_61 "
# -gencode arch=compute_70,code=sm_70 " # compile NMS
cd model/nms/src
echo "Compiling nms kernels by nvcc..."
nvcc -c -o nms_cuda_kernel.cu.o nms_cuda_kernel.cu \
-D GOOGLE_CUDA= -x cu -Xcompiler -fPIC $CUDA_ARCH cd ../
python3 build.py # compile roi_pooling
cd ../../
cd model/roi_pooling/src
echo "Compiling roi pooling kernels by nvcc..."
nvcc -c -o roi_pooling.cu.o roi_pooling_kernel.cu \
-D GOOGLE_CUDA= -x cu -Xcompiler -fPIC $CUDA_ARCH
cd ../
python3 build.py # # compile roi_align
# cd ../../
# cd model/roi_align/src
# echo "Compiling roi align kernels by nvcc..."
# nvcc -c -o roi_align_kernel.cu.o roi_align_kernel.cu \
# -D GOOGLE_CUDA= -x cu -Xcompiler -fPIC $CUDA_ARCH
# cd ../
# python3 build.py # compile roi_crop
cd ../../
cd model/roi_crop/src
echo "Compiling roi crop kernels by nvcc..."
nvcc -c -o roi_crop_cuda_kernel.cu.o roi_crop_cuda_kernel.cu \
-D GOOGLE_CUDA= -x cu -Xcompiler -fPIC $CUDA_ARCH
cd ../
python3 build.py # compile roi_align (based on Caffe2's implementation)
cd ../../
cd modeling/roi_xfrom/roi_align/src
echo "Compiling roi align kernels by nvcc..."
nvcc -c -o roi_align_kernel.cu.o roi_align_kernel.cu \
-D GOOGLE_CUDA= -x cu -Xcompiler -fPIC $CUDA_ARCH
cd ../
python3 build.py

you also need to copy the file: e2e_mask_rcnn_R-50-C4_1x.yaml and rename it as: e2e_mask_rcnn_R-50-C4.yml

then, you can run the script to train the model: 

$ python3 tools/train_net_step.py --dataset coco2017 --cfg configs/baselines/e2e_mask_rcnn_R-50-C4.yml --use_tfboard --bs 5 --nw 2

wangxiao@AHU:~/Documents/Detectron.pytorch$ python3 tools/train_net_step.py --dataset coco2017 --cfg configs/baselines/e2e_mask_rcnn_R--C4.yml --use_tfboard --bs  --nw 
Called with args:
Namespace(batch_size=, cfg_file='configs/baselines/e2e_mask_rcnn_R-50-C4.yml', cuda=True, dataset='coco2017', disp_interval=, iter_size=, load_ckpt=None, load_detectron=None, lr=None, lr_decay_gamma=None, no_save=False, num_workers=, optimizer=None, resume=False, set_cfgs=[], start_step=, use_tfboard=True)
effective_batch_size = batch_size * iter_size = *
Adaptive config changes:
effective_batch_size: -->
NUM_GPUS: -->
IMS_PER_BATCH: -->
Adjust BASE_LR linearly according to batch_size change:
BASE_LR: 0.01 --> 0.00125
Adjust SOLVER.STEPS and SOLVER.MAX_ITER linearly based on effective_batch_size change:
SOLVER.STEPS: [, , ] --> [, , ]
SOLVER.MAX_ITER: -->
Number of data loading threads:
loading annotations into memory...
Done (t=.39s)
creating index...
index created!
INFO json_dataset.py: : Loading cached gt_roidb from /home/wangxiao/Documents/Detectron.pytorch/data/cache/coco_2017_train_gt_roidb.pkl
INFO roidb.py: : Appending horizontally-flipped training examples...
INFO roidb.py: : Loaded dataset: coco_2017_train
INFO roidb.py: : Filtered roidb entries: ->
INFO roidb.py: : Computing image aspect ratios and ordering the ratios...
INFO roidb.py: : done
INFO roidb.py: : Computing bounding-box regression targets...
INFO roidb.py: : done
INFO train_net_step.py: : roidb entries
INFO train_net_step.py: : Takes 93.39 sec(s) to construct roidb
INFO train_net_step.py: : Training starts !
INFO net.py: : Changing learning rate 0.000000 -> 0.000417
/usr/local/lib/python3./site-packages/torch/nn/functional.py:: UserWarning: nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.
warnings.warn("nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.")
/usr/local/lib/python3./site-packages/torch/nn/functional.py:: UserWarning: size_average and reduce args will be deprecated, please use reduction='sum' instead.
warnings.warn(warning.format(ret))
[Nov24---26_AHU_step][e2e_mask_rcnn_R--C4.yml][Step / ]
loss: 6.916170, lr: 0.000417 time: 0.721983, eta: days, ::
accuracy_cls: 0.001953
loss_cls: 4.648660, loss_bbox: 0.030453, loss_mask: 0.858463
loss_rpn_cls: 0.676336, loss_rpn_bbox: 0.702258

==

Something on RoIAlign --- basic introduction and implementation的更多相关文章

  1. The basic introduction to MIX language and machine

    reference: The MIX Computer, The MIX Introduction sets, The basic info storage unit in MIX computer ...

  2. RESTFul basic introduction

    http://www.ruanyifeng.com/blog/2011/09/restful.html

  3. 可分离卷积详解及计算量 Basic Introduction to Separable Convolutions

    任何看过MobileNet架构的人都会遇到可分离卷积(separable convolutions)这个概念.但什么是“可分离卷积”,它与标准的卷积又有什么区别?可分离卷积主要有两种类型: 空间可分离 ...

  4. Cyber Security - Palo Alto Basic Introduction

    Preparation of the Lab Environment: Download and Install Pan-OS from the following website https://d ...

  5. 6.在MVC中使用泛型仓储模式和依赖注入实现增删查改

    原文链接:http://www.c-sharpcorner.com/UploadFile/3d39b4/crud-operations-using-the-generic-repository-pat ...

  6. 机器学习公开课笔记(4):神经网络(Neural Network)——表示

    动机(Motivation) 对于非线性分类问题,如果用多元线性回归进行分类,需要构造许多高次项,导致特征特多学习参数过多,从而复杂度太高. 神经网络(Neural Network) 一个简单的神经网 ...

  7. TensorFlow tutorial

    代码示例来自https://github.com/aymericdamien/TensorFlow-Examples tensorflow先定义运算图,在run的时候才会进行真正的运算. run之前需 ...

  8. CSC 172 (Data Structures and Algorithms)

    Project #3 (STREET MAPPING)CSC 172 (Data Structures and Algorithms), Spring 2019,University of Roche ...

  9. How do I learn machine learning?

    https://www.quora.com/How-do-I-learn-machine-learning-1?redirected_qid=6578644   How Can I Learn X? ...

随机推荐

  1. 补充:MySQL整理

    1.连接Mysql 格式: mysql -h主机地址 -u用户名 -p用户密码 1.连接到本机上的MYSQL.首先打开DOS窗口,然后进入目录mysql\bin,再键入命令mysql -u root ...

  2. PHP(css样式)

    布局页面的时候 大色块 小色块 ...(就是宽高) 内容布局:浮动,定位,显示,层级 浮动:float(样式名):值:left right设一个父标签,设定宽高,里面随便浮动!!!!!!!!!!!!! ...

  3. jsignature 中文开发手册

    2017年5月9日21:23:17,最近比较忙,没时间写博客,真的是越来越懒来了 github:https://github.com/brinley/jSignature http://www.unb ...

  4. arcpy 零碎知识

    记忆力越来越差,在这里记些东西: 1.使用 CURRENT 引用 ArcMap 中当前加载的地图文档时,有时需要刷新内容列表或活动视图(数据视图或布局视图). 在 Python 窗口中输入以下两行,在 ...

  5. python下载网页视频

    因网站不同需要修改. 下载 mp4 连接 from bs4 import BeautifulSoup import requests import urllib import re import js ...

  6. Spring事物管理--相关要点及配置事物管理器

    事务的四大特征 1.原子性:一个事务中所有对数据库的操作是一个不可分割的操作序列,要么全做要么全不做 2.一致性:数据不会因为事务的执行而遭到破坏 3.隔离性:一个事物的执行,不受其他事务的干扰,即并 ...

  7. RoR - Creating and Modifying Table and Columns

    自动生成的id 被当作primary key来使用 timestamp method生成 created_at 与 updated_at columns create_table 和 drop_tab ...

  8. 【UML】NO.53.EBook.5.UML.1.013-【UML 大战需求分析】- 组合结构图(Composition Structure Diagram)

    1.0.0 Summary Tittle:[UML]NO.52.EBook.1.UML.1.012-[UML 大战需求分析]- 交互概览图(Interaction Overview Diagram) ...

  9. asp.net机制理解(Javaweb同理)

    1.页面运行先后顺序 先执行aspx中的代码,然后再合并到HTML中,最后一起送到浏览器执行,HTML是从上到下执行的,而HTML中的Windows.onload()最后执行.而由于aspx中的代码是 ...

  10. python second lesson

    1.系统模块 新建的文件名不能和导入的库名相同,要不然python会优先从自己的目录下寻找. import sys  sys是一个系统变量,sys.argv会调出文件的相对路径,sys.argv[2] ...