hi,I want to konw can the code run on windows? It only run on ubuntu?

Modified, with gpu_nms supports I ran it on windows successfully (Python 3.6.6, VS2015 compiler, CUDA 9.0 with CUDNN v7), just modify some code. Tested both cpu_nms and gpu_nms (but don't know why gpu_nms is a little slower than cpu_nms).

Note: If any strange error occurred, I suggest deleting all the generated .c and .cpp files (lib/nms/cpu_nms.c, lib/nms/gpu_nms.cpp, lib/utils/bbox.c) and everything in lib/build

file lib/nms/cpu_nms.pyx:
change (line 25)

cdef np.ndarray[np.int_t, ndim=1] order = scores.argsort()[::-1]

to

cdef np.ndarray[np.int64_t, ndim=1] order = scores.argsort()[::-1]

file lib/nms/gpu_nms.pyx: change (line 25)

    cdef np.ndarray[np.int_t, ndim=1] \

to

    cdef np.ndarray[np.int64_t, ndim=1] \

file lib/datasets/pascal_voc.py: change (line 226)

      '{:s}.xml')

to

      '{0:s}.xml')

file lib/datasets/voc_eval.py change (line 121)

    with open(cachefile, 'w') as f:

to

    with open(cachefile, 'wb') as f:

file lib/setup.py (nearly full modified, new code is as follow):

# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------

import os
from os.path import join as pjoin
import numpy as np
from distutils.core import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext

def find_in_path(name, path):
    "Find a file in a search path"
    #adapted fom http://code.activestate.com/recipes/52224-find-a-file-given-a-search-path/
    for dir in path.split(os.pathsep):
        binpath = pjoin(dir, name)
        if os.path.exists(binpath):
            return os.path.abspath(binpath)
    return None

def locate_cuda():
    """Locate the CUDA environment on the system

    Returns a dict with keys 'home', 'nvcc', 'include', and 'lib64'
    and values giving the absolute path to each directory.

    Starts by looking for the CUDAHOME env variable. If not found, everything
    is based on finding 'nvcc' in the PATH.
    """

    # first check if the CUDAHOME env variable is in use
    if 'CUDAHOME' in os.environ:
        home = os.environ['CUDAHOME']
        nvcc = pjoin(home, 'bin', 'nvcc')
    else:
        # otherwise, search the PATH for NVCC
        nvcc = find_in_path('nvcc.exe', os.environ['PATH'])
        if nvcc is None:
            raise EnvironmentError('The nvcc binary could not be '
                'located in your $PATH. Either add it to your path, or set $CUDAHOME')
        home = os.path.dirname(os.path.dirname(nvcc))

    cudaconfig = {'home':home, 'nvcc':nvcc,
                  'include': pjoin(home, 'include'),
                  'lib64': pjoin(home, 'lib', 'x64')}
    for k, v in iter(cudaconfig.items()):
        if not os.path.exists(v):
            raise EnvironmentError('The CUDA %s path could not be located in %s' % (k, v))

    return cudaconfig
CUDA = locate_cuda()

# Obtain the numpy include directory.  This logic works across numpy versions.
try:
    numpy_include = np.get_include()
except AttributeError:
    numpy_include = np.get_numpy_include()

def customize_compiler_for_nvcc(self):
    # _msvccompiler.py imports:
    import os
    import shutil
    import stat
    import subprocess
    import winreg

    from distutils.errors import DistutilsExecError, DistutilsPlatformError, \
                                 CompileError, LibError, LinkError
    from distutils.ccompiler import CCompiler, gen_lib_options
    from distutils import log
    from distutils.util import get_platform

    from itertools import count

    super = self.compile
    self.src_extensions.append('.cu')
    # find python include
    import sys
    py_dir = sys.executable.replace('\\', '/').split('/')[:-1]
    py_include = pjoin('/'.join(py_dir), 'include')

    # override method in _msvccompiler.py, starts from line 340
    def compile(sources,
                output_dir=None, macros=None, include_dirs=None, debug=0,
                extra_preargs=None, extra_postargs=None, depends=None):

        if not self.initialized:
            self.initialize()
        compile_info = self._setup_compile(output_dir, macros, include_dirs,
                                           sources, depends, extra_postargs)
        macros, objects, extra_postargs, pp_opts, build = compile_info

        compile_opts = extra_preargs or []
        compile_opts.append('/c')
        if debug:
            compile_opts.extend(self.compile_options_debug)
        else:
            compile_opts.extend(self.compile_options)

        add_cpp_opts = False

        for obj in objects:
            try:
                src, ext = build[obj]
            except KeyError:
                continue
            if debug:
                # pass the full pathname to MSVC in debug mode,
                # this allows the debugger to find the source file
                # without asking the user to browse for it
                src = os.path.abspath(src)

            if ext in self._c_extensions:
                input_opt = "/Tc" + src
            elif ext in self._cpp_extensions:
                input_opt = "/Tp" + src
                add_cpp_opts = True
            elif ext in self._rc_extensions:
                # compile .RC to .RES file
                input_opt = src
                output_opt = "/fo" + obj
                try:
                    self.spawn([self.rc] + pp_opts + [output_opt, input_opt])
                except DistutilsExecError as msg:
                    raise CompileError(msg)
                continue
            elif ext in self._mc_extensions:
                # Compile .MC to .RC file to .RES file.
                #   * '-h dir' specifies the directory for the
                #     generated include file
                #   * '-r dir' specifies the target directory of the
                #     generated RC file and the binary message resource
                #     it includes
                #
                # For now (since there are no options to change this),
                # we use the source-directory for the include file and
                # the build directory for the RC file and message
                # resources. This works at least for win32all.
                h_dir = os.path.dirname(src)
                rc_dir = os.path.dirname(obj)
                try:
                    # first compile .MC to .RC and .H file
                    self.spawn([self.mc, '-h', h_dir, '-r', rc_dir, src])
                    base, _ = os.path.splitext(os.path.basename(src))
                    rc_file = os.path.join(rc_dir, base + '.rc')
                    # then compile .RC to .RES file
                    self.spawn([self.rc, "/fo" + obj, rc_file])

                except DistutilsExecError as msg:
                    raise CompileError(msg)
                continue
            elif ext == '.cu':
                # a trigger for cu compile
                try:
                    # use the cuda for .cu files
                    # self.set_executable('compiler_so', CUDA['nvcc'])
                    # use only a subset of the extra_postargs, which are 1-1 translated
                    # from the extra_compile_args in the Extension class
                    postargs = extra_postargs['nvcc']
                    arg = [CUDA['nvcc']] + sources + ['-odir', pjoin(output_dir, 'nms')]
                    for include_dir in include_dirs:
                        arg.append('-I')
                        arg.append(include_dir)
                    arg += ['-I', py_include]
                    # arg += ['-lib', CUDA['lib64']]
                    arg += ['-Xcompiler', '/EHsc,/W3,/nologo,/Ox,/MD']
                    arg += postargs
                    self.spawn(arg)
                    continue
                except DistutilsExecError as msg:
                    # raise CompileError(msg)
                    continue
            else:
                # how to handle this file?
                raise CompileError("Don't know how to compile {} to {}"
                                   .format(src, obj))

            args = [self.cc] + compile_opts + pp_opts
            if add_cpp_opts:
                args.append('/EHsc')
            args.append(input_opt)
            args.append("/Fo" + obj)
            args.extend(extra_postargs)

            try:
                self.spawn(args)
            except DistutilsExecError as msg:
                raise CompileError(msg)

        return objects

    self.compile = compile

# run the customize_compiler
class custom_build_ext(build_ext):
    def build_extensions(self):
        customize_compiler_for_nvcc(self.compiler)
        build_ext.build_extensions(self)

ext_modules = [
    Extension(
        "utils.cython_bbox",
        ["utils/bbox.pyx"],
        extra_compile_args={'gcc': ["-Wno-cpp", "-Wno-unused-function"]},
        include_dirs = [numpy_include]
    ),
    Extension(
        "nms.cpu_nms",
        ["nms/cpu_nms.pyx"],
        include_dirs = [numpy_include]
    ),
    Extension('nms.gpu_nms',
        ['nms/nms_kernel.cu', 'nms/gpu_nms.pyx'],
        library_dirs=[CUDA['lib64']],
        libraries=['cudart'],
        language='c++',
        # this syntax is specific to this build system
        # we're only going to use certain compiler args with nvcc and not with gcc
        # the implementation of this trick is in customize_compiler() below
        extra_compile_args={'gcc': ["-Wno-unused-function"],
                            'nvcc': ['-arch=sm_52',
                                     '--ptxas-options=-v',
                                     '-c']},
        include_dirs = [numpy_include, CUDA['include']]
    )
]

setup(
    name='tf_faster_rcnn',
    ext_modules=ext_modules,
    # inject our custom trigger
    cmdclass={'build_ext': custom_build_ext},
)

It's take me some time to understand how MSVC compiler works, so I made an ugly patch for the compiler by overriding the compile method.

Note: Change the -arch=sm_52 above to fit your graphic card, otherwise using gpu_nms will get the corrupt result. You can follow the original installation guide.

Now, turn to lib directory, run python setup.py build_ext. It possible reports an error:

nms\gpu_nms.cpp(2075): error C2664: "void _nms(int *,int *,const float *,int,int,float,int)": cannot convert parameter 1 from '__pyx_t_5numpy_int32_t *' to 'int *'

Modify one line in the generated file in lib/nms/gpu_nms.cpp, search the keyword _nms, find the following line: change (line 2075 in my generated cpp file)

  _nms((&(*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int32_t *, __pyx_pybuffernd_keep.rcbuffer->pybuffer.buf, __pyx_t_10, ...

to

  _nms((&(*__Pyx_BufPtrStrided1d(int *, __pyx_pybuffernd_keep.rcbuffer->pybuffer.buf, __pyx_t_10, ...

At last, run python setup.py build_ext again, copy everything in lib/build/lib.win-amd64-3.6 to lib.

After trying this ^ and launching "python setup.py build_ext" getting running build_ext cythoning utils/bbox.pyx to utils\bbox.c building 'utils.cython_bbox' extension error: Unable to find vcvarsall.bat

I guess problem is i'm using VS2017... Any way to avoid that error? Only installation of VS2015?

Hey, doing the same atm.. Currently trying this: https://stackoverflow.com/questions/43372235/vcvarsall-bat-for-visual-studio-2017

will notify if it works. It's probably the same issue for you

cpu_nms.cp36-win_amd64 I want to download. How do I download this file?

can it run with gpu_nms on windows?

nms_kernel.cu @qhgz2013 I tried your method, andI met a link error: 'cannot open input file 'build\temp.win-amd64-3.5\Release\nms/nms_kernel.obj' Any thoughts how to fix this? Thanks

@sunglowzhang it seems that nvcc could not compile the cu file, it is helpful to figure out what went wrong if you provide a detailed output.

Here is some suggestions. Use cpu_nms only, just follow the first version of my answer. Make sure that nvcc is in your PATH environment, run nvcc --version to see whether it works or not. Or maybe the python 3.5 builtin _msvccompiler.py file is different from python 3.6, to fix it, you need to rewrite the def compile function in setup.py based on python 3.5.

C:\Users\AppData\Local\Continuum\miniconda3\envs\py36tf\python.exe D:/cProjects/Github/rcnn/tf-faster-rcnn-master/lib/setup.py build_ext --inplace running build_ext skipping 'utils\bbox.c' Cython extension (up-to-date) building 'utils.cython_bbox' extension C:\Program Files (x86)\Microsoft Visual Studio\2017\BuildTools\VC\Tools\MSVC\14.15.26726\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -IC:\Users\AppData\Local\Continuum\miniconda3\envs\py36tf\lib\site-packages\numpy\core\include -IC:\Users\AppData\Local\Continuum\miniconda3\envs\py36tf\include -IC:\Users\AppData\Local\Continuum\miniconda3\envs\py36tf\include "-IC:\Program Files (x86)\Microsoft Visual Studio\2017\BuildTools\VC\Tools\MSVC\14.15.26726\include" "-IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.6.1\include\um" "-IC:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\ucrt" "-IC:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\shared" "-IC:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\um" "-IC:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\winrt" "-IC:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\cppwinrt" /Tcutils\bbox.c /Fobuild\temp.win-amd64-3.6\Release\utils\bbox.obj gcc bbox.c cl : Command line warning D9024 : unrecognized source file type 'gcc', object file assumed cl : Command line warning D9027 : source file 'gcc' ignored c:\users\appdata\local\continuum\miniconda3\envs\py36tf\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION utils\bbox.c(1938): warning C4244: '=': conversion from 'npy_intp' to 'unsigned int', possible loss of data utils\bbox.c(1947): warning C4244: '=': conversion from 'npy_intp' to 'unsigned int', possible loss of data C:\Program Files (x86)\Microsoft Visual Studio\2017\BuildTools\VC\Tools\MSVC\14.15.26726\bin\HostX86\x64\link.exe /nologo /INCREMENTAL:NO /LTCG /DLL /MANIFEST:EMBED,ID=2 /MANIFESTUAC:NO /LIBPATH:C:\Users\AppData\Local\Continuum\miniconda3\envs\py36tf\libs /LIBPATH:C:\Users\AppData\Local\Continuum\miniconda3\envs\py36tf\PCbuild\amd64 "/LIBPATH:C:\Program Files (x86)\Microsoft Visual Studio\2017\BuildTools\VC\Tools\MSVC\14.15.26726\lib\x64" "/LIBPATH:C:\Program Files (x86)\Windows Kits\NETFXSDK\4.6.1\lib\um\x64" "/LIBPATH:C:\Program Files (x86)\Windows Kits\10\lib\10.0.17134.0\ucrt\x64" "/LIBPATH:C:\Program Files (x86)\Windows Kits\10\lib\10.0.17134.0\um\x64" /EXPORT:PyInit_cython_bbox build\temp.win-amd64-3.6\Release\utils\bbox.obj /OUT:D:\cProjects\Github\rcnn\tf-faster-rcnn-master\lib\utils\cython_bbox.cp36-win_amd64.pyd /IMPLIB:build\temp.win-amd64-3.6\Release\utils\cython_bbox.cp36-win_amd64.lib Creating library build\temp.win-amd64-3.6\Release\utils\cython_bbox.cp36-win_amd64.lib and object build\temp.win-amd64-3.6\Release\utils\cython_bbox.cp36-win_amd64.exp Generating code Finished generating code cythoning nms/cpu_nms.pyx to nms\cpu_nms.c error: D:\cProjects\Github\rcnn\tf-faster-rcnn-master\lib\nms\cpu_nms.pyx

Process finished with exit code 1

Modified, with gpu_nms supports I ran it on windows successfully (Python 3.6.6, VS2015 compiler, CUDA 9.0 with CUDNN v7), just modify some code. Tested both cpu_nms and gpu_nms (but don't know why gpu_nms is a little slower than cpu_nms). Note: If any strange error occurred, I suggest deleting all the generated .c and .cpp files (lib/nms/cpu_nms.c, lib/nms/gpu_nms.cpp, lib/utils/bbox.c) and everything in lib/build file lib/nms/cpu_nms.pyx: change (line 25) cdef np.ndarray[np.int_t, ndim=1] order = scores.argsort()[::-1] to cdef np.ndarray[np.int64_t, ndim=1] order = scores.argsort()[::-1] file lib/nms/gpu_nms.pyx: change (line 25) cdef np.ndarray[np.int_t, ndim=1]
to cdef np.ndarray[np.int64_t, ndim=1]
file lib/datasets/pascal_voc.py: change (line 226) '{:s}.xml') to '{0:s}.xml') file lib/datasets/voc_eval.py change (line 121) with open(cachefile, 'w') as f: to with open(cachefile, 'wb') as f: file lib/setup.py (nearly full modified, new code is as follow):

--------------------------------------------------------

Fast R-CNN

Copyright (c) 2015 Microsoft

Licensed under The MIT License [see LICENSE for details]

Written by Ross Girshick

--------------------------------------------------------

import os from os.path import join as pjoin import numpy as np from distutils.core import setup from distutils.extension import Extension from Cython.Distutils import build_ext

def find_in_path(name, path): "Find a file in a search path" #adapted fom http://code.activestate.com/recipes/52224-find-a-file-given-a-search-path/ for dir in path.split(os.pathsep): binpath = pjoin(dir, name) if os.path.exists(binpath): return os.path.abspath(binpath) return None

def locate_cuda(): """Locate the CUDA environment on the system

Returns a dict with keys 'home', 'nvcc', 'include', and 'lib64'
and values giving the absolute path to each directory.

Starts by looking for the CUDAHOME env variable. If not found, everything
is based on finding 'nvcc' in the PATH.
"""

# first check if the CUDAHOME env variable is in use
if 'CUDAHOME' in os.environ:
    home = os.environ['CUDAHOME']
    nvcc = pjoin(home, 'bin', 'nvcc')
else:
    # otherwise, search the PATH for NVCC
    nvcc = find_in_path('nvcc.exe', os.environ['PATH'])
    if nvcc is None:
        raise EnvironmentError('The nvcc binary could not be '
            'located in your $PATH. Either add it to your path, or set $CUDAHOME')
    home = os.path.dirname(os.path.dirname(nvcc))

cudaconfig = {'home':home, 'nvcc':nvcc,
              'include': pjoin(home, 'include'),
              'lib64': pjoin(home, 'lib', 'x64')}
for k, v in iter(cudaconfig.items()):
    if not os.path.exists(v):
        raise EnvironmentError('The CUDA %s path could not be located in %s' % (k, v))

return cudaconfig

CUDA = locate_cuda()

Obtain the numpy include directory. This logic works across numpy versions.

try: numpy_include = np.get_include() except AttributeError: numpy_include = np.get_numpy_include()

def customize_compiler_for_nvcc(self): # _msvccompiler.py imports: import os import shutil import stat import subprocess import winreg

from distutils.errors import DistutilsExecError, DistutilsPlatformError, \
                             CompileError, LibError, LinkError
from distutils.ccompiler import CCompiler, gen_lib_options
from distutils import log
from distutils.util import get_platform

from itertools import count

super = self.compile
self.src_extensions.append('.cu')
# find python include
import sys
py_dir = sys.executable.replace('\\', '/').split('/')[:-1]
py_include = pjoin('/'.join(py_dir), 'include')

# override method in _msvccompiler.py, starts from line 340
def compile(sources,
            output_dir=None, macros=None, include_dirs=None, debug=0,
            extra_preargs=None, extra_postargs=None, depends=None):

    if not self.initialized:
        self.initialize()
    compile_info = self._setup_compile(output_dir, macros, include_dirs,
                                       sources, depends, extra_postargs)
    macros, objects, extra_postargs, pp_opts, build = compile_info

    compile_opts = extra_preargs or []
    compile_opts.append('/c')
    if debug:
        compile_opts.extend(self.compile_options_debug)
    else:
        compile_opts.extend(self.compile_options)

    add_cpp_opts = False

    for obj in objects:
        try:
            src, ext = build[obj]
        except KeyError:
            continue
        if debug:
            # pass the full pathname to MSVC in debug mode,
            # this allows the debugger to find the source file
            # without asking the user to browse for it
            src = os.path.abspath(src)

        if ext in self._c_extensions:
            input_opt = "/Tc" + src
        elif ext in self._cpp_extensions:
            input_opt = "/Tp" + src
            add_cpp_opts = True
        elif ext in self._rc_extensions:
            # compile .RC to .RES file
            input_opt = src
            output_opt = "/fo" + obj
            try:
                self.spawn([self.rc] + pp_opts + [output_opt, input_opt])
            except DistutilsExecError as msg:
                raise CompileError(msg)
            continue
        elif ext in self._mc_extensions:
            # Compile .MC to .RC file to .RES file.
            #   * '-h dir' specifies the directory for the
            #     generated include file
            #   * '-r dir' specifies the target directory of the
            #     generated RC file and the binary message resource
            #     it includes
            #
            # For now (since there are no options to change this),
            # we use the source-directory for the include file and
            # the build directory for the RC file and message
            # resources. This works at least for win32all.
            h_dir = os.path.dirname(src)
            rc_dir = os.path.dirname(obj)
            try:
                # first compile .MC to .RC and .H file
                self.spawn([self.mc, '-h', h_dir, '-r', rc_dir, src])
                base, _ = os.path.splitext(os.path.basename(src))
                rc_file = os.path.join(rc_dir, base + '.rc')
                # then compile .RC to .RES file
                self.spawn([self.rc, "/fo" + obj, rc_file])

            except DistutilsExecError as msg:
                raise CompileError(msg)
            continue
        elif ext == '.cu':
            # a trigger for cu compile
            try:
                # use the cuda for .cu files
                # self.set_executable('compiler_so', CUDA['nvcc'])
                # use only a subset of the extra_postargs, which are 1-1 translated
                # from the extra_compile_args in the Extension class
                postargs = extra_postargs['nvcc']
                arg = [CUDA['nvcc']] + sources + ['-odir', pjoin(output_dir, 'nms')]
                for include_dir in include_dirs:
                    arg.append('-I')
                    arg.append(include_dir)
                arg += ['-I', py_include]
                # arg += ['-lib', CUDA['lib64']]
                arg += ['-Xcompiler', '/EHsc,/W3,/nologo,/Ox,/MD']
                arg += postargs
                self.spawn(arg)
                continue
            except DistutilsExecError as msg:
                # raise CompileError(msg)
                continue
        else:
            # how to handle this file?
            raise CompileError("Don't know how to compile {} to {}"
                               .format(src, obj))

        args = [self.cc] + compile_opts + pp_opts
        if add_cpp_opts:
            args.append('/EHsc')
        args.append(input_opt)
        args.append("/Fo" + obj)
        args.extend(extra_postargs)

        try:
            self.spawn(args)
        except DistutilsExecError as msg:
            raise CompileError(msg)

    return objects

self.compile = compile

run the customize_compiler

class custom_build_ext(build_ext): def build_extensions(self): customize_compiler_for_nvcc(self.compiler) build_ext.build_extensions(self)

ext_modules = [ Extension( "utils.cython_bbox", ["utils/bbox.pyx"], extra_compile_args={'gcc': ["-Wno-cpp", "-Wno-unused-function"]}, include_dirs = [numpy_include] ), Extension( "nms.cpu_nms", ["nms/cpu_nms.pyx"], include_dirs = [numpy_include] ), Extension('nms.gpu_nms', ['nms/nms_kernel.cu', 'nms/gpu_nms.pyx'], library_dirs=[CUDA['lib64']], libraries=['cudart'], language='c++', # this syntax is specific to this build system # we're only going to use certain compiler args with nvcc and not with gcc # the implementation of this trick is in customize_compiler() below extra_compile_args={'gcc': ["-Wno-unused-function"], 'nvcc': ['-arch=sm_52', '--ptxas-options=-v', '-c']}, include_dirs = [numpy_include, CUDA['include']] ) ]

setup( name='tf_faster_rcnn', ext_modules=ext_modules, # inject our custom trigger cmdclass={'build_ext': custom_build_ext}, ) It's take me some time to understand how MSVC compiler works, so I made an ugly patch for the compiler by overriding the compile method. Note: Change the -arch=sm_52 above to fit your graphic card, otherwise using gpu_nms will get the corrupt result. You can follow the original installation guide. Now, turn to lib directory, run python setup.py build_ext. It possible reports an error: nms\gpu_nms.cpp(2075): error C2664: "void _nms(int *,int *,const float *,int,int,float,int)": cannot convert parameter 1 from '__pyx_t_5numpy_int32_t *' to 'int *'

Modify one line in the generated file in lib/nms/gpu_nms.cpp, search the keyword _nms, find the following line: change (line 2075 in my generated cpp file) _nms((&(*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int32_t , __pyx_pybuffernd_keep.rcbuffer->pybuffer.buf, __pyx_t_10, ... to _nms((&(__Pyx_BufPtrStrided1d(int *, __pyx_pybuffernd_keep.rcbuffer->pybuffer.buf, __pyx_t_10, ... At last, run python setup.py build_ext again, copy everything in lib/build/lib.win-amd64-3.6 to lib.

I am really glad to see your work , I have met an issue about build box_utils modul in windows , not this project,here is the link: https://github.com/DetectionTeamUCAS/RetinaNet_Tensorflow_Rotation/issues/50

the author can't solve the problem too ,I have tried for a long time but with no luck. wish your help, please!

@qhgz2013 really need your help , please....

@qhgz2013 really need your help , please....

@ZOUYIyi : I'm sorry that I have too much work to do now, and my research tasks are not related to computer vision (except something I'm quite interested in, like StyleGAN). So I suggest to install a dual system, and configure your bios settings to boot from either linux or windows, it can be done in several days, including backing up data, resize the disk partitions, installing CUDA and python environment, etc. It's much more efficient than wait for a solution.

@qhgz2013 I see. ... I have already done all the things you said , but I really need to run the project in windows, thanks for your advice anyway. I will keep search for the solution. : )

nms_kernel.cu @qhgz2013 I tried your method, andI met a link error: 'cannot open input file 'build\temp.win-amd64-3.5\Release\nms/nms_kernel.obj' Any thoughts how to fix this? Thanks

have you solved this problem? I also meet with it....

nms_kernel.cu @qhgz2013 I tried your method, andI met a link error: 'cannot open input file 'build\temp.win-amd64-3.5\Release\nms/nms_kernel.obj' Any thoughts how to fix this? Thanks

have you solved this problem? I also meet with it....

Has anyone found a solution for this?

I had the same issue as @vmirea @YYsmith, using the script provided above. I solved this by compiling nms_kernel and gpu_nms manually, following this. I just replaced some of the command parameters and the path to rc.exe and link.exe with those printed when I was running python setup.py. Just make sure to add /MD in the compiler-options parameters when compiling nms_kernel with nvcc, otherwise, you will end up with a linker problem (the original command from the setup.py didn't seem to include it). Hope it will help some people.