はじめに
BiSeNetとLEDNetもinferenceはできたのですが、Trainingがちょっとあって停滞していて、先にこの、"Training-Time-Friendly Network for Real-Time Object Detection"の記事を書こうと思います。CenterNetやCornerNet-LiteはInferenceは速いのですが、Trainingははっきり言ってしんどいので、よほど強力なGPUがないとやってられません。
その点、これは非常に短い時間でそれなりのTrainingができるので、独自のデータを学習させたり、COCOのカテゴリを減らしたらmAPがどう変わるかなどといったTrainingにかかわるいろいろなことが個人所有のPCやGPUで出来そうなので、有意義だと思いました。
#0.注意
ディレクトリ名が途中でttfnet2,mmdetection2となったり、仮想環境がopen-mmlab2となるのは、いったん作った環境ではなく、再度この記事のために作ったためにこうなっています。皆さんは*2ではなく、2がついていないと思ってやってください。
#1.準備
INSTALL.mdの通りなのですが、Windows10なので適当に躓きます。
(base) F:\Users\sounansu\Anaconda3>conda create -n open-mmlab python=3.7 -y
Collecting package metadata (current_repodata.json): done
Solving environment: done
## Package Plan ##
environment location: F:\Users\sounansu\Anaconda3\envs\open-mmlab
added / updated specs:
- python=3.7
The following packages will be downloaded:
package | build
---------------------------|-----------------
ca-certificates-2019.8.28 | 0 165 KB
certifi-2019.9.11 | py37_0 155 KB
pip-19.2.2 | py37_0 1.7 MB
python-3.7.4 | h5263a28_0 14.7 MB
setuptools-41.2.0 | py37_0 665 KB
sqlite-3.29.0 | he774522_0 624 KB
vc-14.1 | h0510ff6_4 6 KB
wheel-0.33.6 | py37_0 58 KB
wincertstore-0.2 | py37_0 14 KB
------------------------------------------------------------
Total: 18.0 MB
The following NEW packages will be INSTALLED:
ca-certificates pkgs/main/win-64::ca-certificates-2019.8.28-0
certifi pkgs/main/win-64::certifi-2019.9.11-py37_0
openssl pkgs/main/win-64::openssl-1.1.1d-he774522_0
pip pkgs/main/win-64::pip-19.2.2-py37_0
python pkgs/main/win-64::python-3.7.4-h5263a28_0
setuptools pkgs/main/win-64::setuptools-41.2.0-py37_0
sqlite pkgs/main/win-64::sqlite-3.29.0-he774522_0
vc pkgs/main/win-64::vc-14.1-h0510ff6_4
vs2015_runtime pkgs/main/win-64::vs2015_runtime-14.16.27012-hf0eaf9b_0
wheel pkgs/main/win-64::wheel-0.33.6-py37_0
wincertstore pkgs/main/win-64::wincertstore-0.2-py37_0
Downloading and Extracting Packages
python-3.7.4 | 14.7 MB | ################################################################################################################## | 100%
certifi-2019.9.11 | 155 KB | ################################################################################################################## | 100%
ca-certificates-2019 | 165 KB | ################################################################################################################## | 100%
sqlite-3.29.0 | 624 KB | ################################################################################################################## | 100%
wincertstore-0.2 | 14 KB | ################################################################################################################## | 100%
setuptools-41.2.0 | 665 KB | ################################################################################################################## | 100%
wheel-0.33.6 | 58 KB | ################################################################################################################## | 100%
vc-14.1 | 6 KB | ################################################################################################################## | 100%
pip-19.2.2 | 1.7 MB | ################################################################################################################## | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
# $ conda activate open-mmlab
#
# To deactivate an active environment, use
#
# $ conda deactivate
(base) F:\Users\sounansu\Anaconda3>conda activate open-mmlab
(open-mmlab) F:\Users\sounansu\Anaconda3>conda install cython
Collecting package metadata (current_repodata.json): done
Solving environment: done
## Package Plan ##
environment location: F:\Users\sounansu\Anaconda3\envs\open-mmlab
added / updated specs:
- cython
The following packages will be downloaded:
package | build
---------------------------|-----------------
cython-0.29.13 | py37ha925a31_0 1.8 MB
------------------------------------------------------------
Total: 1.8 MB
The following NEW packages will be INSTALLED:
cython pkgs/main/win-64::cython-0.29.13-py37ha925a31_0
Proceed ([y]/n)? y
Downloading and Extracting Packages
cython-0.29.13 | 1.8 MB | ################################################################################################################## | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(open-mmlab) F:\Users\sounansu\Anaconda3>conda install pytorch torchvision cudatoolkit=10.0 -c pytorch
Collecting package metadata (current_repodata.json): done
Solving environment: done
## Package Plan ##
environment location: F:\Users\sounansu\Anaconda3\envs\open-mmlab
added / updated specs:
- cudatoolkit=10.0
- pytorch
- torchvision
The following packages will be downloaded:
package | build
---------------------------|-----------------
blas-1.0 | mkl 6 KB
mkl_fft-1.0.14 | py37h14836fe_0 118 KB
mkl_random-1.0.2 | py37h343c172_0 272 KB
ninja-1.9.0 | py37h74a9793_0 238 KB
numpy-1.16.5 | py37h19fb1c0_0 50 KB
olefile-0.46 | py37_0 49 KB
pillow-6.1.0 | py37hdc69c19_0 636 KB
pycparser-2.19 | py37_0 170 KB
pytorch-1.2.0 |py3.7_cuda100_cudnn7_1 479.3 MB pytorch
six-1.12.0 | py37_0 23 KB
torchvision-0.4.0 | py37_cu100 2.3 MB pytorch
------------------------------------------------------------
Total: 483.1 MB
The following NEW packages will be INSTALLED:
blas pkgs/main/win-64::blas-1.0-mkl
cffi pkgs/main/win-64::cffi-1.12.3-py37h7a1dbc1_0
cudatoolkit pkgs/main/win-64::cudatoolkit-10.0.130-0
freetype pkgs/main/win-64::freetype-2.9.1-ha9979f8_1
icc_rt pkgs/main/win-64::icc_rt-2019.0.0-h0cc432a_1
intel-openmp pkgs/main/win-64::intel-openmp-2019.4-245
jpeg pkgs/main/win-64::jpeg-9b-hb83a4c4_2
libpng pkgs/main/win-64::libpng-1.6.37-h2a8f88b_0
libtiff pkgs/main/win-64::libtiff-4.0.10-hb898794_2
mkl pkgs/main/win-64::mkl-2019.4-245
mkl-service pkgs/main/win-64::mkl-service-2.3.0-py37hb782905_0
mkl_fft pkgs/main/win-64::mkl_fft-1.0.14-py37h14836fe_0
mkl_random pkgs/main/win-64::mkl_random-1.0.2-py37h343c172_0
ninja pkgs/main/win-64::ninja-1.9.0-py37h74a9793_0
numpy pkgs/main/win-64::numpy-1.16.5-py37h19fb1c0_0
numpy-base pkgs/main/win-64::numpy-base-1.16.5-py37hc3f5095_0
olefile pkgs/main/win-64::olefile-0.46-py37_0
pillow pkgs/main/win-64::pillow-6.1.0-py37hdc69c19_0
pycparser pkgs/main/win-64::pycparser-2.19-py37_0
pytorch pytorch/win-64::pytorch-1.2.0-py3.7_cuda100_cudnn7_1
six pkgs/main/win-64::six-1.12.0-py37_0
tk pkgs/main/win-64::tk-8.6.8-hfa6e2cd_0
torchvision pytorch/win-64::torchvision-0.4.0-py37_cu100
xz pkgs/main/win-64::xz-5.2.4-h2fa13f4_4
zlib pkgs/main/win-64::zlib-1.2.11-h62dcd97_3
zstd pkgs/main/win-64::zstd-1.3.7-h508b16e_0
Proceed ([y]/n)? y
Downloading and Extracting Packages
mkl_fft-1.0.14 | 118 KB | ################################################################################################################## | 100%
olefile-0.46 | 49 KB | ################################################################################################################## | 100%
pycparser-2.19 | 170 KB | ################################################################################################################## | 100%
mkl_random-1.0.2 | 272 KB | ################################################################################################################## | 100%
six-1.12.0 | 23 KB | ################################################################################################################## | 100%
ninja-1.9.0 | 238 KB | ################################################################################################################## | 100%
numpy-1.16.5 | 50 KB | ################################################################################################################## | 100%
torchvision-0.4.0 | 2.3 MB | ################################################################################################################## | 100%
pillow-6.1.0 | 636 KB | ################################################################################################################## | 100%
blas-1.0 | 6 KB | ################################################################################################################## | 100%
pytorch-1.2.0 | 479.3 MB | ################################################################################################################## | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
次にリポジトリを取ってきましょう。
(open-mmlab) F:\Users\sounansu\Anaconda3>git clone https://github.com/ZJULearning/ttfnet.git
'git' は、内部コマンドまたは外部コマンド、
操作可能なプログラムまたはバッチ ファイルとして認識されていません。
(open-mmlab) F:\Users\sounansu\Anaconda3>
gitはデフォルトではないので先に入れて、
(open-mmlab) F:\Users\sounansu\Anaconda3>conda install git
Collecting package metadata (current_repodata.json): done
Solving environment: done
## Package Plan ##
environment location: F:\Users\sounansu\Anaconda3\envs\open-mmlab
added / updated specs:
- git
The following NEW packages will be INSTALLED:
git pkgs/main/win-64::git-2.20.1-h6bb4b03_0
Proceed ([y]/n)? y
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(open-mmlab) F:\Users\sounansu\Anaconda3>git clone https://github.com/ZJULearning/ttfnet.git
Cloning into 'ttfnet'...
remote: Enumerating objects: 4913, done.
remote: Counting objects: 100% (4913/4913), done.
remote: Compressing objects: 100% (1647/1647), done.
remote: Total 4913 (delta 3279), reused 4873 (delta 3240), pack-reused 0
Receiving objects: 100% (4913/4913), 5.45 MiB | 1.59 MiB/s, done.
Resolving deltas: 100% (3279/3279), done.
下準備をするのですが、、、
(open-mmlab) F:\Users\sounansu\Anaconda3>cd ttfnet
(open-mmlab) F:\Users\sounansu\Anaconda3\ttfnet>python setup.py develop
ものすごく時間がかかって
C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\VC\Tools\MSVC\14.16.27023\bin\HostX86\x64\link.exe /nologo /INCREMENTAL:NO /LTCG /DLL /MANIFEST:EMBED,ID=2 /MANIFESTUAC:NO /LIBPATH:F:\Users\sounansu\Anaconda3\envs\open-mmlab\lib\site-packages\torch\lib "/LIBPATH:C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0\lib/x64" /LIBPATH:F:\Users\sounansu\Anaconda3\envs\open-mmlab\libs /LIBPATH:F:\Users\sounansu\Anaconda3\envs\open-mmlab\PCbuild\amd64 "/LIBPATH:C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\VC\Tools\MSVC\14.16.27023\ATLMFC\lib\x64" "/LIBPATH:C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\VC\Tools\MSVC\14.16.27023\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\10.0.17763.0\ucrt\x64" "/LIBPATH:C:\Program Files (x86)\Windows Kits\10\lib\10.0.17763.0\um\x64" cudart.lib c10.lib c10_cuda.lib torch.lib torch_python.lib _C.lib /EXPORT:PyInit_sigmoid_focal_loss_cuda build\temp.win-amd64-3.7\Release\mmdet\ops\sigmoid_focal_loss\src/sigmoid_focal_loss.obj build\temp.win-amd64-3.7\Release\mmdet\ops\sigmoid_focal_loss\src/sigmoid_focal_loss_cuda.obj /OUT:build\lib.win-amd64-3.7\mmdet\ops\sigmoid_focal_loss\sigmoid_focal_loss_cuda.cp37-win_amd64.pyd /IMPLIB:build\temp.win-amd64-3.7\Release\mmdet\ops\sigmoid_focal_loss\src\sigmoid_focal_loss_cuda.cp37-win_amd64.lib
ライブラリ build\temp.win-amd64-3.7\Release\mmdet\ops\sigmoid_focal_loss\src\sigmoid_focal_loss_cuda.cp37-win_amd64.lib とオブジェクト build\temp.win-amd64-3.7\Release\mmdet\ops\sigmoid_focal_loss\src\sigmoid_focal_loss_cuda.cp37-win_amd64.exp を作成中
sigmoid_focal_loss_cuda.obj : error LNK2001: 外部シンボル ""public: long * __cdecl at::Tensor::data<long>(void)const " (??$data@J@Tensor@at@@QEBAPEAJXZ)" は未解決です。
build\lib.win-amd64-3.7\mmdet\ops\sigmoid_focal_loss\sigmoid_focal_loss_cuda.cp37-win_amd64.pyd : fatal error LNK1120: 1 件の未解決の外部参照
error: command 'C:\\Program Files (x86)\\Microsoft Visual Studio\\2017\\Community\\VC\\Tools\\MSVC\\14.16.27023\\bin\\HostX86\\x64\\link.exe' failed with exit status 1120
(open-mmlab) F:\Users\sounansu\Anaconda3\ttfnet>
あらあらまあまあエラーが出てしまっています。ttfnetのissueをみてもそれらしいのがないので、ttfnetがつかっている環境であるopen-mmlabの方にヒントがないか見に行きましょう。
#2.MMDetection open-mmlab
open-mmlabは、MMDetection: Open MMLab Detection Toolbox and Benchmarkであるように、COCOのチャレンジの際にMMDetチームが使ったコードをもとに整備されているもので、open-mmlabにはmmcv, mmskelton, mmsr, mmaction, mmstyle等のコードが入っています。
MMDetectionには、RPN, Fast R-CNN, Faster R-CNN, Mask R-CNN, Cascade R-CNN, Cascade Mask R-CNN, SSD, RetinaNet, GHM, Mask Scoring R-CNN, FCOS, Double-Head R-CNN, Grid R-CNN (Plus), Hybrid Task Cascade, Libra R-CNN, Guided Anchoringのベンチマークとモデルズ―があり、ほぼ同じ環境での構造の比較や、すでにトレーニングされたウエイトデータもあるので、インファレンスをお試し等もできます。
よくある、githubだと、トレーニングしかできなかったり、インファレンスしかできなかったり、トレーニングデータがこっちはCOCO、こっちはCityScape等で比較できないのですが、そこも含めて比べられるので、一度覗いてみてはいかがでしょうか？
と、今回はTTFNetを実行するために、mmdetectionをまずは動かすということで。
##2.1 Install
Install mmdetectionの初めの方はTTFNetと同じなので、mmdetectionのgitを取ってくるところから、
(open-mmlab2) F:\Users\sounansu\Anaconda3>git clone https://github.com/open-mmlab/mmdetection.git mmdetection2
Cloning into 'mmdetection2'...
remote: Enumerating objects: 5, done.
remote: Counting objects: 100% (5/5), done.
remote: Compressing objects: 100% (5/5), done.
remote: Total 5254 (delta 0), reused 0 (delta 0), pack-reused 5249
Receiving objects: 100% (5254/5254), 5.01 MiB | 1.25 MiB/s, done.
Resolving deltas: 100% (3528/3528), done.
(open-mmlab2) F:\Users\sounansu\Anaconda3>cd mmdetection2
(open-mmlab2) F:\Users\sounansu\Anaconda3\mmdetection2>set PYTHONPATH=f:\Users\sounansu\Anaconda3\mmdetection2
(open-mmlab2) F:\Users\sounansu\Anaconda3\mmdetection2>python setup.py develop
いろいろあって
cl : コマンド ライン error D8021 : 数値型引数 '/Wno-cpp' は無効です。
error: Setup script exited with error: command 'C:\\Program Files (x86)\\Microsoft Visual Studio\\2017\\Community\\VC\\Tools\\MSVC\\14.16.27023\\bin\\HostX86\\x64\\cl.exe' failed with exit status 2
issueをみると
issue1088に
1.Install community version of pycocotools for windows (official repository does not support windows)
とあるのでそれを入れてみると、
(open-mmlab2) F:\Users\sounansu\Anaconda3\mmdetection2> pip install git+https://github.com/philferriere/cocoapi.git#subdirectory=PythonAPI
Collecting git+https://github.com/philferriere/cocoapi.git#subdirectory=PythonAPI
Cloning https://github.com/philferriere/cocoapi.git to e:\temp\pip-req-build-n5g737fa
Running command git clone -q https://github.com/philferriere/cocoapi.git 'E:\TEMP\pip-req-build-n5g737fa'
Building wheels for collected packages: pycocotools
Building wheel for pycocotools (setup.py) ... done
Created wheel for pycocotools: filename=pycocotools-2.0-cp37-cp37m-win_amd64.whl size=82677 sha256=16c7e7544004c242838d2be3c711f3c2a8a12c7f235bcf342401aad4275812f1
Stored in directory: E:\TEMP\pip-ephem-wheel-cache-i9qk_qxe\wheels\69\2b\12\2fa959e49f73d26cff202c2f4e5079096c9c57c8a8509fd75c
Successfully built pycocotools
ERROR: mmdet 1.0rc0+d88ad8f requires matplotlib, which is not installed.
ERROR: mmdet 1.0rc0+d88ad8f requires mmcv>=0.2.10, which is not installed.
ERROR: mmdet 1.0rc0+d88ad8f requires terminaltables, which is not installed.
Installing collected packages: pycocotools
Successfully installed pycocotools-2.0
と文句を言われるので、この3つを入れましょう。
まず、matplotlibはcondaで
(open-mmlab2) F:\Users\sounansu\Anaconda3\mmdetection2>conda install matplotlib
（ログが消えちゃうんですよね。。）
mmcvはInstallにあるように
(open-mmlab2) F:\Users\sounansu\Anaconda3>git clone https://github.com/open-mmlab/mmcv.git
(open-mmlab2) F:\Users\sounansu\Anaconda3>cd mmcv
(open-mmlab2) F:\Users\sounansu\Anaconda3\mmcv>pip install -e .
Obtaining file:///F:/Users/sounansu/Anaconda3/mmcv
Requirement already satisfied: numpy>=1.11.1 in f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages (from mmcv==0.2.13) (1.16.5)
Requirement already satisfied: pyyaml in f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages (from mmcv==0.2.13) (5.1.2)
Requirement already satisfied: six in f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages (from mmcv==0.2.13) (1.12.0)
Requirement already satisfied: addict in f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages (from mmcv==0.2.13) (2.2.1)
Requirement already satisfied: requests in f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages (from mmcv==0.2.13) (2.22.0)
Requirement already satisfied: opencv-python in f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages (from mmcv==0.2.13) (4.1.1.26)
Requirement already satisfied: Cython in f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages (from mmcv==0.2.13) (0.29.13)
Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages (from requests->mmcv==0.2.13) (1.25.6)
Requirement already satisfied: chardet<3.1.0,>=3.0.2 in f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages (from requests->mmcv==0.2.13) (3.0.4)
Requirement already satisfied: certifi>=2017.4.17 in f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages (from requests->mmcv==0.2.13) (2019.9.11)
Requirement already satisfied: idna<2.9,>=2.5 in f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages (from requests->mmcv==0.2.13) (2.8)
ERROR: mmdet 1.0rc0+d88ad8f requires terminaltables, which is not installed.
Installing collected packages: mmcv
Found existing installation: mmcv 0.2.13
Uninstalling mmcv-0.2.13:
Successfully uninstalled mmcv-0.2.13
Running setup.py develop for mmcv
Successfully installed mmcv
(open-mmlab2) F:\Users\sounansu\Anaconda3\mmcv>
あれ？すでに入れていたようですね。（なぜさっきは、入ってないと表示された？）
最後に、terminaltablesは
(open-mmlab2) F:\Users\sounansu\Anaconda3\mmdetection>pip install terminaltables
Collecting terminaltables
Installing collected packages: terminaltables
Successfully installed terminaltables-3.1.0
としていれて、改めてpython setup.py developをすると
(open-mmlab2) F:\Users\sounansu\Anaconda3\mmdetection2>python setup.py develop
F:\Users\sounansu\Anaconda3\envs\open-mmlab2\lib\site-packages\setuptools\dist.py:474: UserWarning: Normalizing '1.0.rc0+d88ad8f' to '1.0rc0+d88ad8f'
normalized_version,
running develop
running egg_info
writing mmdet.egg-info\PKG-INFO
writing dependency_links to mmdet.egg-info\dependency_links.txt
writing requirements to mmdet.egg-info\requires.txt
writing top-level names to mmdet.egg-info\top_level.txt
reading manifest file 'mmdet.egg-info\SOURCES.txt'
writing manifest file 'mmdet.egg-info\SOURCES.txt'
running build_ext
F:\Users\sounansu\Anaconda3\envs\open-mmlab2\lib\site-packages\torch\utils\cpp_extension.py:189: UserWarning: Error checking compiler version for cl: 'utf-8' codec can't decode byte 0x8e in position 132: invalid start byte
warnings.warn('Error checking compiler version for {}: {}'.format(compiler, error))
copying build\lib.win-amd64-3.7\mmdet\ops\nms\soft_nms_cpu.cp37-win_amd64.pyd -> mmdet\ops\nms
copying build\lib.win-amd64-3.7\mmdet\ops\nms\nms_cpu.cp37-win_amd64.pyd -> mmdet\ops\nms
copying build\lib.win-amd64-3.7\mmdet\ops\nms\nms_cuda.cp37-win_amd64.pyd -> mmdet\ops\nms
copying build\lib.win-amd64-3.7\mmdet\ops\roi_align\roi_align_cuda.cp37-win_amd64.pyd -> mmdet\ops\roi_align
copying build\lib.win-amd64-3.7\mmdet\ops\roi_pool\roi_pool_cuda.cp37-win_amd64.pyd -> mmdet\ops\roi_pool
copying build\lib.win-amd64-3.7\mmdet\ops\dcn\deform_conv_cuda.cp37-win_amd64.pyd -> mmdet\ops\dcn
copying build\lib.win-amd64-3.7\mmdet\ops\dcn\deform_pool_cuda.cp37-win_amd64.pyd -> mmdet\ops\dcn
copying build\lib.win-amd64-3.7\mmdet\ops\sigmoid_focal_loss\sigmoid_focal_loss_cuda.cp37-win_amd64.pyd -> mmdet\ops\sigmoid_focal_loss
copying build\lib.win-amd64-3.7\mmdet\ops\masked_conv\masked_conv2d_cuda.cp37-win_amd64.pyd -> mmdet\ops\masked_conv
Creating f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\mmdet.egg-link (link to .)
Adding mmdet 1.0rc0+d88ad8f to easy-install.pth file
Installed f:\users\sounansu\anaconda3\mmdetection2
Processing dependencies for mmdet==1.0rc0+d88ad8f
Searching for opencv-python-headless>=4.1.1
Reading https://pypi.org/simple/opencv-python-headless/
Downloading https://files.pythonhosted.org/packages/9a/a2/1a7feb6565cd932d9c9d06c9bde22fe9345a348ee3ed4f55f2457e95b111/opencv_python_headless-4.1.1.26-cp37-cp37m-win_amd64.whl#sha256=a6e9114c1e57280f47c796d87ffaea49aa3e3bcb4ed1ccde18c500b8cd143c73
Best match: opencv-python-headless 4.1.1.26
Processing opencv_python_headless-4.1.1.26-cp37-cp37m-win_amd64.whl
Installing opencv_python_headless-4.1.1.26-cp37-cp37m-win_amd64.whl to f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
writing requirements to f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\opencv_python_headless-4.1.1.26-py3.7-win-amd64.egg\EGG-INFO\requires.txt
Adding opencv-python-headless 4.1.1.26 to easy-install.pth file
Installed f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\opencv_python_headless-4.1.1.26-py3.7-win-amd64.egg
Searching for imgaug<0.2.7,>=0.2.5
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Best match: imgaug 0.2.6
Processing imgaug-0.2.6.tar.gz
Writing E:\TEMP\easy_install-9y1j8wcb\imgaug-0.2.6\setup.cfg
Running imgaug-0.2.6\setup.py -q bdist_egg --dist-dir E:\TEMP\easy_install-9y1j8wcb\imgaug-0.2.6\egg-dist-tmp-ln0f2ba0
File "build\bdist.win-amd64\egg\imgaug\bak\affine.py", line 108
return shear = shear
^
SyntaxError: invalid syntax
Sorry: IndentationError: unexpected indent (parameters-testcode.py, line 2)
zip_safe flag not set; analyzing archive contents...
imgaug.__pycache__.imgaug.cpython-37: module references __file__
creating f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\imgaug-0.2.6-py3.7.egg
Extracting imgaug-0.2.6-py3.7.egg to f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Sorry: IndentationError: unexpected indent (parameters-testcode.py, line 2)
File "f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\imgaug-0.2.6-py3.7.egg\imgaug\bak\affine.py", line 108
return shear = shear
^
SyntaxError: invalid syntax
Adding imgaug 0.2.6 to easy-install.pth file
Installed f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\imgaug-0.2.6-py3.7.egg
Searching for scipy
Reading https://pypi.org/simple/scipy/
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Best match: scipy 1.3.1
Processing scipy-1.3.1-cp37-cp37m-win_amd64.whl
Installing scipy-1.3.1-cp37-cp37m-win_amd64.whl to f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
writing requirements to f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\scipy-1.3.1-py3.7-win-amd64.egg\EGG-INFO\requires.txt
Adding scipy 1.3.1 to easy-install.pth file
Installed f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\scipy-1.3.1-py3.7-win-amd64.egg
Searching for scikit-image>=0.15
Reading https://pypi.org/simple/scikit-image/
Downloading https://files.pythonhosted.org/packages/79/16/c5a36a03f90d4a246791d4ff1879f1868e1c5db58fac9f03427395c5e2d6/scikit_image-0.15.0-cp37-none-win_amd64.whl#sha256=f0491621a6b1d2828d47acaf41d3167a647eaae44ef8fcf83b72eb3e1cc7ac51
Best match: scikit-image 0.15.0
Processing scikit_image-0.15.0-cp37-none-win_amd64.whl
Installing scikit_image-0.15.0-cp37-none-win_amd64.whl to f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
writing requirements to f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\scikit_image-0.15.0-py3.7-win-amd64.egg\EGG-INFO\requires.txt
Adding scikit-image 0.15.0 to easy-install.pth file
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Installed f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\scikit_image-0.15.0-py3.7-win-amd64.egg
Searching for networkx>=2.0
Reading https://pypi.org/simple/networkx/
Downloading https://files.pythonhosted.org/packages/85/08/f20aef11d4c343b557e5de6b9548761811eb16e438cee3d32b1c66c8566b/networkx-2.3.zip#sha256=8311ddef63cf5c5c5e7c1d0212dd141d9a1fe3f474915281b73597ed5f1d4e3d
Best match: networkx 2.3
Processing networkx-2.3.zip
Writing E:\TEMP\easy_install-0_rr4pbl\networkx-2.3\setup.cfg
Running networkx-2.3\setup.py -q bdist_egg --dist-dir E:\TEMP\easy_install-0_rr4pbl\networkx-2.3\egg-dist-tmp-8bjpvqs3
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creating f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\networkx-2.3-py3.7.egg
Extracting networkx-2.3-py3.7.egg to f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Adding networkx 2.3 to easy-install.pth file
Installed f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\networkx-2.3-py3.7.egg
Searching for imageio>=2.0.1
Reading https://pypi.org/simple/imageio/
Downloading https://files.pythonhosted.org/packages/af/0a/943c965d372dae0b1f1482677d29030ab834351a61a9a632fd62f27f1523/imageio-2.5.0-py3-none-any.whl#sha256=1a2bbbb7cd38161340fa3b14d806dfbf914abf3ee6fd4592af2afb87d049f209
Best match: imageio 2.5.0
Processing imageio-2.5.0-py3-none-any.whl
Installing imageio-2.5.0-py3-none-any.whl to f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
writing requirements to f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\imageio-2.5.0-py3.7.egg\EGG-INFO\requires.txt
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Installing imageio_remove_bin.exe script to F:\Users\sounansu\Anaconda3\envs\open-mmlab2\Scripts
Installed f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\imageio-2.5.0-py3.7.egg
Searching for PyWavelets>=0.4.0
Reading https://pypi.org/simple/PyWavelets/
Downloading https://files.pythonhosted.org/packages/71/57/1b6c06f2b681975e5b43ff13ba127031f668d65b592cc56fae6445b675c7/PyWavelets-1.0.3-cp37-none-win_amd64.whl#sha256=ab02363467ee3cb222c5b425bc53453270ddae72bce313e72fd14616692d725a
Best match: PyWavelets 1.0.3
Processing PyWavelets-1.0.3-cp37-none-win_amd64.whl
Installing PyWavelets-1.0.3-cp37-none-win_amd64.whl to f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
writing requirements to f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\PyWavelets-1.0.3-py3.7-win-amd64.egg\EGG-INFO\requires.txt
Adding PyWavelets 1.0.3 to easy-install.pth file
Installed f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\pywavelets-1.0.3-py3.7-win-amd64.egg
Searching for decorator>=4.3.0
Reading https://pypi.org/simple/decorator/
Downloading https://files.pythonhosted.org/packages/5f/88/0075e461560a1e750a0dcbf77f1d9de775028c37a19a346a6c565a257399/decorator-4.4.0-py2.py3-none-any.whl#sha256=f069f3a01830ca754ba5258fde2278454a0b5b79e0d7f5c13b3b97e57d4acff6
Best match: decorator 4.4.0
Processing decorator-4.4.0-py2.py3-none-any.whl
Installing decorator-4.4.0-py2.py3-none-any.whl to f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Adding decorator 4.4.0 to easy-install.pth file
Installed f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\decorator-4.4.0-py3.7.egg
Searching for albumentations==0.3.3
Best match: albumentations 0.3.3
Processing albumentations-0.3.3-py3.7.egg
albumentations 0.3.3 is already the active version in easy-install.pth
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\albumentations-0.3.3-py3.7.egg
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Best match: imagecorruptions 1.0.0
Processing imagecorruptions-1.0.0-py3.7.egg
imagecorruptions 1.0.0 is already the active version in easy-install.pth
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\imagecorruptions-1.0.0-py3.7.egg
Searching for torchvision==0.4.0
Best match: torchvision 0.4.0
Adding torchvision 0.4.0 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for torch==1.2.0
Best match: torch 1.2.0
Adding torch 1.2.0 to easy-install.pth file
Installing convert-caffe2-to-onnx-script.py script to F:\Users\sounansu\Anaconda3\envs\open-mmlab2\Scripts
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Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for pycocotools==2.0
Best match: pycocotools 2.0
Adding pycocotools 2.0 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for terminaltables==3.1.0
Best match: terminaltables 3.1.0
Adding terminaltables 3.1.0 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for six==1.12.0
Best match: six 1.12.0
Adding six 1.12.0 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for matplotlib==3.1.1
Best match: matplotlib 3.1.1
Adding matplotlib 3.1.1 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for numpy==1.16.5
Best match: numpy 1.16.5
Adding numpy 1.16.5 to easy-install.pth file
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Installing f2py.exe script to F:\Users\sounansu\Anaconda3\envs\open-mmlab2\Scripts
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for mmcv==0.2.13
Best match: mmcv 0.2.13
mmcv 0.2.13 is already the active version in easy-install.pth
Using f:\users\sounansu\anaconda3\mmcv
Searching for PyYAML==5.1.2
Best match: PyYAML 5.1.2
Adding PyYAML 5.1.2 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for opencv-python==4.1.1.26
Best match: opencv-python 4.1.1.26
Adding opencv-python 4.1.1.26 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for Pillow==6.1.0
Best match: Pillow 6.1.0
Adding Pillow 6.1.0 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for python-dateutil==2.8.0
Best match: python-dateutil 2.8.0
Adding python-dateutil 2.8.0 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for pyparsing==2.4.2
Best match: pyparsing 2.4.2
Adding pyparsing 2.4.2 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for kiwisolver==1.1.0
Best match: kiwisolver 1.1.0
Adding kiwisolver 1.1.0 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for cycler==0.10.0
Best match: cycler 0.10.0
Adding cycler 0.10.0 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for Cython==0.29.13
Best match: Cython 0.29.13
Adding Cython 0.29.13 to easy-install.pth file
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Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for requests==2.22.0
Best match: requests 2.22.0
Adding requests 2.22.0 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for addict==2.2.1
Best match: addict 2.2.1
Adding addict 2.2.1 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
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Best match: setuptools 41.2.0
Adding setuptools 41.2.0 to easy-install.pth file
Installing easy_install-script.py script to F:\Users\sounansu\Anaconda3\envs\open-mmlab2\Scripts
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Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for idna==2.8
Best match: idna 2.8
Adding idna 2.8 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for certifi==2019.9.11
Best match: certifi 2019.9.11
Adding certifi 2019.9.11 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for urllib3==1.25.6
Best match: urllib3 1.25.6
Adding urllib3 1.25.6 to easy-install.pth file
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Searching for chardet==3.0.4
Best match: chardet 3.0.4
Adding chardet 3.0.4 to easy-install.pth file
Installing chardetect-script.py script to F:\Users\sounansu\Anaconda3\envs\open-mmlab2\Scripts
Installing chardetect.exe script to F:\Users\sounansu\Anaconda3\envs\open-mmlab2\Scripts
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages
Finished processing dependencies for mmdet==1.0rc0+d88ad8f
(open-mmlab2) F:\Users\sounansu\Anaconda3\mmdetection2>
なんかエラーっぽいものが出ていますが、Finishしていますね。問題が出たらその時対応するということで。
##2.2 モデルズーでテスト
いきなり、TTFNetは上手くいかないかもしれないので（うまくいきませんでした。）まずはmmdetectionのご本尊のMODEL ZOOでテストしましょう。
MODEL ZOOのmodelをブラウザでクリックするかして、ウエイトデータをダウンロードしてください。
ダウンロードしたssd300_coco_vgg16_caffe_120e_20181221-84d7110b.pthをmmdetectionのフォルダにおいて、GETTING_STARTEDのpython tools/test.py configs/faster_rcnn_r50_fpn_1x.py checkpoints/faster_rcnn_r50_fpn_1x_20181010-3d1b3351.pth --showを参考にSSDを実行してみましょう。
(open-mmlab2) F:\Users\sounansu\Anaconda3\mmdetection2>python tools\test.py configs\ssd300_coco.py ssd300_coco_vgg16_caffe_120e_20181221-84d7110b.pth --show
loading annotations into memory...
Traceback (most recent call last):
File "tools\test.py", line 224, in <module>
main()
File "tools\test.py", line 161, in main
dataset = build_dataset(cfg.data.test)
File "f:\Users\sounansu\Anaconda3\mmdetection2\mmdet\datasets\builder.py", line 39, in build_dataset
dataset = build_from_cfg(cfg, DATASETS, default_args)
File "f:\Users\sounansu\Anaconda3\mmdetection2\mmdet\utils\registry.py", line 76, in build_from_cfg
return obj_cls(**args)
File "f:\Users\sounansu\Anaconda3\mmdetection2\mmdet\datasets\custom.py", line 64, in __init__
self.img_infos = self.load_annotations(self.ann_file)
File "f:\Users\sounansu\Anaconda3\mmdetection2\mmdet\datasets\coco.py", line 27, in load_annotations
self.coco = COCO(ann_file)
File "F:\Users\sounansu\Anaconda3\envs\open-mmlab2\lib\site-packages\pycocotools\coco.py", line 85, in __init__
dataset = json.load(open(annotation_file, 'r'))
FileNotFoundError: [Errno 2] No such file or directory: 'data/coco/annotations/instances_val2017.json'
data/coco/annotations以下がないといわれていますが、そもそもmmdetectionの下にdata自体がありません。INSTALLのprepare datasetsを参考にCOCOの部分を作ってください。VOCやCityScapeも、私は作りましたが。
(open-mmlab2) F:\Users\sounansu\Anaconda3\mmdetection2>python tools\test.py configs\ssd300_coco.py ssd300_coco_vgg16_caffe_120e_20181221-84d7110b.pth --show
loading annotations into memory...
Done (t=0.94s)
creating index...
index created!
[ ] 0/5000, elapsed: 0s, ETA:
これがプロンプロに出て、
このような絵が出れば正解です。
お疲れさまでした。(TTFNetにはまだまだ。。。。)
#3 TTFNetの続き
せっかくmmdetectionができたので、TTFNetのconfigとウエイトデータを持って行って実行したのですが、TTFNetで使っている一部のネットがmmdetectionの本体には入っていないようなので、TTFNetのpython setup.py developから続きをやってみました。
##3.1TTFNetのインストール
python setup.py developから再開すると、
(open-mmlab2) F:\Users\sounansu\Anaconda3\ttfnet2>python setup.py develop
.....
sigmoid_focal_loss_cuda.obj : error LNK2001: 外部シンボル ""public: long * __cdecl at::Tensor::data<long>(void)const " (??$data@J@Tensor@at@@QEBAPEAJXZ)" は未解決です。
build\lib.win-amd64-3.7\mmdet\ops\sigmoid_focal_loss\sigmoid_focal_loss_cuda.cp37-win_amd64.pyd : fatal error LNK1120: 1 件の未解決の外部参照
error: command 'C:\\Program Files (x86)\\Microsoft Visual Studio\\2017\\Community\\VC\\Tools\\MSVC\\14.16.27023\\bin\\HostX86\\x64\\link.exe' failed with exit status 1120
ここまでは、TTFNetのgithubがmmdetectionのと同じならば、本当ならば、うまくいくはずですが、TTFNetへfolkしたあと、mmdetectionの修正を追随していないようなので、mmdetection側のissueであるCompile successfully on Windows. #1088の
- edit mmdetection/ops/masked_conv/src/masked_conv2d_kernel.cu`
find and replace: long -> int64_t
- edit mmdetection/ops/sigmoid_focal_loss/src/sigmoid_focal_loss_cuda.cu
find and replace: long -> int64_t
in line 112, add type casting to values
dim3 grid(std::min(THCCeilDiv((long)losses_size, 512L), 4096L))
to
dim3 grid(std::min(THCCeilDiv((int64_t)losses_size, (int64_t)512L), (int64_t)4096L));
in line 150, add type casting to values
dim3 grid(std::min(THCCeilDiv((long)d_logits_size, 512L), 4096L));
to
dim3 grid(std::min(THCCeilDiv((int64_t)d_logits_size, (int64_t)512L), (int64_t)4096L));
をコードに反映されればいいのです。
mmdetection側は、この2.,3.はgitに反映されているのですが、TTFNetのgitにはされていないので、この2つのファイルをmmdetectionからとってきてTTFNetのフォルダに入れちゃいましょう。
(open-mmlab2) F:\Users\sounansu\Anaconda3>copy mmdetection\mmdet\ops\masked_conv\src\masked_conv2d_kernel.cu ttfnet\mmdet\ops\masked_conv\src\masked_conv2d_kernel.cu
ttfnet\mmdet\ops\masked_conv\src\masked_conv2d_kernel.cu を上書きしますか? (Yes/No/All): Y
1 個のファイルをコピーしました。
(open-mmlab2) F:\Users\sounansu\Anaconda3>copy mmdetection\mmdet\ops\sigmoid_focal_loss\src\sigmoid_focal_loss_cuda.cu ttfnet\mmdet\ops\sigmoid_focal_loss\src\sigmoid_focal_loss_cuda.cu
ttfnet\mmdet\ops\sigmoid_focal_loss\src\sigmoid_focal_loss_cuda.cu を上書きしますか? (Yes/No/All): y
1 個のファイルをコピーしました。
ではもう一度、python setup.py developを実行しましょう。
(open-mmlab2) F:\Users\sounansu\Anaconda3\ttfnet2>python setup.py develop
...
Using f:\users\sounansu\anaconda3\envs\open-mmlab2\lib\site-packages\decorator-4.4.0-py3.7.egg
Finished processing dependencies for mmdet==1.0rc0+99e9a6e
上手くいったっぽい。というかmmdetectionで実行したのと同じメッセージのようです。
##3.2 TTFNetウエイトデータのダウンロード
TTFNetのREADME.mdのinferenceにあるLinkをクリックするとウエイトデータが得られるのでダウンロードしましょう。せっかくですので、全部取ってきましょう。とってきたデータはTTFnetのフォルダに入れておきましょう。また、mmdetectionに作ったcocoのデータが入っているdataフォルダと同じものをTTFnetのフォルダにも作っておきましょう。
#4.TTFNetのインファレンス
早速インファレンスを実行してみましょう。
(open-mmlab2) F:\Users\sounansu\Anaconda3\ttfnet2>set PYTHONPATH=F:\Users\sounansu\Anaconda3\ttfnet2
(open-mmlab2) F:\Users\sounansu\Anaconda3\ttfnet2>python tools\test.py configs\ttfnet\ttfnet_d53_1x.py ttfnet53_1x-4811e4.pth --show
loading annotations into memory...
Done (t=0.79s)
creating index...
index created!
The model and loaded state dict do not match exactly
unexpected key in source state_dict: bbox_head.shortcut_layers.0.shortcut.weight, bbox_head.shortcut_layers.0.shortcut.bias, bbox_head.shortcut_layers.1.shortcut.weight, bbox_head.shortcut_layers.1.shortcut.bias, bbox_head.shortcut_layers.2.shortcut.weight, bbox_head.shortcut_layers.2.shortcut.bias
[ ] 0/5000, elapsed: 0s, ETA:
ウインドウがでて
のようなものが出れば正解です。set PYTHONPATHを忘れずに。
#5.トレーニング
ここまできたら、勝ったも同然。トレーニングをしましょう。dataフォルダが正しければちゃんと動きます。もしうまくいかなかったらdataフォルダを見直してください。
(open-mmlab2) F:\Users\sounansu\Anaconda3\ttfnet2>python tools\train.py configs\ttfnet\ttfnet_r18_1x.py
2019-10-06 19:37:25,824 - INFO - Distributed training: False
2019-10-06 19:37:26,388 - INFO - load model from: modelzoo://resnet18
2019-10-06 19:37:26,704 - WARNING - The model and loaded state dict do not match exactly
unexpected key in source state_dict: fc.weight, fc.bias
loading annotations into memory...
Done (t=23.91s)
creating index...
index created!
2019-10-06 19:37:59,831 - INFO - Start running, host: sounansu@sounansu-PC, work_dir: F:\Users\sounansu\Anaconda3\ttfnet2\work_dirs\ttfnet18_1x
2019-10-06 19:37:59,831 - INFO - workflow: [('train', 1)], max: 12 epochs
2019-10-06 19:40:25,909 - INFO - Epoch [1][50/7330] lr: 0.00445, eta: 2 days, 23:16:16, time: 2.919, data_time: 1.341, memory: 5856, losses/ttfnet_loss_heatmap: 4.4741, losses/ttfnet_loss_wh: 4.8743, loss: 9.3484
うごいたことには動いたのですが、
eta: 2 days, 23:16:16, time:
2日以上？？？。タスクマネージャを見ると16GBしかメモリがないのに、15GB以上使っていそうで、いわゆるスワップが発生しているようです。
いよいよ、CPU＋MB＋メモリの載せ替え時期が来たようです。。。。
#終わりに
TTFNetどうでしたでしょうか？たしかに、mAPの値とかはSOTAより劣っていますが、学習時間が短いというのは、比較的小さなGPUしかもっていない人には優しいといえなくもないです。PCのメインメモリが少ないため、私の環境では残念な結果になってしまいましたが、そもそも16GBは、前からしょぼすぎると思っていたので、これがいい機会かなと思います。（いまさらDDR3を32GBにはしたくないので、MB+CPU+MEM+SSDというフルセットでの変更になるでしょう。。。。
では、またWindowsでInferenceやTrainingができるものがありましたら、紹介していきます。