\n\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u305f\u3089\u300cAnaconda Prompt\u300d\u3092\u8d77\u52d5\u3059\u308b\u3002<\/p>\n
\u3053\u3093\u306a\u306e\u3002<\/p>\n
Anaconda\u3067\u306f\u4eee\u60f3\u74b0\u5883\u3092\u7c21\u5358\u306b\u4f5c\u3063\u305f\u308a\u3001\u5207\u308a\u66ff\u3048\u305f\u308a\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3002<\/p>\n \u307e\u305a\u306f\u4ee5\u4e0b\u306e\u30b3\u30de\u30f3\u30c9\u3067TecoGAN\u3067\u4f7f\u7528\u3059\u308b\u74b0\u5883\u3092\u7528\u610f\u3059\u308b\u3002tcgn\u306e\u90e8\u5206\u306f\u4eee\u60f3\u74b0\u5883\u306e\u540d\u524d\u306a\u306e\u3067\u81ea\u7531\u306b\u3057\u3066\u3088\u3044\u3002<\/p>\n \u3057\u3070\u3089\u304f\u3059\u308b\u3068\u5404\u7a2e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u304c\u5b8c\u4e86\u3059\u308b\u306e\u3067\u3001\u4ee5\u4e0b\u3092\u5b9f\u884c\u3057\u4eee\u60f3\u74b0\u5883\u306b\u5165\u308b\u3002<\/p>\n <\/p>\n \u3055\u3066\u3001\u4eee\u60f3\u74b0\u5883\u3092\u4f5c\u3063\u305f\u3068\u3053\u308d\u3067\u3001github\u304b\u3089TecoGAN\u4e00\u5f0f\u3092\u5165\u624b\u3001ZIP\u3067\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3057\u3066\u9069\u5f53\u306a\u5834\u6240\u306b\u89e3\u51cd\u3057\u3066\u304a\u304f\u3002<\/p>\n https:\/\/github.com\/thunil\/TecoGAN<\/a><\/p>\n github\u304b\u3089\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3057\u305f\u3082\u306e\u306b\u306f\u30c6\u30b9\u30c8\u7528\u306e\u30d5\u30a1\u30a4\u30eb\u306a\u3069\u304c\u542b\u307e\u308c\u3066\u304a\u3089\u305a\u3001\u672c\u6765\u3067\u3042\u308c\u3070rungan.py 0\u3068\u3059\u308b\u3053\u3068\u3067\u5fc5\u8981\u306a\u30d5\u30a1\u30a4\u30eb\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3057\u3066\u304f\u308b\u306e\u3060\u304c\u3001\u3053\u306e\u30b3\u30fc\u30c9\u306fWindows\u5411\u3051\u306b\u66f8\u304b\u308c\u3066\u3044\u306a\u3044\u305f\u3081\u624b\u52d5\u3067model.zip<\/strong>\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3059\u308b\u3002\u4ed6\u306e\u3082\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3057\u3066\u3082\u3088\u3044\u304c\u3001\u3054\u81ea\u7531\u306b\u3002URL\u306frunGan.py\u5185\u3092\u53c2\u7167\u306e\u3053\u3068\u3002<\/p>\n runGan.py\u3092\u958b\u3044\u305f\u3064\u3044\u3067\u306b\u3001\u300cpython3\u300d\u3068\u306a\u3063\u3066\u3044\u308b\u90e8\u5206\u3092\u300cpython\u300d\u306b\u66f8\u304d\u63db\u3048\u3066\u304a\u304f\u3002<\/p>\n <\/p>\n \u3053\u3053\u304b\u3089\u306f\u5fc5\u8981\u306a\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u4eee\u60f3\u74b0\u5883\u306b\u8ffd\u52a0\u3057\u3066\u3044\u304f\u304c\u3001GPU\u3067\u8a08\u7b97\u3055\u305b\u308b\u5834\u5408\u3068CPU\u3067\u8a08\u7b97\u3055\u305b\u308b\u5834\u5408\u3067\u30d1\u30c3\u30b1\u30fc\u30b8\u304c\u7570\u306a\u308b\u3002<\/p>\n GPU\u3067\u8a08\u7b97\u3055\u305b\u308b\u5834\u5408\u3001NVIDIA\u88fd\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30c1\u30c3\u30d7\u3067CUDA\u74b0\u5883\u304c\u5fc5\u8981\u306a\u308b\u3002\u306a\u3093\u3060\u304bRADEON\u3067\u3069\u3046\u3053\u3046\u3059\u308b\u65b9\u6cd5\u3082\u3042\u308b\u3088\u3046\u3060\u304c\u3001\u4eca\u56de\u306f\u89e6\u308c\u306a\u3044\u3002<\/p>\n \u307e\u305a\u306fCUDA9\u74b0\u5883\u304b\u3089\u3002CPU\u3067\u8a08\u7b97\u3055\u305b\u308b\u5834\u5408\u306f\u5f8c\u306e\u30d1\u30fc\u30c8\u307e\u3067\u8aad\u307f\u98db\u3070\u3057\u3066\u307b\u3057\u3044\u3002<\/p>\n <\/p>\n GPU\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\uff08CUDA9 + cuDNNv7.1\u74b0\u5883\uff09<\/strong><\/span><\/p>\n \u5927\u5143\u306e\u524d\u63d0\u3068\u3057\u3066\u5fc5\u8981\u306a\u3082\u306e\uff1a CUDA9\u306b\u3064\u3044\u3066\u306fCUDA9\u672c\u4f53\u3068\u30d1\u30c3\u30c1\u304c4\u3064\u3042\u308b\u306e\u3067\u3059\u3079\u3066\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3057\u3001\u9806\u756a\u306b\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3092\u884c\u3046\u3002<\/p>\n cuDNN\u306fNVIDIA\u30a2\u30ab\u30a6\u30f3\u30c8\u3078\u306e\u767b\u9332\u304c\u5fc5\u8981\u3060\u304c\u3001\u7279\u306b\u96e3\u3057\u3044\u3082\u306e\u306f\u306a\u3044\u306e\u3067\u767b\u9332\u3057\u3066\u5165\u624b\u3002\u6700\u65b0\u7248\u3067\u306f\u306a\u304f7.1.x\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3059\u308b\u3053\u3068\u3002<\/p>\n cuDNN\u306fzip\u3092\u89e3\u51cd\u5f8c\u3001”C:\/Program Files\/NVIDIA GPU Computing Toolkit\/CUDA\/v9.0″<\/em>\u5185\u306e\u540c\u540d\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u306b\u4e2d\u8eab\u3092\u30b3\u30d4\u30fc\u3059\u308c\u3070\u5c0e\u5165\u5b8c\u4e86\u3002<\/p>\n <\/p>\n \u5c0e\u5165\u3067\u304d\u305f\u3089\u3001\u5fc5\u305aAnacondaPrompt\u3092\u518d\u8d77\u52d5\u3057\u3066\u304b\u3089\u6b21\u306e\u624b\u9806\u3078\u3002<\/p>\n \u4ee5\u4e0b\u30b3\u30de\u30f3\u30c9\u3067\u5fc5\u8981\u306a\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u8ffd\u52a0\u3059\u308b\u3002(base)\u3067\u306a\u304f\u3001\u6700\u521d\u306b\u4f5c\u6210\u3057\u305f\u4eee\u60f3\u74b0\u5883\u306b\u5165\u308b\u306e\u3092\u5fd8\u308c\u305a\u306b\u3002<\/p>\n <\/p>\n \u5b8c\u4e86\u3057\u305f\u3089\u300c\u52d5\u304b\u3057\u3066\u307f\u308b\u300d\u3078\u9032\u3080\u3002<\/p>\n <\/p>\n CPU\u3067\u8a08\u7b97\u3092\u884c\u3046\u65b9\u6cd5<\/strong><\/span><\/p>\n \u6700\u521d\u306b\u4f5c\u3063\u305f\u4eee\u60f3\u74b0\u5883\u304c\u30a2\u30af\u30c6\u30a3\u30d6\u306b\u306a\u3063\u3066\u3044\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3057\u3066\u3001\u6b21\u306e\u30b3\u30de\u30f3\u30c9\u3092\u5b9f\u884c\u3059\u308b\u3002<\/p>\n \u3053\u308c\u3067\u52d5\u304f\u306f\u305a\u3060\u304c\u3001\u3084\u306f\u308aGPU\u3092\u4f7f\u7528\u3059\u308b\u5834\u5408\u3068\u6bd4\u3079\u3066\u5927\u5206\u9045\u3044\u3002<\/p>\n \u753b\u50cf32\u679a\u51e6\u7406\u6642\u306e\u53c2\u8003\u5024\uff1a <\/p>\n \u52d5\u304b\u3057\u3066\u307f\u308b<\/strong><\/span><\/p>\n \u3042\u3068\u306fTecoGAN\u3092\u5c55\u958b\u3057\u305f\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u306b\u79fb\u52d5\u3057\u3001<\/p>\n \u3068\u3059\u308c\u3070\u300cLR\u300d\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u306e\u300ccalender\u300d\u304c\u51e6\u7406\u3055\u308c\u300cresult\u300d\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u5185\u306e\u540c\u540d\u30d5\u30a1\u30a4\u30eb\u306b\u4fdd\u5b58\u3055\u308c\u308b\u3002<\/p>\n calender\u4ee5\u5916\u306e\u51e6\u7406\u3092\u8a66\u3057\u305f\u3051\u308c\u3070runGan.py\u5185\u306ecalender\u3092\u5225\u306e\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u540d\u306b\u66f8\u304d\u63db\u3048\u308c\u3070\u3088\u3044\u3002<\/p>\n <\/p>\n \u81ea\u524d\u306e\u52d5\u753b\u3092\u51e6\u7406\u3057\u3066\u307f\u305f\u3044\u5834\u5408\u306f\u3001ffmpeg<\/a>\u3092\u4f7f\u7528\u3057\u3066\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u3057\u3066\u30d5\u30ec\u30fc\u30e0\u3092png\u306b\u5207\u308a\u51fa\u3059\u3053\u3068\u3067TecoGAN\u306b\u51e6\u7406\u3092\u3055\u305b\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3002<\/p>\n \u51fa\u529b\u7d50\u679c\u3092\u52d5\u753b\u306b\u623b\u3059\u5834\u5408\u306f\u6b21\u306e\u3088\u3046\u306b\u3059\u308b\u3002<\/p>\n \u30b3\u30fc\u30c7\u30c3\u30af\u3084\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u306f\u9069\u5b9c\u5909\u66f4\u306e\u3053\u3068\u3002\u30b3\u30de\u30f3\u30c9\u5185\u306e\u300c24\u300d\u306f\u30d5\u30ec\u30fc\u30e0\u30ec\u30fc\u30c8\u306a\u306e\u3067\u3001\u5143\u306e\u52d5\u753b\u306e\u30d5\u30ec\u30fc\u30e0\u30ec\u30fc\u30c8\u3092\u5165\u529b\u3059\u308b\u3002<\/p>\n <\/p>\n TecoGAN\u3001\u5143\u304c\u305d\u308c\u306a\u308a\u306e\u89e3\u50cf\u5ea6\u3067\u3001\u610f\u56f3\u3057\u3066\u89e3\u50cf\u5ea6\u304c\u843d\u3068\u3055\u308c\u3066\u3044\u308b\u3088\u3046\u306a\u3082\u306e\u306b\u3064\u3044\u3066\u306f\u3088\u304f\u88dc\u5b8c\u3059\u308b\u3051\u3069\u3001\u3084\u3063\u3071\u308a\u5143\u3005\u8352\u304b\u3063\u305f\u308a\u3001\u30ce\u30a4\u30ba\u304c\u591a\u3044\u3082\u306e\u306b\u3064\u3044\u3066\u306f\u5c11\u3005\u96e3\u3057\u3044\u306a\u3068\u306f\u601d\u3046\u3002 <\/p>\n \u6700\u5f8c\u306b\u3001\u52d5\u4f5c\u30c1\u30a7\u30c3\u30af\u3092\u3057\u305f\u74b0\u5883\u3067\u306e\u300cconda list\u300d\u306e\u7d50\u679c\u3092\u6dfb\u4ed8\u3057\u3066\u304a\u304f\u3002\u3046\u307e\u304f\u52d5\u304b\u306a\u3044\u5834\u5408\u306e\u30d0\u30fc\u30b8\u30e7\u30f3\u306a\u3069\u306e\u53c2\u8003\u306b\u3002<\/p>\n <\/p>\n <\/p>\n GPU\u6f14\u7b97\u6642<\/em><\/p>\n <\/p>\n <\/p>\n CPU\u6f14\u7b97\u6642<\/em><\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":" \u4f4e\u89e3\u50cf\u5ea6\u30d3\u30c7\u30aa\u3092\u9ad8\u89e3\u50cf\u5ea6\u30d3\u30c7\u30aa\u306b\u5909\u63db\u3067\u304d\u308b\u3001\u3068\u3044\u3046\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u304c\u8a71\u984c\u306b\u306a\u3063\u3066\u3044\u305f\u306e\u3067\u8a66\u3057\u3066\u307f\u305f\u3002 \u74b0\u5883\u306f\u4ee5\u4e0b\u3002 \u30fbMS-Windows10 1809 \u30fbIntel Core i7 7700K \u30fbGeForce GTX10 … \u7d9a\u304d\u3092\u8aad\u3080 ![\"\"](\"https:\/\/www.eximradar.jp\/wordpress\/wp-content\/uploads\/2019\/05\/anacondaprompt-1024x534.png\")
<\/a><\/p>\nconda create -n tcgn python=3.5 anaconda<\/pre>\n
conda activate tcgn<\/pre>\n
\n\u30fbCUDA9\u00a0 \u30c0\u30a6\u30f3\u30ed\u30fc\u30c9<\/a>
\n\u30fbcuDNN 7.1\u3000\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9<\/a><\/p>\nconda install tensorflow-gpu keras-gpu opencv<\/pre>\n
conda install tensorflow keras opencv<\/pre>\n
\nCPU\uff1atotal time 55.7
\nGPU\uff1atotal time 3.54<\/p>\npython runGan.py 1<\/pre>\n
ffmpeg -i test.mp4 -vcodec png image_%03d.png<\/pre>\n
ffmpeg -r 24 -i image_%03d.png -vcodec libx264 -pix_fmt yuv420p -r 24 test.mp4<\/pre>\n
\n\u3044\u308d\u3044\u308d\u8a66\u3057\u3066\u307f\u305f\u3044\u3002<\/p>\n# Name Version Build Channel\r\n_tflow_select 2.1.0 gpu\r\nabsl-py 0.7.1 py36_0\r\nalabaster 0.7.12 py36_0\r\nanaconda custom py36h363777c_0\r\nanaconda-client 1.7.2 py36_0\r\nanaconda-project 0.8.2 py36_0\r\nasn1crypto 0.24.0 py36_0\r\nastor 0.7.1 py36_0\r\nastroid 2.2.5 py36_0\r\nastropy 3.1.2 py36he774522_0\r\natomicwrites 1.3.0 py36_1\r\nattrs 19.1.0 py36_1\r\nbabel 2.6.0 py36_0\r\nbackcall 0.1.0 py36_0\r\nbackports 1.0 py36_1\r\nbackports.os 0.1.1 py36_0\r\nbackports.shutil_get_terminal_size 1.0.0 py36_2\r\nbeautifulsoup4 4.7.1 py36_1\r\nbitarray 0.8.3 py36hfa6e2cd_0\r\nbkcharts 0.2 py36h7e685f7_0\r\nblas 1.0 mkl\r\nbleach 3.1.0 py36_0\r\nblosc 1.15.0 h7bd577a_0\r\nbokeh 1.0.4 py36_0\r\nboto 2.49.0 py36_0\r\nbottleneck 1.2.1 py36h452e1ab_1\r\nbzip2 1.0.6 hfa6e2cd_5\r\nca-certificates 2019.1.23 0\r\ncertifi 2019.3.9 py36_0\r\ncffi 1.12.2 py36h7a1dbc1_1\r\nchardet 3.0.4 py36_1\r\nclick 7.0 py36_0\r\ncloudpickle 0.8.0 py36_0\r\nclyent 1.2.2 py36_1\r\ncolorama 0.4.1 py36_0\r\ncomtypes 1.1.7 py36_0\r\nconsole_shortcut 0.1.1 3\r\ncontextlib2 0.5.5 py36he5d52c0_0\r\ncryptography 2.6.1 py36h7a1dbc1_0\r\ncudatoolkit 10.0.130 0\r\ncudnn 7.3.1 cuda10.0_0\r\ncurl 7.64.0 h2a8f88b_2\r\ncycler 0.10.0 py36h009560c_0\r\ncython 0.29.6 py36ha925a31_0\r\ncytoolz 0.9.0.1 py36hfa6e2cd_1\r\ndask 1.1.4 py36_1\r\ndask-core 1.1.4 py36_1\r\ndecorator 4.4.0 py36_1\r\ndefusedxml 0.5.0 py36_1\r\ndistributed 1.26.0 py36_1\r\ndocutils 0.14 py36h6012d8f_0\r\nentrypoints 0.3 py36_0\r\net_xmlfile 1.0.1 py36h3d2d736_0\r\nfastcache 1.0.2 py36hfa6e2cd_2\r\nflask 1.0.2 py36_1\r\nfreetype 2.9.1 ha9979f8_1\r\ngast 0.2.2 py36_0\r\nget_terminal_size 1.0.0 h38e98db_0\r\ngevent 1.4.0 py36he774522_0\r\ngreenlet 0.4.15 py36hfa6e2cd_0\r\ngrpcio 1.16.1 py36h351948d_1\r\nh5py 2.8.0 py36h3bdd7fb_2\r\nhdf5 1.10.2 hac2f561_1\r\nheapdict 1.0.0 py36_2\r\nhtml5lib 1.0.1 py36_0\r\nicc_rt 2019.0.0 h0cc432a_1\r\nicu 58.2 ha66f8fd_1\r\nidna 2.8 py36_0\r\nimageio 2.5.0 py36_0\r\nimagesize 1.1.0 py36_0\r\nimportlib_metadata 0.8 py36_0\r\nintel-openmp 2019.3 203\r\nipykernel 5.1.0 py36h39e3cac_0\r\nipython 7.4.0 py36h39e3cac_0\r\nipython_genutils 0.2.0 py36h3c5d0ee_0\r\nipywidgets 7.4.2 py36_0\r\nisort 4.3.16 py36_0\r\nitsdangerous 1.1.0 py36_0\r\njdcal 1.4 py36_0\r\njedi 0.13.3 py36_0\r\njinja2 2.10 py36_0\r\njpeg 9b hb83a4c4_2\r\njsonschema 3.0.1 py36_0\r\njupyter 1.0.0 py36_7\r\njupyter_client 5.2.4 py36_0\r\njupyter_console 6.0.0 py36_0\r\njupyter_core 4.4.0 py36_0\r\njupyterlab 0.35.4 py36hf63ae98_0\r\njupyterlab_server 0.2.0 py36_0\r\nkeras-applications 1.0.7 py_0\r\nkeras-base 2.2.4 py36_0\r\nkeras-gpu 2.2.4 0\r\nkeras-preprocessing 1.0.9 py_0\r\nkeyring 18.0.0 py36_0\r\nkiwisolver 1.0.1 py36h6538335_0\r\nkrb5 1.16.1 hc04afaa_7\r\nlazy-object-proxy 1.3.1 py36hfa6e2cd_2\r\nlibcurl 7.64.0 h2a8f88b_2\r\nlibiconv 1.15 h1df5818_7\r\nlibopencv 3.4.1 h875b8b8_3\r\nlibpng 1.6.36 h2a8f88b_0\r\nlibprotobuf 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