{ "cells": [ { "cell_type": "code", "execution_count": 23, "metadata": { "id": "JQBzL7WTdYKC" }, "outputs": [], "source": [ "# please commment %%capture in the first line of the follwing code block,\n", "# , if you want to see the output. \n", "!pip install -q gwpy" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "id": "yk6FWIzLq78J" }, "outputs": [], "source": [ "%%capture\n", "!pip install openmim\n", "!mim install mmcv-full" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "id": "7hTKwxWsujLV" }, "outputs": [], "source": [ "%%capture\n", "!mkdir -p ~/.insightface/models\n", "%cd ~/.insightface/models\n", "!wget https://keeper.mpdl.mpg.de/f/2d58b7fed5a74cb5be83/?dl=1 -O antelopev2.zip\n", "!wget https://keeper.mpdl.mpg.de/f/8faabd353cfc457fa5c5/?dl=1 -O buffalo_l.zip\n", "!mkdir -p antelopev2 && cd antelopev2 && unzip -o ../antelopev2.zip\n", "!mkdir -p buffalo_l && cd buffalo_l && unzip -o ../buffalo_l.zip" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "id": "Vx-Vk7S_dF0H" }, "outputs": [], "source": [ "# !curl -LO https://github.com/open-mmlab/mmcv/archive/refs/tags/v1.6.0.tar.gz\n", "# !tar xzf v1.6.0.tar.gz\n", "# %cd mmcv-1.6.0\n", "# !pip install -r requirements/optional.txt\n", "# !MMCV_WITH_OPS=1 pip install -e . -v\n", "# %cd /content" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "id": "6qxwz7jrORsM" }, "outputs": [], "source": [ "%%capture\n", "%cd /content\n", "!git clone https://github.com/yhw-yhw/SHOW.git\n", "!wget https://www.dropbox.com/s/gqdcu51ilo44k3i/models.zip?dl=0 -O models.zip\n", "!wget https://www.dropbox.com/s/r14bl9mhvngohla/data.zip?dl=0 -O data.zip\n", "!unzip data.zip\n", "!7za x models.zip" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "id": "_Pu-qnq3gBfA" }, "outputs": [], "source": [ "%%capture\n", "%cd /content\n", "!cd /content/SHOW/modules/MICA && pip install -r requirements.txt\n", "!cd /content/SHOW/modules/PIXIE && pip install -r requirements.txt\n", "!cd /content/SHOW/modules/PyMAF && pip install -r requirements.txt\n", "!cd /content/SHOW/modules/DECA && pip install -r requirements.txt\n", "!cd /content/SHOW && pip install -r requirements.txt\n", "!pip uninstall -y xtcocotools && pip install xtcocotools --no-binary xtcocotools" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "id": "Rd6Gxfj3s5FU" }, "outputs": [], "source": [ "%%capture\n", "%cd /content\n", "!git clone https://github.com/open-mmlab/mmdetection\n", "!cd /content/mmdetection && python setup.py install\n", "!git clone https://github.com/open-mmlab/mmpose\n", "!cd /content/mmpose && python setup.py install" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "44O8Tbne7XtB", "outputId": "95681678-fd6c-45cb-ebcd-dd53a50524f1" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "env: mmpose_root=/content/mmpose\n" ] } ], "source": [ "%env mmpose_root = /content/mmpose" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "id": "QxrrDUw-xZJP" }, "outputs": [], "source": [ "!rm /usr/local/lib/python3.8/dist-packages/torchgeometry/core/conversions.py\n", "!cp /content/SHOW/conversions.py /usr/local/lib/python3.8/dist-packages/torchgeometry/core/conversions.py" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "id": "m6NhsC33shky" }, "outputs": [], "source": [ "%%capture\n", "import os\n", "import sys\n", "import torch\n", "need_pytorch3d=False\n", "try:\n", " import pytorch3d\n", "except ModuleNotFoundError:\n", " need_pytorch3d=True\n", "if need_pytorch3d:\n", " if torch.__version__.startswith(\"1.13.\") and sys.platform.startswith(\"linux\"):\n", " # We try to install PyTorch3D via a released wheel.\n", " pyt_version_str=torch.__version__.split(\"+\")[0].replace(\".\", \"\")\n", " version_str=\"\".join([\n", " f\"py3{sys.version_info.minor}_cu\",\n", " torch.version.cuda.replace(\".\",\"\"),\n", " f\"_pyt{pyt_version_str}\"\n", " ])\n", " !pip install fvcore iopath\n", " !pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html\n", " else:\n", " # We try to install PyTorch3D from source.\n", " !curl -LO https://github.com/NVIDIA/cub/archive/1.10.0.tar.gz\n", " !tar xzf 1.10.0.tar.gz\n", " os.environ[\"CUB_HOME\"] = os.getcwd() + \"/cub-1.10.0\"\n", " !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "id": "8Jci8Eqs0Wxq" }, "outputs": [], "source": [ "%%capture\n", "import os\n", "from os.path import exists, join, basename, splitext\n", "\n", "git_repo_url = 'https://github.com/CMU-Perceptual-Computing-Lab/openpose.git'\n", "project_name = splitext(basename(git_repo_url))[0]\n", "if not exists(project_name):\n", " # see: https://github.com/CMU-Perceptual-Computing-Lab/openpose/issues/949\n", " # install new CMake becaue of CUDA10\n", " !wget -q https://cmake.org/files/v3.13/cmake-3.13.0-Linux-x86_64.tar.gz\n", " !tar xfz cmake-3.13.0-Linux-x86_64.tar.gz --strip-components=1 -C /usr/local\n", "\n", " # clone openpose\n", " !git clone -q --depth 1 $git_repo_url\n", " # download models\n", " !wget -O /content/openpose/models/hand/pose_iter_102000.caffemodel https://polybox.ethz.ch/index.php/s/Oim76cuqrDVbdxm/download\n", " !wget -O /content/openpose/models/pose/body_25/pose_iter_584000.caffemodel https://polybox.ethz.ch/index.php/s/m5NQAhd7ukVPRoL/download\n", " !wget -O /content/openpose/models/face/pose_iter_116000.caffemodel https://polybox.ethz.ch/index.php/s/cEaF1FTpKjjJZbH/download\n", " !sed -i 's/execute_process(COMMAND git checkout master WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}\\/3rdparty\\/caffe)/execute_process(COMMAND git checkout f019d0dfe86f49d1140961f8c7dec22130c83154 WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}\\/3rdparty\\/caffe)/g' openpose/CMakeLists.txt\n", " # install system dependencies\n", " !apt-get -qq install -y libatlas-base-dev libprotobuf-dev libleveldb-dev libsnappy-dev libhdf5-serial-dev protobuf-compiler libgflags-dev libgoogle-glog-dev liblmdb-dev opencl-headers ocl-icd-opencl-dev libviennacl-dev\n", " # install python dependencies\n", " !pip install -q youtube-dl\n", " # build openpose\n", " !cd openpose && rm -rf build || true && mkdir build && cd build && cmake .. -DUSE_CUDNN=OFF && make -j`nproc`\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "rQHzIiw8biUy", "outputId": "14e95ac9-03b0-49bb-f866-a82bea3ecb67" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/usr/local/lib/python3.8/dist-packages/mmcv/__init__.py:20: UserWarning: On January 1, 2023, MMCV will release v2.0.0, in which it will remove components related to the training process and add a data transformation module. In addition, it will rename the package names mmcv to mmcv-lite and mmcv-full to mmcv. See https://github.com/open-mmlab/mmcv/blob/master/docs/en/compatibility.md for more details.\n", " warnings.warn(\n", "2023-02-24 05:57:24.668226: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F FMA\n", "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", "2023-02-24 05:57:25.683403: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/lib/python3.8/dist-packages/cv2/../../lib64:/usr/lib64-nvidia\n", "2023-02-24 05:57:25.683543: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/lib/python3.8/dist-packages/cv2/../../lib64:/usr/lib64-nvidia\n", "2023-02-24 05:57:25.683563: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n", "tmp_dir: /content/SHOW/test/demo_video/half.mp4\n", "(\"machine_info: {'host_name': 'd12dd4ebb354', 'gpu_info': {'gpu_count': 1, \"\n", " \"'gpu_name': 'Tesla T4', 'gpu_version': '510.47.03', 'gpu_Total': 15360.0, \"\n", " \"'gpu_Free': 14303.875, 'gpu_Used': 1056.125}}\")\n", "\u001b[32m2023-02-24 05:57:34.447\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mstage1_main\u001b[0m:\u001b[36mupdate_betas_name_cfg\u001b[0m:\u001b[36m110\u001b[0m - \u001b[1mnot loading betas\u001b[0m\n", "\u001b[32m2023-02-24 05:57:34.449\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mstage1_main\u001b[0m:\u001b[36mupdate_betas_name_cfg\u001b[0m:\u001b[36m120\u001b[0m - \u001b[1mover_write_cfg: {'to_dict': }>}\u001b[0m\n", "\u001b[32m2023-02-24 05:57:34\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mstage1_main\u001b[0m:\u001b[36m155\u001b[0m - \u001b[33m\u001b[1mno need to optimize\u001b[0m\n", "(\"machine_info: {'host_name': 'd12dd4ebb354', 'gpu_info': {'gpu_count': 1, \"\n", " \"'gpu_name': 'Tesla T4', 'gpu_version': '510.47.03', 'gpu_Total': 15360.0, \"\n", " \"'gpu_Free': 14303.875, 'gpu_Used': 1056.125}}\")\n", "\u001b[32m2023-02-24 05:57:34\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mstage2_main\u001b[0m:\u001b[36m108\u001b[0m - \u001b[33m\u001b[1mbs_at_a_time: 9\u001b[0m\n", "\u001b[32m2023-02-24 05:57:36\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mSHOW.load_assets\u001b[0m:\u001b[36m110\u001b[0m - \u001b[1mshape_id/speaker_name: -1\u001b[0m\n", "\u001b[32m2023-02-24 05:57:36\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mSHOW.load_assets\u001b[0m:\u001b[36m114\u001b[0m - \u001b[1mcurrent shape_id: -1\u001b[0m\n", "load checkpoint from http path: https://download.openmmlab.com/mmpose/top_down/hrnet/hrnet_w48_coco_256x192-b9e0b3ab_20200708.pth\n", "load checkpoint from http path: https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_1x_coco_20200130-047c8118.pth\n", "\u001b[32m2023-02-24 05:57:41\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mSHOW.load_assets\u001b[0m:\u001b[36m48\u001b[0m - \u001b[1mmmpose det length before: 1\u001b[0m\n", "\u001b[32m2023-02-24 05:57:41\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mSHOW.load_assets\u001b[0m:\u001b[36m55\u001b[0m - \u001b[1mmmpose det length after: 1\u001b[0m\n", "\u001b[32m2023-02-24 05:57:41\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mSHOW.load_assets\u001b[0m:\u001b[36m66\u001b[0m - \u001b[1mpose_results_size_list: [374564.94]\u001b[0m\n", "\u001b[32m2023-02-24 05:57:41\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mSHOW.load_assets\u001b[0m:\u001b[36m71\u001b[0m - \u001b[1mcropped image from left:580,top:40,right:1140,bottom:708\u001b[0m\n", "\u001b[32m2023-02-24 05:57:52\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmicalib.flame\u001b[0m:\u001b[36m54\u001b[0m - \u001b[1m[FLAME] creating the FLAME Decoder\u001b[0m\n", "\u001b[32m2023-02-24 05:57:54\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmicalib.flame\u001b[0m:\u001b[36m54\u001b[0m - \u001b[1m[FLAME] creating the FLAME Decoder\u001b[0m\n", "\u001b[32m2023-02-24 05:57:54\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmicalib.mica\u001b[0m:\u001b[36m52\u001b[0m - \u001b[1m[MICA] Trained model found. Path: /content/models/models_MICA/pretrained/mica.tar | GPU: cuda:0\u001b[0m\n", "/usr/local/lib/python3.8/dist-packages/pytorch3d/io/obj_io.py:542: UserWarning: No mtl file provided\n", " warnings.warn(\"No mtl file provided\")\n", "Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}\n", "find model: /root/.insightface/models/antelopev2/1k3d68.onnx landmark_3d_68 ['None', 3, 192, 192] 0.0 1.0\n", "Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}\n", "find model: /root/.insightface/models/antelopev2/2d106det.onnx landmark_2d_106 ['None', 3, 192, 192] 0.0 1.0\n", "Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}\n", "find model: /root/.insightface/models/antelopev2/genderage.onnx genderage ['None', 3, 96, 96] 0.0 1.0\n", "Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}\n", "find model: /root/.insightface/models/antelopev2/glintr100.onnx recognition ['None', 3, 112, 112] 127.5 127.5\n", "Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}\n", "find model: /root/.insightface/models/antelopev2/scrfd_10g_bnkps.onnx detection [1, 3, '?', '?'] 127.5 128.0\n", "set det-size: (224, 224)\n", "\u001b[32m2023-02-24 05:57:58\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmodules.MICA.api_MICA\u001b[0m:\u001b[36m51\u001b[0m - \u001b[1mMICA api init done.\u001b[0m\n", "\u001b[32m2023-02-24 05:57:58\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmodules.MICA.api_MICA\u001b[0m:\u001b[36m110\u001b[0m - \u001b[1mread and process arcface done.\u001b[0m\n", "\u001b[32m2023-02-24 05:57:59\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmodules.MICA.api_MICA\u001b[0m:\u001b[36m161\u001b[0m - \u001b[1mMICA ply: /tmp/cd89627fad95c9be9c16d039475fbab105870343ba6545ad.ply\u001b[0m\n", "\u001b[32m2023-02-24 05:57:59\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mSHOW.load_assets\u001b[0m:\u001b[36m194\u001b[0m - \u001b[1mshape_id/speaker_name: cd89627fad95c9be9c16d039475fbab105870343ba6545ad\u001b[0m\n", "2023-02-24 05:57:59 | INFO | SHOW.utils.timer:58 - %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 05:57:59 | INFO | SHOW.utils.timer:59 - %%%%%%%%%%%%%%%%%%%%START: BUILD_VARS_STAGE%%%%%%%%%%%%%%%%%%%%\n", "INFO: Created TensorFlow Lite XNNPACK delegate for CPU.\n", "/usr/local/lib/python3.8/dist-packages/pytorch3d/io/obj_io.py:546: UserWarning: Mtl file does not exist: /content/SHOW/../data/template.mtl\n", " warnings.warn(f\"Mtl file does not exist: {f}\")\n", "2023-02-24 05:58:10 | INFO | SHOW.utils.timer:71 - %%%%%%%%%%%%%%%%%%%%EXIT: BUILD_VARS_STAGE%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 05:58:10 | INFO | SHOW.utils.timer:72 - %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 05:58:10 | INFO | SHOW.utils.timer:90 - Average BUILD_VARS_STAGE = 11.5125 seconds\n", "2023-02-24 05:58:10 | INFO | SHOW.utils.timer:91 - \n", "\n", "2023-02-24 05:58:10 | INFO | stage2_main:233 - origin input data frame batchsize:9\n", "2023-02-24 05:58:10 | INFO | SHOW.utils.timer:58 - %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 05:58:10 | INFO | SHOW.utils.timer:59 - %%%%%%%%%%%%%%%%%%%%START: LOAD_DATASET_STAGE%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 05:59:37 | INFO | SHOW.face_iders.utils:15 - found sim:0.856342077255249\n", "2023-02-24 05:59:37 | INFO | SHOW.smplx_dataset:226 - matched face from lmk\n", "2023-02-24 05:59:37 | INFO | SHOW.smplx_dataset:228 - match failed: 0.00078125 0.03333333333333333\n", "2023-02-24 05:59:37 | INFO | SHOW.smplx_dataset:226 - matched face from lmk\n", "2023-02-24 05:59:37 | INFO | SHOW.smplx_dataset:228 - match failed: 0.0 0.002777777777777778\n", "2023-02-24 05:59:37 | INFO | SHOW.smplx_dataset:226 - matched face from lmk\n", "2023-02-24 05:59:37 | INFO | SHOW.smplx_dataset:228 - match failed: 0.0 0.005555555555555556\n", "2023-02-24 05:59:37 | INFO | SHOW.smplx_dataset:226 - matched face from lmk\n", "2023-02-24 05:59:37 | INFO | SHOW.smplx_dataset:228 - match failed: 0.00078125 0.005555555555555556\n", "2023-02-24 05:59:37 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 05:59:38 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 05:59:38 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 05:59:38 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 05:59:38 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 05:59:38 | INFO | stage2_main:259 - valid input data frame batchsize:9\n", "2023-02-24 05:59:38 | INFO | stage2_main:260 - valid_bool: tensor([True, True, True, True, True, True, True, True, True], device='cuda:0')\n", "2023-02-24 05:59:38 | INFO | SHOW.utils.timer:71 - %%%%%%%%%%%%%%%%%%%%EXIT: LOAD_DATASET_STAGE%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 05:59:38 | INFO | SHOW.utils.timer:72 - %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 05:59:38 | INFO | SHOW.utils.timer:90 - Average LOAD_DATASET_STAGE = 87.5183 seconds\n", "2023-02-24 05:59:38 | INFO | SHOW.utils.timer:91 - \n", "\n", "2023-02-24 05:59:38 | INFO | SHOW.utils.timer:58 - %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 05:59:38 | INFO | SHOW.utils.timer:59 - %%%%%%%%%%%%%%%%%%%%START: OPTIMIZE_STAGE%%%%%%%%%%%%%%%%%%%%\n", "100%|##########| 447/447 [01:48<00:00, 4.10it/s] lmk=0.1775 lmk_mount=0.211 lmk_oval=0.0296 jaw_reg=0.0463 exp_reg=1.5563 tex_reg=1.9312 loss_sexp=0.0475 loss_sjaw=0.0004 pho=39.7885 all_loss=43.7881: \n", "2023-02-24 06:01:27 | INFO | SHOW.utils.timer:71 - %%%%%%%%%%%%%%%%%%%%EXIT: OPTIMIZE_STAGE%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 06:01:27 | INFO | SHOW.utils.timer:72 - %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 06:01:27 | INFO | SHOW.utils.timer:90 - Average OPTIMIZE_STAGE = 108.9336 seconds\n", "2023-02-24 06:01:27 | INFO | SHOW.utils.timer:91 - \n", "\n", "2023-02-24 06:01:27 | INFO | SHOW.utils.timer:58 - %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 06:01:27 | INFO | SHOW.utils.timer:59 - %%%%%%%%%%%%%%%%%%%%START: SAVING_STAGE%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 06:01:27 | INFO | stage2_main:748 - mica pkl part path: /content/SHOW/test/demo_video/ours_exp/w_mica_part_0_9_0_23.pkl\n", "2023-02-24 06:01:27 | INFO | stage2_main:752 - mica render to origin path: /content/SHOW/test/demo_video/ours_exp/mica_org\n", "saving ours final pyrender images: 100%|##########| 9/9 [00:03<00:00, 2.75it/s]\n", "2023-02-24 06:01:38 | INFO | SHOW.utils.timer:71 - %%%%%%%%%%%%%%%%%%%%EXIT: SAVING_STAGE%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 06:01:38 | INFO | SHOW.utils.timer:72 - %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 06:01:38 | INFO | SHOW.utils.timer:90 - Average SAVING_STAGE = 10.7471 seconds\n", "2023-02-24 06:01:38 | INFO | SHOW.utils.timer:91 - \n", "\n", "2023-02-24 06:01:38 | INFO | stage2_main:233 - origin input data frame batchsize:9\n", "2023-02-24 06:01:38 | INFO | SHOW.utils.timer:58 - %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 06:01:38 | INFO | SHOW.utils.timer:59 - %%%%%%%%%%%%%%%%%%%%START: LOAD_DATASET_STAGE%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 06:01:49 | INFO | SHOW.face_iders.utils:15 - found sim:0.8327088356018066\n", "2023-02-24 06:01:49 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 06:01:50 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 06:01:50 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 06:01:50 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 06:01:50 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 06:01:50 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 06:01:50 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 06:01:50 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 06:01:50 | INFO | SHOW.smplx_dataset:208 - lmk_list len == 1\n", "2023-02-24 06:01:50 | INFO | stage2_main:259 - valid input data frame batchsize:9\n", "2023-02-24 06:01:50 | INFO | stage2_main:260 - valid_bool: tensor([True, True, True, True, True, True, True, True, True], device='cuda:0')\n", "2023-02-24 06:01:50 | INFO | SHOW.utils.timer:71 - %%%%%%%%%%%%%%%%%%%%EXIT: LOAD_DATASET_STAGE%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 06:01:50 | INFO | SHOW.utils.timer:72 - %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", "2023-02-24 06:01:50 | INFO | SHOW.utils.timer:90 - Average LOAD_DATASET_STAGE = 12.3520 seconds\n", "2023-02-24 06:01:50 | INFO | SHOW.utils.timer:91 - \n", "\n", "2023-02-24 06:01:50 | INFO | SHOW.utils.timer:58 - %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", " 0%| | 0/447 [00:00