{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "provenance": [] }, "kernelspec": { "name": "python3", "display_name": "Python 3" }, "language_info": { "name": "python" }, "accelerator": "GPU", "gpuClass": "standard" }, "cells": [ { "cell_type": "markdown", "source": [ "# Simple HigherHRNet\n", "This is a light Google Colab notebook showing how to use the [simple-HigherHRNet](https://github.com/stefanopini/simple-HigherHRNet) repository.\n", "\n", "It includes the conversion to TensorRT and a test of the converted model.\n", "Please skip the section \"TensorRT\" if not interested." ], "metadata": { "id": "xZqqnmmNfX1d" } }, { "cell_type": "markdown", "source": [ "## Pytorch" ], "metadata": { "id": "ZFihjwzqhA04" } }, { "cell_type": "markdown", "source": [ "### Clone the repo and install the dependencies" ], "metadata": { "id": "X_ugGAxdd6Hu" } }, { "cell_type": "code", "source": [ "# clone the repo\n", "!git clone https://github.com/stefanopini/simple-HigherHRNet.git" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "FIecXpzEY7IJ", "outputId": "51ddb584-9a9f-4f36-ecca-9d6ff9f1bf4a" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Cloning into 'simple-HigherHRNet'...\n", "remote: Enumerating objects: 120, done.\u001b[K\n", "remote: Counting objects: 100% (120/120), done.\u001b[K\n", "remote: Compressing objects: 100% (87/87), done.\u001b[K\n", "remote: Total 120 (delta 47), reused 88 (delta 28), pack-reused 0\u001b[K\n", "Receiving objects: 100% (120/120), 15.57 MiB | 8.21 MiB/s, done.\n", "Resolving deltas: 100% (47/47), done.\n" ] } ] }, { "cell_type": "code", "source": [ "%cd simple-HigherHRNet\n", "!pwd" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "JDNRl8a8dl7Z", "outputId": "36e6d64a-ea0b-416d-8a16-f635eb67d0f2" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "/content/simple-HigherHRNet\n", "/content/simple-HigherHRNet\n" ] } ] }, { "cell_type": "code", "source": [ "# install requirements\n", "!pip install -r requirements.txt" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "FGsHqGPNdbHt", "outputId": "52f6c2d1-62d5-4126-8682-9bbbc5531e36" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", "Requirement already satisfied: ffmpeg-python>=0.2.0 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 1)) (0.2.0)\n", "Requirement already satisfied: matplotlib>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 2)) (3.2.2)\n", "Requirement already satisfied: munkres>=1.1.2 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 3)) (1.1.4)\n", "Requirement already satisfied: numpy>=1.16 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 4)) (1.21.6)\n", "Requirement already satisfied: opencv-python>=3.4 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 5)) (4.6.0.66)\n", "Requirement already satisfied: Pillow>=5.4 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 6)) (7.1.2)\n", "Requirement already satisfied: vidgear>=0.1.4 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 7)) (0.2.6)\n", "Requirement already satisfied: torch>=1.4.0 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 8)) (1.12.1+cu113)\n", "Requirement already satisfied: torchvision>=0.5.0 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 9)) (0.13.1+cu113)\n", "Requirement already satisfied: tqdm>=4.26 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 10)) (4.64.1)\n", "Requirement already satisfied: future in /usr/local/lib/python3.7/dist-packages (from ffmpeg-python>=0.2.0->-r requirements.txt (line 1)) (0.16.0)\n", "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.0.2->-r requirements.txt (line 2)) (2.8.2)\n", "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.0.2->-r requirements.txt (line 2)) (3.0.9)\n", "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.0.2->-r requirements.txt (line 2)) (1.4.4)\n", "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.0.2->-r requirements.txt (line 2)) (0.11.0)\n", "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from vidgear>=0.1.4->-r requirements.txt (line 7)) (2.23.0)\n", "Requirement already satisfied: cython in /usr/local/lib/python3.7/dist-packages (from vidgear>=0.1.4->-r requirements.txt (line 7)) (0.29.32)\n", "Requirement already satisfied: colorlog in /usr/local/lib/python3.7/dist-packages (from vidgear>=0.1.4->-r requirements.txt (line 7)) (6.7.0)\n", "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch>=1.4.0->-r requirements.txt (line 8)) (4.1.1)\n", "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.1->matplotlib>=3.0.2->-r requirements.txt (line 2)) (1.15.0)\n", "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->vidgear>=0.1.4->-r requirements.txt (line 7)) (2.10)\n", "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->vidgear>=0.1.4->-r requirements.txt (line 7)) (1.24.3)\n", "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->vidgear>=0.1.4->-r requirements.txt (line 7)) (3.0.4)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->vidgear>=0.1.4->-r requirements.txt (line 7)) (2022.9.24)\n" ] } ] }, { "cell_type": "code", "source": [ "# install vlc to get video codecs\n", "!apt install vlc" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "qMynH2IPebr8", "outputId": "95dc4639-d770-44f6-b877-6e235cc3065b" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Reading package lists... Done\n", "Building dependency tree \n", "Reading state information... Done\n", "The following package was automatically installed and is no longer required:\n", " libnvidia-common-460\n", "Use 'apt autoremove' to remove it.\n", "The following additional packages will be installed:\n", " fonts-freefont-ttf liba52-0.7.4 libaa1 libaribb24-0\n", " libbasicusageenvironment1 libcddb2 libdca0 libdvbpsi10 libdvdnav4\n", " libdvdread4 libebml4v5 libfaad2 libgroupsock8 libkate1 libldb1\n", " liblirc-client0 liblivemedia62 liblua5.2-0 libmad0 libmatroska6v5\n", " libmicrodns0 libmpcdec6 libmpeg2-4 libmtp-common libmtp-runtime libmtp9\n", " libnfs11 libnotify4 libopenmpt-modplug1 libplacebo4 libprotobuf-lite10\n", " libproxy-tools libqt5svg5 libqt5x11extras5 libresid-builder0c2a\n", " libsdl-image1.2 libsdl1.2debian libsecret-1-0 libsecret-common libshout3\n", " libsidplay2 libsmbclient libspeexdsp1 libtag1v5 libtag1v5-vanilla libtalloc2\n", " libtdb1 libtevent0 libupnp6 libusageenvironment3 libva-wayland2 libvlc-bin\n", " libvlc5 libvlccore9 libvulkan1 libwbclient0 libxcb-xv0 mesa-vulkan-drivers\n", " notification-daemon python-talloc samba-libs vlc-bin vlc-data vlc-l10n\n", " vlc-plugin-base vlc-plugin-notify vlc-plugin-qt vlc-plugin-samba\n", " vlc-plugin-skins2 vlc-plugin-video-output vlc-plugin-video-splitter\n", " vlc-plugin-visualization\n", "Suggested packages:\n", " libdvdcss2 lirc\n", "The following NEW packages will be installed:\n", " fonts-freefont-ttf liba52-0.7.4 libaa1 libaribb24-0\n", " libbasicusageenvironment1 libcddb2 libdca0 libdvbpsi10 libdvdnav4\n", " libdvdread4 libebml4v5 libfaad2 libgroupsock8 libkate1 libldb1\n", " liblirc-client0 liblivemedia62 liblua5.2-0 libmad0 libmatroska6v5\n", " libmicrodns0 libmpcdec6 libmpeg2-4 libmtp-common libmtp-runtime libmtp9\n", " libnfs11 libnotify4 libopenmpt-modplug1 libplacebo4 libprotobuf-lite10\n", " libproxy-tools libqt5svg5 libqt5x11extras5 libresid-builder0c2a\n", " libsdl-image1.2 libsdl1.2debian libsecret-1-0 libsecret-common libshout3\n", " libsidplay2 libsmbclient libspeexdsp1 libtag1v5 libtag1v5-vanilla libtalloc2\n", " libtdb1 libtevent0 libupnp6 libusageenvironment3 libva-wayland2 libvlc-bin\n", " libvlc5 libvlccore9 libvulkan1 libwbclient0 libxcb-xv0 mesa-vulkan-drivers\n", " notification-daemon python-talloc samba-libs vlc vlc-bin vlc-data vlc-l10n\n", " vlc-plugin-base vlc-plugin-notify vlc-plugin-qt vlc-plugin-samba\n", " vlc-plugin-skins2 vlc-plugin-video-output vlc-plugin-video-splitter\n", " vlc-plugin-visualization\n", "0 upgraded, 73 newly installed, 0 to remove and 7 not upgraded.\n", "Need to get 27.3 MB of archives.\n", "After this operation, 124 MB of additional disk space will be used.\n", "Get:1 http://archive.ubuntu.com/ubuntu bionic/main amd64 libmtp-common all 1.1.13-1 [43.6 kB]\n", "Get:2 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic/main amd64 libvulkan1 amd64 1.1.126.0-2~gpu18.04.1 [101 kB]\n", "Get:3 http://archive.ubuntu.com/ubuntu bionic/main amd64 libmtp9 amd64 1.1.13-1 [154 kB]\n", "Get:4 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video" ], "metadata": { "id": "HqHg_VATg6CO" } }, { "cell_type": "code", "source": [ "# download weights (pose_higher_hrnet_w32_512.pth)\n", "!gdown 1V9Iz0ZYy9m8VeaspfKECDW0NKlGsYmO1\n", "!mkdir weights\n", "!mv /content/simple-HigherHRNet/pose_higher_hrnet_w32_512.pth /content/simple-HigherHRNet/weights/pose_higher_hrnet_w32_512.pth" ], "metadata": { "id": "3LURZ12cfCcU", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "59659ccf-d001-41d5-b0a3-c6f463ba775a" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Downloading...\n", "From: https://drive.google.com/uc?id=1V9Iz0ZYy9m8VeaspfKECDW0NKlGsYmO1\n", "To: /content/simple-HigherHRNet/pose_higher_hrnet_w32_512.pth\n", "100% 115M/115M [00:00<00:00, 220MB/s]\n" ] } ] }, { "cell_type": "code", "source": [ "# download a publicly available video (or just get your own)\n", "!wget https://commondatastorage.googleapis.com/gtv-videos-bucket/sample/WeAreGoingOnBullrun.mp4" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "OLIrIc14eUPM", "outputId": "7d707a13-66e0-4219-afa2-a2a27b29995d" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "--2022-11-21 23:37:17-- https://commondatastorage.googleapis.com/gtv-videos-bucket/sample/WeAreGoingOnBullrun.mp4\n", "Resolving commondatastorage.googleapis.com (commondatastorage.googleapis.com)... 142.251.10.128, 2404:6800:4003:c0f::80\n", "Connecting to commondatastorage.googleapis.com (commondatastorage.googleapis.com)|142.251.10.128|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 13183260 (13M) [video/mp4]\n", "Saving to: ‘WeAreGoingOnBullrun.mp4’\n", "\n", "WeAreGoingOnBullrun 100%[===================>] 12.57M --.-KB/s in 0.07s \n", "\n", "2022-11-21 23:37:18 (190 MB/s) - ‘WeAreGoingOnBullrun.mp4’ saved [13183260/13183260]\n", "\n" ] } ] }, { "cell_type": "markdown", "source": [ "### Test the live script\n", "This step can be skipped if interested in the TensorRT conversion." ], "metadata": { "id": "ZWUN1C5RgGYS" } }, { "cell_type": "code", "source": [ "!python ./scripts/live-demo.py --filename WeAreGoingOnBullrun.mp4 --save_video" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "VEPfVe2bg1dS", "outputId": "f287bde9-4463-4a54-8896-8e48b8904dbd" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\u001b[32m23:43:27\u001b[0m :: \u001b[1;35m Helper \u001b[0m :: \u001b[1;36m INFO \u001b[0m :: \u001b[1;37mRunning VidGear Version: 0.2.6\u001b[0m\n", "device: 'cuda' - 1 GPU(s) will be used\n", "/content/simple-HigherHRNet/misc/HeatmapParser.py:168: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n", " y = (ind // w).long()\n", "framerate: 8.096502 fps / detected people: 0 /content/simple-HigherHRNet/misc/HeatmapParser.py:236: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n", " index = index // dim\n", "framerate: 9.491158 fps / detected people: 0 \n", "Time elapsed == 209.30760788917542\n" ] } ] }, { "cell_type": "markdown", "source": [ "Now check out the video output.avi\n" ], "metadata": { "id": "RsTTv7A5gGvF" } }, { "cell_type": "markdown", "source": [ "## TensorRT\n", "This section install TensorRT 8.5, converts the model to TensorRT (.engine) and tests the converted model.\n", "\n", "Tested with TensorRT 8.5.1-1+cuda11.8 and python package tensorrt 8.5.1.7 ." ], "metadata": { "id": "YHj3FQEyf1yD" } }, { "cell_type": "markdown", "source": [ "### Install TensorRT\n", "A GPU is needed for this step. Please change the runtime type to \"GPU\".\n" ], "metadata": { "id": "VsFWYxaNc-gl" } }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "LsAlxRGVXhrt", "outputId": "834363d2-8d74-450a-b6d3-110e8fdeb404" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Mon Nov 21 23:47:24 2022 \n", "+-----------------------------------------------------------------------------+\n", "| NVIDIA-SMI 460.32.03 Driver Version: 460.32.03 CUDA Version: 11.2 |\n", "|-------------------------------+----------------------+----------------------+\n", "| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n", "| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n", "| | | MIG M. |\n", "|===============================+======================+======================|\n", "| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n", "| N/A 67C P8 11W / 70W | 0MiB / 15109MiB | 0% Default |\n", "| | | N/A |\n", "+-------------------------------+----------------------+----------------------+\n", " \n", "+-----------------------------------------------------------------------------+\n", "| Processes: |\n", "| GPU GI CI PID Type Process name GPU Memory |\n", "| ID ID Usage |\n", "|=============================================================================|\n", "| No running processes found |\n", "+-----------------------------------------------------------------------------+\n" ] } ], "source": [ "# check a GPU runtime is selected\n", "!nvidia-smi" ] }, { "cell_type": "code", "source": [ "%%bash\n", "wget https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb\n", "\n", "dpkg -i nvidia-machine-learning-repo-*.deb\n", "apt-get update\n", "\n", "sudo apt-get install libnvinfer8 python3-libnvinfer" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "9vZ35qN5XkHE", "outputId": "8d8e9af3-39e8-4edf-8a67-bbc1173156e2" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(Reading database ... 123994 files and directories currently installed.)\n", "Preparing to unpack nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb ...\n", "Unpacking nvidia-machine-learning-repo-ubuntu1804 (1.0.0-1) over (1.0.0-1) ...\n", "Setting up nvidia-machine-learning-repo-ubuntu1804 (1.0.0-1) ...\n", "Hit:1 https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/ InRelease\n", "Hit:2 http://security.ubuntu.com/ubuntu bionic-security InRelease\n", "Hit:3 http://ppa.launchpad.net/c2d4u.team/c2d4u4.0+/ubuntu bionic InRelease\n", "Ign:4 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 InRelease\n", "Hit:5 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 InRelease\n", "Hit:6 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 Release\n", "Hit:7 http://archive.ubuntu.com/ubuntu bionic InRelease\n", "Hit:8 http://ppa.launchpad.net/cran/libgit2/ubuntu bionic InRelease\n", "Hit:9 http://archive.ubuntu.com/ubuntu bionic-updates InRelease\n", "Hit:10 http://archive.ubuntu.com/ubuntu bionic-backports InRelease\n", "Hit:11 http://ppa.launchpad.net/deadsnakes/ppa/ubuntu bionic InRelease\n", "Hit:13 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic InRelease\n", "Reading package lists...\n", "Reading package lists...\n", "Building dependency tree...\n", "Reading state information...\n", "The following package was automatically installed and is no longer required:\n", " libnvidia-common-460\n", "Use 'sudo apt autoremove' to remove it.\n", "The following additional packages will be installed:\n", " libnvinfer-plugin8 libnvonnxparsers8 libnvparsers8\n", "The following NEW packages will be installed:\n", " libnvinfer-plugin8 libnvinfer8 libnvonnxparsers8 libnvparsers8\n", " python3-libnvinfer\n", "0 upgraded, 5 newly installed, 0 to remove and 7 not upgraded.\n", "Need to get 290 MB of archives.\n", "After this operation, 915 MB of additional disk space will be used.\n", "Get:1 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 libnvinfer8 8.5.1-1+cuda11.8 [274 MB]\n", "Get:2 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 libnvinfer-plugin8 8.5.1-1+cuda11.8 [13.3 MB]\n", "Get:3 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 libnvonnxparsers8 8.5.1-1+cuda11.8 [714 kB]\n", "Get:4 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 libnvparsers8 8.5.1-1+cuda11.8 [804 kB]\n", "Get:5 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 python3-libnvinfer 8.5.1-1+cuda11.8 [610 kB]\n", "Fetched 290 MB in 5s (62.7 MB/s)\n", "Selecting previously unselected package libnvinfer8.\r\n", "(Reading database ... \r(Reading database ... 5%\r(Reading database ... 10%\r(Reading database ... 15%\r(Reading database ... 20%\r(Reading database ... 25%\r(Reading database ... 30%\r(Reading database ... 35%\r(Reading database ... 40%\r(Reading database ... 45%\r(Reading database ... 50%\r(Reading database ... 55%\r(Reading database ... 60%\r(Reading database ... 65%\r(Reading database ... 70%\r(Reading database ... 75%\r(Reading database ... 80%\r(Reading database ... 85%\r(Reading database ... 90%\r(Reading database ... 95%\r(Reading database ... 100%\r(Reading database ... 123994 files and directories currently installed.)\r\n", "Preparing to unpack .../libnvinfer8_8.5.1-1+cuda11.8_amd64.deb ...\r\n", "Unpacking libnvinfer8 (8.5.1-1+cuda11.8) ...\r\n", "Selecting previously unselected package libnvinfer-plugin8.\r\n", "Preparing to unpack .../libnvinfer-plugin8_8.5.1-1+cuda11.8_amd64.deb ...\r\n", "Unpacking libnvinfer-plugin8 (8.5.1-1+cuda11.8) ...\r\n", "Selecting previously unselected package libnvonnxparsers8.\r\n", "Preparing to unpack .../libnvonnxparsers8_8.5.1-1+cuda11.8_amd64.deb ...\r\n", "Unpacking libnvonnxparsers8 (8.5.1-1+cuda11.8) ...\r\n", "Selecting previously unselected package libnvparsers8.\r\n", "Preparing to unpack .../libnvparsers8_8.5.1-1+cuda11.8_amd64.deb ...\r\n", "Unpacking libnvparsers8 (8.5.1-1+cuda11.8) ...\r\n", "Selecting previously unselected package python3-libnvinfer.\r\n", "Preparing to unpack .../python3-libnvinfer_8.5.1-1+cuda11.8_amd64.deb ...\r\n", "Unpacking python3-libnvinfer (8.5.1-1+cuda11.8) ...\r\n", "Setting up libnvinfer8 (8.5.1-1+cuda11.8) ...\r\n", "Setting up libnvinfer-plugin8 (8.5.1-1+cuda11.8) ...\r\n", "Setting up libnvparsers8 (8.5.1-1+cuda11.8) ...\r\n", "Setting up libnvonnxparsers8 (8.5.1-1+cuda11.8) ...\r\n", "Setting up python3-libnvinfer (8.5.1-1+cuda11.8) ...\r\n", "Processing triggers for libc-bin (2.27-3ubuntu1.6) ...\r\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "--2022-11-21 23:10:05-- https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb\n", "Resolving developer.download.nvidia.com (developer.download.nvidia.com)... 152.199.39.144\n", "Connecting to developer.download.nvidia.com (developer.download.nvidia.com)|152.199.39.144|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 2926 (2.9K) [application/x-deb]\n", "Saving to: ‘nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb.1’\n", "\n", " 0K .. 100% 180M=0s\n", "\n", "2022-11-21 23:10:05 (180 MB/s) - ‘nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb.1’ saved [2926/2926]\n", "\n", "W: Target Packages (Packages) is configured multiple times in /etc/apt/sources.list:51 and /etc/apt/sources.list.d/nvidia-machine-learning.list:1\n", "W: Target Packages (Packages) is configured multiple times in /etc/apt/sources.list:51 and /etc/apt/sources.list.d/nvidia-machine-learning.list:1\n", "debconf: unable to initialize frontend: Dialog\n", "debconf: (No usable dialog-like program is installed, so the dialog based frontend cannot be used. at /usr/share/perl5/Debconf/FrontEnd/Dialog.pm line 76, <> line 5.)\n", "debconf: falling back to frontend: Readline\n", "debconf: unable to initialize frontend: Readline\n", "debconf: (This frontend requires a controlling tty.)\n", "debconf: falling back to frontend: Teletype\n", "dpkg-preconfigure: unable to re-open stdin: \n", "W: Target Packages (Packages) is configured multiple times in /etc/apt/sources.list:51 and /etc/apt/sources.list.d/nvidia-machine-learning.list:1\n" ] } ] }, { "cell_type": "code", "source": [ "# check TensorRT version\n", "print(\"TensorRT version: \")\n", "!dpkg -l | grep nvinfer" ], "metadata": { "id": "GlGh_J2WYH8u", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "eb7d90c9-2bed-4a9d-88f7-fdaaf360fa82" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "TensorRT version: \n", "ii libnvinfer-plugin8 8.5.1-1+cuda11.8 amd64 TensorRT plugin libraries\n", "ii libnvinfer8 8.5.1-1+cuda11.8 amd64 TensorRT runtime libraries\n", "ii python3-libnvinfer 8.5.1-1+cuda11.8 amd64 Python 3 bindings for TensorRT\n" ] } ] }, { "cell_type": "code", "source": [ "!pip install tensorrt onnx" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "NUR0P_HklFbz", "outputId": "e6542f82-66e4-4043-8b3c-3837ae031505" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", "Requirement already satisfied: tensorrt in /usr/local/lib/python3.7/dist-packages (8.5.1.7)\n", "Collecting onnx\n", " Downloading onnx-1.12.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.1 MB)\n", "\u001b[K |████████████████████████████████| 13.1 MB 24.5 MB/s \n", "\u001b[?25hRequirement already satisfied: nvidia-cudnn-cu11 in /usr/local/lib/python3.7/dist-packages (from tensorrt) (8.6.0.163)\n", "Requirement already satisfied: nvidia-cublas-cu11 in /usr/local/lib/python3.7/dist-packages (from tensorrt) (11.11.3.6)\n", "Requirement already satisfied: nvidia-cuda-runtime-cu11 in /usr/local/lib/python3.7/dist-packages (from tensorrt) (11.8.89)\n", "Requirement already satisfied: numpy>=1.16.6 in /usr/local/lib/python3.7/dist-packages (from onnx) (1.21.6)\n", "Requirement already satisfied: typing-extensions>=3.6.2.1 in /usr/local/lib/python3.7/dist-packages (from onnx) (4.1.1)\n", "Requirement already satisfied: protobuf<=3.20.1,>=3.12.2 in /usr/local/lib/python3.7/dist-packages (from onnx) (3.19.6)\n", "Installing collected packages: onnx\n", "Successfully installed onnx-1.12.0\n" ] } ] }, { "cell_type": "markdown", "source": [ "### Export the model with tensorrt" ], "metadata": { "id": "I2u6Xn72eEBE" } }, { "cell_type": "code", "source": [ "!python scripts/export-tensorrt-model.py --device 0 --half" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "S57JsLacdnoF", "outputId": "429a5090-4b27-439f-cdb2-d3fe952b9d71" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\u001b[34m\u001b[1mexport-tensorrt-model: \u001b[0mweights=./weights/pose_higher_hrnet_w32_512.pth, hrnet_c=32, hrnet_j=17, imgsz=[512, 960], batch_size=1, device=0, half=True, int8=False, dynamic=False, simplify=False, opset=12, verbose=False, workspace=1, include=['engine']\n", "YOLOv5 🚀 2022-11-21 Python-3.7.15 torch-1.12.1+cu113 CUDA:0 (Tesla T4, 15110MiB)\n", "\n", "\n", "\u001b[34m\u001b[1mONNX:\u001b[0m starting export with onnx 1.12.0...\n", "\u001b[34m\u001b[1mONNX:\u001b[0m export success ✅ 52.5s, saved as weights/pose_higher_hrnet_w32_512.onnx (109.3 MB)\n", "\n", "\u001b[34m\u001b[1mTensorRT:\u001b[0m starting export with TensorRT 8.5.1.7...\n", "[11/21/2022-23:54:02] [TRT] [I] [MemUsageChange] Init CUDA: CPU +0, GPU +0, now: CPU 0, GPU 1572 (MiB)\n", "[11/21/2022-23:54:05] [TRT] [I] [MemUsageChange] Init builder kernel library: CPU +0, GPU +74, now: CPU 0, GPU 1646 (MiB)\n", "[11/21/2022-23:54:05] [TRT] [W] CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#env-vars\n", "scripts/export-tensorrt-model.py:132: DeprecationWarning: Use set_memory_pool_limit instead.\n", " config.max_workspace_size = workspace * 1 << 30\n", "[11/21/2022-23:54:05] [TRT] [I] ----------------------------------------------------------------\n", "[11/21/2022-23:54:05] [TRT] [I] Input filename: weights/pose_higher_hrnet_w32_512.onnx\n", "[11/21/2022-23:54:05] [TRT] [I] ONNX IR version: 0.0.7\n", "[11/21/2022-23:54:05] [TRT] [I] Opset version: 12\n", "[11/21/2022-23:54:05] [TRT] [I] Producer name: pytorch\n", "[11/21/2022-23:54:05] [TRT] [I] Producer version: 1.12.1\n", "[11/21/2022-23:54:05] [TRT] [I] Domain: \n", "[11/21/2022-23:54:05] [TRT] [I] Model version: 0\n", "[11/21/2022-23:54:05] [TRT] [I] Doc string: \n", "[11/21/2022-23:54:05] [TRT] [I] ----------------------------------------------------------------\n", "[11/21/2022-23:54:06] [TRT] [W] onnx2trt_utils.cpp:377: Your ONNX model has been generated with INT64 weights, while TensorRT does not natively support INT64. Attempting to cast down to INT32.\n", "\u001b[34m\u001b[1mTensorRT:\u001b[0m input \"images\" with shape(1, 3, 512, 960) DataType.FLOAT\n", "\u001b[34m\u001b[1mTensorRT:\u001b[0m output \"output0\" with shape(1, 34, 128, 240) DataType.FLOAT\n", "\u001b[34m\u001b[1mTensorRT:\u001b[0m output \"output1\" with shape(1, 17, 256, 480) DataType.FLOAT\n", "\u001b[34m\u001b[1mTensorRT:\u001b[0m building FP16 engine as weights/pose_higher_hrnet_w32_512.engine\n", "scripts/export-tensorrt-model.py:159: DeprecationWarning: Use build_serialized_network instead.\n", " with builder.build_engine(network, config) as engine, open(f, 'wb') as t:\n", "[11/21/2022-23:54:10] [TRT] [I] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 0, GPU 1654 (MiB)\n", "[11/21/2022-23:54:10] [TRT] [I] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 0, GPU 1662 (MiB)\n", "[11/21/2022-23:54:10] [TRT] [W] TensorRT was linked against cuDNN 8.6.0 but loaded cuDNN 8.3.2\n", "[11/21/2022-23:54:10] [TRT] [I] Local timing cache in use. Profiling results in this builder pass will not be stored.\n", "[11/21/2022-23:54:19] [TRT] [I] Some tactics do not have sufficient workspace memory to run. Increasing workspace size will enable more tactics, please check verbose output for requested sizes.\n", "[11/22/2022-00:00:29] [TRT] [I] Total Activation Memory: 1602586624\n", "[11/22/2022-00:00:29] [TRT] [I] Detected 1 inputs and 2 output network tensors.\n", "[11/22/2022-00:00:30] [TRT] [I] Total Host Persistent Memory: 930704\n", "[11/22/2022-00:00:30] [TRT] [I] Total Device Persistent Memory: 3670528\n", "[11/22/2022-00:00:30] [TRT] [I] Total Scratch Memory: 0\n", "[11/22/2022-00:00:30] [TRT] [I] [MemUsageStats] Peak memory usage of TRT CPU/GPU memory allocators: CPU 55 MiB, GPU 574 MiB\n", "[11/22/2022-00:00:30] [TRT] [I] [BlockAssignment] Started assigning block shifts. This will take 341 steps to complete.\n", "[11/22/2022-00:00:30] [TRT] [I] [BlockAssignment] Algorithm ShiftNTopDown took 16.2806ms to assign 14 blocks to 341 nodes requiring 51609600 bytes.\n", "[11/22/2022-00:00:30] [TRT] [I] Total Activation Memory: 51609600\n", "[11/22/2022-00:00:30] [TRT] [W] TensorRT encountered issues when converting weights between types and that could affect accuracy.\n", "[11/22/2022-00:00:30] [TRT] [W] If this is not the desired behavior, please modify the weights or retrain with regularization to adjust the magnitude of the weights.\n", "[11/22/2022-00:00:30] [TRT] [W] Check verbose logs for the list of affected weights.\n", "[11/22/2022-00:00:30] [TRT] [W] - 317 weights are affected by this issue: Detected subnormal FP16 values.\n", "[11/22/2022-00:00:30] [TRT] [W] - 88 weights are affected by this issue: Detected values less than smallest positive FP16 subnormal value and converted them to the FP16 minimum subnormalized value.\n", "[11/22/2022-00:00:30] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in building engine: CPU +55, GPU +58, now: CPU 55, GPU 58 (MiB)\n", "\u001b[34m\u001b[1mTensorRT:\u001b[0m export success ✅ 440.8s, saved as weights/pose_higher_hrnet_w32_512.engine (56.9 MB)\n", "\n", "Export complete (446.1s)\n" ] } ] }, { "cell_type": "markdown", "source": [ "### Test the tensorrt model" ], "metadata": { "id": "npgGj4cGemZd" } }, { "cell_type": "code", "source": [ "!python scripts/live-demo.py --enable_tensorrt --filename=WeAreGoingOnBullrun.mp4 --hrnet_weights='weights/pose_higher_hrnet_w32_512.engine' --save_video" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "LnIpbqV0fVps", "outputId": "fce1e062-c975-421a-be89-51c533f2f879" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\u001b[32m00:02:18\u001b[0m :: \u001b[1;35m Helper \u001b[0m :: \u001b[1;36m INFO \u001b[0m :: \u001b[1;37mRunning VidGear Version: 0.2.6\u001b[0m\n", "[11/22/2022-00:02:20] [TRT] [I] Loaded engine size: 56 MiB\n", "[11/22/2022-00:02:21] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +58, now: CPU 0, GPU 58 (MiB)\n", "[11/22/2022-00:02:21] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +1, GPU +52, now: CPU 1, GPU 110 (MiB)\n", "[11/22/2022-00:02:21] [TRT] [W] CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#env-vars\n", "/content/simple-HigherHRNet/misc/HeatmapParser.py:168: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n", " y = (ind // w).long()\n", "framerate: 22.181639 fps / detected people: 0 /content/simple-HigherHRNet/misc/HeatmapParser.py:236: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n", " index = index // dim\n", "framerate: 23.412900 fps / detected people: 0 \n", "Time elapsed == 134.7310082912445\n" ] } ] }, { "cell_type": "markdown", "source": [ "Now check out the video output.avi\n" ], "metadata": { "id": "WbQk0PeNnM5-" } } ] }