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HRNet (code, colab, models, paper)

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  1. .gitattributes +21 -0
  2. Bottom-Up Human Pose Estimation by Ranking Heatmap-Guided Adaptive Keypoint Estimates.pdf +3 -0
  3. Deep High-Resolution Representation Learning for Human Pose Estimation.pdf +3 -0
  4. Deep High-Resolution Representation Learning for Visual Recognition.pdf +3 -0
  5. Dite-HRNet. Dynamic Lightweight High-Resolution Network for Human Pose Estimation.pdf +3 -0
  6. EfficientHRNet. Efficient Scaling for Lightweight High-Resolution Multi-Person Pose Estimation.pdf +3 -0
  7. FCOS. Fully Convolutional One-Stage Object Detection.pdf +3 -0
  8. High-Resolution Representations for Labeling Pixels and Regions.pdf +3 -0
  9. HigherHRNet. Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation.pdf +3 -0
  10. Lite-HRNet. A Lightweight High-Resolution Network.pdf +3 -0
  11. Segmentation Transformer, Object-Contextual Representations for Semantic Segmentation.pdf +3 -0
  12. code/APRCP-HRNet.zip +3 -0
  13. code/DEKR.zip +3 -0
  14. code/Dite-HRNet.zip +3 -0
  15. code/EfficientHRNet.zip +3 -0
  16. code/HRNet-Bottom-Up-Pose-Estimation.zip +3 -0
  17. code/HRNet-FCOS.zip +3 -0
  18. code/HRNet-Facial-Landmark-Detection.zip +3 -0
  19. code/HRNet-Human-Pose-Estimation.zip +3 -0
  20. code/HRNet-Image-Classification.zip +3 -0
  21. code/HRNet-MaskRCNN-Benchmark.zip +3 -0
  22. code/HRNet-Semantic-Segmentation.zip +3 -0
  23. code/HRNet-V2.zip +3 -0
  24. code/HRNet-for-Fashion-Landmark-Estimation.PyTorch.zip +3 -0
  25. code/HRNet-keras-semantic-segmentation.zip +3 -0
  26. code/HigherHRNet-Human-Pose-Estimation.zip +3 -0
  27. code/Lite-HRNet.zip +3 -0
  28. code/deep-high-resolution-net.TensorFlow.zip +3 -0
  29. code/dual-hrnet.zip +3 -0
  30. code/facial-landmark-detection-hrnet.zip +3 -0
  31. code/hrnet (lxy5513).zip +3 -0
  32. code/hrnet-pytorch.zip +3 -0
  33. code/lite_hrnet.zip +3 -0
  34. code/simple-HigherHRNet.zip +3 -0
  35. code/tf-hrnet.zip +3 -0
  36. colab/SimpleHigherHRNet_notebook.ipynb +1097 -0
  37. models/DeepHRNet-TensorFlow/.gitattributes +35 -0
  38. models/DeepHRNet-TensorFlow/checkpoint +6 -0
  39. models/DeepHRNet-TensorFlow/epoch0.ckpt-189176.data-00000-of-00001 +3 -0
  40. models/DeepHRNet-TensorFlow/epoch0.ckpt-189176.index +0 -0
  41. models/DeepHRNet-TensorFlow/epoch0.ckpt-189176.meta +3 -0
  42. models/DeepHRNet-TensorFlow/epoch1.ckpt-378352.data-00000-of-00001 +3 -0
  43. models/DeepHRNet-TensorFlow/epoch1.ckpt-378352.index +0 -0
  44. models/DeepHRNet-TensorFlow/epoch1.ckpt-378352.meta +3 -0
  45. models/DeepHRNet-TensorFlow/epoch2.ckpt-567528.data-00000-of-00001 +3 -0
  46. models/DeepHRNet-TensorFlow/epoch2.ckpt-567528.index +0 -0
  47. models/DeepHRNet-TensorFlow/epoch2.ckpt-567528.meta +3 -0
  48. models/DeepHRNet-TensorFlow/epoch3.ckpt-756704.data-00000-of-00001 +3 -0
  49. models/DeepHRNet-TensorFlow/epoch3.ckpt-756704.index +0 -0
  50. models/DeepHRNet-TensorFlow/epoch3.ckpt-756704.meta +3 -0
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+ Bottom-Up[[:space:]]Human[[:space:]]Pose[[:space:]]Estimation[[:space:]]by[[:space:]]Ranking[[:space:]]Heatmap-Guided[[:space:]]Adaptive[[:space:]]Keypoint[[:space:]]Estimates.pdf filter=lfs diff=lfs merge=lfs -text
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+ EfficientHRNet.[[:space:]]Efficient[[:space:]]Scaling[[:space:]]for[[:space:]]Lightweight[[:space:]]High-Resolution[[:space:]]Multi-Person[[:space:]]Pose[[:space:]]Estimation.pdf filter=lfs diff=lfs merge=lfs -text
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+ FCOS.[[:space:]]Fully[[:space:]]Convolutional[[:space:]]One-Stage[[:space:]]Object[[:space:]]Detection.pdf filter=lfs diff=lfs merge=lfs -text
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+ "name": "python3",
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+ "gpuClass": "standard"
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+ },
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+ "cells": [
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+ {
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+ "cell_type": "markdown",
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+ "source": [
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+ "# Simple HigherHRNet\n",
23
+ "This is a light Google Colab notebook showing how to use the [simple-HigherHRNet](https://github.com/stefanopini/simple-HigherHRNet) repository.\n",
24
+ "\n",
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+ "It includes the conversion to TensorRT and a test of the converted model.\n",
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+ "Please skip the section \"TensorRT\" if not interested."
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+ ],
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+ "metadata": {
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+ "id": "xZqqnmmNfX1d"
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+ }
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "source": [
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+ "## Pytorch"
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+ ],
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+ "metadata": {
38
+ "id": "ZFihjwzqhA04"
39
+ }
40
+ },
41
+ {
42
+ "cell_type": "markdown",
43
+ "source": [
44
+ "### Clone the repo and install the dependencies"
45
+ ],
46
+ "metadata": {
47
+ "id": "X_ugGAxdd6Hu"
48
+ }
49
+ },
50
+ {
51
+ "cell_type": "code",
52
+ "source": [
53
+ "# clone the repo\n",
54
+ "!git clone https://github.com/stefanopini/simple-HigherHRNet.git"
55
+ ],
56
+ "metadata": {
57
+ "colab": {
58
+ "base_uri": "https://localhost:8080/"
59
+ },
60
+ "id": "FIecXpzEY7IJ",
61
+ "outputId": "51ddb584-9a9f-4f36-ecca-9d6ff9f1bf4a"
62
+ },
63
+ "execution_count": null,
64
+ "outputs": [
65
+ {
66
+ "output_type": "stream",
67
+ "name": "stdout",
68
+ "text": [
69
+ "Cloning into 'simple-HigherHRNet'...\n",
70
+ "remote: Enumerating objects: 120, done.\u001b[K\n",
71
+ "remote: Counting objects: 100% (120/120), done.\u001b[K\n",
72
+ "remote: Compressing objects: 100% (87/87), done.\u001b[K\n",
73
+ "remote: Total 120 (delta 47), reused 88 (delta 28), pack-reused 0\u001b[K\n",
74
+ "Receiving objects: 100% (120/120), 15.57 MiB | 8.21 MiB/s, done.\n",
75
+ "Resolving deltas: 100% (47/47), done.\n"
76
+ ]
77
+ }
78
+ ]
79
+ },
80
+ {
81
+ "cell_type": "code",
82
+ "source": [
83
+ "%cd simple-HigherHRNet\n",
84
+ "!pwd"
85
+ ],
86
+ "metadata": {
87
+ "colab": {
88
+ "base_uri": "https://localhost:8080/"
89
+ },
90
+ "id": "JDNRl8a8dl7Z",
91
+ "outputId": "36e6d64a-ea0b-416d-8a16-f635eb67d0f2"
92
+ },
93
+ "execution_count": null,
94
+ "outputs": [
95
+ {
96
+ "output_type": "stream",
97
+ "name": "stdout",
98
+ "text": [
99
+ "/content/simple-HigherHRNet\n",
100
+ "/content/simple-HigherHRNet\n"
101
+ ]
102
+ }
103
+ ]
104
+ },
105
+ {
106
+ "cell_type": "code",
107
+ "source": [
108
+ "# install requirements\n",
109
+ "!pip install -r requirements.txt"
110
+ ],
111
+ "metadata": {
112
+ "colab": {
113
+ "base_uri": "https://localhost:8080/"
114
+ },
115
+ "id": "FGsHqGPNdbHt",
116
+ "outputId": "52f6c2d1-62d5-4126-8682-9bbbc5531e36"
117
+ },
118
+ "execution_count": null,
119
+ "outputs": [
120
+ {
121
+ "output_type": "stream",
122
+ "name": "stdout",
123
+ "text": [
124
+ "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
125
+ "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",
126
+ "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",
127
+ "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",
128
+ "Requirement already satisfied: numpy>=1.16 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 4)) (1.21.6)\n",
129
+ "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",
130
+ "Requirement already satisfied: Pillow>=5.4 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 6)) (7.1.2)\n",
131
+ "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",
132
+ "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",
133
+ "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",
134
+ "Requirement already satisfied: tqdm>=4.26 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 10)) (4.64.1)\n",
135
+ "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",
136
+ "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",
137
+ "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",
138
+ "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",
139
+ "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",
140
+ "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",
141
+ "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",
142
+ "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",
143
+ "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",
144
+ "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",
145
+ "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",
146
+ "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",
147
+ "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",
148
+ "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"
149
+ ]
150
+ }
151
+ ]
152
+ },
153
+ {
154
+ "cell_type": "code",
155
+ "source": [
156
+ "# install vlc to get video codecs\n",
157
+ "!apt install vlc"
158
+ ],
159
+ "metadata": {
160
+ "colab": {
161
+ "base_uri": "https://localhost:8080/"
162
+ },
163
+ "id": "qMynH2IPebr8",
164
+ "outputId": "95dc4639-d770-44f6-b877-6e235cc3065b"
165
+ },
166
+ "execution_count": null,
167
+ "outputs": [
168
+ {
169
+ "output_type": "stream",
170
+ "name": "stdout",
171
+ "text": [
172
+ "Reading package lists... Done\n",
173
+ "Building dependency tree \n",
174
+ "Reading state information... Done\n",
175
+ "The following package was automatically installed and is no longer required:\n",
176
+ " libnvidia-common-460\n",
177
+ "Use 'apt autoremove' to remove it.\n",
178
+ "The following additional packages will be installed:\n",
179
+ " fonts-freefont-ttf liba52-0.7.4 libaa1 libaribb24-0\n",
180
+ " libbasicusageenvironment1 libcddb2 libdca0 libdvbpsi10 libdvdnav4\n",
181
+ " libdvdread4 libebml4v5 libfaad2 libgroupsock8 libkate1 libldb1\n",
182
+ " liblirc-client0 liblivemedia62 liblua5.2-0 libmad0 libmatroska6v5\n",
183
+ " libmicrodns0 libmpcdec6 libmpeg2-4 libmtp-common libmtp-runtime libmtp9\n",
184
+ " libnfs11 libnotify4 libopenmpt-modplug1 libplacebo4 libprotobuf-lite10\n",
185
+ " libproxy-tools libqt5svg5 libqt5x11extras5 libresid-builder0c2a\n",
186
+ " libsdl-image1.2 libsdl1.2debian libsecret-1-0 libsecret-common libshout3\n",
187
+ " libsidplay2 libsmbclient libspeexdsp1 libtag1v5 libtag1v5-vanilla libtalloc2\n",
188
+ " libtdb1 libtevent0 libupnp6 libusageenvironment3 libva-wayland2 libvlc-bin\n",
189
+ " libvlc5 libvlccore9 libvulkan1 libwbclient0 libxcb-xv0 mesa-vulkan-drivers\n",
190
+ " notification-daemon python-talloc samba-libs vlc-bin vlc-data vlc-l10n\n",
191
+ " vlc-plugin-base vlc-plugin-notify vlc-plugin-qt vlc-plugin-samba\n",
192
+ " vlc-plugin-skins2 vlc-plugin-video-output vlc-plugin-video-splitter\n",
193
+ " vlc-plugin-visualization\n",
194
+ "Suggested packages:\n",
195
+ " libdvdcss2 lirc\n",
196
+ "The following NEW packages will be installed:\n",
197
+ " fonts-freefont-ttf liba52-0.7.4 libaa1 libaribb24-0\n",
198
+ " libbasicusageenvironment1 libcddb2 libdca0 libdvbpsi10 libdvdnav4\n",
199
+ " libdvdread4 libebml4v5 libfaad2 libgroupsock8 libkate1 libldb1\n",
200
+ " liblirc-client0 liblivemedia62 liblua5.2-0 libmad0 libmatroska6v5\n",
201
+ " libmicrodns0 libmpcdec6 libmpeg2-4 libmtp-common libmtp-runtime libmtp9\n",
202
+ " libnfs11 libnotify4 libopenmpt-modplug1 libplacebo4 libprotobuf-lite10\n",
203
+ " libproxy-tools libqt5svg5 libqt5x11extras5 libresid-builder0c2a\n",
204
+ " libsdl-image1.2 libsdl1.2debian libsecret-1-0 libsecret-common libshout3\n",
205
+ " libsidplay2 libsmbclient libspeexdsp1 libtag1v5 libtag1v5-vanilla libtalloc2\n",
206
+ " libtdb1 libtevent0 libupnp6 libusageenvironment3 libva-wayland2 libvlc-bin\n",
207
+ " libvlc5 libvlccore9 libvulkan1 libwbclient0 libxcb-xv0 mesa-vulkan-drivers\n",
208
+ " notification-daemon python-talloc samba-libs vlc vlc-bin vlc-data vlc-l10n\n",
209
+ " vlc-plugin-base vlc-plugin-notify vlc-plugin-qt vlc-plugin-samba\n",
210
+ " vlc-plugin-skins2 vlc-plugin-video-output vlc-plugin-video-splitter\n",
211
+ " vlc-plugin-visualization\n",
212
+ "0 upgraded, 73 newly installed, 0 to remove and 7 not upgraded.\n",
213
+ "Need to get 27.3 MB of archives.\n",
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+ "After this operation, 124 MB of additional disk space will be used.\n",
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+ "Get:1 http://archive.ubuntu.com/ubuntu bionic/main amd64 libmtp-common all 1.1.13-1 [43.6 kB]\n",
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+ "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",
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+ "Get:3 http://archive.ubuntu.com/ubuntu bionic/main amd64 libmtp9 amd64 1.1.13-1 [154 kB]\n",
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+ "Get:4 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libqt5svg5 amd64 5.9.5-0ubuntu1.1 [129 kB]\n",
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+ "Get:5 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libwbclient0 amd64 2:4.7.6+dfsg~ubuntu-0ubuntu2.28 [33.6 kB]\n",
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+ "Get:6 http://archive.ubuntu.com/ubuntu bionic/main amd64 libtalloc2 amd64 2.1.10-2ubuntu1 [36.0 kB]\n",
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+ "Get:7 http://archive.ubuntu.com/ubuntu bionic/main amd64 libtdb1 amd64 1.3.15-2 [39.7 kB]\n",
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+ "Get:10 http://archive.ubuntu.com/ubuntu bionic/main amd64 python-talloc amd64 2.1.10-2ubuntu1 [9,124 B]\n",
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+ "Get:13 http://archive.ubuntu.com/ubuntu bionic/main amd64 fonts-freefont-ttf all 20120503-7 [4,202 kB]\n",
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+ "Get:27 http://archive.ubuntu.com/ubuntu bionic/main amd64 liblua5.2-0 amd64 5.2.4-1.1build1 [108 kB]\n",
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+ "Get:28 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libmad0 amd64 0.15.1b-9ubuntu18.04.1 [64.6 kB]\n",
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+ "Get:29 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libmatroska6v5 amd64 1.4.8-1.1 [122 kB]\n",
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+ "Get:31 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libmpcdec6 amd64 2:0.1~r495-1 [32.3 kB]\n",
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+ "Get:35 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libnotify4 amd64 0.7.7-3ubuntu0.18.04.1 [18.7 kB]\n",
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+ "Get:54 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libvlc5 amd64 3.0.8-0ubuntu18.04.1 [68.0 kB]\n",
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+ "Get:64 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 vlc-plugin-base amd64 3.0.8-0ubuntu18.04.1 [2,900 kB]\n",
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+ "Get:70 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 vlc-plugin-samba amd64 3.0.8-0ubuntu18.04.1 [18.9 kB]\n",
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+ "Get:71 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 vlc-plugin-skins2 amd64 3.0.8-0ubuntu18.04.1 [468 kB]\n",
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+ "Get:72 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 vlc-plugin-video-splitter amd64 3.0.8-0ubuntu18.04.1 [31.3 kB]\n",
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+ "Get:73 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 vlc-plugin-visualization amd64 3.0.8-0ubuntu18.04.1 [39.6 kB]\n",
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+ "Setting up libproxy-tools (0.4.15-1ubuntu0.2) ...\n",
529
+ "Setting up libmicrodns0:amd64 (0.0.8-1) ...\n",
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+ "Setting up libebml4v5:amd64 (1.3.5-2ubuntu0.1) ...\n",
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534
+ "Setting up liblirc-client0:amd64 (0.10.0-2) ...\n",
535
+ "Setting up libsdl1.2debian:amd64 (1.2.15+dfsg2-0.1ubuntu0.2) ...\n",
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+ "Setting up vlc-l10n (3.0.8-0ubuntu18.04.1) ...\n",
537
+ "Setting up libnfs11:amd64 (2.0.0-1~exp1) ...\n",
538
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540
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541
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542
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+ "Setting up liblua5.2-0:amd64 (5.2.4-1.1build1) ...\n",
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562
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563
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564
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565
+ "Setting up libtag1v5-vanilla:amd64 (1.11.1+dfsg.1-0.2build2) ...\n",
566
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567
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568
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+ "Setting up libtevent0:amd64 (0.9.34-1) ...\n",
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+ "Setting up vlc-plugin-video-output:amd64 (3.0.8-0ubuntu18.04.1) ...\n",
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+ "Setting up vlc-bin (3.0.8-0ubuntu18.04.1) ...\n",
581
+ "Setting up libldb1:amd64 (2:1.2.3-1ubuntu0.2) ...\n",
582
+ "Setting up vlc (3.0.8-0ubuntu18.04.1) ...\n",
583
+ "Setting up samba-libs:amd64 (2:4.7.6+dfsg~ubuntu-0ubuntu2.28) ...\n",
584
+ "Setting up libsmbclient:amd64 (2:4.7.6+dfsg~ubuntu-0ubuntu2.28) ...\n",
585
+ "Setting up vlc-plugin-samba:amd64 (3.0.8-0ubuntu18.04.1) ...\n",
586
+ "Processing triggers for udev (237-3ubuntu10.56) ...\n",
587
+ "Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n",
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+ "Processing triggers for hicolor-icon-theme (0.17-2) ...\n",
589
+ "Processing triggers for fontconfig (2.12.6-0ubuntu2) ...\n",
590
+ "Processing triggers for mime-support (3.60ubuntu1) ...\n",
591
+ "Processing triggers for libc-bin (2.27-3ubuntu1.6) ...\n",
592
+ "Processing triggers for libvlc-bin:amd64 (3.0.8-0ubuntu18.04.1) ...\n",
593
+ "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"
594
+ ]
595
+ }
596
+ ]
597
+ },
598
+ {
599
+ "cell_type": "markdown",
600
+ "source": [
601
+ "### Download weights and video"
602
+ ],
603
+ "metadata": {
604
+ "id": "HqHg_VATg6CO"
605
+ }
606
+ },
607
+ {
608
+ "cell_type": "code",
609
+ "source": [
610
+ "# download weights (pose_higher_hrnet_w32_512.pth)\n",
611
+ "!gdown 1V9Iz0ZYy9m8VeaspfKECDW0NKlGsYmO1\n",
612
+ "!mkdir weights\n",
613
+ "!mv /content/simple-HigherHRNet/pose_higher_hrnet_w32_512.pth /content/simple-HigherHRNet/weights/pose_higher_hrnet_w32_512.pth"
614
+ ],
615
+ "metadata": {
616
+ "id": "3LURZ12cfCcU",
617
+ "colab": {
618
+ "base_uri": "https://localhost:8080/"
619
+ },
620
+ "outputId": "59659ccf-d001-41d5-b0a3-c6f463ba775a"
621
+ },
622
+ "execution_count": null,
623
+ "outputs": [
624
+ {
625
+ "output_type": "stream",
626
+ "name": "stdout",
627
+ "text": [
628
+ "Downloading...\n",
629
+ "From: https://drive.google.com/uc?id=1V9Iz0ZYy9m8VeaspfKECDW0NKlGsYmO1\n",
630
+ "To: /content/simple-HigherHRNet/pose_higher_hrnet_w32_512.pth\n",
631
+ "100% 115M/115M [00:00<00:00, 220MB/s]\n"
632
+ ]
633
+ }
634
+ ]
635
+ },
636
+ {
637
+ "cell_type": "code",
638
+ "source": [
639
+ "# download a publicly available video (or just get your own)\n",
640
+ "!wget https://commondatastorage.googleapis.com/gtv-videos-bucket/sample/WeAreGoingOnBullrun.mp4"
641
+ ],
642
+ "metadata": {
643
+ "colab": {
644
+ "base_uri": "https://localhost:8080/"
645
+ },
646
+ "id": "OLIrIc14eUPM",
647
+ "outputId": "7d707a13-66e0-4219-afa2-a2a27b29995d"
648
+ },
649
+ "execution_count": null,
650
+ "outputs": [
651
+ {
652
+ "output_type": "stream",
653
+ "name": "stdout",
654
+ "text": [
655
+ "--2022-11-21 23:37:17-- https://commondatastorage.googleapis.com/gtv-videos-bucket/sample/WeAreGoingOnBullrun.mp4\n",
656
+ "Resolving commondatastorage.googleapis.com (commondatastorage.googleapis.com)... 142.251.10.128, 2404:6800:4003:c0f::80\n",
657
+ "Connecting to commondatastorage.googleapis.com (commondatastorage.googleapis.com)|142.251.10.128|:443... connected.\n",
658
+ "HTTP request sent, awaiting response... 200 OK\n",
659
+ "Length: 13183260 (13M) [video/mp4]\n",
660
+ "Saving to: ‘WeAreGoingOnBullrun.mp4’\n",
661
+ "\n",
662
+ "WeAreGoingOnBullrun 100%[===================>] 12.57M --.-KB/s in 0.07s \n",
663
+ "\n",
664
+ "2022-11-21 23:37:18 (190 MB/s) - ‘WeAreGoingOnBullrun.mp4’ saved [13183260/13183260]\n",
665
+ "\n"
666
+ ]
667
+ }
668
+ ]
669
+ },
670
+ {
671
+ "cell_type": "markdown",
672
+ "source": [
673
+ "### Test the live script\n",
674
+ "This step can be skipped if interested in the TensorRT conversion."
675
+ ],
676
+ "metadata": {
677
+ "id": "ZWUN1C5RgGYS"
678
+ }
679
+ },
680
+ {
681
+ "cell_type": "code",
682
+ "source": [
683
+ "!python ./scripts/live-demo.py --filename WeAreGoingOnBullrun.mp4 --save_video"
684
+ ],
685
+ "metadata": {
686
+ "colab": {
687
+ "base_uri": "https://localhost:8080/"
688
+ },
689
+ "id": "VEPfVe2bg1dS",
690
+ "outputId": "f287bde9-4463-4a54-8896-8e48b8904dbd"
691
+ },
692
+ "execution_count": null,
693
+ "outputs": [
694
+ {
695
+ "output_type": "stream",
696
+ "name": "stdout",
697
+ "text": [
698
+ "\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",
699
+ "device: 'cuda' - 1 GPU(s) will be used\n",
700
+ "/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",
701
+ " y = (ind // w).long()\n",
702
+ "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",
703
+ " index = index // dim\n",
704
+ "framerate: 9.491158 fps / detected people: 0 \n",
705
+ "Time elapsed == 209.30760788917542\n"
706
+ ]
707
+ }
708
+ ]
709
+ },
710
+ {
711
+ "cell_type": "markdown",
712
+ "source": [
713
+ "Now check out the video output.avi\n"
714
+ ],
715
+ "metadata": {
716
+ "id": "RsTTv7A5gGvF"
717
+ }
718
+ },
719
+ {
720
+ "cell_type": "markdown",
721
+ "source": [
722
+ "## TensorRT\n",
723
+ "This section install TensorRT 8.5, converts the model to TensorRT (.engine) and tests the converted model.\n",
724
+ "\n",
725
+ "Tested with TensorRT 8.5.1-1+cuda11.8 and python package tensorrt 8.5.1.7 ."
726
+ ],
727
+ "metadata": {
728
+ "id": "YHj3FQEyf1yD"
729
+ }
730
+ },
731
+ {
732
+ "cell_type": "markdown",
733
+ "source": [
734
+ "### Install TensorRT\n",
735
+ "A GPU is needed for this step. Please change the runtime type to \"GPU\".\n"
736
+ ],
737
+ "metadata": {
738
+ "id": "VsFWYxaNc-gl"
739
+ }
740
+ },
741
+ {
742
+ "cell_type": "code",
743
+ "execution_count": null,
744
+ "metadata": {
745
+ "colab": {
746
+ "base_uri": "https://localhost:8080/"
747
+ },
748
+ "id": "LsAlxRGVXhrt",
749
+ "outputId": "834363d2-8d74-450a-b6d3-110e8fdeb404"
750
+ },
751
+ "outputs": [
752
+ {
753
+ "output_type": "stream",
754
+ "name": "stdout",
755
+ "text": [
756
+ "Mon Nov 21 23:47:24 2022 \n",
757
+ "+-----------------------------------------------------------------------------+\n",
758
+ "| NVIDIA-SMI 460.32.03 Driver Version: 460.32.03 CUDA Version: 11.2 |\n",
759
+ "|-------------------------------+----------------------+----------------------+\n",
760
+ "| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n",
761
+ "| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n",
762
+ "| | | MIG M. |\n",
763
+ "|===============================+======================+======================|\n",
764
+ "| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n",
765
+ "| N/A 67C P8 11W / 70W | 0MiB / 15109MiB | 0% Default |\n",
766
+ "| | | N/A |\n",
767
+ "+-------------------------------+----------------------+----------------------+\n",
768
+ " \n",
769
+ "+-----------------------------------------------------------------------------+\n",
770
+ "| Processes: |\n",
771
+ "| GPU GI CI PID Type Process name GPU Memory |\n",
772
+ "| ID ID Usage |\n",
773
+ "|=============================================================================|\n",
774
+ "| No running processes found |\n",
775
+ "+-----------------------------------------------------------------------------+\n"
776
+ ]
777
+ }
778
+ ],
779
+ "source": [
780
+ "# check a GPU runtime is selected\n",
781
+ "!nvidia-smi"
782
+ ]
783
+ },
784
+ {
785
+ "cell_type": "code",
786
+ "source": [
787
+ "%%bash\n",
788
+ "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",
789
+ "\n",
790
+ "dpkg -i nvidia-machine-learning-repo-*.deb\n",
791
+ "apt-get update\n",
792
+ "\n",
793
+ "sudo apt-get install libnvinfer8 python3-libnvinfer"
794
+ ],
795
+ "metadata": {
796
+ "colab": {
797
+ "base_uri": "https://localhost:8080/"
798
+ },
799
+ "id": "9vZ35qN5XkHE",
800
+ "outputId": "8d8e9af3-39e8-4edf-8a67-bbc1173156e2"
801
+ },
802
+ "execution_count": null,
803
+ "outputs": [
804
+ {
805
+ "output_type": "stream",
806
+ "name": "stdout",
807
+ "text": [
808
+ "(Reading database ... 123994 files and directories currently installed.)\n",
809
+ "Preparing to unpack nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb ...\n",
810
+ "Unpacking nvidia-machine-learning-repo-ubuntu1804 (1.0.0-1) over (1.0.0-1) ...\n",
811
+ "Setting up nvidia-machine-learning-repo-ubuntu1804 (1.0.0-1) ...\n",
812
+ "Hit:1 https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/ InRelease\n",
813
+ "Hit:2 http://security.ubuntu.com/ubuntu bionic-security InRelease\n",
814
+ "Hit:3 http://ppa.launchpad.net/c2d4u.team/c2d4u4.0+/ubuntu bionic InRelease\n",
815
+ "Ign:4 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 InRelease\n",
816
+ "Hit:5 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 InRelease\n",
817
+ "Hit:6 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 Release\n",
818
+ "Hit:7 http://archive.ubuntu.com/ubuntu bionic InRelease\n",
819
+ "Hit:8 http://ppa.launchpad.net/cran/libgit2/ubuntu bionic InRelease\n",
820
+ "Hit:9 http://archive.ubuntu.com/ubuntu bionic-updates InRelease\n",
821
+ "Hit:10 http://archive.ubuntu.com/ubuntu bionic-backports InRelease\n",
822
+ "Hit:11 http://ppa.launchpad.net/deadsnakes/ppa/ubuntu bionic InRelease\n",
823
+ "Hit:13 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic InRelease\n",
824
+ "Reading package lists...\n",
825
+ "Reading package lists...\n",
826
+ "Building dependency tree...\n",
827
+ "Reading state information...\n",
828
+ "The following package was automatically installed and is no longer required:\n",
829
+ " libnvidia-common-460\n",
830
+ "Use 'sudo apt autoremove' to remove it.\n",
831
+ "The following additional packages will be installed:\n",
832
+ " libnvinfer-plugin8 libnvonnxparsers8 libnvparsers8\n",
833
+ "The following NEW packages will be installed:\n",
834
+ " libnvinfer-plugin8 libnvinfer8 libnvonnxparsers8 libnvparsers8\n",
835
+ " python3-libnvinfer\n",
836
+ "0 upgraded, 5 newly installed, 0 to remove and 7 not upgraded.\n",
837
+ "Need to get 290 MB of archives.\n",
838
+ "After this operation, 915 MB of additional disk space will be used.\n",
839
+ "Get:1 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 libnvinfer8 8.5.1-1+cuda11.8 [274 MB]\n",
840
+ "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",
841
+ "Get:3 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 libnvonnxparsers8 8.5.1-1+cuda11.8 [714 kB]\n",
842
+ "Get:4 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 libnvparsers8 8.5.1-1+cuda11.8 [804 kB]\n",
843
+ "Get:5 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 python3-libnvinfer 8.5.1-1+cuda11.8 [610 kB]\n",
844
+ "Fetched 290 MB in 5s (62.7 MB/s)\n",
845
+ "Selecting previously unselected package libnvinfer8.\r\n",
846
+ "(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",
847
+ "Preparing to unpack .../libnvinfer8_8.5.1-1+cuda11.8_amd64.deb ...\r\n",
848
+ "Unpacking libnvinfer8 (8.5.1-1+cuda11.8) ...\r\n",
849
+ "Selecting previously unselected package libnvinfer-plugin8.\r\n",
850
+ "Preparing to unpack .../libnvinfer-plugin8_8.5.1-1+cuda11.8_amd64.deb ...\r\n",
851
+ "Unpacking libnvinfer-plugin8 (8.5.1-1+cuda11.8) ...\r\n",
852
+ "Selecting previously unselected package libnvonnxparsers8.\r\n",
853
+ "Preparing to unpack .../libnvonnxparsers8_8.5.1-1+cuda11.8_amd64.deb ...\r\n",
854
+ "Unpacking libnvonnxparsers8 (8.5.1-1+cuda11.8) ...\r\n",
855
+ "Selecting previously unselected package libnvparsers8.\r\n",
856
+ "Preparing to unpack .../libnvparsers8_8.5.1-1+cuda11.8_amd64.deb ...\r\n",
857
+ "Unpacking libnvparsers8 (8.5.1-1+cuda11.8) ...\r\n",
858
+ "Selecting previously unselected package python3-libnvinfer.\r\n",
859
+ "Preparing to unpack .../python3-libnvinfer_8.5.1-1+cuda11.8_amd64.deb ...\r\n",
860
+ "Unpacking python3-libnvinfer (8.5.1-1+cuda11.8) ...\r\n",
861
+ "Setting up libnvinfer8 (8.5.1-1+cuda11.8) ...\r\n",
862
+ "Setting up libnvinfer-plugin8 (8.5.1-1+cuda11.8) ...\r\n",
863
+ "Setting up libnvparsers8 (8.5.1-1+cuda11.8) ...\r\n",
864
+ "Setting up libnvonnxparsers8 (8.5.1-1+cuda11.8) ...\r\n",
865
+ "Setting up python3-libnvinfer (8.5.1-1+cuda11.8) ...\r\n",
866
+ "Processing triggers for libc-bin (2.27-3ubuntu1.6) ...\r\n"
867
+ ]
868
+ },
869
+ {
870
+ "output_type": "stream",
871
+ "name": "stderr",
872
+ "text": [
873
+ "--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",
874
+ "Resolving developer.download.nvidia.com (developer.download.nvidia.com)... 152.199.39.144\n",
875
+ "Connecting to developer.download.nvidia.com (developer.download.nvidia.com)|152.199.39.144|:443... connected.\n",
876
+ "HTTP request sent, awaiting response... 200 OK\n",
877
+ "Length: 2926 (2.9K) [application/x-deb]\n",
878
+ "Saving to: ‘nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb.1’\n",
879
+ "\n",
880
+ " 0K .. 100% 180M=0s\n",
881
+ "\n",
882
+ "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",
883
+ "\n",
884
+ "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",
885
+ "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",
886
+ "debconf: unable to initialize frontend: Dialog\n",
887
+ "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",
888
+ "debconf: falling back to frontend: Readline\n",
889
+ "debconf: unable to initialize frontend: Readline\n",
890
+ "debconf: (This frontend requires a controlling tty.)\n",
891
+ "debconf: falling back to frontend: Teletype\n",
892
+ "dpkg-preconfigure: unable to re-open stdin: \n",
893
+ "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"
894
+ ]
895
+ }
896
+ ]
897
+ },
898
+ {
899
+ "cell_type": "code",
900
+ "source": [
901
+ "# check TensorRT version\n",
902
+ "print(\"TensorRT version: \")\n",
903
+ "!dpkg -l | grep nvinfer"
904
+ ],
905
+ "metadata": {
906
+ "id": "GlGh_J2WYH8u",
907
+ "colab": {
908
+ "base_uri": "https://localhost:8080/"
909
+ },
910
+ "outputId": "eb7d90c9-2bed-4a9d-88f7-fdaaf360fa82"
911
+ },
912
+ "execution_count": null,
913
+ "outputs": [
914
+ {
915
+ "output_type": "stream",
916
+ "name": "stdout",
917
+ "text": [
918
+ "TensorRT version: \n",
919
+ "ii libnvinfer-plugin8 8.5.1-1+cuda11.8 amd64 TensorRT plugin libraries\n",
920
+ "ii libnvinfer8 8.5.1-1+cuda11.8 amd64 TensorRT runtime libraries\n",
921
+ "ii python3-libnvinfer 8.5.1-1+cuda11.8 amd64 Python 3 bindings for TensorRT\n"
922
+ ]
923
+ }
924
+ ]
925
+ },
926
+ {
927
+ "cell_type": "code",
928
+ "source": [
929
+ "!pip install tensorrt onnx"
930
+ ],
931
+ "metadata": {
932
+ "colab": {
933
+ "base_uri": "https://localhost:8080/"
934
+ },
935
+ "id": "NUR0P_HklFbz",
936
+ "outputId": "e6542f82-66e4-4043-8b3c-3837ae031505"
937
+ },
938
+ "execution_count": null,
939
+ "outputs": [
940
+ {
941
+ "output_type": "stream",
942
+ "name": "stdout",
943
+ "text": [
944
+ "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
945
+ "Requirement already satisfied: tensorrt in /usr/local/lib/python3.7/dist-packages (8.5.1.7)\n",
946
+ "Collecting onnx\n",
947
+ " Downloading onnx-1.12.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.1 MB)\n",
948
+ "\u001b[K |████████████████████████████████| 13.1 MB 24.5 MB/s \n",
949
+ "\u001b[?25hRequirement already satisfied: nvidia-cudnn-cu11 in /usr/local/lib/python3.7/dist-packages (from tensorrt) (8.6.0.163)\n",
950
+ "Requirement already satisfied: nvidia-cublas-cu11 in /usr/local/lib/python3.7/dist-packages (from tensorrt) (11.11.3.6)\n",
951
+ "Requirement already satisfied: nvidia-cuda-runtime-cu11 in /usr/local/lib/python3.7/dist-packages (from tensorrt) (11.8.89)\n",
952
+ "Requirement already satisfied: numpy>=1.16.6 in /usr/local/lib/python3.7/dist-packages (from onnx) (1.21.6)\n",
953
+ "Requirement already satisfied: typing-extensions>=3.6.2.1 in /usr/local/lib/python3.7/dist-packages (from onnx) (4.1.1)\n",
954
+ "Requirement already satisfied: protobuf<=3.20.1,>=3.12.2 in /usr/local/lib/python3.7/dist-packages (from onnx) (3.19.6)\n",
955
+ "Installing collected packages: onnx\n",
956
+ "Successfully installed onnx-1.12.0\n"
957
+ ]
958
+ }
959
+ ]
960
+ },
961
+ {
962
+ "cell_type": "markdown",
963
+ "source": [
964
+ "### Export the model with tensorrt"
965
+ ],
966
+ "metadata": {
967
+ "id": "I2u6Xn72eEBE"
968
+ }
969
+ },
970
+ {
971
+ "cell_type": "code",
972
+ "source": [
973
+ "!python scripts/export-tensorrt-model.py --device 0 --half"
974
+ ],
975
+ "metadata": {
976
+ "colab": {
977
+ "base_uri": "https://localhost:8080/"
978
+ },
979
+ "id": "S57JsLacdnoF",
980
+ "outputId": "429a5090-4b27-439f-cdb2-d3fe952b9d71"
981
+ },
982
+ "execution_count": null,
983
+ "outputs": [
984
+ {
985
+ "output_type": "stream",
986
+ "name": "stdout",
987
+ "text": [
988
+ "\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",
989
+ "YOLOv5 🚀 2022-11-21 Python-3.7.15 torch-1.12.1+cu113 CUDA:0 (Tesla T4, 15110MiB)\n",
990
+ "\n",
991
+ "\n",
992
+ "\u001b[34m\u001b[1mONNX:\u001b[0m starting export with onnx 1.12.0...\n",
993
+ "\u001b[34m\u001b[1mONNX:\u001b[0m export success ✅ 52.5s, saved as weights/pose_higher_hrnet_w32_512.onnx (109.3 MB)\n",
994
+ "\n",
995
+ "\u001b[34m\u001b[1mTensorRT:\u001b[0m starting export with TensorRT 8.5.1.7...\n",
996
+ "[11/21/2022-23:54:02] [TRT] [I] [MemUsageChange] Init CUDA: CPU +0, GPU +0, now: CPU 0, GPU 1572 (MiB)\n",
997
+ "[11/21/2022-23:54:05] [TRT] [I] [MemUsageChange] Init builder kernel library: CPU +0, GPU +74, now: CPU 0, GPU 1646 (MiB)\n",
998
+ "[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",
999
+ "scripts/export-tensorrt-model.py:132: DeprecationWarning: Use set_memory_pool_limit instead.\n",
1000
+ " config.max_workspace_size = workspace * 1 << 30\n",
1001
+ "[11/21/2022-23:54:05] [TRT] [I] ----------------------------------------------------------------\n",
1002
+ "[11/21/2022-23:54:05] [TRT] [I] Input filename: weights/pose_higher_hrnet_w32_512.onnx\n",
1003
+ "[11/21/2022-23:54:05] [TRT] [I] ONNX IR version: 0.0.7\n",
1004
+ "[11/21/2022-23:54:05] [TRT] [I] Opset version: 12\n",
1005
+ "[11/21/2022-23:54:05] [TRT] [I] Producer name: pytorch\n",
1006
+ "[11/21/2022-23:54:05] [TRT] [I] Producer version: 1.12.1\n",
1007
+ "[11/21/2022-23:54:05] [TRT] [I] Domain: \n",
1008
+ "[11/21/2022-23:54:05] [TRT] [I] Model version: 0\n",
1009
+ "[11/21/2022-23:54:05] [TRT] [I] Doc string: \n",
1010
+ "[11/21/2022-23:54:05] [TRT] [I] ----------------------------------------------------------------\n",
1011
+ "[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",
1012
+ "\u001b[34m\u001b[1mTensorRT:\u001b[0m input \"images\" with shape(1, 3, 512, 960) DataType.FLOAT\n",
1013
+ "\u001b[34m\u001b[1mTensorRT:\u001b[0m output \"output0\" with shape(1, 34, 128, 240) DataType.FLOAT\n",
1014
+ "\u001b[34m\u001b[1mTensorRT:\u001b[0m output \"output1\" with shape(1, 17, 256, 480) DataType.FLOAT\n",
1015
+ "\u001b[34m\u001b[1mTensorRT:\u001b[0m building FP16 engine as weights/pose_higher_hrnet_w32_512.engine\n",
1016
+ "scripts/export-tensorrt-model.py:159: DeprecationWarning: Use build_serialized_network instead.\n",
1017
+ " with builder.build_engine(network, config) as engine, open(f, 'wb') as t:\n",
1018
+ "[11/21/2022-23:54:10] [TRT] [I] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 0, GPU 1654 (MiB)\n",
1019
+ "[11/21/2022-23:54:10] [TRT] [I] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 0, GPU 1662 (MiB)\n",
1020
+ "[11/21/2022-23:54:10] [TRT] [W] TensorRT was linked against cuDNN 8.6.0 but loaded cuDNN 8.3.2\n",
1021
+ "[11/21/2022-23:54:10] [TRT] [I] Local timing cache in use. Profiling results in this builder pass will not be stored.\n",
1022
+ "[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",
1023
+ "[11/22/2022-00:00:29] [TRT] [I] Total Activation Memory: 1602586624\n",
1024
+ "[11/22/2022-00:00:29] [TRT] [I] Detected 1 inputs and 2 output network tensors.\n",
1025
+ "[11/22/2022-00:00:30] [TRT] [I] Total Host Persistent Memory: 930704\n",
1026
+ "[11/22/2022-00:00:30] [TRT] [I] Total Device Persistent Memory: 3670528\n",
1027
+ "[11/22/2022-00:00:30] [TRT] [I] Total Scratch Memory: 0\n",
1028
+ "[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",
1029
+ "[11/22/2022-00:00:30] [TRT] [I] [BlockAssignment] Started assigning block shifts. This will take 341 steps to complete.\n",
1030
+ "[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",
1031
+ "[11/22/2022-00:00:30] [TRT] [I] Total Activation Memory: 51609600\n",
1032
+ "[11/22/2022-00:00:30] [TRT] [W] TensorRT encountered issues when converting weights between types and that could affect accuracy.\n",
1033
+ "[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",
1034
+ "[11/22/2022-00:00:30] [TRT] [W] Check verbose logs for the list of affected weights.\n",
1035
+ "[11/22/2022-00:00:30] [TRT] [W] - 317 weights are affected by this issue: Detected subnormal FP16 values.\n",
1036
+ "[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",
1037
+ "[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",
1038
+ "\u001b[34m\u001b[1mTensorRT:\u001b[0m export success ✅ 440.8s, saved as weights/pose_higher_hrnet_w32_512.engine (56.9 MB)\n",
1039
+ "\n",
1040
+ "Export complete (446.1s)\n"
1041
+ ]
1042
+ }
1043
+ ]
1044
+ },
1045
+ {
1046
+ "cell_type": "markdown",
1047
+ "source": [
1048
+ "### Test the tensorrt model"
1049
+ ],
1050
+ "metadata": {
1051
+ "id": "npgGj4cGemZd"
1052
+ }
1053
+ },
1054
+ {
1055
+ "cell_type": "code",
1056
+ "source": [
1057
+ "!python scripts/live-demo.py --enable_tensorrt --filename=WeAreGoingOnBullrun.mp4 --hrnet_weights='weights/pose_higher_hrnet_w32_512.engine' --save_video"
1058
+ ],
1059
+ "metadata": {
1060
+ "colab": {
1061
+ "base_uri": "https://localhost:8080/"
1062
+ },
1063
+ "id": "LnIpbqV0fVps",
1064
+ "outputId": "fce1e062-c975-421a-be89-51c533f2f879"
1065
+ },
1066
+ "execution_count": null,
1067
+ "outputs": [
1068
+ {
1069
+ "output_type": "stream",
1070
+ "name": "stdout",
1071
+ "text": [
1072
+ "\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",
1073
+ "[11/22/2022-00:02:20] [TRT] [I] Loaded engine size: 56 MiB\n",
1074
+ "[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",
1075
+ "[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",
1076
+ "[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",
1077
+ "/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",
1078
+ " y = (ind // w).long()\n",
1079
+ "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",
1080
+ " index = index // dim\n",
1081
+ "framerate: 23.412900 fps / detected people: 0 \n",
1082
+ "Time elapsed == 134.7310082912445\n"
1083
+ ]
1084
+ }
1085
+ ]
1086
+ },
1087
+ {
1088
+ "cell_type": "markdown",
1089
+ "source": [
1090
+ "Now check out the video output.avi\n"
1091
+ ],
1092
+ "metadata": {
1093
+ "id": "WbQk0PeNnM5-"
1094
+ }
1095
+ }
1096
+ ]
1097
+ }
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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ all_model_checkpoint_paths: "/home/cv/YuSun/algorithms/human_pose_detection/HR_Net/models/epoch4.ckpt-945880"
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