58 lines
1.7 KiB
Markdown
58 lines
1.7 KiB
Markdown
# Install the dependencies of tensorrtx
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## Ubuntu
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Ubuntu16.04 / cuda10.0 / cudnn7.6.5 / tensorrt7.0.0 / opencv3.3 would be the example, other versions might also work, just need you to try.
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It is strongly recommended to use `apt` to manage software in Ubuntu.
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### 1. Install CUDA
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Go to [cuda-10.0-download](https://developer.nvidia.com/cuda-10.0-download-archive). Choose `Linux` -> `x86_64` -> `Ubuntu` -> `16.04` -> `deb(local)` and download the .deb package.
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Then follow the installation instructions.
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```
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sudo dpkg -i cuda-repo-ubuntu1604-10-0-local-10.0.130-410.48_1.0-1_amd64.deb
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sudo apt-key add /var/cuda-repo-<version>/7fa2af80.pub
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sudo apt-get update
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sudo apt-get install cuda
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```
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### 2. Install TensorRT
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Go to [nvidia-tensorrt-7x-download](https://developer.nvidia.com/nvidia-tensorrt-7x-download). You might need login.
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Choose TensorRT 7.0 and `TensorRT 7.0.0.11 for Ubuntu 1604 and CUDA 10.0 DEB local repo packages`
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Install with following commands, after `apt install tensorrt`, it will automatically install cudnn, nvinfer, nvinfer-plugin, etc.
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```
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sudo dpkg -i nv-tensorrt-repo-ubuntu1604-cuda10.0-trt7.0.0.11-ga-20191216_1-1_amd64.deb
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sudo apt update
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sudo apt install tensorrt
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```
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### 3. Install OpenCV
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```
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sudo add-apt-repository ppa:timsc/opencv-3.3
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sudo apt-get update
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sudo apt install libopencv-dev
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```
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### 4. Check your installation
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```
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dpkg -l | grep cuda
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dpkg -l | grep nvinfer
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dpkg -l | grep opencv
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```
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### 5. Run tensorrtx
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It is recommanded to go through the [getting started guide, lenet5 as a demo.](https://github.com/wang-xinyu/tensorrtx/blob/master/tutorials/getting_started.md) first.
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But if you are proficient in tensorrt, please check the readme of the model you want directly.
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