add install guide, etc.

wang-xinyu · wang-xinyu · commit 555d90150f96 · 2020-10-12T11:55:23.000+08:00
diff --git a/README.md b/README.md
@@ -25,6 +25,7 @@ All the models are implemented in pytorch or mxnet first, and export a weights f
 
 ## Tutorials
 
+- [Install the dependencies.](./tutorials/install.md)
 - [A guide for quickly getting started, taking lenet5 as a demo.](./tutorials/getting_started.md)
 - [Frequently Asked Questions (FAQ)](./tutorials/faq.md)
 - [Migrating from TensorRT 4 to 7](./tutorials/migrating_from_tensorrt_4_to_7.md)
diff --git a/tutorials/faq.md b/tutorials/faq.md
@@ -4,6 +4,8 @@
 
 `NvInfer.h` is one of the headers of TensorRT. If you install the tensorrt DEB package, the headers should in `/usr/include/x86_64-linux-gnu/`. If you install tensorrt TAR or ZIP file, the `include_directories` and `link_directories` of tensorrt should be added in `CMakeLists.txt`.
 
+`dpkg -L` can print out the contents of a DEB package.
+
 ```
 $ dpkg -L libnvinfer-dev 
 /.
diff --git a/tutorials/install.md b/tutorials/install.md
@@ -0,0 +1,57 @@
+# Install the dependencies of tensorrtx
+
+## Ubuntu
+
+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.
+
+It is strongly recommended to use `apt` to manage software in Ubuntu.
+
+### 1. Install CUDA
+
+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.
+
+Then follow the installation instructions.
+
+```
+sudo dpkg -i cuda-repo-ubuntu1604-10-0-local-10.0.130-410.48_1.0-1_amd64.deb
+sudo apt-key add /var/cuda-repo-<version>/7fa2af80.pub
+sudo apt-get update
+sudo apt-get install cuda
+```
+
+### 2. Install TensorRT
+
+Go to [nvidia-tensorrt-7x-download](https://developer.nvidia.com/nvidia-tensorrt-7x-download). You might need login.
+
+Choose TensorRT 7.0 and `TensorRT 7.0.0.11 for Ubuntu 1604 and CUDA 10.0 DEB local repo packages`
+
+Install with following commands, after `apt install tensorrt`, it will automatically install cudnn, nvinfer, nvinfer-plugin, etc.
+
+```
+sudo dpkg -i nv-tensorrt-repo-ubuntu1604-cuda10.0-trt7.0.0.11-ga-20191216_1-1_amd64.deb
+sudo apt update
+sudo apt install tensorrt
+```
+
+### 3. Install OpenCV
+
+```
+sudo add-apt-repository ppa:timsc/opencv-3.3
+sudo apt-get update
+sudo apt install libopencv-dev
+```
+
+### 4. Check your installation
+
+```
+dpkg -l | grep cuda
+dpkg -l | grep nvinfer
+dpkg -l | grep opencv
+```
+
+### 5. Run tensorrtx
+
+It is recommanded to go through the [getting started guide, lenet5 as a demo.](./tutorials/getting_started.md) first.
+
+But if you are proficient in tensorrt, please check the readme of the model you want directly.
+
diff --git a/yolov5/CMakeLists.txt b/yolov5/CMakeLists.txt
@@ -13,16 +13,13 @@ find_package(CUDA REQUIRED)
 set(CUDA_NVCC_PLAGS ${CUDA_NVCC_PLAGS};-std=c++11;-g;-G;-gencode;arch=compute_30;code=sm_30)
 
 include_directories(${PROJECT_SOURCE_DIR}/include)
-if (CMAKE_SYSTEM_PROCESSOR MATCHES "aarch64")
-    message("embed_platform on")
-    include_directories(/usr/local/cuda/targets/aarch64-linux/include)
-    link_directories(/usr/local/cuda/targets/aarch64-linux/lib)
-else()
-    message("embed_platform off")
-    include_directories(/usr/local/cuda/include)
-    link_directories(/usr/local/cuda/lib64)
-endif()
-
+# include and link dirs of cuda and tensorrt, you need adapt them if yours are different
+# cuda
+include_directories(/usr/local/cuda/include)
+link_directories(/usr/local/cuda/lib64)
+# tensorrt
+include_directories(/usr/include/x86_64-linux-gnu/)
+link_directories(/usr/lib/x86_64-linux-gnu/)
 
 set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -Wall -Ofast -Wfatal-errors -D_MWAITXINTRIN_H_INCLUDED")
 
