add dockerfile trt8_cuda11 (#1010)

* add dockerfile trt8_cuda11

* update docker readme

docker/trt8/Dockerfile

@@ -0,0 +1,4 @@
+ARG TENSORRT="8"
+ARG CUDA="11"
+
+FROM hakuyyf/tensorrtx:trt${TENSORRT}_cuda${CUDA}

docker/trt8/README.md

@@ -0,0 +1,30 @@
+# Tutorials
+
+## Pull docker image And build opencv with dnn module from source
+- docker pull hakuyyf/tensorrtx:trt8_cuda11
+- sudo docker run -it --name={yourname} --gpus all --privileged --net=host --ipc=host --pid=host -v {localpath}:{dockerpath} hakuyyf/tensorrtx:trt8_cuda11 /bin/bash
+- docker start {container_id}
+- docker attach {container_id}
+- apt update
+- cd /home
+- git clone https://github.com/opencv/opencv.git
+- git clone https://github.com/opencv/opencv_contrib.git
+- cd opencv
+- git checkout 4.5.5
+- cd ../
+- cd opencv_contrib
+- git checkout 4.5.5
+- cd ../
+- cd opencv
+- mkdir build && cd build
+- cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D INSTALL_PYTHON_EXAMPLES=ON -D INSTALL_C_EXAMPLES=OFF -D OPENCV_ENABLE_NONFREE=ON -D WITH_CUDA=ON -D WITH_CUDNN=ON -D OPENCV_DNN_CUDA=ON -D ENABLE_FAST_MATH=1 -D CUDA_FAST_MATH=1 -D CUDA_ARCH_BIN={[Your GPU Compute Capability](https://developer.nvidia.com/zh-cn/cuda-gpus#compute)} -D WITH_CUBLAS=1 -D OPENCV_EXTRA_MODULES_PATH=/home/opencv_contrib/modules/ -D HAVE_opencv_python3=ON -D PYTHON_EXECUTABLE=/usr/bin/python3 -D BUILD_EXAMPLES=ON ..
+- make -j
+- make install
+- ldconfig
+- ln -s /usr/local/lib/python3.8/site-packages/cv2/python-3.8/cv2.cpython-38-x86_64-linux-gnu.so /usr/lib/python3.8/cv2.so
+
+## Test
+- cd /home
+- python3 -c "import cv2; print(cv2.__version__)"
+- git clone https://github.com/wang-xinyu/tensorrtx.git
+