[Documentation] add ncnn backend docs (open-mmlab#122)

* add ncnn backend docs

* remove fix version

* reply for code review

docs/backends/ncnn.md

@@ -1,3 +1,65 @@
 ## ncnn Support
 
 ### Installation
+
+#### Install ncnn
+
+- Download VulkanTools for the compilation of ncnn.
+    ```bash
+    wget https://sdk.lunarg.com/sdk/download/1.2.176.1/linux/vulkansdk-linux-x86_64-1.2.176.1.tar.gz?Human=true -O vulkansdk-linux-x86_64-1.2.176.1.tar.gz
+    tar -xf vulkansdk-linux-x86_64-1.2.176.1.tar.gz
+    export VULKAN_SDK=$(pwd)/1.2.176.1/x86_64
+- Check your gcc version.
+You should ensure your gcc satisfies `gcc >= 6`.
+- Prepare ncnn Framework
+
+    - Download ncnn source code
+        ```bash
+        git clone git@github.com:Tencent/ncnn.git
+        ```
+    - <font color=red>Make install</font> ncnn library
+        ```bash
+        cd ncnn
+        mkdir build
+        cmake -DNCNN_VULKAN=ON -DNCNN_SYSTEM_GLSLANG=ON -DNCNN_BUILD_EXAMPLES=ON -DNCNN_PYTHON=ON -DNCNN_BUILD_TOOLS=ON -DNCNN_BUILD_BENCHMARK=ON -DNCNN_BUILD_TESTS=ON ..
+        make install
+        ```
+    - Install pyncnn module
+        ```bash
+        cd ncnn/python
+        pip install .
+        ```
+
+#### Build custom ops
+
+Some custom ops are created to support models in OpenMMLab, the custom ops can be built as follows:
+
+```bash
+cd ${MMDEPLOY_DIR}
+mkdir build
+cd build
+cmake -DBUILD_NCNN_OPS=ON ..
+make -j$(nproc)
+```
+
+If you haven't installed NCNN in default path, please add `-DNCNN_DIR` flag in cmake.
+
+```bash
+ cmake -DBUILD_NCNN_OPS=ON -DNCNN_DIR=${NCNN_DIR} ..
+ make -j$(nproc)
+```
+
+### Convert model
+- This follows the tutorial on [How to convert model](tutorials/how_to_convert_model.md).
+- The converted model has two files: `.param` and `.bin`, as model structure file and weight file respectively.
+
+### FAQs
+1. When running ncnn models for inference with custom ops, it fails and shows the error message like:
+
+    ```
+    TypeError: register mm custom layers(): incompatible function arguments. The following argument types are supported:
+        1.(ar0: ncnn:Net) -> int
+
+    Invoked with: <ncnn.ncnn.Net object at 0x7f7fc4038bb0>
+    ```
+    This is because of the failure to bind ncnn C++ library to pyncnn. You should build pyncnn from C++ ncnn source code, but not by `pip install`