Refine doc (open-mmlab#3388)

* Refine docs and fix format issues

* reformat

* fix mock

* Refine format

* Reorganize tutorials

* Update install doc

* resolve comments

docs/install.md

@@ -9,7 +9,6 @@
 - GCC 5+
 - [mmcv](https://github.com/open-mmlab/mmcv)
 
-
 ### Install mmdetection
 
 a. Create a conda virtual environment and activate it.
@@ -54,17 +53,33 @@ pip install mmcv-full==latest+torch1.5.0+cu101 -f https://openmmlab.oss-accelera
 See [here]((https://github.com/open-mmlab/mmcv#install-with-pip)) for different versions of MMCV compatible to different PyTorch and CUDA versions.
 Optionally you can choose to compile mmcv from source by the following command
 
-```
+```shell
 git clone https://github.com/open-mmlab/mmcv.git
 cd mmcv
 MMCV_WITH_OPS=1 pip install -e .  # package mmcv-full will be installed after this step
 cd ..
 ```
+
 Or directly run
-```python
+
+```shell
 pip install mmcv-full
 ```
-**Important**: You need to run `pip unisntall mmcv` first if you have mmcv installed.
+
+**Important**:
+
+1. The required versions of MMCV for different versions of MMDetection since V2.0 are as below. Please install the correct version of MMCV to avoid installation issues.
+
+| MMDetection version |    MMCV version     |
+|:-------------------:|:-------------------:|
+| master              | mmcv-full>=1.0.2    |
+| 2.3.0rc0            | mmcv-full>=1.0.2    |
+| 2.2.1               | mmcv==0.6.2         |
+| 2.2.0               | mmcv==0.6.2         |
+| 2.1.0               | mmcv>=0.5.9, <=0.6.1|
+| 2.0.0               | mmcv>=0.5.1, <=0.5.8|
+
+2. You need to run `pip unisntall mmcv` first if you have mmcv installed.
 If mmcv and mmcv-full are both installed, there will be `ModuleNotFoundError`.
 
 d. Clone the mmdetection repository.
@@ -85,7 +100,7 @@ pip install -v -e .  # or "python setup.py develop"
 
 If you build mmdetection on macOS, replace the last command with
 
-```
+```shell
 CC=clang CXX=clang++ CFLAGS='-stdlib=libc++' pip install -e .
 ```
 
@@ -96,7 +111,7 @@ It is recommended that you run step d each time you pull some updates from githu
 
     > Important: Be sure to remove the `./build` folder if you reinstall mmdet with a different CUDA/PyTorch version.
 
-    ```
+    ```shell
     pip uninstall mmdet
     rm -rf ./build
     find . -name "*.so" | xargs rm
@@ -110,6 +125,7 @@ you can install it before installing MMCV.
 4. Some dependencies are optional. Simply running `pip install -v -e .` will only install the minimum runtime requirements. To use optional dependencies like `albumentations` and `imagecorruptions` either install them manually with `pip install -r requirements/optional.txt` or specify desired extras when calling `pip` (e.g. `pip install -v -e .[optional]`). Valid keys for the extras field are: `all`, `tests`, `build`, and `optional`.
 
 ### Install with CPU only
+
 The code can be built for CPU only environment (where CUDA isn't available).
 
 In CPU mode you can run the demo/webcam_demo.py for example.
@@ -169,3 +185,35 @@ To use the default MMDetection installed in the environment rather than that you
 ```shell
 PYTHONPATH="$(dirname $0)/..":$PYTHONPATH
 ```
+
+### Common issues
+
+We list some common issues and their corresponding solutions here. Feel free to enrich the list if you find any frequent issues and have ways to help others to solve them.
+
+<details>
+<summary>
+Compatibility issue between MMCV and MMDetection; "ConvWS is already registered in conv layer";
+</summary>
+    Please install the correct version of MMCV for the version of your MMDetection following the instruction above.
+</details>
+
+<details>
+<summary>
+"No module named 'mmcv.ops'"; "No module named 'mmcv._ext'".
+</summary>
+
+1. Uninstall existing mmcv in the environment using `pip uninstall mmcv`.
+2. Install mmcv-full following the instruction above.
+
+</details>
+
+<details>
+<summary>
+"invalid device function" or "no kernel image is available for execution".
+</summary>
+
+1. Check the CUDA compute capability of you GPU.
+2. Run `python mmdet/utils/collect_env.py` to check whether PyTorch, torchvision, and MMCV are built for the correct GPU architecture. You may need to set `TORCH_CUDA_ARCH_LIST` to reinstall MMCV. The compatibility issue could happen when using old GPUS, e.g., Tesla K80 (3.7) on colab.
+3. Check whether the running environment is the same as that when mmcv/mmdet is compiled. For example, you may compile mmcv using CUDA 10.0 bug run it on CUDA9.0 environments.
+
+</details>