update document and some words in scripts

Signed-off-by: roger mao <[email protected]>

Author: maozhong1

doc/CONTRIBUTING.md

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+We welcome community contributions to SVET sample application. Thank you for your time!
+
+Please note that review and merge might take some time at this point.
+
+SVET sample application is licensed under MIT license. By contributing to the project, you agree to the license and copyright terms therein and release your contribution under these terms.
+
+Steps:
+ - In the commit message, explain what bug is fixed or what new feature is added in details.
+ - Validate that your changes don't break a build. [build instruction](../README.md#how-to-build)
+ - Pass [testing](#testing)
+ - Wait while your patchset is reviewed and tested by our internal validation cycle
+
+# Testing
+
+## Requirements
+
+Hardware Requirements: Coffee Lake or Whiskey Lake
+Software Requirements: Ubuntu 18.04, MediaSDK 19.4.0 and OpenVINO 2019 R3 
+
+## How to test your changes
+
+### 1. Build the SVET sample applicaton
+
+```sh
+./build_and_install.sh
+```
+Apply the changes to MediaSDK/samples/video_e2e_sample/. Then build video_e2e_sample:
+```sh
+cp msdk_build.sh MediaSDK
+cd MediaSDK
+./msdk_build.sh
+```
+
+### 2. Run tests to make sure below tests can run without error 
+
+Simple display test:
+```sh
+./bin/video_e2e_sample -par par_file/par_file_name.par
+```
+Basic video decoding and inference tests:
+n16_1080p_1080p_dp_noinfer.par
+n16_1080p_1080p_dp.par
+n16_1080p_4k_dp.par
+n4_1080p_1080p_dp.par
+n4_vehical_detect_1080p.par
+n64_d1_1080p_dp.par
+
+RTSP play and saving tests:
+rtsp_dump_only.par
+n16_1080p_rtsp_simu.pa
+n4_1080p_rtsp_simu_dp.par
+n16_1080p_rtsp_simu_dump.par
+
+Multiple display tests:
+```sh
+./bin/video_e2e_sample -par par_file/n16_1080p_1080p_dp_noinfer.par -par par_file/n16_1080p_1080p_dp.par
+```
+ 

doc/FAQ.md

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+# Frequently asked questions (SVET sample application)
+
+## Where can I find the descritpion of options used in par file?
+See chapter 2.4 in doc/svet_sample_application_user_guide_2020.1.0.pdf
+Running the SVET sample applicton with option "-?" can show the usage of options.
+
+## Why does the system need to be switched to text mode before running the sample application
+The sample application uses libDRM to render the video directly to display, so it needs to act as master of the DRM display, which isn't allowed when X server is running. 
+If the par file doesn't include display session, there is no need to switch to text mode.
+
+## Why it needs "su -p" to switch to root user before running the sample application
+To become DRM master, it needs root privileges. With option "-p", it will preserve environment variables, like LIBVA_DRIVERS_PATH, LIBVA_DRIVER_NAME and LD_LIBRARY_PATH. If without "-p", these environment variables will be reset and the sample application will run into problems.
+
+## The loading time of 16-channel face detection demo is too long
+Please enable cl_cache by running command "export cl_cache_dir=/tmp/cl_cache" and "mkdir -p /tmp/cl_cache". Then after the first running of 16-channel face detection demo, the compiled OpenCL kernles are cached and the model loading time of next runnings of 16-channel face detection demo will only take about 10 seconds.
+More details about cl_cache can be found at https://github.com/intel/compute-runtime/blob/master/opencl/doc/FAQ.md
+
+## Can sources number for "-vpp_comp_only" or "-vpp_comp" be different from number of decoding sessions?  
+No. The sources number for "-vpp_comp_only" or "-vpp_comp" must be equal to the numer of decoding sessions. Otherwise, the sample application will fail during pipeline initialization or running. 
+
+## How to limit the fps of whole pipeline to 30?
+Add "-fps 30" to every decoding session.
+
+## How to limit the frame number of input to 1000?
+Add "-n 1000" to every decoding dessions. However this option won't work if both "-vpp_comp_only" and "-vpp_comp" are set.
+
+## Where can I find tutorials for inference engine?
+Please refer to https://docs.openvinotoolkit.org/latest/_docs_IE_DG_Deep_Learning_Inference_Engine_DevGuide.html
+
+## Where can I find information for the models?
+Please refer to https://github.com/opencv/open_model_zoo/tree/master/models/intel. The names of models used in sample application are
+face-detection-retail-0004, human-pose-estimation-0001, vehicle-attributes-recognition-barrier-0039, vehicle-license-plate-detection-barrier-0106.
+
+## Can I use other OpenVINO version rather than 2019 R3?
+Yes, but you have to modify some code due to interfaces changing. And also you need to download the IR files and copy them to ./model manually. Please refer to script/download_and_copy_models.sh for how to download the IR files.