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AdMiRe EPFL

Currently, TV audiences can only interact with the shows they are watching through social media or hybrid broadcast broadband TV. Additionally, content creators in film, TV or live productions face technical challenges that result in less engaging content. The EU-funded AdMiRe project aims to tackle both these problems by developing, validating and demonstrating innovative solutions based on mixed reality technology. These solutions will enable audiences at home to be incorporated into the live TV programme they are watching and to interact with people in the TV studio. They will also provide content creators with tools that radically improve talent immersion and interaction with computer-generated elements.

This repository contains the result of EPFL's contribution to the project, i.e the Background Extraction and Super Resolution modules, with input and output as NDI streams.

Table of contents

Requirements

Operating System: Windows 10 64-bit

Graphics card: NVIDIA® GeForce RTX® 20XX and 30XX Series, Quadro RTX™ 3000, TITAN RTX™, or higher (any NVIDIA GPUs with Tensor Cores)

Installation

1. Visual Studio 2017

Download Visual Studio 2017 here (it might ask you to connect with your Microsoft account).

Desktop development with C++ is the only required checkbox [x]

2. NVIDIA Maxine Video Effects SDK

Install the requirements:

Download the NVIDIA Maxine Video Effects SDK here

Follow the instructions on NVIDIA Maxine Video Effects' documentation

Don't forget to:

  • Rename the folder MAXINE-VFX-SDK-master-OSS and move it to C:/Users/[username]/
  • Install the SDK installer (this was specified in their github repository)
  • [CMake] click "Configure", check the "Install SDK" box, click "Generate" and select:
    1. Visual Studio 2017
    2. x64
  • [Visual Studio 2017] Make sure that you are building the Release version (and not the Debug one)
  • [Visual Studio 2017 - if needed] Wait for the error containing the link and add the h264 dll file to the Release folder, alongside the executables

[WARNING] You cannot build anything until you have finished the installation of OpenCV (see below). So leave this window open and continue the installation process. We explain everything in the last section, 7. Final Steps.

3. Python and dependencies

  1. Install Miniconda
  2. Run conda init in the terminal, close the terminal and reopen it to take the changes into account
  3. Run conda install pytorch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0 cudatoolkit=11.3 -c pytorch to install a compatible version of pytorch
  4. Run pip install -r requirements.txt to install the required dependencies

4. GStreamer

  1. Download and run both the runtime and the development installers, and select complete installation for both
  2. Add the bin and the lib folders (inside the GStreamer folder) to the PATH
  3. Add an enviroment variable called GSTREAMER_DIR with the path to GStreamer (usually C:/gstreamer or D:/gstreamer)

Run the following command to make sure that GStreamer works properly:

gst-launch-1.0 -v videotestsrc ! autovideosink

5. NDI plugin for GStreamer

  1. Clone gst-plugin-ndi inside C:/Users/[username] for example
  2. Download and install Rust from here
  3. If not already installed, install the regular (not advanced) NDI sdk
  4. Copy .dll and .lib files from Bin and Lib folder of the NDI sdk installation path to gst-plugin-ndi folder
  5. Run cargo build --release from the git repository folder (C:/Users/[username]/gst-plugin-ndi/ for example)
  6. Move the NDI SDK .dll and .lib files from C:/Program Files/NDI/NDI 5 SDK/Bin and C:/Program Files/NDI/NDI 5 SDK/Lib to .../gst-plugin-ndi/target/release
  7. Add the release folder to the PATH
  8. Add the release folder as an environment variable called GST_PLUGIN_PATH
  9. Run gst-inspect-1.0.exe ndisrc, gst-inspect-1.0.exe ndisink and gst-inspect-1.0.exe ndi to make sure the plugin was correctly installed. These commands should output details about the GStreamer elements.

6. OpenCV 3.4.6

  1. Download the source code for OpenCV 3.4.6, unzip it, and put it inside C:/Users/[username] for example
  2. Run CMake, specify the path to the OpenCV folder as the source, the build folder as the output, and click Configure
  3. Check that GStreamer is found (there should be a list of paths appearing next to GStreamer elements), and that the WITH_GSTREAMER box is ticked
  4. Tick the OPENCV_PYTHON3_VERSION box
  5. Tick the BUILD_opencv_world box
  6. Click Generate
  7. Open the solution file located in the build folder
  8. Make sure that Release is selected on top (not Debug)
  9. Rebuild (and wait, this can take from several minutes to 1 hour depending on your computer)

7. Final steps

  1. Run git clone https://github.com/mmspg/AdMiRe_EPFL.git in the folder of your choice

  2. Open the Visual Studio 2017 solution file from the NVIDIA MAxine Video Effects SDK Release folder

  3. Remove the AigsEffectApp.cpp from the AigsEffectApp/Source Files folder in Visual Studio 2017 (right menu)

  4. Remove the VideoEffectsApp.cpp from the VideoEffectsApp/Source Files folder in Visual Studio 2017 (right menu)

  5. Copy the AigsEffectApp.cpp and VideoEffectsApp.cpp files located in the NVIDIA_Maxine_modules folder of this repository to the AigsEffectApp/Source Files and VideoEffectsApp/Source Files directories respectively, in Visual Studio 2017 (right menu). This will link the .cpp files of this repo to the Visual Studio 2017 solution project.

  6. Right-click on AigsEffectApp and Rebuild

  7. Right-click on VideoEffectsApp and Rebuild

  8. Install NDI Tools here

General installation advices:

  • [CMake] Make sure to delete the cache and/or delete the build folder before configurating if needed.

Usage

Once you have installed everything, you should be able to run our pipelines.

First, make sure that you have an NDI stream to provide as input. If you need to create one, you can simply use the Screen Capture application shipped with NDI Tools. To do so, open the application, right-click on its icon in the taskbar and select Webcam Video Source > [YOUR VIDEO INPUT].

You can check that your computer indeed receives the NDI stream of interest with the Studio Monitor application shipped with NDI Tools.

Once you made sure that you are receiving an NDI stream, open the Webcam Input application shipped with NDI Tools, right-click on its icon in the taskbar and select [YOUR COMPUTER NAME] > [YOUR NDI STREAM]. Also, right-click on its icon in the taskbar and select Video > 720p30. This will turn the stream into a 720p/30fps virtual webcam. This step is required in order for our pipeline to handle dynamic changes in resolution or aspect-ratio.

Powershell pipelines

The PowerShell pipelines are located in src/powershell_pipelines. Here is the list of pipelines and their goal:

BE = Background Extraction

SR = Super-Resolution

  • pipeline_MODNet_nvidiaMaxineSR.ps1 - webcam -> MODNet BE -> UDP link -> NVIDIA Maxine SR -> NDI stream
  • pipeline_byteDanceRvmBE_nvidiaMaxineSR.ps1 - webcam -> RVM BE -> UDP link -> NVIDIA Maxine SR -> NDI stream
  • pipeline_nvidiaMaxineBE.ps1 - webcam -> NVIDIA Maxine BE -> NDI stream
  • pipeline_nvidiaMaxineBE_SR.ps1 - webcam -> NVIDIA Maxine BE -> UDP link -> NVIDIA Maxine SR -> NDI stream
  • pipeline_nvidiaMaxineBE_SR_linkNDI.ps1 - webcam -> MODNet BE -> NDI link -> NVIDIA Maxine SR -> NDI stream
  • pipeline_nvidiaMaxineSR.ps1 - webcam -> NVIDIA Maxine SR -> NDI stream

Parameters:

  • index_val: The webcam index to use as input (default: 0)
  • comp_mode: The compositing mode (default: 2 (green screen)). See module_config_doc.md in src/helper for more information.
  • fps: The desired framerate (default: 25)
  • output: The output stream type, ndi or udp (default: ndi)

Usage:

  • Default parameters:
    • right-click on the selected pipeline - Run with PowerShell
  • Non-default parameters:
    • Open a Windows PowerShell window
    • Navigate to the powershell_pipelines folder
    • Run the PowerShell script with the desired parameters (see above).
    • Example: .\pipeline_nvidiaMaxineBE.ps1 -index_val=1 -comp_mode=7

After a few seconds, you should see something similar to the screenshot below.

Make sure that your new NDI stream was created, by using the Studio Monitor application.

HTTP server and client

A more user-friendly way to run the modules was implemented using an HTTP client/server communication.

1/ Run the HTTP server by typing on the command line python run_server.py

2/ Change src/helper/default_module_config.json to match the desired module choices and parameters for background extraction and/or super-resolution. A detailed explanation of this file is available at src/helper/module_config_doc.md.

3/ Run the HTTP client by typing on the command line python run_client.py

4/ Choose whether to START, STOP, or CHECK the modules using the client terminal output

Licenses

The GPL v3 License applies to the original source code from this project. The same License applies to files from the third party Robust Video Matting. The Apache-2.0 license applies to the third party code from MODNet.

Acknowledgement

The authors will like to acknowledge contributions from the H2020 Innovation Action "Advanced Mixed Realities (AdMiRe)" under grant agreement 952027. Valuable interactions and feedback received from project partners during integration, testing and validation of the modules reported in this paper are also acknowledged.

Collaborators