diff --git a/README.md b/README.md
index 2229ff2fb..b8d221149 100755
--- a/README.md
+++ b/README.md
@@ -1,9 +1,13 @@
+
+ 
+
# ApraPipes
-A pipeline framework for developing video and image processing applications. Supports multiple GPUs and Machine Learning toolkits. More details can be found here https://apra-labs.github.io/ApraPipes.
+A pipeline framework for developing video and image processing applications. Supports multiple GPUs and Machine Learning toolkits.
+Learn more about ApraPipes here https://apra-labs.github.io/ApraPipes.
## Build status
-Automatically built and tested on Ubuntu 18.04, Jetson Boards and Windows 11 x64 Visual Studio 2017 Community (without CUDA)
+Aprapipes is automatically built and tested on Ubuntu (18.04 and 20.04), Jetson Boards (Jetpack 4.4) and Windows (11) x64 Visual Studio 2017 Community (without CUDA)
|OS|Version|With Cuda|Tests|Status|
|--|-------|---------|------|------|
|Windows|2019|No|[](https://gist.githubusercontent.com/kumaakh/f80af234a4aabedc69af3ee197f66944/raw/badge_Windows.svg)|[](https://github.com/Apra-Labs/ApraPipes/actions/workflows/CI-Win-NoCUDA.yml)|
@@ -14,19 +18,37 @@ Automatically built and tested on Ubuntu 18.04, Jetson Boards and Windows 11 x64
|Ubuntu x64_86-WSL|20.04|Yes|[](https://gist.githubusercontent.com/kumaakh/f80af234a4aabedc69af3ee197f66944/raw/badge_WSL.svg)|[](https://github.com/Apra-Labs/ApraPipes/actions/workflows/CI-Linux-CUDA-wsl.yml)|
|Ubuntu x64_86-docker|18.04|Yes|No|[](https://github.com/Apra-Labs/ApraPipes/actions/workflows/CI-Linux-CUDA-Docker.yml)|
+## Getting Started with ApraPipes
+
+ Please select your Operating System
+
+
-## Setup
+ * Note : Make sure to clone using recursive flag
+ ```
+ git clone --recursive https://github.com/Apra-Labs/ApraPipes.git
+ ```
-### Prerequisites for CUDA
-* Make account on developer.nvidia.com, else the next steps will show HTTP 404/403 errors
-* Download and install CUDA tool kit based on your OS: __Note: we test both with CUDA v10.2 and v11.7 so either is fine__
- * Ubuntu 18.04 : [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-10.2-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1804&target_type=debnetwork) or [CUDA Toolkit 11.7](https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu&target_version=18.04&target_type=deb_network)
- * Windows 10/11 : [Cuda Toolkit 10.2](https://developer.nvidia.com/cuda-10.2-download-archive?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal) or [CUDA Toolkit 11.7](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64)
-* Download [Cudnn](https://developer.nvidia.com/rdp/cudnn-archive#a-collapse765-102) and extract where cuda is installed. Note: this is a painful process. Here are the steps:
+Windows (Version ≥ 10)
+
+
+ Requirements
+
+ ### Cuda
+ * Create an account on developer.nvidia.com if you're not already a member. Note : Otherwise the next step will show HTTP 404/403 error.
+ * Windows 10/11 : [Cuda Toolkit 10.2](https://developer.nvidia.com/cuda-10.2-download-archive?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal) or [CUDA Toolkit 11.7](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64).
+
+ ### Cudnn
+ * Download [Cudnn](https://developer.nvidia.com/rdp/cudnn-archive#a-collapse765-102) and extract files where cuda is installed. Note: Please be aware that this process requires some effort. Here are the necessary steps:
* Download the correct tar/zip file matching your cuda version. _Do not download the exe/installer/deb package._
* Windows:
- * download [this file](https://developer.nvidia.com/compute/cudnn/secure/8.3.2/local_installers/10.2/cudnn-windows-x86_64-8.3.2.44_cuda10.2-archive.zip).
+ * Download [this file](https://developer.nvidia.com/compute/cudnn/secure/8.3.2/local_installers/10.2/cudnn-windows-x86_64-8.3.2.44_cuda10.2-archive.zip).
* Extract the downloaded file and copy files to ```C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.2``` using an __administrative command prompt__ as follows
```
cd .\extracted_folder
@@ -37,8 +59,87 @@ Automatically built and tested on Ubuntu 18.04, Jetson Boards and Windows 11 x64
cd ..\bin
copy *.dll "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.2\bin\"
```
- * Linux:
- * download [this file](https://developer.nvidia.com/compute/cudnn/secure/8.3.2/local_installers/10.2/cudnn-linux-x86_64-8.3.2.44_cuda10.2-archive.tar.xz)
+ ### Prerequisites
+ * Install Visual Studio 2019 Community
+ * Install Desktop development C++
+ * .NET Desktop development
+ * Universal Windows Development Platform
+ * Install choco:
+ Open Windows PowerShell as Administrator and run:
+ ```
+ Set-ExecutionPolicy AllSigned
+ Set-ExecutionPolicy Bypass -Scope Process -Force; [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072; iex ((New-Object System.Net.WebClient).DownloadString('https://chocolatey.org/install.ps1'))
+ ```
+ * Install build dependencies using choco:
+ ```
+ choco feature enable -n allowEmptyChecksums && choco install 7zip git python3 cmake pkgconfiglite -y && pip3 install ninja && pip3 install meson
+ ```
+ * Clone with submodules and LFS.
+ ```
+ git clone --recursive https://github.com/Apra-Labs/ApraPipes.git
+ ```
+
+
+
+
+ Build
+
+ ### Build Without Cuda
+ If your windows system does not have an NVIDIA GPU use this script
+ ```
+ build_windows_no_cuda.bat
+ ```
+ ### Build With Cuda
+ ```
+ build_windows_cuda.bat
+ ```
+
+
+
+
+ Test
+
+ ### Run Tests
+ * list all tests
+ ```
+ _build/BUILD_TYPE/aprapipesut.exe --list_content
+ ```
+ * run all tests
+ ```
+ _build/BUILD_TYPE/aprapipesut.exe
+ ```
+ * run all tests disabling memory leak dumps and better progress logging
+ ```
+ _build/BUILD_TYPE/aprapipesut.exe -p -l all --detect_memory_leaks=0
+ ```
+ * run one test
+ ```
+ _build/BUILD_TYPE/aprapipesut.exe --run_test=filenamestrategy_tests/boostdirectorystrategy
+ ```
+ * run one test with arguments
+ ```
+ _build/BUILD_TYPE/aprapipesut.exe --run_test=unit_tests/params_test -- -ip 10.102.10.121 -data ArgusCamera
+ ```
+ * Look at the unit_tests/params_test to check for sample usage of parameters in test code.
+
+
+
+
+Linux (Ubuntu ≥ 18.04)
+
+
+ Requirements
+
+ ### Cuda
+ * Create an account on developer.nvidia.com if you're not already a member. Note : Otherwise the next step will show HTTP 404/403 error.
+ * Ubuntu 18.04/20.04:
+ 18.04 - [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-10.2-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1804&target_type=debnetwork)
+ 20.04 - [CUDA Toolkit 11.7](https://developer.nvidia.com/cuda-11-7-0-download-archive?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu&target_version=20.04)
+
+ ### Cudnn
+ * Download [Cudnn](https://developer.nvidia.com/rdp/cudnn-archive#a-collapse765-102) and extract files where cuda is installed. Note: Please be aware that this process requires some effort. Here are the necessary steps:
+ * Linux:
+ * Download [this file](https://developer.nvidia.com/compute/cudnn/secure/8.3.2/local_installers/10.2/cudnn-linux-x86_64-8.3.2.44_cuda10.2-archive.tar.xz)
* extract the files
```
xz -d cudnn-linux-x86_64-8.3.2.44_cuda10.2-archive.tar.xz
@@ -50,104 +151,155 @@ Automatically built and tested on Ubuntu 18.04, Jetson Boards and Windows 11 x64
sudo cp -P include/* /usr/local/cuda/include/
sudo cp -P lib/* /usr/local/cuda/lib64/
```
-## Windows
-### Prerequisites
-* Install Visual Studio 2019 Community
- * Install Desktop development C++
- * .NET Desktop development
- * Universal Windows Development Platform
-* Install choco:
- Open Windows PowerShell as Administrator and run:
- ```
- Set-ExecutionPolicy AllSigned
- Set-ExecutionPolicy Bypass -Scope Process -Force; [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072; iex ((New-Object System.Net.WebClient).DownloadString('https://chocolatey.org/install.ps1'))
- ```
-* Install build dependencies using choco:
- ```
- choco feature enable -n allowEmptyChecksums && choco install 7zip git python3 cmake pkgconfiglite -y && pip3 install ninja && pip3 install meson
- ```
-* Clone with submodules and LFS.
- ```
- git clone --recursive https://github.com/Apra-Labs/ApraPipes.git
- ```
-
-### Build for windows
+
-#### Build Without Cuda
-If your windows machies does not have an NVIDIA GPU use this script
-```
-build_windows_no_cuda.bat
-```
-#### Build With Cuda
-```
-build_windows_cuda.bat
-```
-### Run Tests
-* list all tests
- ```
- _build/BUILD_TYPE/aprapipesut.exe --list_content
- ```
-* run all tests
- ```
- _build/BUILD_TYPE/aprapipesut.exe
- ```
-* run all tests disabling memory leak dumps and better progress logging
+
+ Build
+
+ * Run this command to make the script file executable.
```
- _build/BUILD_TYPE/aprapipesut.exe -p -l all --detect_memory_leaks=0
+ chmod +x build_linux_*.sh
```
-* run one test
+ ### Build Without Cuda
+ If your windows system does not have an NVIDIA GPU use this script
```
- _build/BUILD_TYPE/aprapipesut.exe --run_test=filenamestrategy_tests/boostdirectorystrategy
+ ./build_linux_no_cuda.sh
```
-* run one test with arguments
+ ### Build With Cuda
```
- _build/BUILD_TYPE/aprapipesut.exe --run_test=unit_tests/params_test -- -ip 10.102.10.121 -data ArgusCamera
+ ./build_linux_cuda.sh
```
- * Look at the unit_tests/params_test to check for sample usage of parameters in test code
-
-## Ubuntu 18.04 and 20.04 x64
-### Prerequisites
-* Run the following to get latest build tools
- ```
- sudo apt-get update && sudo apt-get -y install autoconf automake autopoint build-essential git-core git-lfs libass-dev libfreetype6-dev libgnutls28-dev libmp3lame-dev libsdl2-dev libtool libsoup-gnome2.4-dev libncurses5-dev libva-dev libvdpau-dev libvorbis-dev libxcb1-dev libxcb-shm0-dev libxcb-xfixes0-dev ninja-build pkg-config texinfo wget yasm zlib1g-dev nasm gperf bison curl zip unzip tar python3-pip flex && pip3 install meson
- ```
-* Note: start a new terminal as pip3 settings do not get effective on the same shell
-* CMake minimum version 3.24 - Follow [this article](https://anglehit.com/how-to-install-the-latest-version-of-cmake-via-command-line/) to update cmake
-* Clone with submodules and LFS.
- ```
- git clone --recursive https://github.com/Apra-Labs/ApraPipes.git
- ```
-
-
-### Build for linux
+ Build can take ~2 hours depending on the machine configuration.
+
-* ```chmod +x build_linux_*.sh```
-* ```./build_linux_x64.sh``` or ```./build_linux_no_cuda.sh``` depending on previous step. No Cuda as the name suggests will not build the Nvidia Cuda GPU Modules. Use this if there is no nvidia GPU present on your host
+
+ Test
-Build can take ~2 hours depending on the machine configuration.
+ ### Run Tests
+ * list all tests
+ ```
+ ./_build/aprapipesut --list_content
+ ```
+ * run all tests
+ ```
+ ./_build/aprapipesut
+ ```
+ * run all tests disabling memory leak dumps and better progress logging
+ ```
+ ./_build/aprapipesut -p -l all --detect_memory_leaks=0
+ ```
+ * run one test
+ ```
+ ./_build/aprapipesut --run_test=filenamestrategy_tests/boostdirectorystrategy
+ ```
+ * run one test with arguments
+ ```
+ ./_buildaprapipesut --run_test=unit_tests/params_test -- -ip 10.102.10.121 -data ArgusCamera
+ ```
+ * Look at the unit_tests/params_test to check for sample usage of parameters in test code.
+
-### Build and test using docker
+Jetson Boards - Nano, TX2, NX, AGX (Jetpack ≥ 4.4)
+
+
+ Requirements
+
+ ### Prerequisites
+ * Setup the board with [Jetpack 4.4](https://docs.nvidia.com/sdk-manager/install-with-sdkm-jetson/index.html) or higher as supported.
+ * Run the following commands to build required libraries.
+ ```
+ sudo apt-get update && sudo apt-get -y install git-lfs libncurses5-dev ninja-build nasm curl libudev-dev libssl-dev && sudo snap install cmake --classic
+ ```
+ * Append following lines to ~/.bashrc.
+ ```
+ export VCPKG_FORCE_SYSTEM_BINARIES=1
+ export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}
+ export LD_LIBRARY_PATH=/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
+ ```
+ * Reload ~/.bashrc:
+ ```
+ source ~/.bashrc:
+ ```
+ * Clone with submodules and LFS.
+ ```
+ git clone --recursive https://github.com/Apra-Labs/ApraPipes.git
+ ```
+ * Run `./bootstrap-vcpkg.sh` in vcpkg/ directory
+ * Run `./vcpkg integrate install`
+
-### Prerequisites
-* Ensure virtualization is enabled in both the BIOS settings of your computer and the Windows virtualization feature -Refer [this article](https://support.microsoft.com/en-us/windows/enable-virtualization-on-windows-11-pcs-c5578302-6e43-4b4b-a449-8ced115f58e1#:~:text=Virtualization%20lets%20your%20PC%20emulate,will%20help%20you%20enable%20virtualization) to enable them
-* Install WSL 2 on your system:
+
+ Build
+
+### Build for Jetson (Only Cuda Build)
+ * Run this command to make the script file executable.
```
- wsl --install
+ chmod +x build_jetson.sh
```
-* Set WSL 2 as the default version using the command line:
+ * ApraPipes builds CUDA version on Jerson Boads.
```
- wsl --set-default-version 2
+ ./build_jetson.sh
```
-* Install Ubuntu-18.04 from [Microsoft store](https://apps.microsoft.com/store/detail/ubuntu-1804-on-windows/9N9TNGVNDL3Q?hl=en-in&gl=in&rtc=1) , Refer [this article](https://learn.microsoft.com/en-us/windows/wsl/install-manual) for any issues regarding installation
-* Install Docker Desktop on Windows -from [here](https://docs.docker.com/desktop/install/windows-install/)
-* Enable Docker integration with WSL 2 (in Docker Desktop settings -> Resources -> WSL integration -> Enable Ubuntu-18.04 -> Apply&restart)
-* Install nvida-container-toolkit using (WSL Ubuntu-18.04) for docker to access Host-system GPU -Follow [this document](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) to install nvidia-container-toolkit
-* Note:"Follow the exact instructions outlined in the document to ensure the correct and successful installation of the NVIDIA Container Toolkit"
-### Build for Docker
+ Build can take ~12 hours on Jetson Nano.
+ Note: Jetson build can also be done using Ubuntu 18.04 x86_64 Laptop via cross compilation.
+
+
+
+ Cross Compilation using qemu
+
+### Cross compilation using qemu
+ Conceptual steps adapted from [here](https://github.com/zhj-buffer/Cross-Compile-Jetson):
-* Use this [docker image](https://github.com/users/kumaakh/packages/container/package/aprapipes-build-x86-ubutu18.04-cuda) with all the software setup.
+ * On any Intel Ubuntu 18.04 computer (physical or virtual including wsl ) mount a Jetson SD Card Image as described above
+ * Copy relevant files from mounted image to created a rootfs
+ * Install qemu on ubuntu host
+ * chroot into emulated aarm64 environment using script provided in the github link above
+ * install extra tools and build aprapipes and aprapipesut
+ * the built aprapipesut can be copied to a Jetson board and run.
+
+ This approach can use all 12-16 cores of a laptop and hence builds faster.
+
+
+
+ Test
+
+### Run Tests
+ * list all tests `./_build/aprapipesut --list_content`
+ * run all tests `./_build/aprapipesut`
+ * run one test `./_build/aprapipesut --run_test=filenamestrategy_tests/boostdirectorystrategy`
+ * run one test with arguments `./_build/aprapipesut --run_test=unit_tests/params_test -- -ip 10.102.10.121 -data ArgusCamera`
+ * Look at the unit_tests/params_test to check for sample usage of parameters in test code
+
+
+Docker
+
+
+ Requirements
+
+### Prerequisites
+ * Ensure virtualization is enabled in both the BIOS settings of your computer and the Windows virtualization feature -Refer [this article](https://support.microsoft.com/en-us/windows/enable-virtualization-on-windows-11-pcs-c5578302-6e43-4b4b-a449-8ced115f58e1#:~:text=Virtualization%20lets%20your%20PC%20emulate,will%20help%20you%20enable%20virtualization) to enable them
+ * Install WSL 2 on your system:
+ ```
+ wsl --install
+ ```
+ * Set WSL 2 as the default version using the command line:
+ ```
+ wsl --set-default-version 2
+ ```
+ * Install Ubuntu-18.04 from [Microsoft store](https://apps.microsoft.com/store/detail/ubuntu-1804-on-windows/9N9TNGVNDL3Q?hl=en-in&gl=in&rtc=1) , Refer [this article](https://learn.microsoft.com/en-us/windows/wsl/install-manual) for any issues regarding installation
+ * Install Docker Desktop on Windows -from [here](https://docs.docker.com/desktop/install/windows-install/)
+ * Enable Docker integration with WSL 2 (in Docker Desktop settings -> Resources -> WSL integration -> Enable Ubuntu-18.04 -> Apply&restart)
+ * Install nvida-container-toolkit using (WSL Ubuntu-18.04) for docker to access Host-system GPU -Follow [this document](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) to install nvidia-container-toolkit
+ * Note:"Follow the exact instructions outlined in the document to ensure the correct and successful installation of the NVIDIA Container Toolkit"
+
+
+
+ Build
+
+### Build for Docker
+ * Use this [docker image](https://github.com/users/kumaakh/packages/container/package/aprapipes-build-x86-ubutu18.04-cuda) with all the software setup.
```
docker pull ghcr.io/kumaakh/aprapipes-build-x86-ubutu18.04-cuda:last-good
```
@@ -168,68 +320,14 @@ Build can take ~2 hours depending on the machine configuration.
* build using build_linux_\*.sh scripts as described [above](#build-for-linux)
This build will be fairly fast (~10 mins) as entire vcpkg cache comes down with the docker image
-
-## Jetson boards - Nano, TX2, NX, AGX
-
-### Prerequisites
-* Setup the board with [Jetpack 4.4](https://docs.nvidia.com/sdk-manager/install-with-sdkm-jetson/index.html)
-* run the following
- ```
- sudo apt-get update && sudo apt-get -y install git-lfs libncurses5-dev ninja-build nasm curl libudev-dev libssl-dev && sudo snap install cmake --classic
- ```
-* append following lines to ~/.bashrc
- ```
- export VCPKG_FORCE_SYSTEM_BINARIES=1
- export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}
- export LD_LIBRARY_PATH=/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
- ```
-* reload ~/.bashrc:
- ```
- source ~/.bashrc:
- ```
-* Clone with submodules and LFS.
- ```
- git clone --recursive https://github.com/Apra-Labs/ApraPipes.git
- ```
-* Run `./bootstrap-vcpkg.sh` in vcpkg/ directory
-* Run `./vcpkg integrate install`
-
-### Build for jetsons
-* `chmod +x build_jetson.sh`
-* `./build_jetson.sh`
-
-Build can take ~12 hours on Jetson Nano.
-Note: Jetson build can also be done using Ubuntu 18.04 x86_64 Laptop via cross compilation.
-
-### Cross compilation using qemu
-Conceptual steps adapted from [here](https://github.com/zhj-buffer/Cross-Compile-Jetson):
-
-* On any Intel Ubuntu 18.04 computer (physical or virtual including wsl ) mount a Jetson SD Card Image as described above
-* Copy relevant files from mounted image to created a rootfs
-* Install qemu on ubuntu host
-* chroot into emulated aarm64 environment using script provided in the github link above
-* install extra tools and build aprapipes and aprapipesut
-* the built aprapipesut can be copied to a Jetson board and run.
-
-This approach can use all 12-16 cores of a laptop and hence builds faster.
-
-
-### Run Tests
-* list all tests `_build/aprapipesut --list_content`
-* run all tests `_build/aprapipesut`
-* run one test `_build/aprapipesut --run_test=filenamestrategy_tests/boostdirectorystrategy`
-* run one test with arguments `_build/aprapipesut --run_test=unit_tests/params_test -- -ip 10.102.10.121 -data ArgusCamera`
- * Look at the unit_tests/params_test to check for sample usage of parameters in test code
-
-This project uses boost tests for unit tests.
+
## Update Submodules
```
git submodule update --init --recursive
```
-
## Update Documentation
-If any changes are made in the documentation i.e. in /docs/source folder, the docs must be regenerated again follwing the steps given below. New contents from the /docs/build directory should be committed.
+ After making changes to the documentation located in the /docs/source folder, it's essential to regenerate the documentation by following the provided steps. Once regenerated, commit the new content to ensure the latest documentation is up-to-date.
### To regenerate documentation
```
@@ -238,4 +336,4 @@ apt-install get python-sphinx
pip install sphinx-rtd-theme
cd docs
make html
-```
+```
\ No newline at end of file
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