What is this?

This repository contains our attempt at developing a working model for auto labelling road marking geometry on images.

• Indending to use ProbFX (or a derivative) to allow for ergonomic & reusable models
• Currently using the Haskell Image Processing Library (HIP) for image handling (currently unstable, so looking to move to an openCV binding)

How will this work?

The long-term goal is to build the pipeline described below...

File Structure

├── CHANGELOG.md
├── README.md     # This readme
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├── ProbFX-RoadMarkings.cabal  # Cabal configuration
├── Setup.hs                   # Hooks for running C++ side build
├── cabal.project              # ProbFX dependency
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├── data ───── ... # Data used for testing (i.e images)
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├── .vscode
|    └── settings.json  # Helpful vscode configuration (e.g for clang tidy extension)
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├── backend ── ... # The C++ side of the project
├── app ────── ... # The main 
└── src ────── ... # The Haskell side of the project (contains bindings, logic)

Repo Goals (Short Term)

• Implement basic image transformations (hough, edge detections, filtering etc)
• Implement a basic model for road geometry
• Improve basic equation to error function check routines
• Implement our own metropolis hastings to improve/refine model parameters on a single image

Building The Project

System Dependencies

On Ubuntu ensure you have installed the following:

sudo apt-get install 
    # required for C++ build
    make
    cmake
    g++ 

    # Required for openCV install
    wget 
    unzip 

    # Required for OpenGL
    libx11-dev 
    mesa-common-dev 
    libgl1-mesa-dev 
    libglu1-mesa-dev 
    libxinerama1 
    libxinerama-dev 
    libxcursor-dev 
    libxrandr-dev 
    libxi-dev 
    libxmu-dev 
    libblas-dev

OpenCV is also required for this project ande can be installed with the following instructions:

# create a directory to build openCV in:
mkdir openCV && cd openCV

# Download the required sources:
wget -O opencv.zip https://github.com/opencv/opencv/archive/4.x.zip
unzip opencv.zip
mv opencv-4.x opencv

# create build directory
mkdir -p build && cd build

# Configure cmake and build
cmake ../opencv
make -j4

# install system-wide
sudo make install

To complete installation a reboot is required, otherwise you may get a cannot open shared object file error (similar issue). On WSL use:

wsl --shutdown
# reopen wsl terminal to restart

Python 3.10 is also required for benchmarking.

Build & Clean

To simplify the build process we use a makefile to invoke cabal

make       # same as make build
make run
make build
make clean

Benchmarking

To run the synthetic benchmark suite

make bench