Crosswalk detection algorithm

Introduction
Getting Started
- Prerequisites
General Layout
How to run

Introduction

This repository contains the model for the road markings project. The purpose of the project is to be able to identify road markings on a photograph, and classify them by damage. The classification is using the CROW standards, which are shown in second figure below. The figure below shows the goal of the project; Classified road markings.

Currently we're only focussing on the crosswalks, nothing more.

Getting Started

Prerequisites

for all the Prerequisites, I would suggest downloading all the requirements.txt file with:

$ pip install -r .\Mask_RCNN\requirements.txt

if there are any problem with finding the file you can manually go to the location.

General Layout

├── Detectron2-final
│   ├── input 
│   │   └── ...
│   ├── output
│   │   └── ...
│   ├── train
│   │   ├── Annotations_coco.json
│   │   ├── zebra1.jpg
│   │   └── ...
│   ├── valid
│   │   ├── Annotations_coco.json
│   │   ├── zebra1.jpg
│   │   └── ...
│   ├── classification.py
│   ├── custom_config_detectron.py
│   ├── environment.yml
│   ├── predicting.py
│   └── training.py
│
├── Harris_Corner_Detection_Test
│   ├── Harris.ipynb 
│   ├── img.jpg 
│   └── ... 
│
├── images
│   ├── img.jpg 
│   └── ... 
│
├── Mask_RCNN
│   ├── common 
│   │   ├── gason.cpp
│   │   ├── gason.h
│   │   ├── maskApi.c
│   │   └── maskApi.h
│   ├── datasets
│   │   ├── input
│   │   ├── output
│   │   ├── train
│   │   └── val
│   ├── logs (log files)
│   │   └── ... 
│   ├── mrcnn
│   │   ├── __init__.py
│   │   ├── config.py
│   │   ├── model.py
│   │   ├── parallel_model.py
│   │   ├── utils.py
│   │   └── visualize.py
│   ├── PythonAPI
│   │   ├── pycocotools
│   │   │   ├── __init__.py
│   │   │   ├── _mask.c
│   │   │   ├── _mask.pyx
│   │   │   ├── coco.py
│   │   │   ├── cocoeval.py
│   │   │   └── mask.py
│   │   ├── Makefile
│   │   ├── pycocoDemo.ipynb
│   │   ├── pycocoEvalDemo.ipynb
│   │   └── setup.py
│   ├── scripts
│   ├── requirements.txt
│   ├── setup.cfg
│   └── setup.py
│
├── .gitignore
└── README.md

How to run

if you've installed everything correctly you should be able to run the application.

NOTE: We expect you to run these commands in the home dir of the repo.

EDIT: This repo is no longer maintained. We suggest looking at the documentation of Detectron2 or Mask_RCNN for more information on how to make your own model with custom datasets.