README.md

Documentation

In this folder I will share more links and information about the implementation. This felt necessary since I want to keep the main README file updated and still readable and "clean" as more content is added to the project.

NOTE : Make sure you checkout the jupyter notebook tutorial of how to use the library.

Table of Contents

• Code Review and Explaination
  • Easy and fast setup with Docker
  • Run Jupyter Notebook locally
• Docker
  • Run on Docker
• Run
  • Run old style
• Solved Issues
• References and Imports

Code Review and Explanation

Here we explain how to use the Floorplan to blender library utilizing Jupyter notebook.

Easy and fast setup with Docker

I created a docker-compose to setup everything needed for jupyter notebook to start. Just install docker, run the command below and open a webbrowser at localhost:8888. Lastly navigate to Docs/FloorplanToBlenderLibrary.ipynb.

docker-compose up -d

NOTE: If you have earlier built versions of the container without the Jupyter support add the '--build' flag to the command to rebuild the container.

Run Jupyter Notebook locally

In an effort to get familiar with Jupyter Notebook I will create some demos of how to use the library here too.

To get started install all requirements by installing the requirements.txt file!

# Install requirements file in this folder to start jupyter.
pip install -r requirements.txt

# Start jupyter and open the .ipynb file!
jupyter notebook

Docker

Why Docker?

Docker makes development efficient and predictable. Docker takes away repetitive, mundane configuration tasks and is used throughout the development lifecycle for fast, easy and portable application development - desktop and cloud. Docker’s comprehensive end to end platform includes UIs, CLIs, APIs and security that are engineered to work together across the entire application delivery lifecycle. (docker.com, 2021)

Run on Docker

Firstly you need to install a suitable Docker environment on your device. This project contains a DockerFile which uses the Ubuntu 18.04 image so make sure your docker environment is set to linux containers.

NOTE : This tutorial might be slightly deprecated!

1. Download or clone this repository.

2. Build docker image from Dockerfile by running:

NOTE : This step can take a long time.

 docker build . --tag=floorplan_to_blender:1.0

3. To start the image run:

 docker run -it floorplan_to_blender:1.0 bash

This will take you into your virtual environment where you can safely test the implementation.

4. To run the program, enter the container and run:

  python3 create_blender_project_from_floorplan.py

Blender is installed on path /usr/local/blender/blender, the path can be changed in the config.ini file with nano inside the container. The generated .blender file can be retreived with scp or using volumes.

5. Some useful docker commands:

  # Get into a running container
 docker exec -it container_name bash

 # Stop all containers
 docker rm -f $(docker ps -aq)

 # Remove all images
 docker rmi $(docker images)

Run

Here we explain further how the run process works.

Run old style

NOTE: This part is deprecated!

This tutorial takes you through the execution of this program in examples.

1. Receive floorplan as image, from pdf or by using other method (for example paint)
2. Set image file path in Examples/floorplan_to_datafile.py
3. Run floorplan_to_datafile.py to create data files for your floorplan.
4. Edit path in floorplan_to_datafile.py to generated data files.
5. Start blender
6. Open Blender text editor
7. Open floorplan_to_3dObject_in_blender.py in blender by pressing the text editor, then alt+o and find the file
8. Run script

Solved issues

Here we share information about several issues that has been resolved. This can be useful if someone in the future struggle with similar issues.

Resolved version issues:

• Changed origin position of resulting objects.
• If a later Blender3d version than 2.79 is used, several changes has to done in all files in the /Blender folder.
• If a later OpenCV library version than 3.4.1.15 for python is used, several changes has to be done in the /FloorplanToBlender3d/detect.py file. Please create an issue if you encounter any problems with this implementation.

Code format

For autoformating in python we use the black library. It requires python version 3.6.0+. To use it install using pip install black and then run in root folder black ./*

References and Imports

During the development of this project I have been searching a lot and copied code from StackOverflow. I share links to copied code and other contributors here:

• First look at problem : https://mathematica.stackexchange.com/questions/19546/image-processing-floor-plan-detecting-rooms-borders-area-and-room-names-t
• Room detection : https://stackoverflow.com/questions/54274610/crop-each-of-them-using-opencv-python
• Watershed : https://docs.opencv.org/3.1.0/d3/db4/tutorial_py_watershed.html
• Shape detection : https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_feature2d/py_features_harris/py_features_harris.html
• Distance in image : https://stackoverflow.com/questions/50930033/drawing-lines-and-distance-to-them-on-image-opencv-python
• Rect contain : https://stackoverflow.com/questions/33065834/how-to-detect-if-a-point-is-contained-within-a-bounding-rect-opecv-python
• Line detection : https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_imgproc/py_houghlines/py_houghlines.html
• Readme tips: https://github.com/matiassingers/awesome-readme