A tiny app that tries its best to replicate an given image.
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![Product Name Screen Shot][product-screenshot] This started as a fun little python project(see this repository), but eventually, due to my desire to learn opencv for C++(using a tiny bit of oop), to see how much faster it would be, to learn cmake and to pottentially use docker, I decided to rewrite it in C++. This app's objective is to try to aproximate as good as it can a given image, using various shapes and colors to achive this. Currently, this repository has one downside: altough the python projects is slower and can only use ellipses to cover images, it stores this ellipses in svg format, which may have some applications.
Here's a blank template to get started:
To avoid retyping too much info. Do a search and replace with your text editor for the following:
georgerapeanu
, ImageDecomposerC
, a.rapeanu49@gmail.com
, Image decomposer
, project_description
To get a local copy up and running follow these simple steps.
This is an example of how to list things you need to use the software and how to install them.
- cmake
sudo apt-get install cmake
- opencv
run
installOpencv.sh
anywhere in your filesystem. - flask
sudo apt-get install python3 sudo apt-get -y install python3-pip pip3 install opencv-python pip3 install flask_wtf pip3 install wtforms pip3 install werkzeug
- Clone the repo
git clone https://github.com/georgerapeanu/ImageDecomposerC.git
- Compile the project
mkdir build cd build cmake ../ make -j8
To run the app, you simply have to run python3 server.py
. The app will use 2 ports.
localhost:8000
will display the current image being processed.
localhost:8001
is the admin interface. You can select here the image and all the additional settings through a form.
For more examples, please refer to the Documentation
See the open issues for a list of proposed features (and known issues).
Contributions are what make the open source community such an amazing place to be learn, inspire, and create. However, currently I would like this project to remain more of a personal one. However, if you still want to contribute, there might be a chance that your pull request is accepted. In that case, follow the next steps:
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Push to the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
Distributed under the MIT License. See LICENSE
for more information.
Project Link: https://github.com/georgerapeanu/ImageDecomposerC