1.8 KiB
1.8 KiB
README
spin up dev environment
# extract archive
$ tar -zxvf project.tar.gz
frontend
$ cd project/frontend
$ yarn
$ yarn dev
backend(py_classifier)
# install miniconda
# https://docs.anaconda.com/miniconda/
# https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe
# download and install miniconda
$ conda create --name opencv3 python=3
$ conda activate opencv3
# optional
$ pip install opencv-contrib-python==3.4.2.16
# run classifier backend
$ cd src
$ ./scripts/run.sh
directory structure
├── docs # some documentation
├── poc # proff of concept workspace
├── 003-crawler # image crawler
├── 010-flask # python flask tryout
└── 013-flask-nextjs-draft # python / nextjs integration
├── training # classifier training code
├── frontend # frontend code
├── py_classifier # backend code
└── test_images # test images
References
- https://youtu.be/6hcjr5ISmzo
- https://docs.opencv.org/4.x/dc/d88/tutorial_traincascade.html
- https://github.com/Paradiddle131/Cigarette-Detection-with-Haar-Cascade-Classifier/tree/master
- https://pythonprogramming.net/haar-cascade-object-detection-python-opencv-tutorial/
- https://saturncloud.io/blog/installing-opencv-with-conda-a-guide-for-data-scientists/
- https://stackoverflow.com/questions/38787748/installing-opencv-3-1-with-anaconda-python3
- https://huggingface.co/chat/conversation/67252f087c8610524e155288
- https://github.com/search?q=opencv_createsamples&type=code&ref=advsearch
- https://github.com/Paradiddle131/Cigarette-Detection-with-Haar-Cascade-Classifier/tree/master