Automatically crops faces from batches of pictures
Perfect for batch work for ID cards or profile picture processing for your website, autocrop will output images centered around the biggest face detected.
>From the command line:
usage: [-h] [-o OUTPUT] [-i INPUT] [-w WIDTH] [-H HEIGHT] [-v] Automatically crops faces from batches of pictures optional arguments: -h, --help Show this help message and exit -o, --output, -p, --path Folder where cropped images will be placed. Default: current working directory -i, --input Folder where images to crop are located. Default: current working directory -w, --width Width of cropped files in px. Default=500 -H, --height Height of cropped files in px. Default=500 -v, --version Show program's version number and exit
- Example: autocrop -i pics -o crop -w 400 -H 400.
What it does
The previous command will: 1. Copy all images found in the top level of pics to crop, 2. Crop around the face and resize to 400x400 pixels all images in crop.
Images where a face can’t be detected will be left in crop. If no output folder is added, asks for confirmation and destructively crops images in-place.
Simple! In your command line, type:
pip install autocrop
Autocrop uses OpenCV to perform face detection, which is installed through binary wheels. If you already have OpenCV 3+ installed, you may wish to uninstall the additional OpenCV installation: pip uninstall opencv-python.
In some cases, you may wish the package directly, instead of through PyPI:
cd ~ git clone https://github.com/leblancfg/autocrop cd autocrop pip install .
Autocrop is currently being tested on: * Python: - 2.7 - 3.4 - 3.5 - 3.6 * OS: - Linux - macOS - Windows
Although autocrop is essentially a CLI wrapper around a single OpenCV function, it is actively developed. It has active users throughout the world.
We have all the love in the world for extra contributors if you’d like to contribute to the codebase. Please follow these steps: * Fork the repository on GitHub. * Install the extra dev packages with pip install -r requirements-test.txt * Make a branch off of master, commit and test your changes to it.
Pull requests are tested on continuous integration (CI) servers before they are green-lit to merge with the master branch. * Run the tests with pytest. * Always run flake8 . before submitting to check your coding style, as your CI will fail otherwise. * Submit a Pull Request to the master branch on GitHub.
If you have any questions regarding this, please reach me at firstname.lastname@example.org. We’ll make sure we get through the steps correctly.
If you’d like to have a development environment for autocrop, you should create a virtualenv and then do pip install -e . from within the directory.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size & hash SHA256 hash help||File type||Python version||Upload date|
|autocrop-0.2.0-py2.py3-none-any.whl (146.4 kB) Copy SHA256 hash SHA256||Wheel||py2.py3||Jan 24, 2018|
|autocrop-0.2.0.tar.gz (9.3 MB) Copy SHA256 hash SHA256||Source||None||Jan 24, 2018|