|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Content aware image cropping|
|Picassofacedetectiontransformation||853||6 years ago||1||Java|
|A memory efficient Android image transformation library providing cropping above Face Detection (Face Centering) for Picasso.|
|Seetafaceengine2||658||5 years ago||41||other||C++|
|Masaccio||531||2||8 years ago||1||December 04, 2014||3||apache-2.0||Java|
|An Android library providing a useful widget class which automatically detects the presence of faces in the source image and crop it accordingly so to achieve the best visual result.|
|Facecropper||479||1||6 years ago||1||October 09, 2017||3||mit||Swift|
|:scissors: Crop faces, inside of your image, with iOS 11 Vision api.|
|Androidfacecropper||454||9 years ago||2||apache-2.0||Java|
|Android bitmap Face Cropper|
|Autocrop||436||10 months ago||19||January 25, 2022||10||other||Python|
|:relieved: Automatically detects and crops faces from batches of pictures.|
|Dfdc_deepfake_challenge||431||2 years ago||5||mit||Python|
|A prize winning solution for DFDC challenge|
|Glidefacedetectiontransformation||347||6 years ago||4||Java|
|A memory efficient Android image transformation library providing cropping above Face Detection (Face Centering) for Glide.|
|Imagedetect||273||2||4 years ago||5||October 22, 2018||mit||Swift|
|✂️ Detect and crop faces, barcodes and texts in image with iOS 11 Vision api.|
Perfect for profile picture processing for your website or batch work for ID cards, autocrop will output images centered around the biggest face detected.
pip install autocrop
Autocrop can be used from the command line or directly from Python API.
Cropper class, set some parameters (optional), and start cropping.
crop method accepts filepaths or
np.ndarray, and returns Numpy arrays. These are easily handled with PIL or Matplotlib.
from PIL import Image from autocrop import Cropper cropper = Cropper() # Get a Numpy array of the cropped image cropped_array = cropper.crop('portrait.png') # Save the cropped image with PIL if a face was detected: if cropped_array: cropped_image = Image.fromarray(cropped_array) cropped_image.save('cropped.png')
Further examples and use cases are found in the accompanying Jupyter Notebook.
usage: autocrop [-h] [-v] [--no-confirm] [-n] [-i INPUT] [-o OUTPUT] [-r REJECT] [-w WIDTH] [-H HEIGHT] [--facePercent FACEPERCENT] [-e EXTENSION] Automatically crops faces from batches of pictures options: -h, --help Show this help message and exit -v, --version Show program's version number and exit --no-confirm, --skip-prompt Bypass any confirmation prompts -n, --no-resize Do not resize images to the specified width and height, but instead use the original image's pixels. -i, --input INPUT Folder where images to crop are located. Default: current working directory -o, -p, --output, --path OUTPUT Folder where cropped images will be moved to. Default: current working directory, meaning images are cropped in place. -r, --reject REJECT Folder where images that could not be cropped will be moved to. Default: current working directory, meaning images that are not cropped will be left in place. -w, --width WIDTH Width of cropped files in px. Default=500 -H, --height HEIGHT Height of cropped files in px. Default=500 --facePercent FACEPERCENT Percentage of face to image height -e, --extension EXTENSION Enter the image extension which to save at output
picsfolder, resize them to 400 px squares, and output them in the
autocrop -i pics -o crop -w 400 -H 400.
autocrop -i pics -o crop -r reject -w 400 -H 400.
autocrop -i pics -o crop -w 400 -H 400 -e png
picsfolder and output to the
cropdirectory, but keep the original pixels from the images:
autocrop -i pics -o crop --no-resize
If no output folder is added, asks for confirmation and destructively crops images in-place.
You can use autocrop to detect faces in frames extracted from a video. A great way to perform the frame extraction step is with
mkdir frames faces # Extract one frame per second ffmpeg -i input.mp4 -filter:v fps=fps=1/60 frames/ffmpeg_%0d.bmp # Crop faces as jpg autocrop -i frames -o faces -e jpg
The following file types are supported:
.gif) (only the first frame of an animated GIF is used)
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 .
Development of a
conda-forge package for the Anaconda Python distribution is currently stalled due to the complexity of setting up the workflow with OpenCV. Please leave feedback on issue #7 to see past attempts if you are insterested in helping out!
Best practice for your projects is of course to use virtual environments. At the very least, you will need to have pip installed.
Autocrop is currently being tested on:
Although autocrop is essentially a CLI wrapper around a single OpenCV function, it is actively developed. It has active users throughout the world.
If you would like to contribute, please consult the contribution docs.