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autocrop-1.3.0


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توضیحات

Automatically crops faces from batches of pictures
ویژگی مقدار
سیستم عامل -
نام فایل autocrop-1.3.0
نام autocrop
نسخه کتابخانه 1.3.0
نگهدارنده []
ایمیل نگهدارنده []
نویسنده François Leblanc
ایمیل نویسنده leblancfg@gmail.com
آدرس صفحه اصلی https://github.com/leblancfg/autocrop
آدرس اینترنتی https://pypi.org/project/autocrop/
مجوز BSD 2-Clause
# autocrop [![CI](https://github.com/leblancfg/autocrop/actions/workflows/ci.yml/badge.svg?branch=master)](https://github.com/leblancfg/autocrop/actions/workflows/ci.yml) [![codecov](https://codecov.io/gh/leblancfg/autocrop/branch/master/graph/badge.svg)](https://codecov.io/gh/leblancfg/autocrop) [![Documentation](https://img.shields.io/badge/docs-passing-success.svg)](https://leblancfg.com/autocrop) [![PyPI version](https://badge.fury.io/py/autocrop.svg)](https://badge.fury.io/py/autocrop) [![Downloads](https://pepy.tech/badge/autocrop)](https://pepy.tech/project/autocrop) <p align="center"><img title="obama_crop" src="https://cloud.githubusercontent.com/assets/15659410/10975709/3e38de48-83b6-11e5-8885-d95da758ca17.png"></p> Perfect for profile picture processing for your website or batch work for ID cards, autocrop will output images centered around the biggest face detected. # Installation Simple! ~~~sh pip install autocrop ~~~ # Use Autocrop can be used [from the command line](#from-the-command-line) or directly [from Python API](#from-python). ## From Python Import the `Cropper` class, set some parameters (optional), and start cropping. The `crop` method accepts filepaths or `np.ndarray`, and returns Numpy arrays. These are easily handled with [PIL](https://pillow.readthedocs.io/) or [Matplotlib](https://matplotlib.org/). ~~~python 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](https://github.com/leblancfg/autocrop/blob/master/examples/visual_tests.ipynb). ## From the command line usage: [-h] [-o OUTPUT] [-i INPUT] [-w WIDTH] [-H HEIGHT] [-e EXTENSION] [-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 -r, --reject Folder where images without detected faces will be placed. Default: same as output 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 --facePercent Zoom factor. Percentage of face height to image height. -e, --extension Enter the image extension which to save at output. Default: Your current image extension -v, --version Show program's version number and exit ### Examples * Crop every image in the `pics` folder, resize them to 400 px squares, and output them in the `crop` directory: - `autocrop -i pics -o crop -w 400 -H 400`. - Images where a face can't be detected will be left in `crop`. * Same as above, but output the images with undetected faces to the `reject` directory: - `autocrop -i pics -o crop -r reject -w 400 -H 400`. * Same as above but the image extension will be `png`: - `autocrop -i pics -o crop -w 400 -H 400 -e png` If no output folder is added, asks for confirmation and destructively crops images in-place. ### Detecting faces from video files You can use autocrop to detect faces in frames extracted from a video. A great way to [perform the frame extraction step is with `ffmpeg`](https://ffmpeg.org/download.html): ```sh 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 ``` # Supported file types The following file types are supported: - EPS files (`.eps`) - GIF files (`.gif`) (only the first frame of an animated GIF is used) - JPEG 2000 files (`.j2k`, `.j2p`, `.jp2`, `.jpx`) - JPEG files (`.jpeg`, `.jpg`, `.jpe`) - LabEye IM files (`.im`) - macOS ICNS files (`.icns`) - Microsoft Paint bitmap files (`.msp`) - PCX files (`.pcx`) - Portable Network Graphics (`.png`) - Portable Pixmap files (`.pbm`, `.pgm`, `.ppm`) - SGI files (`.sgi`) - SPIDER files (`.spi`) - TGA files (`.tga`) - TIFF files (`.tif`, `.tiff`) - WebP (`.webp`) - Windows bitmap files (`.bmp`, `.dib`) - Windows ICO files (`.ico`) - X bitmap files (`.xbm`) # Misc ### Installing directly In some cases, you may wish the package directly, instead of through [PyPI](https://pypi.python.org/pypi): ~~~ cd ~ git clone https://github.com/leblancfg/autocrop cd autocrop pip install . ~~~ ### conda Development of a `conda-forge` package for the [Anaconda Python distribution](https://www.anaconda.com/download/) is currently stalled due to the complexity of setting up the workflow with OpenCV. Please leave feedback on [issue #7](https://github.com/leblancfg/autocrop/issues/7) to see past attempts if you are insterested in helping out! ### Requirements Best practice for your projects is of course to [use virtual environments](http://docs.python-guide.org/en/latest/dev/virtualenvs/). At the very least, you will need to [have pip installed](https://pip.pypa.io/en/stable/installing/). Autocrop is [currently being tested on](https://github.com/leblancfg/autocrop/actions/workflows/ci.yml): * Python 3.7 to 3.10 * OS: - Linux - macOS - Windows # More Info Check out: * http://docs.opencv.org/master/d7/d8b/tutorial_py_face_detection.html#gsc.tab=0 * http://docs.opencv.org/master/d5/daf/tutorial_py_histogram_equalization.html#gsc.tab=0 Adapted from: * http://photo.stackexchange.com/questions/60411/how-can-i-batch-crop-based-on-face-location ### Contributing 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](CONTRIBUTING.md).


نیازمندی

مقدار نام
>=1.10 numpy
<5,>=3 opencv-python-headless
>=9.0.0 Pillow


زبان مورد نیاز

مقدار نام
>=3.6 Python


نحوه نصب


نصب پکیج whl autocrop-1.3.0:

    pip install autocrop-1.3.0.whl


نصب پکیج tar.gz autocrop-1.3.0:

    pip install autocrop-1.3.0.tar.gz