| Name | Github |
|---|---|
| Ruidan Ni | rita-ni |
| Frank Lu | Frank Lu |
| Kexin Zhao | Margaret8521 |
imgtoolpy is a Python package that is intended to allow users to compress, sharpen and crop an input image.
Our package only allows the input image to be a 3D numpy array and output the manipulated image as a 3D numpy array. It contains three functions: compress(), sharpen(), and crop().
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compress:- This function quantizes an image by restricting each pixel to only take on one of the desired colour values and return a version of the image (the same size as the original) where each pixel's original colour is replaced with the nearest prototype colour.
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crop:- A function that crop image size by removing border pixels until desired height and width are reached. This function take image input in the form of a 3D array.
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sharpen:- This function enhances the edges in the image and returns a sharper-looking image. At this moment, this function is restricted to gray-scale images only
pip install -i https://test.pypi.org/simple/ imgtoolpy
There are a few existing Python packages that perform content-aware image resizing, such as pyCAIR (available on PyPI), and seam-carver. Currently, there is no package available on CRAN to resize images based on the same mechanism, however, there is a package available on Github to seam carve image. Also, there are similar packages for image manipulation such as scikit-image, which could be used for filtering and transforming images.
[tool.poetry.dependencies]
- python = "^3.7"
- sklearn = "^0.0"
- numpy = "^1.18.1"
- pandas = "^1.0.1"
- scipy = "^1.4.1"
- scikit-image = "^0.16.2"
[tool.poetry.dev-dependencies]
- pytest-cov = "^2.8.1"
- pytest = "^5.3.5"
- sphinx = "^2.4.3"
- sphinxcontrib-napoleon = "^0.7"
| Task | from imgtoolpy import compress, crop, sharpen |
|---|---|
| Compress an image to 4 bits per channel (2^4=16 colors) | compress.compress(image, 4) |
| crop an image to desired width and height | crop.crop(image, 20, 20) |
| Sharpen an image by detecting and enhancing the edges | sharpen.sharpen(image) |
First, we should load the imgtoolpy library:
from imgtoolpy import compress, crop, sharpen
We are going to use butterfly.jpg image which is in the img folder of this repository for illustration.
We can apply the compress function:
compress.compress(image, 4)
import os
from matplotlib.pyplot import imread, imshow, imsave
image = imread(os.path.join("img", "butterfly.jpg"))
imsave(os.path.join("img", "compress.jpg"), compress.compress(image, 4))
We can also apply the crop function:
crop.crop(image, 400, 400)
import os
from matplotlib.pyplot import imread, imshow, imsave
image = imread(os.path.join("img", "butterfly.jpg"))
imsave(os.path.join("img", "crop.jpg"), crop.crop(image, 400, 400))
We can also apply the sharpen function:
sharpen.sharpen(image)
import os
from matplotlib.pyplot import imread, imsave, cm
image = imread(os.path.join("img", "free-wallpaper.jpg"))
res = sharpen.sharpen(image)
# save the monotoned original image
imsave(os.path.join("img", "sharpen_before.png"), res[0], cmap = cm.gray)
# save the sharpened image
imsave(os.path.join("img", "sharpen_after.png"), res[1], cmap = cm.gray)
The official documentation is hosted on Read the Docs: https://imgtoolpy.readthedocs.io/en/latest/
This package was created with Cookiecutter and the UBC-MDS/cookiecutter-ubc-mds project template, modified from the pyOpenSci/cookiecutter-pyopensci project template and the audreyr/cookiecutter-pypackage.