Caire is a content aware image resize library based on Seam Carving for Content-Aware Image Resizing paper.
|Original image||Energy map||Seams applied|
Key features which differentiates this library from the other existing open source solutions:
The library is capable of detecting human faces prior resizing the images by using the Pigo (https://awesomeopensource.com/project/esimov/pigo) face detection library, which does not require to have OpenCV installed.
The image below illustrates the application capabilities for human face detection prior resizing. It's clearly visible from the image that with face detection activated the algorithm will avoid cropping pixels inside the detected faces, retaining the face zone unaltered.
|Original image||With face detection||Without face detection|
First, install Go, set your
GOPATH, and make sure
$GOPATH/bin is on your
$ export GOPATH="$HOME/go" $ export PATH="$PATH:$GOPATH/bin"
Next download the project and build the binary file.
$ go get -u -f github.com/esimov/caire/cmd/caire $ go install
The library can also be installed via Homebrew.
$ brew install caire
$ caire -in input.jpg -out output.jpg
$ caire --help
The following flags are supported:
||false||Reduce image by percentage|
||false||Reduce image to square dimensions|
||10||Sobel filter threshold|
||false||Use face detection|
||float||Plane rotated faces angle|
To detect faces prior rescaling use the
-face flag. There is no need to provide a face classification cascade file, since it's already embedded into the generated binary file. The sample code below will rescale the provided image with 20% but will search for human faces prior rescaling.
For face detection related settings please check the Pigo documentation.
$ caire -in input.jpg -out output.jpg -face=1 -cc="data/facefinder" -perc=1 -width=20
In case you wish to scale down the image by a specific percentage, it can be used the
-perc boolean flag. In this case the values provided for the
height options are expressed in percentage and not pixel values. For example to reduce the image dimension by 20% both horizontally and vertically you can use the following command:
$ caire -in input/source.jpg -out ./out.jpg -perc=1 -width=20 -height=20 -debug=false
Also the library supports the
-square option. When this option is used the image will be resized to a square, based on the shortest edge.
When an image is resized both horizontally and vertically, the algorithm will try to rescale it prior resizing, but also preserving the image aspect ratio, then the seam carving algorithm is applied only to the remaining points. Ex. : given an image of dimensions 2048x1536 if we want to resize to the 1024x500, the tool first rescale the image to 1024x768 and will remove only the remaining 268px.
The CLI application of the library can also process the images from a specific directory concurrently boosting up the processing speed considerably.
$ caire -in ./input-directory -out ./output-directory
You can also use
$ cat input/source.jpg | caire -in - -out - >out.jpg
out default to
- so you can also use:
$ cat input/source.jpg | caire >out.jpg $ caire -out out.jpg < input/source.jpg
$ snap run caire --h
Copyright © 2018 Endre Simo
This project is under the MIT License. See the LICENSE file for the full license text.