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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://github.com/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 PATH
.
$ 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 tap esimov/caire
$ brew install caire
$ caire -in input.jpg -out output.jpg
$ caire --help
The following flags are supported:
Flag | Default | Description |
---|---|---|
in |
- | Input file |
out |
- | Output file |
width |
n/a | New width |
height |
n/a | New height |
perc |
false | Reduce image by percentage |
square |
false | Reduce image to square dimensions |
scale |
false | Proportional scaling |
blur |
1 | Blur radius |
sobel |
10 | Sobel filter threshold |
debug |
false | Use debugger |
face |
false | Use face detection |
angle |
float | Plane rotated faces angle |
cc |
string | Cascade classifier |
To detect faces prior rescaling use the -face
flag and provide the face classification binary file included into the data
folder. The sample code below will rescale the provided image with 20% but will search for human faces prior rescaling.
For the face detection related arguments 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 width
and 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.
The -scale
option will resize the image proportionally. First the image is scaled down 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.
Notice: Using the -scale
option will reduce drastically the processing time. Use this option whenever is possible!
The CLI command can process all the images from a specific directory:
$ caire -in ./input-directory -out ./output-directory
You can also use stdin
and stdout
with -
:
$ cat input/source.jpg | caire -in - -out - >out.jpg
in
and out
default to -
so you can also use:
$ cat input/source.jpg | caire >out.jpg
$ caire -out out.jpg < input/source.jpg
snap
function (https://snapcraft.io/caire): $ snap run caire --h
Original | Shrunk |
---|---|
Original | Extended |
---|---|
Copyright © 2018 Endre Simo
This project is under the MIT License. See the LICENSE file for the full license text.
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