• Removes extra white boundaries from images to correctly resize canvas.

• Thanks @matthewkmayer for bringing down cropping times (see #1 and #2)!

The borders are just to represent the actual images tested with. (click to zoom)

$ cargo install auto-image-cropper

or if you like to live on the bleeding edge

$ git clone https://github.com/Ritiek/auto-image-cropper
$ cd auto-image-cropper
$ cargo build --release

Use ./target/release/autocrop to start using the tool.

USAGE:
    autocrop [OPTIONS] --input <LOCATION>

FLAGS:
    -h, --help       Prints help information
    -V, --version    Prints version information

OPTIONS:
    -i, --input <LOCATION>     Location of input image/directory
    -o, --output <LOCATION>    Location of output image/directory

For example:

$ ./target/release/autocrop -i benchmarking/face.jpg -o face.out.jpg

This tool also provides Python bindings via PyO3 (using Rust FFI).

You need a Rust nightly toolchain to proceed (PyO3 does not support Rust stable at the moment). If you have rustup, run:

$ rustup default nightly

to switch to nightly channel.

This feature can then be enabled by passing --features "python-binding" to cargo when compiling.

For example:

$ cargo build --release --features "python-binding"

This will generate a dynamic library (*.so) on Linux machines with the name ./target/release/libauto_image_cropper.so.

Let's move this dynamic library into our current working directory:

$ mv target/release/libauto_image_cropper.so .

It can now be utilized via Python scripts using:

>>> import libauto_image_cropper

# Returns the optimal top-left and bottom-right corner
# coordinates for a given image to be cropped
>>> (top_left, bottom_right) = libauto_image_cropper.calculate_corners("benchmarking/face.jpg")
>>> print(top_left)
(442, 73)
>>> print(bottom_right)
(783, 536)

(I haven't checked this out on Windows or OSX, but should follow a similar procedure)

• This tool was hackishly re-written in Python to compare with Rust - just for fun.

• The benchmarks were done on a MacBook Air running macOS Sierra 10.12.2.

• Python struggles to find the optimal coordinates but is quick (quicker than Rust) when saving the cropped image back to disk. Rust really outperforms while finding the optimal coordinates.

[2020 / 03] UPDATE: These benchmarks were done in 2017. Rust and its image libraries have a come long way ahead and I believe should now offer even better performance! I'll update these benchmarks when I'm able to.

The MIT License