7 releases
0.0.7 | Oct 24, 2023 |
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0.0.6 | Nov 21, 2021 |
0.0.3 | Oct 31, 2021 |
#260 in Images
48 downloads per month
26KB
369 lines
libstacker
A multithreaded port of the python code found here: github.com/maitek/image_stacking
This crate contains multithreaded functions that aligns and stacks images using OpenCV and Rayon.
Read more about image alignment with OpenCV here.
Usage:
Download the test images:
git clone https://github.com/maitek/image_stacking image_stacking_py
Build the code:
Opencv-rust can be little tricky to install. Follow the instructions from rust opencv
You will need the "clang-runtime" feature if you experience problems with your clang environment .
cargo build --release
or
cargo build --release --features "clang-runtime"
Run the example:
cargo run --example main --release
or
cargo run --example main --release --features "clang-runtime"
and then wait a few seconds. The program should sort the images by quality, drop the least sharp image, and align and stack the rest. The result should be two windows showing the stacked images using two different alignment methods.
API
let keypoint_match_img:opencv::core::Mat = keypoint_match(
// a Vec<PathBuf> containing paths to image files
collect_image_files(&PathBuf::from("image_stacking_py/images"))?,
KeyPointMatchParameters {
method: opencv::calib3d::RANSAC,
ransac_reproj_threshold: 5.0,
},
)?;
Depending on the parameters the ecc_match()
is much slower, but also more accurate.
let ecc_match_img:opencv::core::Mat = ecc_match(
// a Vec<PathBuf> containing paths to image files
collect_image_files(&PathBuf::from("image_stacking_py/images"))?,
EccMatchParameters {
motion_type: MotionType::Homography,
max_count: Some(5000),
epsilon: Some(1e-5),
gauss_filt_size: 5,
},
)?;
Todo
- Figure out the docs.rs problem
- Figure out what to do with
.reshape()
inkeypoint_match()
Figure out some opencv parametersresponsibility sneakily shifted to end user.- Complete the
sharpness_tenengrad()
function. Mat not square? - Command line options in the example
License
Licensed under either of
- Apache License, Version 2.0, (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)
at your option.
Dependencies
~3–5.5MB
~73K SLoC