MCPcopy Index your code
hub / github.com/OpenStitching/stitching

github.com/OpenStitching/stitching @v0.6.1

Chat with this repo
repository ↗ · DeepWiki ↗ · release v0.6.1 ↗ · + Follow
241 symbols 845 edges 32 files 14 documented · 6%
What it actually does AI analysis from the code graph — generated when you open this
loading…
README

stitching

A Python package for fast and robust Image Stitching.

Based on opencv's stitching module and inspired by the stitching_detailed.py python command line tool.

inputs

result

Installation

use the docker image

or pip to install stitching from PyPI.

pip install stitching

Usage

Python CLI

The command line interface (cli) is available after installation

stitch -h show the help

stitch *.jpg stitches all jpg files in the current directory

stitch img_dir/IMG*.jpg stitches all files in the img_dir directory starting with "IMG" and ending with ".jpg"

stitch img1.jpg img2.jpg img3.jpg stitches the 3 explicit files of the current directory

Enable verbose mode with stitch *.jpg -v. This will create a folder where all intermediate results are stored so that you can find out where there are problems with your images, if any

Docker CLI

If you are familiar with Docker and don't feel like setting up Python and an environment, you can also use the openstitching/stitch Docker image

docker container run --rm -v /path/to/data:/data openstitching/stitch:{version} -h

You can use the Python CLI as described above (read "current directory" as "/data directory").

Python Script

You can also use the Stitcher class in your script

from stitching import Stitcher
stitcher = Stitcher()

Specify your custom settings as

stitcher = Stitcher(detector="sift", confidence_threshold=0.2)

or

settings = {"detector": "sift", "confidence_threshold": 0.2}
stitcher = Stitcher(**settings)

Create a Panorama from your Images:

  • from a list of filenames
panorama = stitcher.stitch(["img1.jpg", "img2.jpg", "img3.jpg"])
  • from a single item list with a wildcard
panorama = stitcher.stitch(["img?.jpg"])
  • from a list of already loaded images
panorama = stitcher.stitch([cv.imread("img1.jpg"), cv.imread("img2.jpg")])

The equivalent of the --affine cli parameter within the script is

from stitching import AffineStitcher
stitcher = AffineStitcher()
panorama = stitcher.stitch(...)

The equivalent of the -v/--verbose cli parameter within the script is

panorama = stitcher.stitch_verbose(...)

Questions

For questions please use our discussions. Please do not use our issue section for questions.

Contribute

Read through how to contribute for information on topics like finding and fixing bugs and improving / maintaining this package.

Tutorial

This package provides utility functions to deeply analyse what's happening behind the stitching. A tutorial was created as Jupyter Notebook. The preview is here.

You can e.g. visualize the RANSAC matches between the images or the seam lines where the images are blended:

matches1 matches2 seams1 seams2

Literature

This package was developed and used for our paper Automatic stitching of fragmented construction plans of hydraulic structures

License

Apache License 2.0

Core symbols most depended-on inside this repo

resize
called by 17
stitching/images.py
load_test_img
called by 15
tests/context.py
write_verbose_result
called by 12
stitching/verbose.py
warp
called by 8
stitching/stitcher.py
get_ratio
called by 7
stitching/images.py
feed
called by 7
stitching/blender.py
stitch
called by 7
stitching/stitcher.py
apply
called by 7
stitching/exposure_error_compensator.py

Shape

Method 181
Class 32
Function 28

Languages

Python100%

Modules by API surface

stitching/stitcher.py34 symbols
stitching/images.py28 symbols
stitching/cropper.py23 symbols
stitching/seam_finder.py16 symbols
tests/test_stitcher.py15 symbols
stitching/feature_matcher.py11 symbols
stitching/warper.py10 symbols
stitching/megapix_scaler.py9 symbols
tests/test_stitch_cli.py8 symbols
stitching/subsetter.py8 symbols
stitching/timelapser.py7 symbols
tests/test_megapix_scaler.py6 symbols

For agents

$ claude mcp add stitching \
  -- python -m otcore.mcp_server <graph>

⬇ download graph artifact