Skip to main content

A library that splits the image into overlapping or non-overlapping patches with the optimal step in order to minimize pixels loss. It can then merge them back together.

Project description

image2patch

image2patch splits the image in different patches with automatic detection of the best step in order to minimize pixels loss. The overlap between patches depends on the patch size. Alternatively, it is possible to choose the step size.
The reconstruction of the original image is possible using patch2image which can merge the patches taking into account the overlap percentage among patches. Hence, the original image is perfectly restored. If there is a minimum pixels loss during patching procedure, resize to its original dimensions is possible.

Example

pic

Installation

pip install image2patch
from image2patch import image2patch
from image2patch import patch2image

How to use it

image2patch(image, patch_size, step=None, verbose=False)

In particular:

  • image : 2D input image
  • patch_size : dimension of the window
  • step : the distance from one step to another, if =None it will be automatically detected in order to avoid pixels loss. If set = patch_size it will provide patches without overlapping but with pixels loss depending on the size of the input image.
  • verbose : if =True it provides details.

patch2image(patched_image, original_dims, step, resize_flag = True)

In particular:

  • patched_image : 2D input patches from image2patch
  • original_dims : dimension of the original image
  • step : step obtained from image2patch
  • resize_flag : allows to resize the image to its original dimension in case of pixels loss.

Licence

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

image2patch-0.1.1.tar.gz (6.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

image2patch-0.1.1-py3-none-any.whl (6.5 kB view details)

Uploaded Python 3

File details

Details for the file image2patch-0.1.1.tar.gz.

File metadata

  • Download URL: image2patch-0.1.1.tar.gz
  • Upload date:
  • Size: 6.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.7.3

File hashes

Hashes for image2patch-0.1.1.tar.gz
Algorithm Hash digest
SHA256 3d5d0fcec807c84f5315e25f08c994f63fb2d5a30b76c5571705397f252f1f87
MD5 3738081491d62e30be4b97410cfdd047
BLAKE2b-256 b32620c7b534c47dc53ddd4bbe3f20e38f754f36b1bcf71473cfbc28ae3aa63e

See more details on using hashes here.

File details

Details for the file image2patch-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: image2patch-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 6.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.7.3

File hashes

Hashes for image2patch-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 c6934ba57b87ec6c0fff5e1639cce71dcf808d5829551fe50fc73f2c3081d2b3
MD5 fa146b106e064de01e34204191316661
BLAKE2b-256 ddcf86419abace2540f856d5022ef06ef7af7d629c5685c82e5c26a75fe2882b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page