Skip to main content

Memories

PyPi Documentation Status License Language grade: Python Downloads

Description

Memories is an easy to use package that helps to seperate clustered images from files and helps add metadata to files. The documentation is in progress and can be found here.

Installation

$ pip install memories

How to Use:

There are 8 functions for the time being:

  • open_image: Returns the Image object to you so that it can be passed around to other functions
  • divided_crop: Takes 3 inputs, the path to the image, the path where the outful folder should be and the number of images present in the input file. It performs the task of dividing a single image into multiple smaller ones.
  • add_date: Takes input as the image path and the datetime to be added. it will add date when the image was originally taken.
  • bulk_add_date: Same as addDate, except it will add date to all images in a folder. The inputs are the folder path and datetime.
  • save_image: Converts a single image into another format
  • make_page: Creates a year book like page in HTML
  • make_border: Creates a border around the image
  • rotate_image: Returns a rotated image

Example

import memories

# Add meta data to images
memories.add_date("./image-1.jpg", "27/04/2021 12:00:03")
memories.bulk_add_date("./", "27/04/2021 12:00:03")

memories.make_page(["./folder1/image1.png", "./folder2/image2.jpg"], ["CSS", "Larry"], ["SASS", "Another line"], "./save_folder")

image = memories.open_image("./image.png")

memories.divided_crop(image, image_quantity = 6, bgr_value = [255, 255, 255])
# Normal squared borders
memories.make_border(image, "normal", bgr_value = [255, 255, 255], border_dimensions = [100, 100, 100, 100])
# Curved borders
memories.make_border(image, "curved", bgr_value = [255, 255, 255], border_dimensions = [100, 100, 100, 100], radius_dimensions = [100, 100, 100, 100])

memories.save_image("image.png", "path/to/save_folder/file.extention")
# Save multiple images at once
memories.save_image(["img-1.png", "img-1.jpg", "img-2.jpg"], "path/to/save_folder/file.extention")
# Save multiple images as a pdf
memories.save_image(["img-1.png", "img-1.jpg", "img-2.jpg"], "path/to/save_folder/file.pdf")

Features

Current features that are present are:

  1. Crop out basic implementation
  2. Add Date and time metadata
  3. Save as PDF, PNG, JPG
  4. Basic Scrapbook implmentation
  5. Documentation
  6. Border

Future features can also be found here:

  1. Collage
  2. Image Age identifyer

License

This software is released under the MIT license, see LICENSE.txt.

Release files for memories 1.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for memories 1.0.1
File Size Uploaded
memories-1.0.1.tar.gz 4.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for memories 1.0.1
File Interpreter ABI Platform
memories-1.0.1-py3-none-any.whl Python 3 none any Details

Total release size: 7.7 kB

Release files / memories-1.0.1.tar.gz

Download URL memories-1.0.1.tar.gz
Size 4.1 kB
Tags Source
SHA-256 checksum
How to use checksums
49343cdae6f150d83022de3079786871fc53ac05341d566bd5278a2fbb49e7c4
BLAKE2b-256 checksum
How to use checksums
7220370b13632c1932b5e6a91de9710651a580843249b7eb854f76f90cf36895
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

Release files / memories-1.0.1-py3-none-any.whl

Download URL memories-1.0.1-py3-none-any.whl
Size 3.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
69d779d59304d333cb61be13b150878bbf98976b959bac99f267286fc65ef868
BLAKE2b-256 checksum
How to use checksums
604256746d3434923f62196835feb2b50fa094555fc7b9425f5cbffeb1b2a86a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

Release history Release notifications | RSS feed

This release

1.0.1 This release

2 release files

1.0.0

2 release files

0.9

2 release files

0.8

2 release files

0.7

2 release files

0.6

2 release files

0.5

2 release files

0.4

1 release file

0.3

1 release file

0.2

1 release file

0.1

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page