Skip to main content

A pure python library that implements abstraction of data.

Project description

pyrebel

A pure python library that implements abstraction of data.

Installation

From PyPI

python3 -m pip install --upgrade pyrebel

From source

git clone https://github.com/ps-nithin/pyrebel
cd pyrebel
python3 -m pip install .

Running demo programs

Demo programs are found in 'demo/' directory.
cd demo/

1. Image abstraction demo

Usage:
python3 pyrebel_main.py --input <filename.png>

Optional arguments
--abs_threshold <value> Selects the threshold of abstraction. (Defaults to 5)

For example,
python3 pyrebel_main.py --input images/abc.png --abs_threshold 10

The output is written to 'output.png'

2. Edge detection demo

This is a demo of edge detection achieved using data abstraction.
Usage:
python3 pyrebel_main_edge.py --input <filename>

For example,
python3 pyrebel_main_edge.py --input images/wildlife.jpg

The output is written to 'output.png'. Below is a sample input image,


Below is the output image,

3. 2D sketch demo

This is a demo of 2D sketch formation using data abstraction.
Usage:
python3 pyrebel_main_vision.py --input <filename>

Optional arguments for tweaking the result,

  1. --edge_threshold <value> Selects the threshold of edge detection.(Defaults to 5)
  2. --abs_threshold <value> Selects the threshold of output abstraction. (Defaults to 10)
  3. --bound_threshold <value> Selects the threshold of boundary size. (Defaults to 100)

For example,
python3 pyrebel_main_vision.py --input images/lotus.jpg

Below is a sample input image,


Below is the output image,

4. Abstract painting

This is a demo of abstract painting using data abstraction. The output of edge detection is painted to obtain the desired output.
Usage:
python3 pyrebel_main_paint.py --input <filename>

Optional arguments for tweaking the result,

  1. --edge_threshold <value> Selects the threshold of edge detection. (Defaults to 10).
  2. --paint_threshold <value> Selects the threshold of painting. (Defaults to 5).
  3. --block_threshold <value> Selects the threshold of block size. (Defaults to 20).

    For example,
    Running python3 pyrebel_main_paint.py --input images/elephant.jpg --edge_threshold 10 --block_threshold 50 --paint_threshold 1

    Below is the sample input image,


    Below is the output image,

5. Pattern recognition demo

This is a demo of pattern recognition achieved using data abstraction.

  1. Learning
    Usage: python3 pyrebel_main_learn.py --learn /path/to/image/directory/
    For example running python3 pyrebel_main_learn.py --learn images/train-hand/ learns all the images in the directory and links the filename with the signatures.

  2. Recognition
    Usage: python3 pyrebel_main_learn.py --recognize <filename>
    For example running python3 pyrebel_main_learn.py --recognize images/recognize.png displays the symbols recognized in the file 'images/recognize.png'.

To reset the knowledge base just delete file 'know_base.pkl' in the current working directory.

Docs here

Read more about abstraction here

Let the data shine!

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

pyrebel-1.2.0.tar.gz (30.1 kB view details)

Uploaded Source

File details

Details for the file pyrebel-1.2.0.tar.gz.

File metadata

  • Download URL: pyrebel-1.2.0.tar.gz
  • Upload date:
  • Size: 30.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.12

File hashes

Hashes for pyrebel-1.2.0.tar.gz
Algorithm Hash digest
SHA256 bbd7d465c879ee1fb506b15f3068b687aa812824bbae8156f221fe5ed93c61d8
MD5 d2e3513d5ca0060a934639957571c916
BLAKE2b-256 0b6d5777b044bf7c17a5e2bec33f0362634b97455655d33d465fa1cf49e24096

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