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Abstract representation of data for machine vision

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ps-nithin/pyrebel

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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. 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 runningpython3 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 runningpython3 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.The program expects a single pattern in the input image. Otherwise, a pattern has to be selected by changing variable 'blob_index' accordingly.

Docshere

Read more about abstractionhere

Let the data shine!


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