Metadata-Version: 2.1
Name: pyamiimage
Version: 0.0.11
Summary: Image analysis for words and graphics.
Home-page: https://github.com/petermr/pyamiimage
Author: Peter Murray-Rust, Anuv Chakraborty
Author-email: petermurrayrust@googlemail.com
License: Apache2
Keywords: text and image mining
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
License-File: LICENSE

# pyamiimage
`pyamiimage` is a set of tools to extract semantic information from scientific diagrams. 

The current goal is to extract terpene synthase pathway diagrams. 
'Extraction' means that we will go from pixel values in an image to a 'smart diagram'. The output of `pyamiimage` is an image with annotations of substrate, products and enzymes.

We are working to add more support for open formats that encode chemical/pathway information such as [CML](https://www.xml-cml.org/) and [GPML](https://github.com/PathVisio/GPML).

## Installation

### Tesseract
To run `pyamiimage` on your local system you need to have `Tesseract` installed. If you don't have `Tesseract` installed, install it from [here](https://tesseract-ocr.github.io/tessdoc/).

```
pip install pyamiimage
```
## Usage

### AmiImage
AmiImage class provides methods for image manipulation. 
```
from test.resources import Resources
from pyamiimage.ami_image import AmiImage

biosynth2_path = Resources.BIOSYNTH_2
gray = AmiImage.create_grayscale_from_file(biosynth2_path)
```

### AmiGraph
AmiGraph class generate a graph from arrows in a diagram.

### AmiOCR
AmiOCR class provides methods to extract words from the iamge. Uses Tesseract.

## Timeline
merged main into nodes_and_pixels and re-branched 


