Metadata-Version: 2.1
Name: imgraph
Version: 0.0.7
Summary: Graph Neural Network Library Built On Top Of  PyTorch and PyTorch Geometric
Author-email: Aryan Singh <aryan.singh@ul.ie>
Project-URL: homepage, https://aryan-at-ul.github.io
Project-URL: documentation, https://aryan-at-ul.github.io
Project-URL: repository, https://github.com/aryan-at-ul/imgraph.git
Keywords: deep-learning,pytorch,geometric-deep-learning,graph-neural-networks,graph-convolutional-networks,gnn-on-images,convert image to graph
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: graphgym
Provides-Extra: modelhub
Provides-Extra: full
Provides-Extra: benchmark
Provides-Extra: test
Provides-Extra: dev
License-File: LICENSE.txt

# IMGRAPH 

### Used for converting image to graph, uses superpixel method for node creation, extract features from CNN models. 

Example Usage: 

```
from imgraph.pipeline import create_graph_pipleline

path = "path/to/image"

create_graph_pipleline(path, 'classification', 'rag', 'resnet18', 10)

```

### Above code will create a graph from the image and save it in the directory .~/cache/imgraph or directory specified by the user in enviornment variable IMGRAPH_HOME.

### The graph will be saved in the PyG Data format or pickle format.




