thomas0809/RxnScribe
A Sequence Generation Model for Reaction Diagram Parsing
This tool helps chemists and chemical researchers automatically extract detailed information from reaction diagrams found in papers or textbooks. You input an image file containing one or more chemical reaction diagrams, and it outputs structured data listing reactants, products (with their chemical structures like SMILES or Molfile), and reaction conditions detected within the diagram. This is ideal for researchers who need to digitize chemical reactions for databases or further computational analysis.
107 stars. No commits in the last 6 months.
Use this if you need to quickly and accurately convert images of chemical reaction diagrams into machine-readable chemical data.
Not ideal if you are looking for a tool to draw or synthesize chemical reactions rather than parse existing diagrams.
Stars
107
Forks
32
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Sep 18, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/thomas0809/RxnScribe"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
deepmodeling/deepmd-kit
A deep learning package for many-body potential energy representation and molecular dynamics
chemprop/chemprop
Message Passing Neural Networks for Molecule Property Prediction
mir-group/nequip
NequIP is a code for building E(3)-equivariant interatomic potentials
Acellera/moleculekit
MoleculeKit: Your favorite molecule manipulation kit
CederGroupHub/chgnet
Pretrained universal neural network potential for charge-informed atomistic modeling...