ChartReader and GraphMaster

ChartReader
36
Emerging
GraphMaster
34
Emerging
Maintenance 0/25
Adoption 10/25
Maturity 8/25
Community 18/25
Maintenance 0/25
Adoption 6/25
Maturity 16/25
Community 12/25
Stars: 128
Forks: 22
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: —
Stars: 19
Forks: 3
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
No License Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About ChartReader

Cvrane/ChartReader

Fully automated end-to-end framework to extract data from bar plots and other figures in scientific research papers using modules such as OpenCV, AWS-Rekognition.

This tool helps researchers, scientists, and data analysts extract numerical data from various types of charts and figures found in scientific papers. It takes images of bar plots, line graphs, and other common visualizations as input and outputs the underlying data points, axes labels, and legend information. This is ideal for anyone needing to digitize graphical data for further analysis or replication.

scientific-research data-extraction literature-review graph-analysis research-data

About GraphMaster

MasterAI-EAM/GraphMaster

Fully automated end to end framework to extract data from complex charts and other figures in scientific literature.

This tool helps researchers and scientists extract numerical data from charts and figures embedded within scientific PDF literature. It takes a scientific PDF document as input and automatically identifies, extracts, and digitizes data points from complex graphs, outputting them into a structured CSV format. Researchers can then use this data for further analysis without manual transcription.

scientific-research data-extraction literature-review graph-digitization research-automation

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