ycchen218/EDA-DRC-Prediction
This is a deep-learning based model for Electronic Design Automation(EDA), predicting the Design Rule Check (DRC) violation location.
This tool helps chip designers and layout engineers quickly identify potential Design Rule Check (DRC) violations in electronic circuit designs. By inputting design data, it predicts specific locations where manufacturing rules might be broken. This allows engineers to proactively address issues before physical fabrication.
No commits in the last 6 months.
Use this if you need to rapidly pinpoint areas in your electronic circuit layouts that are likely to fail Design Rule Checks, helping you accelerate the design iteration process.
Not ideal if you require a comprehensive design rule verification system that also performs rule correction, as this tool focuses solely on predicting violation locations.
Stars
13
Forks
4
Language
Python
License
—
Category
Last pushed
Jun 24, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/ycchen218/EDA-DRC-Prediction"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
torchgeo/torchgeo
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
terrastackai/terratorch
A Python toolkit for fine-tuning Geospatial Foundation Models (GFMs).
DataverseLabs/pyinterpolate
Kriging | Poisson Kriging | Variogram Analysis
OSGeo/grass
GRASS - free and open-source geospatial processing engine
sentinel-hub/eo-learn
Earth observation processing framework for machine learning in Python