edadaltocg/detectors
Python package to accelerate research on generalized out-of-distribution (OOD) detection.
This library helps machine learning researchers quickly compare different methods for identifying unusual data points that a model hasn't been trained on (out-of-distribution detection). It takes in various models and datasets, then applies different detection techniques to them. The output provides benchmark results and evaluations, allowing researchers to develop and test new OOD detection methods efficiently.
No commits in the last 6 months. Available on PyPI.
Use this if you are a machine learning researcher focused on developing, evaluating, or comparing generalized out-of-distribution detection techniques for computer vision models.
Not ideal if you need OOD detection for non-computer vision data types, or if you are looking for a plug-and-play solution for production systems rather than a research tool.
Stars
15
Forks
1
Language
Python
License
Apache-2.0
Category
Last pushed
Jun 19, 2024
Commits (30d)
0
Dependencies
16
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/edadaltocg/detectors"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
yzhao062/pyod
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
unit8co/darts
A python library for user-friendly forecasting and anomaly detection on time series.
elki-project/elki
ELKI Data Mining Toolkit
raphaelvallat/antropy
AntroPy: entropy and complexity of (EEG) time-series in Python
Minqi824/ADBench
Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.