LukasHedegaard/continual-inference
A Python library for Continual Inference Networks in PyTorch
This library helps machine learning engineers efficiently process continuous streams of data, like video or sensor readings, using deep neural networks. It takes a sequence of inputs, such as video frames, and produces real-time predictions without redundant calculations. This is for machine learning practitioners building systems that need to analyze data as it arrives, rather than waiting for entire batches.
No commits in the last 6 months. Available on PyPI.
Use this if you need to deploy deep learning models for real-time analysis on streaming data efficiently, avoiding the overhead of traditional sliding window methods.
Not ideal if your application primarily involves offline processing of complete datasets or if you are not working with deep neural networks.
Stars
56
Forks
12
Language
Python
License
—
Category
Last pushed
Mar 15, 2025
Commits (30d)
0
Dependencies
1
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/LukasHedegaard/continual-inference"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
aimagelab/mammoth
An Extendible (General) Continual Learning Framework based on Pytorch - official codebase of...
LAMDA-CL/PyCIL
PyCIL: A Python Toolbox for Class-Incremental Learning
GMvandeVen/continual-learning
PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR,...
LAMDA-CL/LAMDA-PILOT
🎉 PILOT: A Pre-trained Model-Based Continual Learning Toolbox
mmasana/FACIL
Framework for Analysis of Class-Incremental Learning with 12 state-of-the-art methods and 3 baselines.