PySIFT

GPU-Resident Deterministic SIFT for Deep Learning Vision Pipelines

arXiv Paper GitHub Code pip install staysift Kaggle Tutorial Kaggle Competition

A pure-Python, GPU-resident SIFT implementation that matches OpenCV SIFT accuracy while running 26% faster end-to-end with 4x matching speedup. Zero-copy DLPack interop keeps tensors on the GPU across the full pipeline.

Benchmark	Metric	PySIFT vs OpenCV
HPatches	MMA@10	+2.2pp
IMC Phototourism	Inliers/pair	303 vs 205 (+47%)
MegaDepth-1500	AUC@10	+5.6pp
ROxford5K	mAP	+7.5pp

Quick Start

pip install staysift
from pysift import PySIFT
sift = PySIFT()
keypoints, descriptors = sift.detectAndCompute(gray_image)

Try It: Interactive SIFT Matching

This demo runs OpenCV SIFT on CPU for compatibility. For GPU-accelerated matching, install staysift locally with a CUDA GPU.

Matches

Built by Sivakumar K S at IIT Madras. Read the paper for full details.