GPU-Resident Deterministic SIFT for Deep Learning Vision Pipelines
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 |
pip install staysift
from pysift import PySIFT
sift = PySIFT()
keypoints, descriptors = sift.detectAndCompute(gray_image)