CUDA accelerated SIFT in Python
This library is a wrapper around PopSift to compute SIFT keypoints and descriptors on the GPU using CUDA. It's written to be a drop-in replacement for existing OpenCV functions such as cv2.FeatureDetector_create('SIFT') and cv2.DescriptorExtractor_create('SIFT').
Requirements:
- CUDA Toolkit >= 7
- CMake >= 3.14
- A C++11 capable compiler (g++ 5.4.0 works fine)
# git clone --recurse-submodules https://github.com/uav4geo/pypopsift
# cd pypopsift && mkdir build && cd build
# make -j8
To install the Python package:
# cd pypopsift
# pip install .
import cv2
import numpy as np
from pypopsift import popsift
filename = "/path/to/image.JPG"
config = {
'sift_peak_threshold': 0.1,
'sift_edge_threshold': 10.0,
'feature_min_frames': 8000,
'feature_use_adaptive_suppression': False,
'feature_process_size': 2048
}
def resized_image(image, config):
"""Resize image to feature_process_size."""
max_size = config['feature_process_size']
h, w, _ = image.shape
size = max(w, h)
if 0 < max_size < size:
dsize = w * max_size // size, h * max_size // size
return cv2.resize(image, dsize=dsize, interpolation=cv2.INTER_AREA)
else:
return image
flags = cv2.IMREAD_COLOR
image = cv2.imread(filename, flags)
if image is None:
raise IOError("Unable to load image {}".format(filename))
if len(image.shape) == 3:
image[:, :, :3] = image[:, :, [2, 1, 0]]
assert len(image.shape) == 3
image = resized_image(image, config)
image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
points, desc = popsift(image.astype(np.uint8), # values between 0, 1
peak_threshold=config['sift_peak_threshold'],
edge_threshold=config['sift_edge_threshold'],
target_num_features=config['feature_min_frames'])
print(points.shape)
print(points)
print(desc.shape)
print(desc)
Mozilla Public License 2.0
@inproceedings{Griwodz2018Popsift,
author = {Griwodz, Carsten and Calvet, Lilian and Halvorsen, P{\aa}l},
title = {Popsift: A Faithful SIFT Implementation for Real-time Applications},
booktitle = {Proceedings of the 9th {ACM} Multimedia Systems Conference},
series = {MMSys '18},
year = {2018},
isbn = {978-1-4503-5192-8},
location = {Amsterdam, Netherlands},
pages = {415--420},
numpages = {6},
doi = {10.1145/3204949.3208136},
acmid = {3208136},
publisher = {ACM},
address = {New York, NY, USA},
}