In general, check the crt/host_config.h file to find out which versions are supported.
Sometimes it is possible to hack the requirements there to get some newer versions working, too :)
Thrust version can be found in $CUDA_ROOT/include/thrust/version.h.
Download Archives: https://developer.nvidia.com/cuda-toolkit-archive
Release notes for CUDA Toolkit (CTK):
| #!/usr/bin/env python3 | |
| # Copyright (c) Microsoft Corporation. All rights reserved. | |
| # Licensed under the MIT License. | |
| """torchgeo model inference script.""" | |
| import argparse | |
| import os | |
| from typing import Any, Callable, Dict, Optional, Tuple, Type, cast |
| EPSG: 4326 uses a coordinate system on the surface of a sphere or ellipsoid of reference. | |
| WGS 84 - Earth as Geoid. -Mercator | |
| EPSG: 3857 uses a coordinate system PROJECTED from the surface of the | |
| sphere. Earth as perfectly sphere. -Web Mercator | |
| Think of it as this way: | |
| EPSG 4326 uses a coordinate system the same as a GLOBE (curved surface). | |
| EPSG 3857 uses a coordinate system the same as a MAP (flat surface). |
| import os | |
| import shutil | |
| src_dir = "./Files" | |
| dst_dir = "./Result" | |
| """ |
1. Rescale specfic bands and write them to output tiff
gdal_translate -ot Byte -b 5 -b 3 -b 2 -scale_1 0 1970 0 255 -scale_2 0 1860 0 255 -scale_3 0 1174 0 255 WV.TIF WV_RGB.TIF
We take bands 5 (red), 3 (green) and 2(blue), scale them to 8 bit range and write it to an output file. Things to note:
a. Output scale by default is 0 to 255, so there's no real reason to specify.
b. Once we pick the bands, they are thereafter referred w.r.t output. This is why we specify `scale_1` to rescale band 5 because band 5 in the input is band 1 of output.
| from json import load, dump | |
| from argparse import ArgumentParser | |
| from re import compile | |
| import sys | |
| import os | |
| parser = ArgumentParser(description="Group (merge) multiple GeoJSON files.") | |
| defaults = dict(outfile=sys.stdout) |
In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.
| # -*- coding:utf-8 -*- | |
| import os | |
| import cv2 | |
| import json | |
| import pprint | |
| import numpy as np | |
| from PIL import Image | |
| category_dict = {'plane': 0, 'ship': 1, 'storage-tank': 2, 'baseball-diamond': 3, 'tennis-court': 4, 'basketball-court': 5, | |
| 'ground-track-field': 6, 'harbor': 7, 'bridge': 8, 'small-vehicle': 9, 'large-vehicle': 10, |