Windows 10: opencv installation failed

>>> import cv2
** On entry to DGEBAL parameter number 3 had an illegal value
** On entry to DGEHRD parameter number 2 had an illegal value
** On entry to DORGHR DORGQR parameter number 2 had an illegal value
** On entry to DHSEQR parameter number 4 had an illegal value
Traceback most recent call last:
File "C:\Python\Python39\lib\site-packages\numpy\__init__.py", line 305, in <module>
_win_os_check
File "C:\Python\Python39\lib\site-packages\numpy\__init__.py", line 302, in _win_os_check
raise RuntimeErrormsg.format__file__ from None
RuntimeError: The current Numpy installation 'C:\\Python\\Python39\\lib\\site-packages\\numpy\\__init__.py' fails to pass a sanity check due to a bug in the windows runtime. See this issue for more information: https://tinyurl.com/y3dm3h86
Traceback most recent call last:
File "<stdin>", line 1, in <module>
File "C:\Python\Python39\lib\site-packages\cv2\__init__.py", line 5, in <module>
from .cv2 import *

:)

 

KB4025339 Fails Install 0x80070564

Thanks
I am trying Eagle 51's suggestions now. Windows Update troubleshooter found a bunch of errors and fixed all but one.The update is trying to download KB4025339 again. I'll see what happens. At step one troubleshooter finishes with one error unresolved "Potential Windows Update Database Error Detected-Not Fixed". Windows update stalled at 0%.

At step 2 same troubleshooter error. The KB finished a new download failed to install.
Did step 3 KB has downloaded but fails to install.

If Eagle's suggestion doesn't work I'll try EdTittel's suggestion

Tried bothe Eagle & Ed 's suggestions - do not work. Anyone else?

I have noticed that the latest update for my nvidia drivers has failed to update. Wondering about that!

 

Windows Updates failed to instal

I just did step one and they have just all installed.... thank you so much.... it was quite frustrating having that update window pop up every 5 minutes and failing to instal every time

Thanks mate

 

NVIDIA Adds GPU Acceleration for OpenCV Application Development

NVIDIA today announced CUDA support for OpenCV, the popular Computer Vision library used in developing advanced applications for the robotics, automotive, medical, consumer, security, manufacturing, and research fields.

With the addition of GPU acceleration to OpenCV, developers can run more accurate and sophisticated OpenCV algorithms in real-time on higher-resolution images while consuming less power. This will facilitate the development of scores of new, mainstream Computer Vision applications.

With thousands of developers and well over two million downloads to date, OpenCV is a popular Computer Vision library for the development of computational-intensive and powerful applications, many of which require robust real-time performance. For example, the new OpenCV depth calculation engine performs 5-10 times faster with GPU acceleration than with the equivalent CPU-only implementation.

"Computational power in Computer Vision has been a limiting factor not only for the use of recent powerful algorithms in object recognition, tracking and 3D reconstruction, but also has limited the creativity of algorithms people are willing to invent," said Gary Bradski, senior researcher at Willow Garage, and founder of OpenCV. "With CUDA GPU acceleration, many OpenCV algorithms will run five to ten times faster, making current algorithms more practical for application developers and allowing the invention and combination of more capable applications in the future."

"NVIDIA GPU acceleration of OpenCV now supplies the computational power for the sophisticated algorithms needed for advanced automotive driver assistance applications, and other popular consumer applications," said Taner Ozcelik, general manager of NVIDIA's automotive business. "OpenCV gives developers the toolbox they need to quickly unleash this power for research and development of these products without needing to recreate vision algorithms from scratch. This is a key milestone that could usher in a significant increase in the use of Computer Vision across a broad range of industries."

An initial release of OpenCV with CUDA GPU support for many common and powerful functions is expected to be available in the Spring 2011. Some initial GPU-enabled OpenCV functionality is currently available via the OpenCV source code repository.

"My research lab uses OpenCV extensively in our autonomous vehicles," said Sebastian Thrun, professor of computer science and electrical engineering at Stanford University. "CUDA GPU acceleration for OpenCV provides my research team an instant performance bump which is critical in our research. OpenCV and CUDA will dramatically increase what is possible with computer vision in our autonomous vehicles."

OpenCV Sessions at GTC (Sept. 20-23)
With more than 280 hours of GPU-focused sessions and more than 25 sessions on CUDA C/C++ development, NVIDIA's GPU Technology Conference (GTC) provides a wealth of information on GPU computing news, developments and achievements. GTC also includes presentations discussing OpenCV on GPUs, including the keynote address on Sept. 23 by Sebastian Thrun, a robotics pioneer at Stanford University, who leveraged OpenCV in the development of his DARPA award-winning robotics technology.

For more information on GTC and relevant OpenCV sessions, please visit: this page.