Skip to main content

The installation saga of opencv

 Introduction:

The day is a sunday and I reluctantly was checking with one of my interns about the opencv project I have been helping them complete. She, rohini, told me, that she is finding a "dll error: module not found" type error in opencv video operation. Now, at this point I decided to solve this issue by creating a fresh venv and downloading the files, run them and resolve. And hence starts the issues.

Naive-enough:

The naive me, tried to download opencv saying pip3 install opencv. That sadly ends in a 404 error from pypi; as the project is actually under the name opencv-python. Now, I write pip3 install opencv-python; some downloads start; but it again stops with the statement, 'ModuleNotFoundError: No module named 'skbuild'. Big oof! 

So figures out.. skbuild is not some module to download. It is getting caused because of pip3 versioning. The solution to this issue is found from the github issue here; which is upgrade your pip using

pip3 install --upgrade pip 

and then install opencv using 

pip3 install opencv-python

This time I successfully installed opencv-python-4.4.0.46. Now, let's try to recreate the dll error. Now the most important thread regarding this seems to be the following github issue on tensorflow. It seems that in windows, there is a compatibility issue between tensorflow, cuda and cudnn's different versions. The possible solution is to find out which one supports which and then resolve the conflicts by downgrading/upgrading either one of them.

Now, that above thread is applicable for tensorflow <1.11.0. For 1.13, 1.14; use this thread to read and understand the suggestion.The solution regarding this is again the same, as of to use specific supported versions of cuda (10.0) against tf 1.13 and 1.14; as well as to add cuda and cudnn to the environment path. 

So this is the small story related to opencv installation hazards and cuda, cudnn compatibility. Let me know if these helped, otherwise, I may help you dig more into the issues and resolve such issues.

Comments

Popular posts from this blog

20 Must-Know Math Puzzles for Data Science Interviews: Test Your Problem-Solving Skills

Introduction:   When preparing for a data science interview, brushing up on your coding and statistical knowledge is crucial—but math puzzles also play a significant role. Many interviewers use puzzles to assess how candidates approach complex problems, test their logical reasoning, and gauge their problem-solving efficiency. These puzzles are often designed to test not only your knowledge of math but also your ability to think critically and creatively. Here, we've compiled 20 challenging yet exciting math puzzles to help you prepare for data science interviews. We’ll walk you through each puzzle, followed by an explanation of the solution. 1. The Missing Dollar Puzzle Puzzle: Three friends check into a hotel room that costs $30. They each contribute $10. Later, the hotel realizes there was an error and the room actually costs $25. The hotel gives $5 back to the bellboy to return to the friends, but the bellboy, being dishonest, pockets $2 and gives $1 back to each friend. No...

Deep Learning by Ian GoodFellow, Yoshua Bengio and Aaron courville Review

History: I have been reading deep learning topics from a number of resources like machine learning mastery by Jason Brawlee, Analyticsvidhya, and other blog resources. But the problem has stayed, the problem of inconsistency in the knowledge. Therefore, I have decided to now sit down, and go through a deep learning book thoroughly. And what better name for deep learning other than Ian Goodfellow! So I have found this book named Deep Learning by Ian Goodfellow. Introduction: Plan for this post is reviewing and rewriting the topics from the book, in simpler language and for sharing the pieces of knowledge with my readers. I will update this post continuously as I proceed with the reading also. So ideally this post is broadly about basic to advanced deep learning material discussion. Sponsored Ads Learn deep learning in python with Udemy   Different parts of the book and purpose of them: This book has three parts,which talks about (1) applied mathematics and machine learni...

Pyarabic: python package for Arabic language

 Introduction:  In languages which are non-english and non-european as well, NLP work has progressed slowly in the last few decades because of the lesser number of scholars working on them as well as a lack of global interest in them. But now the time has changed and people from all over the world are collaborating on these lesser explored libraries and they are building resources for working on these languages with the same ease with that of english.  Pyarabic is a package created from such a similar effort which deals with the intricate details of the arabic language and helps processing all kinds of arabic texts. While trying to learn it, being from a non-arab background, I couldn't read lots of parts of the main readthedocs site and had to work my around it. So in this blog post, I will summarize my learnings in english language, so that you can learn it and use the package with much more ease than me. [Credit where credit is due: this article heavily uses the ac...