How to use OpenCV with GPU on Colab?

How to use OpenCV with GPU on Colab?

How to use OpenCV with GPU on Colab? In this article, I will share how I set up the Colab environment for OpenCV’s dnn with GPU in just a few lines of code.

OpenCV’s ‘Deep Neural Network’ (dnn) *module is a convenient tool for computer vision, it is very easy to apply some techniques such as Yolo and OpenPose. However, the major drawback of OpenCV was the lack of GPU support, resulting in slow inference. Luckily since *OpenCV 4.2, NVIDIA GPU/CUDA is supported.

It still required some works to use GPU, you can check Pyimagesearch’s article here, they demonstrate how to set up a Ubuntu machine.

If you do not have a machine with GPU like me, you can consider using Google Colab, which is a free service with powerful NVIDIA GPU. It is also a lot easier to set up, most of the requirements are already satisfied. In this article, I will share how I set up the Colab environment for OpenCV’s dnn with GPU in just a few lines of code. You can also check here, I made slight changes based on the answer.

The code to assign the dnnto GPU is simple:

import cv2
net = cv2.dnn.readNetFromCaffe(protoFile, weightsFile)
net.setPreferableBackend(cv2.dnn.DNN_BACKEND_CUDA)
net.setPreferableTarget(cv2.dnn.DNN_TARGET_CUDA)

However, if you run this cell directly on Colab, you will see this error:

Image for post

computer-vision programming deep-learning data-science opencv

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

Applications Of Data Science On 3D Imagery Data

The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.

Why you should learn Computer Vision and how you can get started

A few compelling reasons for you to starting learning Computer. In today’s world, Computer Vision technologies are everywhere.

Deep Learning — not only for the big ones

How you can use Deep Learning even for small datasets. When you’re working on Deep Learning algorithms you almost always require a large volume of data to train your model on.

Data Science Course in Dallas

Become a data analysis expert using the R programming language in this [data science](https://360digitmg.com/usa/data-science-using-python-and-r-programming-in-dallas "data science") certification training in Dallas, TX. You will master data...

PyTorch for Deep Learning | Data Science | Machine Learning | Python

PyTorch is a library in Python which provides tools to build deep learning models. What python does for programming PyTorch does for deep learning.