📓 DeepLearning and CV notes.

Ready to run Jupyter notebook docker image with Python 3.9, OpenCV 4 and more

Run a Jupyter Notebook to detect, track, and count cars in a video using Maximo Visual Insights (formerly PowerAI Vision) and OpenCV

Projects & Notebooks of Coursera's Self-Driving Cars Specialization.

Basic OpenCV Projects like Face Detection, Contour, Edge Detection etc

From basics of Python to into to image processing

Python opencv notebooks using SIFT, SURF and feature matching using Brute-Force with ORB descriptors

Repositório dos exemplos e desafios utilizados na disciplina de Visão Computacional do curso de MBA Machine Learning da FIAP

opencv python examples in jupyter notebook

Projeto final de conclusão da disciplina de Visão Computacional voltado a auditoria de vídeo e construção de classificadores baseado em transfer learning.

This is a collection of Jupyter notebooks that is intended to provide an introduction to OpenCV's Python interface.

Beginners guide to interactive manipulation of satellite data with open cv

A Docker-based devcontainer for Jupyter Notebook's with a focus on Computer Vision, Machine Learning, Finance, Statistics and Visualization.

Welcome! This is a repository for adding your python projects, data analysis/data science projects or jupyter/kaggle notebooks.

Jupyter notebooks of different python packages like opencv, numpy, PIL (Pillow) etc

The Docker image including Ubuntu 18.04, Python 3.6, OpenCV 3.4.5 and Jupyter Notebook to explore computer-vision topics

This algorithm uses a rectangle made by the user to identify the foreground item. Then, the user can edit to add or remove objects to the foreground. Then, it removes the background and makes it transparent.

AI is Math course repo. Check out the website at: www.AIisMath.com

Computer vision container that includes Jupyter notebooks with built-in code hinting, Anaconda, CUDA 11.8, TensorRT inference accelerator for Tensor cores, CuPy (GPU drop in replacement for Numpy), PyTorch, PyTorch geometric for Graph Neural Networks, TF2, Tensorboard, and OpenCV for accelerated workloads on NVIDIA Tensor cores and GPUs.