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List of OpenCV projects to further increase the computer vision community. Coding in Python & C++(In progress).
| Date | Stars |
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| 2026-07-31 | 404 |
| 2026-08-06 | 404 |
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# OpenCV_Projects This repository includes any projects that I have completed in research, projects, or online classes: [(Rajeev Ratan)](https://www.udemy.com/course/master-computer-vision-with-opencv-in-python/) and [Satya Mallick (CEO) AI OpenCV Bootcamp](https://opencv.org/courses/). My main focus is to study fields that cross over Machine Learning (Convolutionary Neural Network, Support Vector Machines, and Clustering of K-means), Computer Vision and Data Science. <img src="https://github.com/rchavezj/OpenCV_Projects/blob/master/OpenCV_CNN.png" width="864" height="260" /><img src="Sec08_Object_Tracking/05_Optical_Flow/dense_optical_flow_v2.gif" width="410" height="400"><img src="Sec11_Deep_Learning/01_Neural_Style_Transfer/n_style_transfer.gif" width="410" height="400"/><img src="https://github.com/rchavezj/OpenCV_Projects/blob/master/OpenCV_GIF.gif" width="864" height="270" /> # Contents: 1. [Basics of Computer Vision and OpenCV](#Basics-of-Computer-Vision-and-OpenCV) 2. [Image Manipulation and Processing](#Image-Manipulation-and-Processing) 3. [Image Segmentation and Contours](#Image-Segmentation-and-Contours) 4. [Object Detection Part 1: Intro](#Object-Detection-Part-1-Intro) 5. [Object Detection Part 2: Build a Face, people and Car Detectors](#Object-Detection-Part-2-Build-a-Face-people-and-Car-Detectors) 6. [Augmented Reality (AR): Facial Landmark Identification](#Augmented-Reality-AR-Facial-Landmark-Identification) 7. [Simple Machine Learning using OpenCV](#Simple-Machine-Learning-using-OpenCV) 8. [Object Tracking and Motion Analysis](#Object-Tracking-and-Motion-Analysis) 9. [Computational Photography](#Computational-Photography) 10. [Self Driving Cars](#Self-Driving-Cars) 11. [Deep Learning](#Deep-Learning) # Sections: ### Basics of Computer Vision and OpenCV ### ([Return back to Contents](#Contents)) Image Processing. Learn some of the basics of image processing such as blurring an image, understanding image morphology, geometric transforms, and image histograms. </br> | | | | | :---: | :----: | :----: | | [OpenCV Intro](https://github.com/rchavezj/OpenCV_Projects/blob/master/Sec01_Basics_of_CV/01-Reading-Writing-and-displaying-images/01-Reading-Writing-and-displaying-images.ipynb)| <img src="https://github.com/rchavezj/OpenCV_Projects/blob/master/Sec01_Basics_of_CV/01-Reading-Writing-and-displaying-images/output.jpg" width="380" height="70" /> | Learn how to display a simple image </br> plt.imshow(cv2.cvtColor(input, cv2.COLOR_BGR2RGB))| | [Grayscaling](https://github.com/rchavezj/OpenCV_Projects/blob/master/Sec01_Basics_of_CV/02-Grayscaling/02-Grayscaling.ipynb) | <img src="https://github.com/rchavezj/OpenCV_Projects/blob/master/Sec01_Basics_of_CV/02-Grayscaling/Grayscale.jpg" width="90" height="70" />| Grayscaling is a very popular technique in computer vision to find the gradient on edge points of an image. | | [Colors HSV-Hue](https://github.com/rchavezj/OpenCV_Projects/blob/master/Sec01_Basics_of_CV/03-Colors-HSV-Hue-Saturation-Value/03-Colors-HSV-Hue-Saturation-Value.ipynb) | <img src="https://github.com/rchavezj/OpenCV_Projects/blob/master/Sec01_Basics_of_CV/03-Colors-HSV-Hue-Saturation-Value/hsv_image.jpg" width="90" height="70" /> | Now we know how to convert BGR image to HSV, we can use this to extract a colored object. In HSV, it is more easier to represent a color than in BGR color-space. In our application, we will try to extract a blue colored object.| | [Colors Gray-RGB](https://github.com/rchavezj/OpenCV_Projects/blob/master/Sec01_Basics_of_CV/04-Colors-Gray-RGB/04-Colors-Gray-RGB.ipynb) | <img src="https://github.com/rchavezj/OpenCV_Projects/blob/master/Sec01_Basics_of_CV/04-Colors-Gray-RGB/merged_with_blue_amplified.jpg" width="90" height="70" /> | In OpenCV we can convert an RGB image into Grayscale by two ways: 1. By using cvtColor function. 2. By using imread function, where the first parameter specifies t
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