CourseNana | Computer Vision

COMP338 Computer Vision - Assignment 1- Canny Edge Detection, Feature Extraction

COMP338Computer VisionPythonCanny Edge Detection Feature Extraction

OpenCV provides a function canny() to get the edge detection result with an image (you can use any grey image). Please do the following: (25 marks) Reimplement the canny operation without using the built-in canny() function (with some explanations of the code). (10 marks) Test and visualize your implementation results. (with different filters, different thresholds and others) (15 marks) Discuss the difference between your implementation, your results compared with the OpenCV implementation. (Compare the numerical results and the running time and others.)

159731 Studies in Computer Vision - Assignment 3: Video Stabilisation

159731Studies in Computer VisionVideo StabilisationC++OpenCV

Your task for this assignment is to write a program to perform video stabilisation. On stream is a short video shot with no video stabilisation. For this assignment you must write a C++ program using OpenCV to produce a stabilised video. You will need to find cumulative homography matrices for a number of sequential frames

159731 Studies in Computer Vision - Assignment 2: 2D barcode

159731Studies in Computer VisionC++OpenCV2D barcode

Your task is to write a program that reads a colour 2D barcode. The 2D barcodes may be rotated, scaled and slightly distorted and use a simple encoding with 8 colours. The colours are black, blue, green, cyan, red, magenta, yellow, and white. These colours represent three bits.

FIT5225 Cloud computing and security 2024 SM1 Assignment 1: CloudDetect

FIT5225Cloud computing and securityCloudDetectPython

This project aims to build a web-based system that we call CloudDetect. It will allow end-users to send an image to a web service hosted by Docker containers and receive a list of objects detected in their uploaded image. The project will make use of the YOLO (You Only Look Once) library, a state-of-the- art real-time object detection system, and OpenCV (Open-Source Computer Vision Library) to perform the required image operations/transformations.

ENGN4528 Computer Vision Assignment 2 (CLab2) : Harris Corner Detection

ENGN4528Computer VisionHarris Corner DetectionDeep LearningDeep Neural NetworksPython

The goal of this assignment is to develop and assess proficiency at mid-level image processing, including corner detection, and deep learning techniques, including domain adaptation for deep neural networks.

COMP52615 Computer Vision Assignment: Detection of a badminton court and then players on the court

COMP52615Computer VisionPython

In this assignment, you are asked to implement software for the detection of a badminton court and then players on the court. You are then asked to track the players on the court. Data are provided, read the instructions on how to get hold of the dataset in the dedicated section. Image frames of a video clip of two international badminton matches have been zipped.

MAEG5720 Computer Vision in Practice - Mini-Project2: Panorama

MAEG5720Computer Vision in Practicepanorama

The field of view of the image is limited by your lens. However, we could solve this issue by combining multiple images together to form a panorama. The aim of this assignment is to automatically stitch the images acquired by a panning camera.

Introduction to Computer Vision (ECSE 415) Assignment 5: Segmentation

ECSE 415Introduction to Computer VisionSegmentation

In this section, you will be asked to compute image segmentations by using several basic clustering techniques. Clustering is used to determine the class of each pixel, and the result can be different depending on the feature space. The images for this part are placed under the same dictionary.

CS 6476: Computer Vision - Final Project Overview and Topics List

CS 6476Computer VisionPython

For the final project you will apply knowledge that you have learned in class plus additional research to build a computer vision system that achieves near state-of-the-art results in an area you select.