Image Classifier built using Python, OpenCV. Using ORB for feature detection and knn matcher for matching the features.
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Updated
Jul 20, 2020 - Python
Image Classifier built using Python, OpenCV. Using ORB for feature detection and knn matcher for matching the features.
Map images to representation vectors.
Scale Invariant Feature Transform and Feature Matching
This reposetory contains codes to evaluate the extent of attenuation of shock waves.
Implementing the concept of Stereo Vision. We are given 3 different datasets, each of them containing 2 images of the same scenario but taken from two different camera angles. By comparing the information about a scene from 2 vantage points, we can obtain the 3D information by examining the relative positions of objects.
Computer vision small projects. Algorithms from scratch.
CMSC733 - Pipeline to reconstruct a 3D scene and simultaneously obtain the camera poses of a monocular camera w.r.t. the given scene
Stabilo is a Python package for stabilizing video frames or object trajectories using advanced transformation techniques. It supports user-defined masks to exclude specific areas, making it ideal for dynamic scenes with moving objects. Unlike traditional stabilization, it stabilizes content relative to a chosen reference frame.
A collection of scripts that handle and compare images based on terrain traversability estimation grid maps
Implementation of my MSc thesis work, entitled "Optical pose estimation in robotics applications"
A computer vision toolkit focused on color detection and feature matching using OpenCV. It allows you to easily start the picamera in case you're using a Raspberry PI
Match similar image features.
API for panoramer
Structure from Motion using a scratch implementation of Feature Matching, RANSAC for computing Fundamental Matrix, Triangulation, and Bundle Adjustment.<Completed>$
Create panorama from a sequence of images.
A face recognition system built using feature matching with local binary patterns.
This project involves stitching together four images taken from the different camera positions to create a panoramic image. The goal is to seamlessly merge the images together so that the resulting panoramic image looks like a single, continuous image.
This repository consists of two major components for a project called E-waste recycling system. One component is used to generate a labelled dataset to train U-Net segmentation network. The second component is used to perform non-rigid registration using Demon's algorithm.
Using OpenCV to match features and identify an object.
Make Rendered Database using Rendered Image Obtained by Trained Gaussian Splatting
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