Visual Annotation Toolkit for Ultralytics YOLO
Overview
The Ultralytcis ecosystem ships with a lightweight Annotator utility that can overlay detection masks, bounding boxes, oriented boxes, and keypoints on any image or video stream. The snippets below demonstrate typical use-cases.
Interactive sweep counter on a video
The following example tracks every object that crosses a user-draggable ...
Posted on Wed, 24 Jun 2026 16:42:36 +0000 by neex1233
Zhang Zhengyou Camera Calibration Workflow
Data Storage in OpenCV
OpenCV provides flexible data storage through the InputArrayOfArrays interface, which can be implemented by various types: Mat, Mat_<T>, Mat_<T, m, n>, vector<T>, vector<vector<T>>, and vector<Mat>.
Consider vector<vector<T>> as an example: the outer vector holds elements (i ...
Posted on Mon, 22 Jun 2026 18:02:21 +0000 by ericw
CycleGAN Implementation for Unpaired Image Translation
CycleGAN Architecture Overview
CycleGAN enables unpaired image-to-image translation using cycle-consistent adversarial networks. This approach learns mappings between domains without requiring paired training examples, making it suitable for style transfer applications like converting apples to oranges.
Dataset Preparation
The dataset consists ...
Posted on Sat, 20 Jun 2026 17:38:35 +0000 by mrjam
Computer Vision Bounding Box Operations
When resizing images in computer vision applications, bounding box coordinates must be scaled proportionally to maintain accurate object detection.
import cv2
import numpy as np
from ultralytics.utils.ops import scale_boxes
# Load the original image
original_image = cv2.imread("sample_images/vehicle.jpg")
original_height, original_w ...
Posted on Fri, 12 Jun 2026 16:37:48 +0000 by chancho
Gradient Reparameterization-Based RepOptimizer: Core Principles and Implementation Details
Neural network architecture design encodes domain prior knowledge into model structures. For example, residual connections that model feature transformation as (y = f(x) + x) deliver better performance than plain (y=f(x)) mappings, which ResNet implements via shortcut paths. While architectural design has continuously evolved to integrate lates ...
Posted on Sat, 30 May 2026 21:45:51 +0000 by sonehs
Various Attention Mechanisms for YOLO Series: SE, A2-Nets, BAM, and BiFormer
Attention mechanisms have significantly improved the performance of deep learning models in computer vision tasks. This article provides an overview of several popular attention modules that can be easily integrated into object detection models like YOLOv5, YOLOv7, YOLOv8, YOLOv9, and YOLOv10.
SE
Paper: Squeeze-and-Excitation Networks
Link: arX ...
Posted on Fri, 22 May 2026 19:06:16 +0000 by sheephat
Implementation of the Lucas-Kanade Pyramid Optical Flow Method in MATLAB
MATLAB Function for Pyramid-Based LK Optical Flow
This article presents a complete MATLAB implementation of the Lucas-Kanade (LK) optical flow algorithm using a pyramidal (coarse-to-fine) approach. The function estimates the apparent motion vector field between two successive grayscale image frames.
Main Algorithm Function
function [flowX, flow ...
Posted on Fri, 15 May 2026 12:24:19 +0000 by Brandito520
Building a Deepfake Image Detector with EfficientNet and PyTorch
Detecting manipulated media generated by deeppfake algorithms is a pressing challenge. This article presents an end-to-end pipeline for training a binary image classifier that distinguishes real faces from synthetically generaetd ones using EfficientNet, PyTorch, and the timm library.
Task Overview and Data Format
The objective is to assign a p ...
Posted on Fri, 15 May 2026 11:38:16 +0000 by MattAdamson
Image Edge Detection Using Wavelet Transform
Edge detection is a fundamental technique in digital image processing, designed to isolate the boundaries of objects within a scene. These boundaries typically correspond to regions where significant fluctuations in pixel intensity or color occur, providing critical information for object recognition, structural analysis, and texture categoriza ...
Posted on Fri, 15 May 2026 00:47:35 +0000 by waynewex
OpenCV Fundamentals: Environment Setup and Core Image Operations
Follow these steps to set up OpenCV in your VS2019 environment:
Navigate to View → Other Windows → Property Manager → Add Microsoft.Cpp.x64.user under Release|x64
Configure include directories:
Open properties of Microsoft.Cpp.x64.user → VC++ Directories → Include Directories
Add these paths: D:\Libraries\opencv\build\include``D:\Libraries\op ...
Posted on Wed, 13 May 2026 18:00:33 +0000 by Grofit