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tiled-naive-2d-convolution-1-d-histogram-cuda-opencl

2D convolution and 1D histogram calculation was performed in both CUDA and OpenCL. 2D convolution was implemented, taking advantage of both shared memory/tiles and global memory (naive methods). Tiled 2D convolution was performed in CUDA only. For naive 2D convolution, the input to the algorithm is an [M X N] matrix and a [K X K] kernel of odd dime

traffic-sign-recognition-with-machine-learningandopencv

OpenCV & 기계 학습기반 고속 표지판 인식 (Using KNN, SVM)

transformtest

TransformTest with CSharp Activiz x64 , Visual Studio 2017 Community, Windows10

uncalibrated-photometric-stereo

Photometric-Stereo under unknown light source directions using svd

uncalibratedpspcl

vc2-referece

vcglib_samples

samples of vcglib and meshlab.

veiwing-and-rendering-an-object-in-different-style-in-vtk

The Visualization Toolkit (VTK) is an open-source, freely available software system for 3D computer graphics, modeling, image processing, volume rendering, scientific visualization, and information visualization. This project helps showing simple ways in which objects can be rendered in different ways.

vfx-project1-hdr

volume-rendering-app-with-vtk-dicom-type-

voxel-carving

Silhoutte-based 3D Reconstruction using Voxel Carving algorithm

vtk

Mirror of Visualization Toolkit repository

vtk-clipping-planes

CGT377 Lab 5

vtk-examples

This is the VTK Examples Web Site. This is a mirror of the https://gitlab.kitware.com/vtk/vtk-examples repository in order to host web pages. DO NOT SUBMIT MERGE REQUESTS HERE.

vtkcolorcellsrgba

Sample application to create a RGBA-coloured models

vtkdata

git://vtk.org/VTKData.git

vtknamedcolorpatches

VTKNamedColorPatches Generated by python source

vtkviewer

vkt peaks with MATL

wavelettransformtest

Test for wavelet Transform

windows-driver-samples

This repo contains driver samples prepared for use with Microsoft Visual Studio and the Windows Driver Kit (WDK). It contains both Universal Windows Driver and desktop-only driver samples.

yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

yolov5-lite

🍅🍅🍅YOLOv5-Lite: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 930+kb (int8) and 1.7M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size is 320×320~