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visionbang's Projects

deye icon deye

Keep an Eye on Defects Inspection.

dlib icon dlib

A toolkit for making real world machine learning and data analysis applications in C++

dvtk icon dvtk

DICOM Validation Toolkit

easypr icon easypr

An open source project for chinese plate recognition. It aims to be Easy, Flexible, and Accurate. Welcome to contribute your expertise !

easypr-dll-csharp icon easypr-dll-csharp

EasyPR 1.5 的DLL版本——通过C#调用DLL文件来实现界面展现。(The DLL version of EasyPR 1.5: Achieving interface display by using the C # language to call DLL file. )

easypr_mfc icon easypr_mfc

EasyPR_MFC is the Visual interface of EasyPR. You could specify the picture or the foler to be recognized by a button in EasyPR_MFC.

elastix icon elastix

Medical image registration toolkit. This is a clone of the svn repository.

eth-segreg icon eth-segreg

Algorithms and methods for (medical) image registration and segmentation

fast-match icon fast-match

Port of Fast Affine Template Matching algorithm

fmi icon fmi

Feature Mutual Information (FMI) - non-reference image fusion metric

fmt_motion_detection icon fmt_motion_detection

Independent motion detection using the Fourier-Mellin transform for camera motion compensation

gms-feature-matcher icon gms-feature-matcher

C++ code for "GMS: Grid-based Motion Statistics for Fast, Ultra-robust Feature Correspondence"

gradio icon gradio

Create UIs for your machine learning model in Python in 3 minutes

hosts icon hosts

:bowtie:无障碍上网-你~懂得![更新频率7d,需要请 fork]

hugin icon hugin

Panorama photo stitcher. My Github Mirror.

hyperlpr icon hyperlpr

高性能中文车牌识别 High Performance Chinese License Plate Recognition Framework.

image-dehazing-dark-channel-prior icon image-dehazing-dark-channel-prior

Dehazing algorithm based on a research paper titled "Single Image Haze Removal Using Dark Channel Prior". Published by: Kaiming He, Jian Sun, Xiaoou Tang, The Chinese University of Hong Kong, and Microsoft Research Asia

imagestich icon imagestich

The project takes two or more images and stiches them together by finding matching features between images and then using RANSAC to estimate the homography between them, With that homography, an image can be transformed into the plane of the reference image and stitched together.

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