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Name: HeXin
Type: User
Name: HeXin
Type: User
SegNet implementation in Pytorch framework
segmentation repo using pytorch
Semantic Segmentation Architectures Implemented in PyTorch
Build your neural network easy and fast
Pytorch implementation of the U-Net for image semantic segmentation, with dense CRF post-processing
Simple PyTorch implementations of U-Net/FullyConvNet (FCN) for image segmentation
Minimal PyTorch implementation of YOLOv3
这是我学习 PyTorch 的笔记对应的代码,点击查看 PyTorch 笔记在线电子书
基于 Qt 的医学影像阅片工具
QFtpServer - an FTP server written in Qt
A Qt plugin for cipher SQLite.
A Caffe implementation of PSROI-Align
Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST
Richer Convolutional Features for Edge Detection
Richer Convolutional Features for Edge Detection model in pytorch
Author: Xu Liu Date: 02/18/2019 This is a semi-auto labelling software for those who work on image labelling. Input: Click the "Open" button, open the "image" directory and select the first image to start. After this step, the left canvas will display the original image with 50% transparence colored label on it. And the right canvas will display the labelled image with totally black ground and colorful foreground (one color, one instance). All the images in the "image" directory are the outputs(aka. prediction) of the segmentation deep neural network and are located at the "masks" directory. Most parts of the right image are labelled correctly by the neural network, what we need to do is just to revise it slightly. Instructions: 1. Click your right mouse button on the right image to pick a color (the color is corresponding to the pixel where your cursor locates) that you wish to revise on the left image. If there are instances that have not been labelled, you can click your right mouse button on the circular color palatte to pick a different color. 2. Move your cursor to right image, click at the place where you wish to revise the label, keep press the left mouse button and move it can draw curve lines, which can revise a large part. 3. The silder on the top of the two images can control the pen (or brush) size, when you need to paint (revise) a large part, you can move the slider a bit right to get a larger pen size. On the other hand, just move it left can be helpful for revising small part. 4. Click "Save" button on the right can save the revised image (the right one) as a 3 channels, 8 unsigned bits PNG format file at the "output" directory, which is in the same directory as the "images" directory. 5. Click "Next" button then the two canvas can refresh and load the next pair: image and label. Then just repeat the above operations.
tutorial about how to setup environment on Hi3559A
Some of the handy shell scripts I have created/acquired
Multi-platform, free open source software for visualization and image computing.
Object Detection
A super caffe for mobilenet, deep-feature flow, single shot Multi-box detection, flownet, PSPnet
An Open Source Machine Learning Framework for Everyone
Implementation of popular deep learning networks with TensorRT network definition API
Localizing text in scene images using TextProposals algorithm + FCN supression
Pytorch libtorch demo
Tutorials for creating and using ONNX models
U-Net with upsampling layer under caffe
用caffe实现Unet
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.