src

Collection of quality safety articles. Awesome articles.

Responsive images in the browser, simplified

Handbook of information collection for penetration testing and src

Source code for multiple JDK versions(1.6/1.7/1.8/1.9/10/11/12/13/14/15/16/17/18 JDK's src.zip), Only for learning; "rt_debug.jar" can be used for debugging.

日常src平台域名收集

React component to display imgix images

A JavaScript client library for generating image URLs with imgix

A gem for integrating imgix into Rails projects

A PHP client library for generating URLs with imgix

集成crawlergo、xray、dirsearch、nmap等工具的src漏洞挖掘工具，使用docker封装运行；使用oneforall自动遍历子域名并扫描；

A Ruby gem for generating image URLs with imgix

A MATLAB toolbox for classifier: Version 1.0.7

A plugin for integrating imgix into Jekyll sites

SRC情报收集管理系统

PHP源码分析注解。

Minecraft client sources

A Swift client library for generating URLs with imgix

The eager-loading for image files on the web page that loads the files according to your plan. This differs from the lazy-loading, for example, this can be used to avoid that the user waits for the loading.

PostCSS plugin used to replace value inside of url function to base64

Remote gulp.src

A Java client library for generating URLs with imgix

Implemented and evaluated four basic face recognition algorithms: Eigenfaces, Fisherfaces, Support Vector Machine (SVM), and Sparse Representation-based Classification (SRC) on YaleB dataset

An add-on for integrating imgix into Statamic sites

Keeping roads in a good condition is vital to safe driving. To monitor the degradation of road conditions is one of the important component in transportation maintenance which is labor intensive and requires domain expertise. Automatic detection of road damage is an important task in transportation maintenance for driving safety assurance. The intensity of damage and complexity of the background, makes this process a challenging task. A deep-learning based methodology for damage detection is proposed in this project after being inspired by recent success on applying Deep- learning in Computer Sciences. A dataset of 9,053 images is taken with the help of a low cost smart phone and a quantitative evaluation is conducted, which in turn demonstrates that the superior damage detection performance using deep-learning methods perform extremely well when compared with features extracted with existing hand-craft methods. Using convolutional neural networks to train the damage detection model with our dataset, we use the state-of-the-art object detection method, and compute the accuracy and runtime speed on a GPU server. At the end, we show that the type of damage can be distinguished into eight types with acceptable accuracy by applying the proposed object detection method.

A C# client library for generating image URLs with imgix

Convert pdf from file or url to base64

A Go client library for generating image URLs with imgix

A collection of python implementations using SWIG, Instant, F2PY... Optimization like Least Squares Levenberg-Marquardt. Boundary Value problem solvers. Integration Simpson/Trapezoidal. Interpolation like Cubic spline. Tridiagonal/pentadiagonal system of equations solver. Linear algebra like Matrix inversion (Gauss-Jordan) and much more