12 skills found
bcmi / CaGNet Zero Shot Semantic SegmentationCode for our ACMMM2020 paper "Context-aware Feature Generation for Zero-shot Semantic Segmentation".
USTCPCS / CVPR2018 AttentionContext Encoding for Semantic Segmentation MegaDepth: Learning Single-View Depth Prediction from Internet Photos LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume On the Robustness of Semantic Segmentation Models to Adversarial Attacks SPLATNet: Sparse Lattice Networks for Point Cloud Processing Left-Right Comparative Recurrent Model for Stereo Matching Enhancing the Spatial Resolution of Stereo Images using a Parallax Prior Unsupervised CCA Discovering Point Lights with Intensity Distance Fields CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation Learning a Discriminative Feature Network for Semantic Segmentation Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi- Supervised Semantic Segmentation Unsupervised Deep Generative Adversarial Hashing Network Monocular Relative Depth Perception with Web Stereo Data Supervision Single Image Reflection Separation with Perceptual Losses Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains EPINET: A Fully-Convolutional Neural Network for Light Field Depth Estimation by Using Epipolar Geometry FoldingNet: Interpretable Unsupervised Learning on 3D Point Clouds Decorrelated Batch Normalization Unsupervised Learning of Depth and Egomotion from Monocular Video Using 3D Geometric Constraints PU-Net: Point Cloud Upsampling Network Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer Tell Me Where To Look: Guided Attention Inference Network Residual Dense Network for Image Super-Resolution Reflection Removal for Large-Scale 3D Point Clouds PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image Fully Convolutional Adaptation Networks for Semantic Segmentation CRRN: Multi-Scale Guided Concurrent Reflection Removal Network DenseASPP: Densely Connected Networks for Semantic Segmentation SGAN: An Alternative Training of Generative Adversarial Networks Multi-Agent Diverse Generative Adversarial Networks Robust Depth Estimation from Auto Bracketed Images AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation DeepMVS: Learning Multi-View Stereopsis GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation Single-Image Depth Estimation Based on Fourier Domain Analysis Single View Stereo Matching Pyramid Stereo Matching Network A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimation Image Correction via Deep Reciprocating HDR Transformation Occlusion Aware Unsupervised Learning of Optical Flow PAD-Net: Multi-Tasks Guided Prediciton-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing Surface Networks Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation TextureGAN: Controlling Deep Image Synthesis with Texture Patches Aperture Supervision for Monocular Depth Estimation Two-Stream Convolutional Networks for Dynamic Texture Synthesis Unsupervised Learning of Single View Depth Estimation and Visual Odometry with Deep Feature Reconstruction Left/Right Asymmetric Layer Skippable Networks Learning to See in the Dark
feixue94 / Sfd2[CVPR 2023] SFD2: Semantic-guided Feature Detection and Description. Embedding semantics into local features implicitly for long-term visual localization
mengtan00 / SA BEVThis is the implementation of the paper "SA-BEV: Generating Semantic-Aware Bird's-Eye-View Feature for Multi-view 3D Object Detection" (ICCV 2023)
wdhudiekou / STSC[ICRA 2022] Semantic-aware Texture-Structure Feature Collaboration for Underwater Image Enhancement
MateusNobreSilva / App Send MailPHPMailer PHPMailer – A full-featured email creation and transfer class for PHP Test status codecov.io Latest Stable Version Total Downloads License API Docs Features Probably the world's most popular code for sending email from PHP! Used by many open-source projects: WordPress, Drupal, 1CRM, SugarCRM, Yii, Joomla! and many more Integrated SMTP support – send without a local mail server Send emails with multiple To, CC, BCC and Reply-to addresses Multipart/alternative emails for mail clients that do not read HTML email Add attachments, including inline Support for UTF-8 content and 8bit, base64, binary, and quoted-printable encodings SMTP authentication with LOGIN, PLAIN, CRAM-MD5, and XOAUTH2 mechanisms over SMTPS and SMTP+STARTTLS transports Validates email addresses automatically Protects against header injection attacks Error messages in over 50 languages! DKIM and S/MIME signing support Compatible with PHP 5.5 and later, including PHP 8.1 Namespaced to prevent name clashes Much more! Why you might need it Many PHP developers need to send email from their code. The only PHP function that supports this directly is mail(). However, it does not provide any assistance for making use of popular features such as encryption, authentication, HTML messages, and attachments. Formatting email correctly is surprisingly difficult. There are myriad overlapping (and conflicting) standards, requiring tight adherence to horribly complicated formatting and encoding rules – the vast majority of code that you'll find online that uses the mail() function directly is just plain wrong, if not unsafe! The PHP mail() function usually sends via a local mail server, typically fronted by a sendmail binary on Linux, BSD, and macOS platforms, however, Windows usually doesn't include a local mail server; PHPMailer's integrated SMTP client allows email sending on all platforms without needing a local mail server. Be aware though, that the mail() function should be avoided when possible; it's both faster and safer to use SMTP to localhost. Please don't be tempted to do it yourself – if you don't use PHPMailer, there are many other excellent libraries that you should look at before rolling your own. Try SwiftMailer , Laminas/Mail, ZetaComponents etc. License This software is distributed under the LGPL 2.1 license, along with the GPL Cooperation Commitment. Please read LICENSE for information on the software availability and distribution. Installation & loading PHPMailer is available on Packagist (using semantic versioning), and installation via Composer is the recommended way to install PHPMailer. Just add this line to your composer.json file: "phpmailer/phpmailer": "^6.5" or run composer require phpmailer/phpmailer Note that the vendor folder and the vendor/autoload.php script are generated by Composer; they are not part of PHPMailer. If you want to use the Gmail XOAUTH2 authentication class, you will also need to add a dependency on the league/oauth2-client package in your composer.json. Alternatively, if you're not using Composer, you can download PHPMailer as a zip file, (note that docs and examples are not included in the zip file), then copy the contents of the PHPMailer folder into one of the include_path directories specified in your PHP configuration and load each class file manually: <?php use PHPMailer\PHPMailer\PHPMailer; use PHPMailer\PHPMailer\Exception; require 'path/to/PHPMailer/src/Exception.php'; require 'path/to/PHPMailer/src/PHPMailer.php'; require 'path/to/PHPMailer/src/SMTP.php'; If you're not using the SMTP class explicitly (you're probably not), you don't need a use line for the SMTP class. Even if you're not using exceptions, you do still need to load the Exception class as it is used internally. Legacy versions PHPMailer 5.2 (which is compatible with PHP 5.0 — 7.0) is no longer supported, even for security updates. You will find the latest version of 5.2 in the 5.2-stable branch. If you're using PHP 5.5 or later (which you should be), switch to the 6.x releases. Upgrading from 5.2 The biggest changes are that source files are now in the src/ folder, and PHPMailer now declares the namespace PHPMailer\PHPMailer. This has several important effects – read the upgrade guide for more details. Minimal installation While installing the entire package manually or with Composer is simple, convenient, and reliable, you may want to include only vital files in your project. At the very least you will need src/PHPMailer.php. If you're using SMTP, you'll need src/SMTP.php, and if you're using POP-before SMTP (very unlikely!), you'll need src/POP3.php. You can skip the language folder if you're not showing errors to users and can make do with English-only errors. If you're using XOAUTH2 you will need src/OAuth.php as well as the Composer dependencies for the services you wish to authenticate with. Really, it's much easier to use Composer! A Simple Example <?php //Import PHPMailer classes into the global namespace //These must be at the top of your script, not inside a function use PHPMailer\PHPMailer\PHPMailer; use PHPMailer\PHPMailer\SMTP; use PHPMailer\PHPMailer\Exception; //Load Composer's autoloader require 'vendor/autoload.php'; //Create an instance; passing `true` enables exceptions $mail = new PHPMailer(true); try { //Server settings $mail->SMTPDebug = SMTP::DEBUG_SERVER; //Enable verbose debug output $mail->isSMTP(); //Send using SMTP $mail->Host = 'smtp.example.com'; //Set the SMTP server to send through $mail->SMTPAuth = true; //Enable SMTP authentication $mail->Username = 'user@example.com'; //SMTP username $mail->Password = 'secret'; //SMTP password $mail->SMTPSecure = PHPMailer::ENCRYPTION_SMTPS; //Enable implicit TLS encryption $mail->Port = 465; //TCP port to connect to; use 587 if you have set `SMTPSecure = PHPMailer::ENCRYPTION_STARTTLS` //Recipients $mail->setFrom('from@example.com', 'Mailer'); $mail->addAddress('joe@example.net', 'Joe User'); //Add a recipient $mail->addAddress('ellen@example.com'); //Name is optional $mail->addReplyTo('info@example.com', 'Information'); $mail->addCC('cc@example.com'); $mail->addBCC('bcc@example.com'); //Attachments $mail->addAttachment('/var/tmp/file.tar.gz'); //Add attachments $mail->addAttachment('/tmp/image.jpg', 'new.jpg'); //Optional name //Content $mail->isHTML(true); //Set email format to HTML $mail->Subject = 'Here is the subject'; $mail->Body = 'This is the HTML message body <b>in bold!</b>'; $mail->AltBody = 'This is the body in plain text for non-HTML mail clients'; $mail->send(); echo 'Message has been sent'; } catch (Exception $e) { echo "Message could not be sent. Mailer Error: {$mail->ErrorInfo}"; } You'll find plenty to play with in the examples folder, which covers many common scenarios including sending through gmail, building contact forms, sending to mailing lists, and more. If you are re-using the instance (e.g. when sending to a mailing list), you may need to clear the recipient list to avoid sending duplicate messages. See the mailing list example for further guidance. That's it. You should now be ready to use PHPMailer! Localization PHPMailer defaults to English, but in the language folder you'll find many translations for PHPMailer error messages that you may encounter. Their filenames contain ISO 639-1 language code for the translations, for example fr for French. To specify a language, you need to tell PHPMailer which one to use, like this: //To load the French version $mail->setLanguage('fr', '/optional/path/to/language/directory/'); We welcome corrections and new languages – if you're looking for corrections, run the PHPMailerLangTest.php script in the tests folder and it will show any missing translations. Documentation Start reading at the GitHub wiki. If you're having trouble, head for the troubleshooting guide as it's frequently updated. Examples of how to use PHPMailer for common scenarios can be found in the examples folder. If you're looking for a good starting point, we recommend you start with the Gmail example. To reduce PHPMailer's deployed code footprint, examples are not included if you load PHPMailer via Composer or via GitHub's zip file download, so you'll need to either clone the git repository or use the above links to get to the examples directly. Complete generated API documentation is available online. You can generate complete API-level documentation by running phpdoc in the top-level folder, and documentation will appear in the docs folder, though you'll need to have PHPDocumentor installed. You may find the unit tests a good reference for how to do various operations such as encryption. If the documentation doesn't cover what you need, search the many questions on Stack Overflow, and before you ask a question about "SMTP Error: Could not connect to SMTP host.", read the troubleshooting guide. Tests PHPMailer tests use PHPUnit 9, with a polyfill to let 9-style tests run on older PHPUnit and PHP versions. Test status If this isn't passing, is there something you can do to help? Security Please disclose any vulnerabilities found responsibly – report security issues to the maintainers privately. See SECURITY and PHPMailer's security advisories on GitHub. Contributing Please submit bug reports, suggestions and pull requests to the GitHub issue tracker. We're particularly interested in fixing edge-cases, expanding test coverage and updating translations. If you found a mistake in the docs, or want to add something, go ahead and amend the wiki – anyone can edit it. If you have git clones from prior to the move to the PHPMailer GitHub organisation, you'll need to update any remote URLs referencing the old GitHub location with a command like this from within your clone: git remote set-url upstream https://github.com/PHPMailer/PHPMailer.git Please don't use the SourceForge or Google Code projects any more; they are obsolete and no longer maintained. Sponsorship Development time and resources for PHPMailer are provided by Smartmessages.net, the world's only privacy-first email marketing system. Smartmessages.net privacy-first email marketing logo Donations are very welcome, whether in beer 🍺, T-shirts 👕, or cold, hard cash 💰. Sponsorship through GitHub is a simple and convenient way to say "thank you" to PHPMailer's maintainers and contributors – just click the "Sponsor" button on the project page. If your company uses PHPMailer, consider taking part in Tidelift's enterprise support programme. PHPMailer For Enterprise Available as part of the Tidelift Subscription. The maintainers of PHPMailer and thousands of other packages are working with Tidelift to deliver commercial support and maintenance for the open source packages you use to build your applications. Save time, reduce risk, and improve code health, while paying the maintainers of the exact packages you use. Learn more. Changelog See changelog. History PHPMailer was originally written in 2001 by Brent R. Matzelle as a SourceForge project. Marcus Bointon (coolbru on SF) and Andy Prevost (codeworxtech) took over the project in 2004. Became an Apache incubator project on Google Code in 2010, managed by Jim Jagielski. Marcus created his fork on GitHub in 2008. Jim and Marcus decide to join forces and use GitHub as the canonical and official repo for PHPMailer in 2013. PHPMailer moves to the PHPMailer organisation on GitHub in 2013. What's changed since moving from SourceForge? Official successor to the SourceForge and Google Code projects. Test suite. Continuous integration with Github Actions. Composer support. Public development. Additional languages and language strings. CRAM-MD5 authentication support. Preserves full repo history of authors, commits and branches from the original SourceForge project.
mr-chiwang / SGAD[ICCV2025 Highlight]: SGAD: Semantic and Geometric-aware Descriptor for Local Feature Matching
jfzhuang / DAVSSOfficial implementation of "Video Semantic Segmentation with Distortion-Aware Feature Correction", TCSVT 2020.
04RR / SAFENet PytorchPytorch implementation of SAFENet: Self-Supervised Monocular Depth Estimation with Semantic-Aware Feature Extraction: https://arxiv.org/abs/2010.02893
onlyyao / GLFA SOLFGlobal- and local-aware feature augmentation with semantic orthogonality for few-shot image classification (Pattern Recognition 2023)
paipaipake / FECANetThis is the source code for our paper Boosting Few-shot Semantic Segmentation with Feature-Enhanced Context-Aware Network
Pranesh-2005 / Redis Plus AzureOpenAIA blazing fast chat client using Redis semantic cache and Azure OpenAI, featuring language-aware memory, beautiful UI, and PWA support. Includes a Python backend (Gradio, Redis, Azure OpenAI) and a modern frontend with username persistence, Markdown chat, and cache utilities.
