#d_lang

https://github.com/dlang/dmd

#d_lang

https://github.com/Netflix/vectorflow

#d_lang

https://github.com/eth-sri/silq

#d_lang #business #linux #microsoft #office_365 #office365 #onedrive #onedrive_client #onedrive_for_business #onedrive_personal #onedrive_storage #personal

https://github.com/abraunegg/onedrive

#cplusplus #c #dart #http #library #csharp #actionscript #d #thrift #network_server #network_client

https://github.com/apache/thrift

#cplusplus #actionscript #c #cplusplus #csharp #d #dart #http #library #network_client #network_server #thrift

Apache Thrift is a tool that helps programs written in different programming languages communicate with each other. It makes it easy for these programs to share data and call functions on each other, even if they are written in different languages. Thrift supports many languages, so you can use it with the languages you already know. It also allows you to update your server or client without breaking the connection between them, which is very useful for maintaining and upgrading your system. This makes developing and maintaining software much simpler and more efficient.

https://github.com/apache/thrift

#python #d_fine #detr #object_detection

D-FINE is a fast and accurate real-time object detection model that improves how bounding boxes are predicted by refining detailed probability distributions for each box edge, making localization more precise. It uses two main techniques: Fine-grained Distribution Refinement (FDR), which iteratively improves box predictions by focusing on uncertainties, and Global Optimal Localization Self-Distillation (GO-LSD), which helps earlier layers learn from later, more accurate predictions. This approach boosts detection accuracy without extra training or inference costs, making it efficient and effective for detecting objects even in complex scenes. You benefit by getting better, faster object detection with less computational effort.

https://github.com/Peterande/D-FINE