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...Inspired by PaddlePaddle, PaddleOCR is an ultra lightweight OCR system, with multilingual recognition, digit recognition, vertical text recognition, as well as long text recognition. It features a PPOCR series of high-quality pre-trained models, which includes: ultra lightweight ppocr_mobile series models, general ppocr_server series models, and ultra lightweight compression ppocr_mobile_slim series models. PaddleOCR is easy to install and easy to use on Windows, Linux, MacOS and other systems.

Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D and 3D coordinates. Build using FAN's state-of-the-art deep learning-based face alignment method. For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively use dlib, BlazeFace, or pre-existing ground truth bounding boxes. While not required, for optimal performance(especially for the detector) it is highly recommended to run the code using a CUDA-enabled GPU. ...

...What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based global loss, which forces unique predictions via bipartite matching, and a Transformer encoder-decoder architecture. Given a fixed small set of learned object queries, DETR reasons about the relations of the objects and the global image context to directly output the final set of predictions in parallel. Due to this parallel nature, DETR is very fast and efficient.