JieZou1

PanelSeg

Fastest_Image_Pattern_Matching

C++ implementation of a ScienceDirect paper "An accelerating cpu-based correlation-based image alignment for real-time automatic optical inspection"

PaddleClas

A treasure chest for visual classification and recognition powered by PaddlePaddle

PaddleDetection

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

PaddleOCR

Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)

PPOCRLabel

PPOCRLabel is a semi-automatic graphic annotation tool suitable for OCR field, with built-in PP-OCR model to automatically detect and re-recognize data. It is written in Python 3 and PyQT5, supporting rectangular box annotation and four-point annotation modes. Annotations can be directly used for the training of PP-OCR detection and recognition mod

JieZou1/Fastest_Image_Pattern_Matching

C++ implementation of a ScienceDirect paper "An accelerating cpu-based correlation-based image alignment for real-time automatic optical inspection"

JieZou1/PaddleOCR

Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)

JieZou1/PaddleDetection

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

JieZou1/PaddleClas

A treasure chest for visual classification and recognition powered by PaddlePaddle

JieZou1/PPOCRLabel

PPOCRLabel is a semi-automatic graphic annotation tool suitable for OCR field, with built-in PP-OCR model to automatically detect and re-recognize data. It is written in Python 3 and PyQT5, supporting rectangular box annotation and four-point annotation modes. Annotations can be directly used for the training of PP-OCR detection and recognition mod

JieZou1/PanelSeg