A fast, easy-to-use, production-ready inference server for computer vision supporting deployment of many popular model architectures and fine-tuned models.

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

This tool extracts images from a PDF, annotates them using the YOLOv5 model, and converts the annotated images back into a single PDF.. https://github.com/ultralytics/yolov5 https://github.com/HumanSignal/labelImg https://www.kaggle.com/code/sagardeepdas/yolov5-model1

6 month, Intern-ship projet.

NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

Simplify camera trap image analysis with ML species recognition models based around the MegaDetector model

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

YOLO5Face: Why Reinventing a Face Detector (https://arxiv.org/abs/2105.12931) ECCV Workshops 2022)

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

🚀🚀🚀 YOLO series of PaddlePaddle implementation, PP-YOLOE+, RT-DETR, YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOX, YOLOv5u, YOLOv7u, YOLOv6Lite, RTMDet and so on. 🚀🚀🚀

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

Flask Server, 저학년 아동의 건강한 SNS 사용을 위한 SNS 교육 애플리케이션: 뭉게뭉게

Recomendation System

YOLOv5 implementation using PyTorch

MetaSeg: Packaged version of the Segment Anything repository

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