YOLOv5
OpenMMLab Detection Toolbox and Benchmark
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
Label Studio is a multi-type data labeling and annotation tool with standardized output format
YOLOv3 in PyTorch > ONNX > CoreML > TFLite
NEW - YOLOv8
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
YOLOv6: a single-stage object detection framework dedicated to industrial applications.
A collection of SOTA real-time, multi-object trackers for object detectors
Single Shot MultiBox Detector in TensorFlow
DAMO-YOLO: a fast and accurate object detection method with some new techs, including NAS backbones, efficient RepGFPN, ZeroHead, AlignedOTA, and distillation enhancement.
A PyTorch implementation of the YOLO v3 object detection algorithm
mean Average Precision - This code evaluates the performance of your neural net for object recognition.
YoloV3 Implemented in Tensorflow 2.0
Accompanying code for Paperspace tutorial series "How to Implement YOLO v3 Object Detector from Scratch"
Database system for building simpler and faster AI-powered applications
Scaled-YOLOv4: Scaling Cross Stage Partial Network
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with …
Multiple Object Tracker, Based on Hungarian algorithm + Kalman filter.
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