lucasjinreal/yolov7_d2

Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking

Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.

We write your reusable computer vision tools. 💜

OpenMMLab Detection Toolbox and Benchmark

Label Studio is a multi-type data labeling and annotation tool with standardized output format

PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.

OpenVINO™ is an open source toolkit for optimizing and deploying AI inference

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

Effortless data labeling with AI support from Segment Anything and other awesome models.

BoxMOT: Pluggable python and c++ SOTA multi-object tracking modules with support for axis-aligned and oriented bounding boxes

Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, OpenCV Contrib, and OpenVINO.

YOLOv6: a single-stage object detection framework dedicated to industrial applications.