YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
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Updated
Aug 15, 2024 - Python
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
YOLOv3 in PyTorch > ONNX > CoreML > TFLite
NVIDIA DeepStream SDK 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1 implementation for YOLO models
🚀🚀🚀 A collection of some awesome public YOLO object detection series projects.
AI-First Process Automation with Large ([Language (LLMs) / Action (LAMs) / Multimodal (LMMs)] / Visual Language (VLMs)) Models
Easy & Modular Computer Vision Detectors, Trackers & SAM - Run YOLOv9,v8,v7,v6,v5,R,X in under 10 lines of code.
Packaged version of ultralytics/yolov5 + many extra features
xView 2018 Object Detection Challenge: YOLOv3 Training and Inference.
Ultralytics YOLOv8, YOLOv9, YOLOv10 for ROS 2
Use YOLOv8 in real-time, for object detection, instance segmentation, pose estimation and image classification, via ONNX Runtime.
A PyTorch implementation of Spiking-YOLOv3. Two branches are provided, based on two common PyTorch implementation of YOLOv3(ultralytics/yolov3 & eriklindernoren/PyTorch-YOLOv3), with support for Spiking-YOLOv3-Tiny at present.
ROS/ROS 2 package for Ultralytics YOLOv8 real-time object detection and segmentation. https://github.com/ultralytics/ultralytics
Easy-to-use finetuned YOLOv8 models.
Converting COCO annotation (CVAT) to annotation for YOLOv8-seg (instance segmentation) and YOLOv8-obb (oriented bounding box detection)
🚀Simple and efficient use for Ultralytics yolov8🚀
YOLOv8-3D is a LowCode, Simple 2D and 3D Bounding Box Object Detection and Tracking , Python 3.10
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