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ultralytics/ultralytics: NEW - YOLOv8 in PyTorch - GitHub
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Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility. YOLOv8 is designed to be fast, accurate, and easy to use, making i… - We hope that the resources here will help you get the most out of YOLOv8. Please browse the …
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Releases · ultralytics/yolov3 · GitHub
Nov 14, 2021 · This release merges the most recent updates to YOLOv5 🚀 from the October 12th, 2021 YOLOv5 v6.0 release into this Ultralytics YOLOv3 repository. This is part of Ultralytics YOLOv3 maintenance and takes place on every …
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Home - Ultralytics YOLO Docs
Nov 12, 2023 · Ultralytics YOLO Docs is a comprehensive resource for the latest version of the acclaimed real-time object detection and image segmentation model, YOLOv8. Learn how to …
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AILab-CVC/YOLO-World - GitHub
Jan 31, 2024 · YOLO-World is a real-time open-vocabulary object detector that supports zero-shot learning and segmentation. It is under active development and has been accepted by …
YOLOv4 - Ultralytics YOLO Docs
Nov 12, 2023 · Learn about YOLOv4, a real-time object detection model launched in 2020 by Alexey Bochkovskiy. Find out how to install, train, and use YOLOv4 on your own data, and …
yolov5 · PyPI
Oct 16, 2023 · Overview. You can finally install YOLOv5 object detector using pip and integrate into your project easily. This yolov5 package contains everything from ultralytics/yolov5 at this commit plus: 1. Easy installation via pip: pip …
downloads - Ultralytics YOLO Docs
Nov 12, 2023 · Explore and utilize the Ultralytics download utilities to handle URLs, zip/unzip files, and manage GitHub assets effectively.
YOLOv5 | PyTorch
YOLOv5 is a fast, accurate, and easy to use model for object detection, instance segmentation and image classification. Learn how to install, load, and use YOLOv5 from PyTorch Hub with …
kiyoshiiriemon/yolov4_darknet: YOLOv4 - GitHub
Download and install YOLOv4, a neural network for object detection, for Windows and Linux systems. Learn how to use, train, and improve YOLOv4 with various frameworks, datasets, …
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Releases · ultralytics/yolov5 · GitHub
v7.0 - YOLOv5 SOTA Realtime Instance Segmentation Latest. Our new YOLOv5 v7.0 instance segmentation models are the fastest and most accurate in the world, beating all current SOTA …
Models Supported by Ultralytics - Ultralytics YOLO Docs
Nov 12, 2023 · We offer support for a wide range of models, each tailored to specific tasks like object detection, instance segmentation, image classification, pose estimation, and multi …
Improved YOLOv4-tiny network for real-time electronic …
Nov 23, 2021 · The YOLOv4-tiny detector is transplanted to the field of robotics in the electronics industry instead of the traditional method, thus providing a technical reference for the …
YOLO object detection with OpenCV - PyImageSearch
Nov 12, 2018 · Learn how to use YOLO, a fast and accurate deep learning-based object detector, with OpenCV and Python. Download the source code, datasets, and models for YOLO v3 and …
ultralytics/yolov5: YOLOv5 in PyTorch > ONNX - GitHub
Models and datasets download automatically from the latest YOLOv5 release. Training times for YOLOv5n/s/m/l/x are 1/2/4/6/8 days on a V100 GPU (Multi-GPU times faster). Use the largest …
YOLOv8 - Ultralytics YOLO Docs
Nov 12, 2023 · Discover YOLOv8, the latest advancement in real-time object detection, optimizing performance with an array of pre-trained models for diverse tasks.
June 1, 2020. ABSTRACT. instance segmentation called Poly-YOLO. Poly-YOLO builds on the original ideas of YOLOv3 and removes two of its weaknesses: a large amount of rewritten labels.
GitHub - ppogg/YOLOv5-Lite: YOLOv5-Lite: Evolved from yolov5 …
YOLOv5-Lite：Lighter, faster and easier to deploy. Perform a series of ablation experiments on yolov5 to make it lighter (smaller Flops, lower memory, and fewer parameters) and faster (add …
ultralytics/yolov3: YOLOv3 in PyTorch > ONNX > CoreML - GitHub
Models and datasets download automatically from the latest YOLOv3 release. Training times for YOLOv5n/s/m/l/x are 1/2/4/6/8 days on a V100 GPU (Multi-GPU times faster). Use the largest …
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