This repository implements YOLOv3 variants in PyTorch for real time object detection, training, validation, inference, and export.
Open source
24 alternativesYolov5
Ultralytics YOLOv5 supports object detection, instance segmentation, classification, training, and export in PyTorch.
About Yolov5
Ultralytics YOLOv5 is an open-source computer vision model built on the PyTorch framework. The repository provides tools for object detection, instance segmentation, and image classification, along with training and model export. The source describes YOLOv5 as a mature, production-proven model.
The repository includes a detect.py script for running inference on webcam feeds, local images and videos, screen captures, image folders, and lists of image paths or stream URLs. Models can also be loaded through PyTorch Hub. Setup requires Python 3.8.0 or later and PyTorch 1.8 or later. For newer architectures, pose estimation, or oriented object detection, the source points to the separate ultralytics package.
Key features
- Object detection, instance segmentation, and image classification
- Training and model export in PyTorch
- PyTorch Hub inference with pretrained models in sizes n, s, m, l, and x
- detect.py inference on webcams, videos, screen captures, and image folders
- Inference from text files listing image paths or stream URLs
- Results printed to console, displayed in a window, or saved to disk
Best for: Developers and researchers who want an established PyTorch-based model for object detection, segmentation, or classification.
Good for
- The source describes YOLOv5 as mature and production-proven.
- Documentation covers training, testing, and deployment.
- Support is available through GitHub issues and a Discord community.
Watch out for
- The source recommends the separate ultralytics package for newer architectures, pose estimation, and oriented object detection.
- Setup requires Python 3.8.0 or later and PyTorch 1.8 or later.
Yolov5 at a glance
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Yolov5 FAQ
What are the setup requirements?
The source says to use a Python 3.8.0 or later environment with PyTorch 1.8 or later installed, then install the packages listed in requirements.txt after cloning the repository.
Where can I get support?
The source directs users to the YOLOv5 Docs for detailed information, GitHub issues for support, and the Ultralytics Discord community for questions and discussions.
Does YOLOv5 support pose estimation or oriented object detection?
The source does not list these as YOLOv5 features. It says the ultralytics package provides these tasks, along with the latest Ultralytics YOLO models.
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