Home - mariodiasbatista/object-detection GitHub Wiki

๐Ÿค– YOLO (You Only Look Once)

Welcome to the object-detection project using YOLO !

YOLO is a real-time object detection algorithm that detects multiple objects in a single pass through a neural network.

Here we are going to address all the findings related to this demo project. This involve also code and several small snippets but the important is to understand the process.

๐Ÿ”– YOLO versions

YOLO as been around since 2016 and if i would take 2 main date references in is lifetime, it would be before YOLOv4 (Apr 2020) were its was support on Darknet a neural network framework written in C and CUDA and after YOLOv5 (Jun 2020) when it was built using PyTorch an open-source machine learning framework used to build and train deep learning models, currently supported by a company name Ultralytics.

The list of YOLO versions with their release dates.

Version Release Date Notes / Framework Used
YOLOv1 May 2016 Original version by Joseph Redmon (Darknet)
YOLOv2 (YOLO9000) Dec 2016 Improved accuracy & speed (Darknet)
YOLOv3 Apr 2018 Multi-label detection, better architecture (Darknet)
YOLOv4 Apr 2020 By AlexeyAB, community-driven (Darknet)
YOLOv5 Jun 2020 By Ultralytics, rewritten in PyTorch
YOLOv6 Jun 2022 By Meituan, optimized for edge devices (PyTorch)
YOLOv7 Jul 2022 By WongKinYiu, state-of-the-art accuracy (PyTorch)
YOLOv8 Jan 2023 By Ultralytics, modular and flexible (PyTorch)
YOLOv9 Nov 2023 By Ultralytics, focuses on quantization, performance
YOLOv10 Apr 2024 By Ultralytics, added faster inference & RT-DETR support
YOLOv11 Mar 2025 Latest version, focused on transformer integration, performance & multi-task learning

๐Ÿ’ก Real-World Applications

From factory floors to jungle trails, YOLO powers intelligent vision across industriesโ€”hereโ€™s where it shines:

  • Self-driving cars ๐Ÿ›ป
  • Medical imaging ๐Ÿง 
  • Wildlife monitoring ๐Ÿ˜
  • Factory automation ๐Ÿญ
  • Security systems ๐Ÿ”’
  • Surveillance and security ๐Ÿ‘ฎโ€โ™€๏ธ
  • Quality inspection ๐Ÿญ
  • Retail analytics ๐Ÿ›๏ธ
  • Sports analytics โšฝ
  • Anything that you perceive as a pattern that can be detected by the human eye you will be able to detect in yolo.