yolov5 and yolov3

These are ecosystem siblings representing successive generations of the same architecture—YOLOv5 is the newer iteration that supersedes YOLOv3, both maintained by Ultralytics with overlapping export capabilities (PyTorch to ONNX/CoreML/TFLite) but YOLOv5 offering improved accuracy and speed that make it the preferred choice for most new projects.

yolov5
68
Established
yolov3
64
Established
Maintenance 17/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 13/25
Adoption 10/25
Maturity 16/25
Community 25/25
Stars: 57,000
Forks: 17,440
Downloads: —
Commits (30d): 6
Language: Python
License: AGPL-3.0
Stars: 10,563
Forks: 3,448
Downloads: —
Commits (30d): 2
Language: Python
License: AGPL-3.0
No Package No Dependents
No Package No Dependents

About yolov5

ultralytics/yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

This project helps people who need to automatically find and classify objects in images or video. You provide it with visual input, and it identifies and labels the distinct objects it sees. This is ideal for roles like security analysts monitoring CCTV, manufacturing quality control specialists, or agricultural surveyors analyzing crop health.

object-detection image-analysis visual-inspection surveillance automation

About yolov3

ultralytics/yolov3

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

This project helps quickly identify and locate specific items within images or video feeds. You feed it visual data, and it outputs bounding boxes and labels for the objects it recognizes. This is ideal for anyone who needs to automate the process of spotting things in visual media, such as security analysts, quality control inspectors, or autonomous system developers.

object detection computer vision visual inspection surveillance robotics

Related comparisons

yolov5 and yolov3-tf2 yolov5 and Yolo-v2-pytorch

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