env/opencv-4.8.0/doc/tutorials/dnn/dnn_yolo/dnn_yolo.markdown

YOLO DNNs {#tutorial_dnn_yolo}

@tableofcontents

@prev_tutorial{tutorial_dnn_android} @next_tutorial{tutorial_dnn_javascript}

| | | | -: | :- | | Original author | Alessandro de Oliveira Faria | | Compatibility | OpenCV >= 3.3.1 |

Introduction

In this text you will learn how to use opencv_dnn module using yolo_object_detection (Sample of using OpenCV dnn module in real time with device capture, video and image).

We will demonstrate results of this example on the following picture.

Examples

VIDEO DEMO: @youtube{NHtRlndE2cg}

Source Code

Use a universal sample for object detection models written in C++ and in Python languages

Usage examples

Execute in webcam:

@code{.bash}

$ example_dnn_object_detection --config=[PATH-TO-DARKNET]/cfg/yolo.cfg --model=[PATH-TO-DARKNET]/yolo.weights --classes=object_detection_classes_pascal_voc.txt --width=416 --height=416 --scale=0.00392 --rgb

@endcode

Execute with image or video file:

@code{.bash}

$ example_dnn_object_detection --config=[PATH-TO-DARKNET]/cfg/yolo.cfg --model=[PATH-TO-DARKNET]/yolo.weights --classes=object_detection_classes_pascal_voc.txt --width=416 --height=416 --scale=0.00392 --input=[PATH-TO-IMAGE-OR-VIDEO-FILE] --rgb

@endcode

Questions and suggestions email to: Alessandro de Oliveira Faria cabelo@opensuse.org or OpenCV Team.