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YOLO DNNs
@tableofcontents
@prev_tutorial{tutorial_dnn_openvino} @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.