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YOLO DNNs

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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:

Source Code

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

Usage examples

Execute in webcam:

$ 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

Execute with image or video file:

$ 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

Questions and suggestions email to: Alessandro de Oliveira Faria cabel.nosp@m.o@op.nosp@m.ensus.nosp@m.e.or.nosp@m.g or OpenCV Team.