init - 初始化项目

doc/tutorials/dnn/dnn_yolo/dnn_yolo.markdown

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+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.
+![Picture example](images/yolo.jpg)
+
+Examples
+--------
+
+VIDEO DEMO:
+@youtube{NHtRlndE2cg}
+
+Source Code
+-----------
+
+Use a universal sample for object detection models written
+[in C++](https://github.com/opencv/opencv/blob/master/samples/dnn/object_detection.cpp) and
+[in Python](https://github.com/opencv/opencv/blob/master/samples/dnn/object_detection.py) 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.