doc/tutorials/dnn/dnn_yolo/dnn_yolo.markdown

   1 YOLO DNNs  {#tutorial_dnn_yolo}
   2 ===============================
   3
   4 @prev_tutorial{tutorial_dnn_android}
   5 @next_tutorial{tutorial_dnn_javascript}
   6
   7 Introduction
   8 ------------
   9
  10 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).
  11
  12 We will demonstrate results of this example on the following picture.
  13 ![Picture example](images/yolo.jpg)
  14
  15 Examples
  16 --------
  17
  18 VIDEO DEMO:
  19 @youtube{NHtRlndE2cg}
  20
  21 Source Code
  22 -----------
  23
  24 Use a universal sample for object detection models written
  25 [in C++](https://github.com/opencv/opencv/blob/3.4/samples/dnn/object_detection.cpp) and
  26 [in Python](https://github.com/opencv/opencv/blob/3.4/samples/dnn/object_detection.py) languages
  27
  28 Usage examples
  29 --------------
  30
  31 Execute in webcam:
  32
  33 @code{.bash}
  34
  35 $ 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
  36
  37 @endcode
  38
  39 Execute with image or video file:
  40
  41 @code{.bash}
  42
  43 $ 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
  44
  45 @endcode
  46
  47 Questions and suggestions email to: Alessandro de Oliveira Faria cabelo@opensuse.org or OpenCV Team.