From fe79ec14c8180db0ee0b6882e822302172181f85 Mon Sep 17 00:00:00 2001 From: LAGNEAU Romain Date: Thu, 7 Nov 2024 16:23:14 +0100 Subject: [PATCH] [DOC] Updated DNN detection tutorial --- .../detection_dnn/tutorial-detection-dnn.dox | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/doc/tutorial/detection_dnn/tutorial-detection-dnn.dox b/doc/tutorial/detection_dnn/tutorial-detection-dnn.dox index d97c73a9ae..b39f68352c 100644 --- a/doc/tutorial/detection_dnn/tutorial-detection-dnn.dox +++ b/doc/tutorial/detection_dnn/tutorial-detection-dnn.dox @@ -13,8 +13,8 @@ class ids and confidence values of a single or of multiple classes. For other tasks such as image segmentation or more complicated uses, you should use directly the OpenCV DNN API. -This class supports `Faster-RCNN`, `SSD-MobileNet`, `ResNet 10`, `Yolo v3`, `Yolo v4`, `Yolo v5`, `Yolo v7` and -`Yolo v8` convolutional networks that simultaneously predict object boundaries and prediction scores at each position. +This class supports `Faster-RCNN`, `SSD-MobileNet`, `ResNet 10`, `Yolo v3`, `Yolo v4`, `Yolo v5`, `Yolo v7`, +`Yolo v8` and `Yolo v11` convolutional networks that simultaneously predict object boundaries and prediction scores at each position. If you want to use another type of network, you can define your own parsing method of the DNN detection results and give it to the `vpDetectorDNNOpenCV` object. @@ -74,13 +74,13 @@ $ sudo apt install libgtk-3-dev \ libx11-dev \endcode -6. Get the sources. The \b vpDetectorDNNOpenCV has been tested with **OpenCV 4.7**. First, get the OpenCV_contrib -sources, that contain the Cuda DNN module. +6. Get the sources. The \b vpDetectorDNNOpenCV has been tested with **OpenCV 4.7** and **OpenCV 4.10**. First, +get the OpenCV_contrib sources, that contain the Cuda DNN module. On a Debian distribution, you would run: \code{.sh} $ cd ${HOME}/visp_ws/3rdparty/ -$ git clone --branch 4.7.0 https://github.com/opencv/opencv_contrib -$ git clone --branch 4.7.0 https://github.com/opencv/opencv +$ git clone --branch 4.10.0 https://github.com/opencv/opencv_contrib +$ git clone --branch 4.10.0 https://github.com/opencv/opencv \endcode 7. Compile OpenCV and install it from source. On a Debian distribution, you would run: @@ -149,6 +149,7 @@ on DNN models learned from the following networks: - Yolo v5 - Yolo v7 - Yolo v8 +- Yolo v11 It uses video capture capability from OpenCV to capture images from a camera and detect objects using a DNN model learned using one of the previous networks.