Use OpenCvSharp's DNN module to load your own trained TensorFlow model for target detection

Use OpenCvSharp's DNN module to load your own trained TensorFlow model for target detection

Object detection is an important task in computer vision, which can identify the object of interest in an image or video and mark its location. TensorFlow is a popular deep learning framework, while OpenCvSharp is an open source computer vision library in C#. This article will introduce how to use OpenCvSharp's DNN module to load your own trained TensorFlow model for target detection.

First, we need to prepare our own trained TensorFlow model. Before training the model, you can use any popular object detection dataset for training, such as COCO, VOC, etc. .pbThe training process is beyond the scope of this article, we will assume that you have already trained an object detection model and got a TensorFlow model file (usually with or .pbtxtas the extension) containing the network structure and weight parameters.

Next, we will use OpenCvSharp's DNN module to load this model and perform object detection. First, we need to create an Netobject that will be used to load and run our model. Then, we use Net.ReadNetFromTensorflowthe method to load the model file.

using OpenCvSharp;

// 加载模型
Net net = CvDnn.