Have You seen those Sci fi movies in which the detective tells the techie to zoom in on an image of the suspect and run an enhancement program and suddently that part of image is magically enhanced...
A few weeks ago we learned how to do Super-Resolution using OpenCV’s DNN module, in today’s post we will perform Facial Expression Recognition AKA Emotion Recognition using the DNN module. Although...
A few weeks ago I published a tutorial on doing Super-resolution with OpenCV using the DNN module.I would recommend that you go over that tutorial before reading this one but you can still easily...
In this tutorial we will go over Deep learning using OpenCV’s DNN module in detail, I plan to cover various important details of the DNN module that is never discussed, things that usually trip of...
In the previous tutorial we learned how the DNN module in OpenCV works, we went into a lot of details regarding different aspects of the module including where to get the models, how to configure...
This is a really descriptive and interesting tutorial, let me highlight what you will learn in this tutorial.
A Crystal Clear step by step tutorial on training a custom object detector.
A method to download videos and create a custom dataset out of that.
How to use the custom trained network inside the OpenCV DNN module so you can get rid of the TensorFlow framework.
Plus here are two things you will receive from the provided source code:
A Jupyter Notebook that automatically downloads and installs all the required things for you so you don’t have to step outside of that notebook.
A Colab version of the notebook that runs out of the box, just run the cells and train your own network.
I will stress this again that all of the steps are explained in a neat and digestible way. I’ve you ever plan to do Object Detection then this is one tutorial you don’t want to miss.
As mentioned, by downloading the Source Code you will get 2 versions of the notebook: a local version and a colab version.
So first we’re going to see a complete end to end pipeline for training a custom object detector on our data and then we will use it in the OpenCV DNN module so we can get rid of the heavy Tensorflow framework for deployment. We have already discussed the advantages of using the final trained model in OpenCV instead of Tensorflow in my previous post.
Today’s post is the 3rd tutorial in our 3 part Deep Learning with OpenCV series. All three posts are titled as:
Deep Learning with OpenCV DNN Module, A Comprehensive Guide
Training a Custom Image Classifier with OpenCV, Converting to ONNX, and using it in OpenCV DNN module.
Training a Custom Object Detector with Tensorflow and using it with OpenCV DNN (This Post)