AI and Deep Learning for computer vision projects has come to the masses. This can be attributed partly to the community projects that help ease the pain for newbies. [Abhishek] contributes one such project called Monk AI which comes with a GUI for transfer learning.
Monk AI is essentially a wrapper for Computer Vision and deep learning experiments. It facilitates users to finetune deep neural networks using transfer learning and is written in Python. Out of the box, it supports Keras and Pytorch and it comes with a few lines of code; you can get started with your very first AI experiment.
[Abhishek] also has an Object Detection wrapper(GitHub) that has some useful examples as well as a Monk GUI(GitHub) tool that looks similar to the tools available in commercial packages for running, training and inference experiments.
The documentation is a work in progress though it seems like an excellent concept to build on. We need more tools like these to help more people getting started with Deep Learning. Hardware such as the Nvidia Jetson Nano and Google Coral are affordable and facilitate the learning and experimentation.
how detect more than one object? for example I have captcha and text.
how detect char but input are image captcha (whole) and output as asci text. No cuting image
Who would ever want to do that?
The entire point of captcha is to detect human vs program so the only purpose this would have is to bypass that check. The question would then be why would you want to do this automatically? A lot can be inferred but I will withhold judgement if you have a compelling reason.
I had the pleasure of spearheading a Qt project for a scientist over at USGS. We also worked and created an open source Qt application for dealing with Machine learning algorithms. The application is called PyHAT. Feel free to look it up.