I need to create a chess AI, I have read about various algorithms and ways to build a bot using tensorflow. But i chose minimax because of it's simplicity. I need the code to do make a minimax algorithm, I can't find any online tutorials that help with it and searched pub.dev for a minimax algorithm but couldn't find any. Please help
take a look at wikipedias pseudocode example:
https://en.wikipedia.org/wiki/Minimax#Pseudocode
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I have had an infatuation with a certain concept regarding machine learning that Sethbling proved with his Mar.io program: https://youtu.be/qv6UVOQ0F44
I have a decent amount of logical programming experience in a number of different languages and have read around a lot about machine learning and neural networking.
What I'm looking for is a good set of references that could teach me how to apply neural networks in code, rather than just as a mathematical teaching like most of what I have seen thus far.
Thanks in advance!
Sentdex (https://www.youtube.com/user/sentdex) has incredible tutorials on Youtube and walks through teaching a model to play GTA.
It may seem daunting at first, but the rewards of overcoming such a challenging task will be worth it.
You might want to check out the JavaScript library Neataptic to check out how they implemented neural networks in Agar.IO for example.
You might also want to check out the NeuroEvolution of Augmenting Topologies paper for a basic understanding of neuro-evolution.
I am trying to Code a genetic algorithm in Matlab but really dont know how it works in images and how to proceed? Is there any basic tutorial that can help me understand how to apply GA on images (starting from 2d to multidimentional images ).
That will be a great help for me.
Thanking everyone in anticipations.
Kind Regards.
For GA you need two things: a fitness function that can evaluate any solution and tell how good it is, and a representation of your solution so that you can do crossover and mutation. Once you have these, you are good to go. I'm not an expert on image processing so I can't help you with that exactly.
Look at the book Essentials of metaheuristics which is a very good resource for start with evolutionary computation (and not only that) in general. It's free.
There is a paper on this subject which you can find at the IEEE library. I believe it solves the problem you vaguely describe.
I have seen numerous examples and sample code for detecting emotions from a human face. I am in desperate need of some algorithm to change expressions. I am a new OpenCV learner. I am also confused if this image manipulation can be done using opencv ? Can functions such as warpaffine() be used for this ? If shall be grateful if someone can guide me in steps how to perform this eg. input a neutral face emotion and convert it to smile ?
Try using FaceAPI, it is free to use for non-commercial purposes and works brilliantly. It is well documented and easy to use.
I´m a beginner on computer vision, but I know how to use some functions on opencv. I´m tryng to use Opencv for Document Recognition, I want a help to find the steps for it.
I´m thinking to use opencv example find_obj.cpp , but the documents, for example passport, has some variables, name, birthdate, pictures. So, I need a help to define the steps for it, and if is possible how function I have to use on the steps.
I'm not asking a whole code, but if anyone has any example link or you can just type a walkthrough, it is of great help.
There are two very different steps involved here. One is detecting your object, and the other is analyzing it.
For object detection, you're just trying to figure out whether the object is in the frame, and approximately where it's located. The OpenCv features framework is great for this. For some tutorials and comprehensive sample code, see the OpenCv features2d tutorials and especially the feature matching tutorial.
For analysis, you need to dig into optical character recognition (OCR). OpenCv does not include OCR libraries, but I recommend checking out tesseract-ocr, which is a great OCR library. If your documents have a fixed structured (consistent layout of text fields) then tesseract-ocr is all you need. For more advanced analysis checking out ocropus, which uses tesseract-ocr but adds layout analysis.
I am working with OpenCV for a project used for recognition and I had a general question regarding the API and it's terms. I've looked online and couldn't find anything specific to this but I was wondering what the differences were regarding the Discrete Adaboost, Real AdaBoost, LogitBoost, and Gentle AdaBoost. If anyone could direct me to a pros v cons or a general description about these so that I may research which would be useful.
Update
I have added a link to a powerpoint file that goes over the different variations of the Boosting techniques. Hope this hopes someone else out there.
Adaboost powerpoint
Thanks in advance
There isn't really a simple "always use technique X" otherwise there wouldn't be a need for all the others . You really have to understand the details and experiment.
see The opencv discussion and A list of papers and technical summaries