What is the main goal?

Most of online casinos and gambling providers struggle the real problem with the delivery of their products. Why is it? The reason is the problematic fast testing. Of course that it is caused by that fact, that the games are not easy for the standard test automation. And the approaches, that need to be used are much more complicated and advanced. The topic of playing cards detection and also roulette recognition remains the most popular casino topic in the world of testing.

So, what to do? Just hire more QA engineers? With this approach number of QA engineers will be growing proportionally to the number of the games. It doesn’t sound as the best business strategy. Also, most of the companies have no ideas how to handle this case due to its complexity. Yes, automation testing of the games is not an easy process and requires much more additional skills. Will it be easy to find an appropriate Test automation engineer who will do this? 99% of test engineers are specialising in building automation strategies of standard web and mobile applications, using Appium, Selenium, Cucumber. So, what to do to the game-dev companies?

Here, on Testpic, we developed the framework, specially aimed for testing of casino games. 
In the article Part1 we have described a little bit the possibility of detection the playing cards using OpenCV. Let’s take a look here on this example with using of the framework for Deep Learning YOLO3

What we did here?

We have used advanced approaches and techniques of Deep Learning, using YOLO3 for detection the cards of itself. But the recognition of the cards is the only half of the thing. Because the next challenge was to recognise cards values. We have pre-trained own data-set for the most advanced Optical Character Recognition framework called Tesseract version 4. The biggest challenge here was to collect the exact amount of cards that will be enough for training of neural network.

Testpic provides exceptional  highly-qualified test service for the testing of any types of cards games, such as Black Jack, Poker, Spider, Soliter, etc.

Also we have pre-built services for testing of other types of games, such as online racing, shouters, casino slots and many more.

What are the steps to perform the thing like this?

Firstly you need to prepare the data. There are many instruments which allow to do this. We have used the tool Vott.

After the data was prepared – we prepared the correct algorithm of training the network that fit the best our needs.
In the end, we have re-used the algorithm of suite detection which we described in the previous article. In general – this approach is heavy and difficult, but allows to make the recognition more accurate.

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