Dice Image Number detector. (Machine Learning)

What we need is a "Dice" detector.

You need to create an app that accepts url get requests with an image as a parameter.

You should be able to call the app like this:

getDiceNumbers?image=[login to view URL]

The image will always be , 12 , 6 sided dices with dark background.

For example: Here is images data: [login to view URL] (This contains 200 test images).

We will need to generate an image similiar to [login to view URL], after each request and serve it via Flask or something, so we can access it like this: showImage?name=[login to view URL]

The program should be able to detect, each individual dice numbers, and return the get request with a json object like this, OR give errors on dices.


dice_amt_found: 12, (Amount of dice the program has found)

generatedImage: [login to view URL]

dices { dice_1: 1,

dice_2: 3,

dice_3: 4,

dice_4: error, //dice is flipped or something





- We must use ML, because openCV will not be 100% detection rate, and its not always correct.

- The app MUST have a detection rate of 100%.

- We must be able to differentiate on error dices. (The ones that are for example flipped to the side, like image #1 from dataset).

- The app should detect the dices individual pips from the dice, even though the dices touch.

- The app should give error if there was error on 1 of the dices. (Shows 2 sides like on here [login to view URL])

- provided request Image size should not matter (Should be able to accept high res full HD image and 720p as well.)

Skills: Machine Learning (ML), OpenCV, Python

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( 6 reviews ) pecs, Denmark

Project ID: #25645970

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