Input: A screenshot from a minecraft world with a "digit" that is built.
The "digit" must be an image from minecraft (preferrably superflat world with a high contrast block) that is in the shape of the {letter, number, symbol} that you want decoded.
Input2: A world where you would have a 2x2 grid of blocks {9 distinct blocks varying in texture, and color} where you can have a mixture of different blocks on this "wall", in different positions (within the 2x2 grid).
- Different types of blocks
Output2: A list of which blocks are used in the wall.
(1) Data Gathering
- Input: Take a video of all of the pre-constructed {digits, symbols, number}
- Output: Split the video into individual frames
(2) Encoding that data (machine interpretable)
- Input: High Resolution Video Frame (1920x1080)
- Ouput: Low Resolution image (100x100)
(3) Apply our ML Algorithms
- (MVP): We can ask a pre-trained model (that is trained on digit recognition) what their prediction is
- Create our own ML algorithm
(4) Decode into human readable
(5) Output
Model v1.0
Paramaters we can adjust to make it more "minecraftian"
- Change the time of day
- Change the weather
- Change the blocks used to construct the image
- Change the environment {not super-flat}
Output: A minecraft text output with the proper {letter, number, symbol} that you've created.