Context

Solving a Rubik's cube is now too mainstream they say. But what if you have 10,000 pictures of the Rubiks cube and you are asked to stitch it all together? This is not a problem we need, this is a problem we deserve!

Content

For input you will be given a large number of images, for about half of them, we have measured the orientation of the cube. But to be able to stitch all those images together, you have to figure out how to predict the orientation of the Rubik's Cube for the rest of the images.

The training dataset consists of 5000 images of size 512x512 with 3 channels each (for RGB). The associated labels is single continuous variable:

xRot : Orientation of the Cube, in degrees, along an arbitrarily chosen axis (a number between 0 and 360). The axis around which this value is measured is consistent across the whole of the training and the test set.

The test dataset consists of 5001 images of size 512x512 with 3 channels each (for RGB). The goal of the task is to predict the xRot value of the Rubik's Cube in these test images.

Acknowledgements

This dataset was published on AI Crowd in a so-called KIIT AI (mini)Blitz⚡ Challenge. AI Blitz⚡ is a series of educational challenges by AIcrowd, with an aim to make it really easy for anyone to get started with the world of AI. This AI Blitz⚡challenge was an exclusive challenge just for the students and the faculty of the Kalinga Institute of Industrial Technology.