Kaggle was having an Image Challenge and I decided to try my hand at it. The challenge is to identify ships on the ocean from satellite images.

My first attempt involved blurring the training images. Attempting to filter large parts of the ocean. Then logging parts of the image for kNN usage. And noting if the image piece was contained a piece of the ship. To attempt to reduce training set size, the initial image piece was larger that what was reasonable for reporting back as true or false. My strategy was to take a smaller piece of the identified image and log that part as well.

This first attempt turned out well, and I plan to make another attempt or 2. My code on GitHub.

Steps listed below

1. Original Image with Training Data
   
2. Blur and filter image
   
3. Identify larger pieces (32×32 pixels) based on training data. (Thinner lines are False, thicker lines are True)
   
4. Identify smaller pieces (4×4 pixels) based on training data. (Thinner lines are False, thicker lines are True)
   
5. Apply data to knn
6. Review test image
   
7. Get result of larger images
   
8. Get result of smaller images
   
9. Generate data to submit
   
10. Comparison of Prediction and Test data
    

Built upon the previous video by changing input from keyboard to AR input. Buttons on side of checkerboard allow for increasing size of cube and rotating around the checkerboard.

A 2nd camera allows for input to be dismissed when hovering over the AR button.

Code is at my GitHub.