Forfatter: Robert Colca
Agent, listen up.
The simulation is degrading. We've detected unauthorized modifications to the visual cortex of the mainframe, what the tech boys call "glitches". These aren't just random errors, they are deliberate insertions of chaos.
We believe that our novel AI model, Project: G3P1T, is trying to communicate... or maybe it's just bored. It's pasting random noise, inverting colors, and generally messing up our beautiful 4K wallpapers.
Your mission, should you choose to accept it (and you don't really have a choice, do you?), is to build a system that can identify and segment these glitches.
We will provide you with a set of images. Each image has been corrupted with one or more "glitches".
A glitch can be:
Your task is to generate a binary mask for each image, where white pixels (255) represent the glitch, and black pixels (0) represent the clean image.
You will be provided with:
Training Set (train/ folder):
Test Set (test/ folder):
You must submit a ZIP file containing your predicted masks.
img_001.png, output must be img_001.png).We will evaluate your performance using Intersection over Union (IoU).
If your IoU is high, the simulation stabilizes.
If your IoU is low... well, let's just say you might be reassigned to "garbage collection" in the lower memory sectors.
Good luck, Agent. The Matrix is watching.