Live synthetic demo
Read an image. Return an action.
A small trained model looks at the pixels and returns a direction.
Back to finding where to click · Real screenshot recordings
This small trained model reads a 32×32 image and returns UP, RIGHT, DOWN or LEFT. It runs here in your browser. It learned synthetic arrow cards; it is not a general screenshot model.
Loading a small set of trained weights. No large language model download.
Try your own arrow image
Use a dark arrow on a light background. Your image stays in this browser. The model always chooses one of four directions, even for images outside its training.
What actually runs?
A neural network with 32,932 trained parameters receives only the canvas pixels. A 32-unit hidden layer feeds four output scores. The highest score becomes the action. It does not receive the renderer's seed or answer, and it does not generate text.
Try the same test
On 400 new filled-arrow cards, the trained model got 393 / 400 correct; four fixed image templates got 130 / 400. An unseen outline style scored 349 / 400 with the trained model. These are synthetic checks, not evidence of real-screen accuracy.
Training, controls and limitations · Sealed experiment · Every saved result