Creative Technology · Computer Vision

AI-Powered Object Detection

Pick a COCO example or upload your own image. Then choose a pretrained detector and let AI answer: what objects are here, and where are they?

Task Object detection Data COCO validation examples Models RT-DETR · DETR · YOLOS Tiny

Choose an image

Start with a tested COCO example, or try a photo of your own.

Start here · COCO examples

Four images are drawn at random from our pre-tested COCO sample bank.

or try your own

Upload an image

Useful for seeing where the model generalizes well—and where it does not.

Choose detector

RT-DETR is the recommended classroom default.

Confidence threshold 0.50

Higher values only keep predictions the model is more confident about.

Choose a COCO example or upload your own image.

AI prediction

What did the detector find?

Waiting

Choose an image first. The original image appears here before detection.

No detections yet.

Object	Confidence	Bounding box
Run the detector to see details.

What you are doing

Use a learned AI capability instead of rebuilding the traditional task from scratch.

COCO contains everyday-object images with annotations. The selected pretrained detector has already learned the object-detection task from labeled data. In this mini-lab, you can switch models and compare how their predictions differ on the same image.

COCO example or your image→ Selected pretrained detector→ Boxes + labels + confidence

Compare models: keep the image fixed, switch detector, and observe how predictions, confidence, and speed change.