Computer Vision is the ability of machines to "see". Not just to record pixels like a camera, but to understand what those pixels represent.

The AI Object Detector scans your image and draws bounding boxes around items it recognizes, labeling them with a confidence score (e.g., "Dog: 98%").

The Model: COCO-SSD

We use a model trained on the COCO (Common Objects in Context) dataset. It can recognize 80 classes of common items, including:

  • Transport: Car, Bicycle, Bus, Airplane, Train, Truck, Boat.
  • Animals: Person, Bird, Cat, Dog, Horse, Sheep, Cow, Elephant, Bear, Zebra, Giraffe.
  • Household: Chair, Couch, Bed, Dining Table, Toilet, TV, Laptop, Mouse, Remote, Keyboard, Cell Phone.
  • Food: Banana, Apple, Sandwich, Orange, Broccoli, Carrot, Pizza, Donut, Cake.

How It Works (YOLO Architecture)

Older AI models looked at an image thousands of times (sliding window). This was slow. Modern models like YOLO (You Only Look Once) and SSD (Single Shot MultiBox Detector) look at the image once and predict all bounding boxes simultaneously. This makes it fast enough to run in real-time on a video feed.

Use Cases

1. Automated Counting

Need to count how many cars are in a parking lot photo? Or how many people are in a crowd? Don't count manually. Let the AI do it.

2. Accessibility

This technology powers "Screen Readers" for the blind, describing images aloud: "A person holding a dog in a park."

3. Content Moderation

Detecting if a photo contains prohibited items (like weapons) automatically.