Object Detection
Detect everyday objects in images or live video using COCO-SSD — entirely in your browser.
Loading COCO-SSD model (~5MB)...
Loaded once, then cached by your browser.
How to use
- 1
Choose Upload Image or Live Camera.
- 2
Wait for the model to detect objects.
- 3
See bounding boxes and a sidebar list of confidences.
AI Object Detection Online — Real-time Detection Free
Detect and identify objects in images or live video using AI. Powered by TensorFlow.js COCO-SSD. Recognizes 80 object categories. Works in your browser.
Upload an image or enable your camera for real-time object detection. The AI draws bounding boxes around detected objects and labels them with confidence percentages. Detected objects are also listed in a sidebar for easy reference — no signup required to use any of it.
The COCO-SSD model can recognize 80 common object categories including people, vehicles, animals, furniture, food and everyday items. COCO-SSD stands for Common Objects in Context — Single Shot Detector, a widely used real-time object detection architecture trained on Microsoft's COCO dataset of over 200,000 labeled images. The model runs entirely in your browser using TensorFlow.js — no images or video frames are sent to any server.
Object detection differs from simple image classification: instead of just labeling what's in a photo, it locates exactly where each object is with a bounding box, and can detect multiple different objects in the same frame simultaneously. This makes it useful for counting items, building accessibility tools that describe a scene out loud, prototyping computer-vision ideas, or simply exploring what modern AI can recognize in a photo you already have.
Because everything runs client-side via TensorFlow.js and WebAssembly, this tool works entirely offline once the ~25MB model has loaded, and nothing you upload or capture via your camera is ever transmitted anywhere. That makes it suitable for testing with personal or sensitive photos where a cloud-based detection API would be a privacy concern.
Frequently Asked Questions
What objects can the AI detect?
The model recognizes 80 object categories from the COCO dataset including person, car, bicycle, dog, cat, chair, bottle, laptop, phone and many more common objects.
How accurate is the detection?
Accuracy varies by object and image quality. Well-lit, clear images of common objects typically achieve 70-95% confidence. The model works best with objects clearly visible and not overlapping.
Does real-time camera detection affect privacy?
No. All processing happens locally in your browser using TensorFlow.js. Camera frames are never sent to Skycally's servers.
Why does the model take time to load?
The COCO-SSD model is approximately 25MB and loads once when you first visit the page. Subsequent uses within the same session are instant.
What is COCO-SSD?
COCO-SSD (Common Objects in Context — Single Shot Detector) is a real-time object detection model trained on Microsoft's COCO dataset. It's optimized to run efficiently in the browser via TensorFlow.js rather than requiring a server.
Can it detect multiple objects at once?
Yes. The model detects and draws a separate bounding box for every object it recognizes in the frame, whether that's 1 object or 20, and lists each one with its own confidence score.
Does it work on mobile devices?
Yes. The tool works on any modern browser, including mobile, though live camera detection performance depends on your device's processing power.
Is this free to use?
Yes, completely free with no signup and no usage limit — the entire model runs in your browser at no cost to you.
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