AI Image Segmentation
Segment images into different regions using AI that runs 100% in your browser. Upload any image to see color-coded overlays of detected objects, people, sky, ground, and more. Toggle individual segments on and off, then download. Your images never leave your device.
Drop an image here or click to upload
Supports JPG, PNG, WebP — max 10MB
Segmentation Result
How AI Image Segmentation Works in Your Browser
This tool uses the DETR (Detection Transformer) model with a ResNet-50 backbone, fine-tuned for panoptic segmentation. Running directly in your browser via Transformers.js, it identifies and separates every distinct region of an image — from people and animals to furniture, vehicles, sky, and ground. Each detected segment is assigned a unique color overlay that you can toggle on and off.
Panoptic segmentation combines two types of segmentation: semantic segmentation (labeling every pixel with a category like "sky" or "road") and instance segmentation (distinguishing between individual objects of the same type, like "person 1" and "person 2"). This gives you the most comprehensive view of what the AI sees in your image.
What Gets Detected
- People and body parts — Individual people, faces, hands
- Animals — Dogs, cats, birds, horses, and more
- Vehicles — Cars, trucks, bicycles, motorcycles, buses
- Outdoor elements — Sky, trees, grass, water, mountains
- Indoor objects — Furniture, appliances, electronics
- Food and items — Plates, cups, bottles, and everyday objects
Use Cases for Image Segmentation
Photo Editing and Design
Isolate specific objects in photos for compositing, collage creation, or selective editing. Toggle segments on and off to focus on individual elements. Download the segmented overlay and use it as a guide for manual editing in tools like Photoshop, GIMP, or Figma.
Content Creation
Understand the composition of images for social media, marketing materials, or website design. See exactly how the AI breaks down a scene to make better creative decisions about cropping, layering, and visual hierarchy.
Education and Computer Vision
Students and developers learning about computer vision can see panoptic segmentation in action without writing any code. Experiment with different images to understand how AI perceives and categorizes visual information. The interactive toggle feature makes it easy to explore individual segments.
Complete Privacy for Your Images
Every image you process stays entirely on your device. The DETR model is downloaded once (approximately 160MB) and cached in your browser for offline use. No server ever sees your images, making this tool safe for sensitive photos, proprietary design work, or any content you want to keep private.
Frequently Asked Questions
Is my image kept private during segmentation?
Yes. The entire segmentation process runs locally in your browser using Transformers.js. Your image is never uploaded to any server. It is safe for proprietary photos, design work, and sensitive content.
What does panoptic segmentation mean?
Panoptic segmentation combines semantic segmentation (labeling every pixel as sky, road, person, etc.) with instance segmentation (distinguishing between individual objects like person-1 and person-2). This gives you the most complete breakdown of an image.
Can I toggle individual segments on and off?
Yes. After segmentation, each detected segment appears as a clickable chip. Click any chip to toggle that segment off or on. The color overlay updates in real-time on the canvas.
Does this work offline?
Yes. After the first model download (approximately 160MB), the AI is cached in your browser and works without internet. You can segment images anytime.
What browsers are supported?
This works in all modern browsers: Chrome, Firefox, Safari, and Edge. It uses WebAssembly for computation and works on both desktop and mobile devices.
Can I download the segmented result?
Yes. Click the "Download Segmented Image" button to save the current view (overlay, original, or segments-only) as a PNG file. The download includes whichever segments you have toggled on.