Image Tools
Background Remover
Remove image backgrounds automatically.
🔒 Runs entirely in your browser — nothing here is ever uploaded
CalcoTools · Background Remover · generated 9/1/2026, 1:32:43 PM
About the Background Remover
Automatically isolates the subject of a photo and makes everything behind it transparent, using an on-device AI model that runs entirely in your browser — the image is never uploaded anywhere.
100% Free Runs in Your Browser No Sign-Up Required
How to use it
- Upload a PNG or JPG photo.
- Choose Photo type — General for products, objects, or pets, or Selfie / portrait for photos of people.
- Click Remove background. The first run downloads the model (a few MB); later runs are faster.
- Download the result as a transparent PNG.
Formula
General mode runs U^2-Net (Qin et al., "U2-Net: Going Deeper with Nested U-Structure for Salient Object Detection," Pattern Recognition, 2020), a neural network trained to predict which pixels belong to the main subject of an image, producing a soft mask that's applied as the output's alpha channel. Selfie/portrait mode instead runs Google's MediaPipe Selfie Segmentation model, optimized specifically for people rather than general objects. Both run as ONNX/TensorFlow.js models entirely client-side via WebAssembly and WebGL — no server, no upload.
Worked example
A product photo shot against a plain studio backdrop typically comes out cleanly with General mode; a headshot or selfie usually segments more precisely in Selfie / portrait mode.
Recommendations
- • Use Selfie / portrait mode for photos of people — it's trained specifically for that case and tends to produce cleaner edges around hair and shoulders than General mode.
- • Use General mode for products, pets, or other objects — Selfie mode won't detect a non-human subject.
- • A clear, reasonably distinct subject against its background gives the cleanest result; busy or low-contrast scenes are harder for any automated tool to isolate precisely.
Frequently asked questions
No. Both modes run as AI models loaded into your browser and executed locally — the photo itself never leaves your device.
Related searches
Sources
- Qin et al. — U2-Net: Going Deeper with Nested U-Structure for Salient Object Detection (Pattern Recognition, 2020) — accessed 2026-08-24
- Google — MediaPipe Selfie Segmentation — accessed 2026-08-24