AI Background Removal - ISNet Neural Network - Momo Toolbox
AI Background Removal
ISNet neural network matting, batch supported
AI Background Removal Tutorial
Pick AI model (Fast/Standard) and output format (PNG/WebP), drop or click to upload. AI detects subject and removes background automatically. Batch mode processes multiple images and downloads as ZIP.
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🔒 AI model loaded from CDN (unpkg), ~40-80MB first time, cached in IndexedDB for offline use. Neither model nor images touch the server.
- 🤖 Powered by ISNet neural network; best for people, products, animals
- 💾 First use downloads model (Fast ~40MB / Standard ~80MB); cached for instant reuse
- ⚡ Fast model for previews; Standard for final output
- 🔒 Images processed entirely in browser; no data uploaded
- 📦 Batch results can be downloaded as ZIP
- 🖥️ Requires Chrome 90+ / Edge 90+ / Firefox 88+ (WebAssembly SIMD)
AI Background Removal - Use Cases
AI Background Removal is powered by ISNet neural network running entirely in the browser. Ideal for e-commerce product photos, portrait IDs, social media assets, animal/object subjects. No uploads — privacy safe.
Features
- ISNet neural network: industry-leading model for portraits/products, near-commercial quality
- Dual models: Fast (isnet_fp16, ~40MB) / Standard (isnet_quint8, ~80MB)
- Output formats: PNG (lossless transparent) / WebP (smaller, transparent)
- Batch processing: multiple images processed sequentially with grid progress view
- ZIP packaging: batch results downloaded as a single ZIP
- Drag-drop upload: drop images directly onto the upload area
- Progress indicators: real-time model download and inference progress
- Local inference: images never uploaded; processed in-browser
- IndexedDB cache: model cached after first download, instant reuse
FAQ
Why is the first load so slow?
First use downloads the AI model (Fast ~40MB / Standard ~80MB) from CDN and caches it in IndexedDB. Subsequent uses load instantly and work offline.
Are images uploaded to a server?
No. Both model and images are processed in-browser. Open DevTools → Network to verify zero image upload requests. Fully privacy-first.
What is the difference between Fast and Standard models?
Fast (isnet_fp16) uses half-precision floats — smaller and faster, good for previews. Standard (isnet_quint8) uses 8-bit quantization — higher accuracy, better for complex edges (e.g. hair) in final output.
Why does batch run sequentially instead of concurrently?
AI inference consumes significant memory (WebAssembly + ONNX Runtime). Concurrent processing would OOM the browser. Sequential execution ensures stability.
Which browsers are supported?
Requires a modern browser with WebAssembly SIMD: Chrome 90+, Edge 90+, Firefox 88+, Safari 14.1+. IE and older browsers are not supported.
Want more details? See the full AI Background Removal Tutorial