Remove backgrounds from images with BiRefNet via inference.sh CLI. Model: BiRefNet (high accuracy background removal). Use for: product photos, portraits, e-commerce, transparent PNGs, photo editing. Triggers: remove background, background removal, remove bg, transparent background, cut out image, background remover, rembg, product photo editing, cutout, transparent png, bg removal, photo cutout
Install with the open skills CLI (global, non-interactive — available in every Claude Code session):
npx skills add 101-skills/skills --skill "background-removal" -g -a claude-code -yOr manually — copy the SKILL.md below into:
~/.claude/skills/background-removal-101-skills/SKILL.md---
name: background-removal
description: "Remove backgrounds from images with BiRefNet via inference.sh CLI. Model: BiRefNet (high accuracy background removal). Use for: product photos, portraits, e-commerce, transparent PNGs, photo editing. Triggers: remove background, background removal, remove bg, transparent background, cut out image, background remover, rembg, product photo editing, cutout, transparent png, bg removal, photo cutout"
allowed-tools: Bash(belt *)
---
> **Install the belt CLI skill:** `npx skills add belt-sh/cli`
# Background Removal
Remove backgrounds from images via [inference.sh](https://inference.sh) CLI.

## Quick Start
> Requires inference.sh CLI (`belt`). [Install instructions](https://raw.githubusercontent.com/inference-sh/skills/refs/heads/main/cli-install.md)
```bash
belt login
belt app run infsh/birefnet --input '{"image_url": "https://your-photo.jpg"}'
```
## How To
Use Reve for image editing including background changes:
```bash
belt app run falai/reve --input '{
"prompt": "remove the background, make it transparent",
"image_url": "https://portrait.jpg"
}'
```
Or change background directly:
```bash
belt app run falai/reve --input '{
"prompt": "change the background to a beach",
"image_url": "https://product-photo.jpg"
}'
```
## Workflow: Generate and Edit
```bash
# 1. Generate an image
belt app run falai/flux-dev-lora --input '{"prompt": "a cute robot mascot"}' > robot.json
# 2. Edit with Reve
belt app run falai/reve --input '{
"prompt": "remove background, transparent",
"image_url": "<url-from-step-1>"
}'
```
## Use Cases
- **E-commerce**: Clean product photos
- **Portraits**: Professional headshots
- **Marketing**: Assets for design
- **Social Media**: Profile pictures
- **Design**: Elements for compositions
## Output
Returns a PNG with transparent background.
## Related Skills
```bash
# Full platform skill (all apps)
npx skills add inference-sh/skills@infsh-cli
# Image generation
npx skills add inference-sh/skills@ai-image-generation
# FLUX models (including inpainting)
npx skills add inference-sh/skills@flux-image
# Upscaling
npx skills add inference-sh/skills@image-upscaling
```
Browse all image apps: `belt app store --category image`
## Documentation
- [Running Apps](https://inference.sh/docs/apps/running) - How to run apps via CLI
- [Image Generation Example](https://inference.sh/docs/examples/image-generation) - Complete image workflow guide
- [Apps Overview](https://inference.sh/docs/apps/overview) - Understanding the app ecosystem
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Use when you have a written implementation plan to execute in a separate session with review checkpoints