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SKILL verified MIT Self-run

Remove Background

skill-nc9-skills-remove-background · by nc9

Remove backgrounds from images using AI segmentation. Use when user asks to remove, delete, or make transparent backgrounds from photos or images.

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Install

$ agentstack add skill-nc9-skills-remove-background

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

✓ Security review passed
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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Remove Background

Remove image backgrounds using BiRefNet_lite model. Runs locally on CPU, MPS (Apple Silicon), or CUDA.

When to Use

  • User wants to remove background from an image
  • User wants a transparent PNG version of an image
  • User wants to isolate a subject from its background

Requirements

No API keys required. Model downloads automatically on first run (~100MB, cached).

Command

./scripts/remove_background  [options]

Options

| Option | Description | |--------|-------------| | input | Input image path (required) | | -o, --output | Output path (default: {name}_nobg.png) | | -c, --crop | Smart crop to foreground bounding box | | -p, --padding | Padding around crop in pixels (default: 0) | | --device | Force device: cuda/mps/cpu (default: auto-detect) | | -f, --format | Output: json (default) or table |

Examples

# Basic usage - outputs photo_nobg.png
./scripts/remove_background photo.jpg

# Smart crop to subject
./scripts/remove_background photo.jpg --crop

# Smart crop with 20px padding
./scripts/remove_background photo.jpg --crop --padding 20

# Custom output path
./scripts/remove_background photo.jpg -o transparent.png

# Force CPU (if MPS has issues)
./scripts/remove_background photo.jpg --device cpu

# Human-readable output
./scripts/remove_background photo.jpg --format table

Output Format

JSON (default):

{
  "input": "photo.jpg",
  "output": "photo_nobg.png",
  "device": "mps",
  "original_size": [1920, 1080],
  "output_size": [800, 600],
  "cropped": true,
  "crop_box": [120, 80, 920, 680],
  "model": "ZhengPeng7/BiRefNet_lite"
}

Notes

  • First run downloads model (~100MB), subsequent runs use cache
  • Output is always PNG with alpha channel (transparency)
  • Device auto-detection: CUDA > MPS > CPU
  • MPS (Apple Silicon) may have some op fallbacks to CPU

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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