Remove Background Skill

When to Use This Skill

• User asks to remove background from an image
• User wants to make an image transparent
• User needs to cut out a subject from a photo
• User wants to process multiple images for background removal

Prerequisites

• Python 3.8+ installed
• Run setup once: pip install "rembg[cpu]" (or rembg[gpu] for NVIDIA GPU)

How It Works

1. User provides image path(s) or glob pattern
2. Run rembg to remove backgrounds
3. Save transparent PNG files with _nobg suffix

Procedure

# Install rembg (first time only)
pip install "rembg[cpu]"

# Remove background from single image
rembg i input.png output.png

# Process multiple images
for f in *.png; do rembg i "$f" "${f%.png}_nobg.png"; done

# Process entire folder
rembg p input_folder output_folder

Options

• -m MODEL - Use specific model (u2net, u2netp, u2net_human_seg, silueta, isnet-general-use, isnet-anime)
• -a - Alpha matting for better edges
• -ae - Alpha matting foreground erosion size
• -om - Only output the mask

Models

• u2net (default) - General purpose, good quality
• u2netp - Lightweight, faster but lower quality
• u2net_human_seg - Optimized for human subjects
• silueta - Good for portraits
• isnet-general-use - High quality general purpose
• isnet-anime - Optimized for anime/cartoon images

Examples

User: "Remove background from player.png"

Expected behavior:

1. Run rembg i player.png player_nobg.png
2. Report success and output path

User: "Remove backgrounds from all images in the characters folder"

Expected behavior:

1. Run rembg p characters/ characters_nobg/
2. Or loop: for f in characters/*.png; do rembg i "$f" "${f%.png}_nobg.png"; done
3. Report number of images processed

User: "Remove background from this anime character"

Expected behavior:

1. Use anime-optimized model: rembg i -m isnet-anime input.png output.png
2. Report success