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Overview

Image Background Remover automatically removes backgrounds from images with precision edge detection and smart object recognition. The API isolates subjects from their backgrounds, creating clean cutouts perfect for compositing and design work.

API Spec

See API details

Product Page

Learn more about Image Background Remover

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How It Works

  1. Provide an image - Upload the image with the subject you want to isolate
  2. API processes the image - AI detects the subject and removes the background
  3. Download the result - Retrieve your transparent PNG

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Use Cases

  • E-commerce product photos - Clean product images on white/transparent backgrounds
  • Profile photos - Professional headshots without distracting backgrounds
  • Graphic design - Isolate subjects for compositing and collages
  • Social media content - Create cutouts for creative posts
  • Marketing materials - Prepare images for various backgrounds

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Best Practices

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Image Quality

Clear subject separation works best - Images where the subject is clearly distinct from the background produce the cleanest results.
  • Good contrast - Subject should be visually distinct from background
  • Clear edges - Sharp, well-defined subject boundaries help accuracy
  • Minimal overlapping elements - Avoid subjects blending with background

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Subject Types That Work Well

✅ Excellent results:
  • People and portraits
  • Products on simple backgrounds
  • Objects with clear edges
  • Animals and pets
⚠️ May need refinement:
  • Hair against complex backgrounds (very fine details)
  • Transparent or semi-transparent objects
  • Subjects that blend with background colors

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Output Format

The API returns a PNG with transparent background, which:
  • Preserves subject with full quality
  • Has alpha channel for transparency
  • Can be placed on any new background
  • Works in most design software

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Code Examples

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Basic Background Removal

from magic_hour import Client
import os

client = Client(token=os.getenv("MAGIC_HOUR_API_KEY"))

result = client.v1.image_background_remover.generate(
    assets={
        "image_file_path": "https://raw.githubusercontent.com/runshouse/Sample_Assets/main/tomcruise.png"
    },
    name="Product Cutout",
    wait_for_completion=True,
    download_outputs=True,
    download_directory="./outputs/"
)

if result.status == "complete":
    print(f"✅ Background removal complete!")
    print(f"Downloaded to: {result.downloaded_paths}")
    print(f"Credits charged: {result.credits_charged}")
else:
    print(f"❌ Job failed with status: {result.status}")
    if hasattr(result, 'error_message'):
        print(f"Error: {result.error_message}")

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Batch Processing

# Process multiple images
images = [
    "https://raw.githubusercontent.com/runshouse/Sample_Assets/main/tomcruise.png",
    "https://raw.githubusercontent.com/runshouse/Sample_Assets/main/tomcruise.png",
    "https://raw.githubusercontent.com/runshouse/Sample_Assets/main/tomcruise.png"
]

for i, image_url in enumerate(images):
    result = client.v1.image_background_remover.generate(
        assets={
            "image_file_path": image_url
        },
        name=f"Product Cutout {i+1}",
        wait_for_completion=True,
        download_outputs=True,
        download_directory="./outputs/"
    )
    print(f"✅ Downloaded: {result.downloaded_paths}")

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Pricing

OutputCredits
1 background removal5 credits
Try this in our Google Colab Cookbook: Run this API with sample code. Just add your API key.

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API Reference

Image Background Remover API Reference

View full API specification

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