Remove background from an image

This is lucataco’s implementation of the Carve/tracer_b7 model for removing backgrounds from images. It takes any image and returns a transparent PNG with the background removed.

What does this do?

Give this model an image, and it automatically detects the main subject and removes everything else. You get back a clean PNG with a transparent background, ready to drop into your project or design.

The model works well with: - Product photos - Portraits and people - Animals - Objects with complex edges like hair or fur

How it works

This model uses tracer_b7, a neural network trained to identify the main subject in an image and separate it from the background. It’s particularly good at handling tricky edges and complex backgrounds.

The model runs fast—typically finishing in about 2 seconds—which makes it practical for processing lots of images quickly.

Example

After running through the model, you get the same shoe with a transparent background, ready to composite onto any backdrop you want.

What you can use this for

This model is useful for:

Product photography: Clean up product shots for your online store by removing distracting backgrounds. Get that consistent, professional look across all your listings.

Design work: Quickly extract subjects to use in mockups, composites, or marketing materials without manually masking in an image editor.

Social media content: Create images with different backgrounds for posts, ads, or promotional content.

Batch processing: Need to process hundreds of images? This model’s speed makes it practical for large-scale background removal tasks.

Tips for best results

The model works best when the subject is clearly defined and distinguishable from the background. Photos with good lighting and clear separation between subject and background will give you the cleanest results.

If you’re working with images that have very fine details like hair or fur, the model handles these reasonably well, though you might need to do minor touch-ups for the most demanding use cases.

About this implementation

This is lucataco’s implementation of the open source tracer_b7 model from the CarveKit framework. The model achieves strong accuracy on standard benchmarks and balances speed with quality.

Try this model on the Replicate Playground.

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