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Remove Background

Automatically remove backgrounds from images with AI-powered technology.

Step 1: Upload Image

Upload Image

Drag and drop your image here, or click to select

Supports JPG, PNG, WebP, and more

How it Works:

  1. 1. Upload an image with a background
  2. 2. Our AI automatically detects and removes it
  3. 3. Choose your processing mode and output format
  4. 4. Use PNG or WebP for transparency, or JPEG for white
  5. 5. Use it in designs, websites, or other projects

Features

  • • AI-powered detection
  • • Automatic background removal
  • • Multiple output formats
  • • Standard and HQ model modes
  • • Edge quality varies by subject

Create a cutout with model-generated edges

Remove Background uploads a JPEG, PNG, or WebP image to a server model that estimates foreground and background. Standard mode uses U2Net; HQ mode uses BiRefNet General and can take longer.

Subjects that usually give the model a clear signal

  • •A product photographed against a contrasting surface.
  • •A profile image where the person is visually distinct from the background.
  • •A simple object cutout for a presentation or catalog draft.

How to use this tool

  1. 1.Upload a JPEG, PNG, or WebP no larger than 20 MB.
  2. 2.Try Standard first; use HQ when the edge needs another pass.
  3. 3.Choose PNG or WebP to retain transparency, or JPG to place the cutout on white.
  4. 4.Zoom into edges before downloading.

Output and model behavior

  • The server runs rembg with U2Net or BiRefNet General and initially creates an RGBA PNG.
  • PNG keeps alpha transparency; WebP is encoded with quality 85; JPG is flattened onto white at quality 90.
  • Temporary model input, output, and script files are deleted in the request cleanup path.

Example: isolate a dark shoe on a light table

Standard mode may create a usable product cutout because the boundary is distinct. Choose PNG for a transparent catalog layer. If a pale shoelace blends into the table, HQ may improve it, but the missing edge can still require manual masking.

Edges that remain difficult

  • Hair, fur, smoke, glass, translucent fabric, motion blur, and fine spokes are hard segmentation cases.
  • Foreground and background with similar colors can produce missing or extra regions.
  • The tool has no manual brush or edge-refinement controls, and model output is not guaranteed to be exact.

Get a cleaner cutout

  • Use an image with stronger lighting and foreground/background contrast.
  • Try HQ mode once; if the same region fails, use an editor with a manual mask.
  • Transparency missing: choose PNG or WebP, because JPG is intentionally flattened to white.

Continue the workflow

Return to Image tools, or continue with a complementary tool:

Crop ImageTighten composition before or after creating a cutout.Resize ImageSet final cutout dimensions.Compress ImageReduce delivery size after checking edges.

Questions about this specific tool

Which formats can I upload?

The server validates JPEG, PNG, and WebP input and enforces a 20 MB maximum.

Which output keeps transparency?

Choose PNG or WebP. JPG cannot carry alpha transparency and is flattened onto a white background.

What is the difference between Standard and HQ?

Standard uses U2Net. HQ uses BiRefNet General, which is a larger model and may take longer; neither guarantees a perfect edge.

Why did hair or glass disappear?

Fine and translucent boundaries contain mixed foreground/background information, which segmentation models can classify incorrectly.