withoutBG Open Weights vs Pro Model
58 examples, 36 with ground truth. Lower is better. Use the view controls on each row to switch between transparency, chroma key, and alpha matte on all outputs.
| Metric | withoutBG Open-Weight Model | withoutBG Pro Model |
|---|---|---|
| MGE (Edge Quality) | 0.03887 | 0.03233 ✓ |
| MAE (Overall Accuracy) | 0.03281 | 0.03071 ✓ |
| Connectivity | 0.03238 | 0.03060 ✓ |
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Photo by Alexander Dummer on Unsplash
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Photo by Andreas Rasmussen on Unsplash
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Photo by Camila Quintero Franco on Unsplash
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Photo by Carlo Sierra on Unsplash
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Photo by Conor Samuel on Unsplash
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Photo by Lars Bo Nielsen on Unsplash
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Photo by Mayer Tawfik on Unsplash
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Photo by Niko Tsviliov on Unsplash
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Photo by Norbert Braun on Unsplash
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Photo by Vinicius Wiesehofer on Unsplash
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
Not Available
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- 0.03827
- MAE
- 0.00801
- Conn.
- 0.00745
- MGE
- 0.02449✓
- MAE
- 0.00561✓
- Conn.
- 0.00513✓
- MGE
- 0.02810
- MAE
- 0.02909
- Conn.
- 0.02904
- MGE
- 0.02219✓
- MAE
- 0.02769✓
- Conn.
- 0.02764✓
- MGE
- 0.03931
- MAE
- 0.01038
- Conn.
- 0.01018
- MGE
- 0.02617✓
- MAE
- 0.00732✓
- Conn.
- 0.00722✓
- MGE
- 0.01556
- MAE
- 0.00499
- Conn.
- 0.00447
- MGE
- 0.01126✓
- MAE
- 0.00339✓
- Conn.
- 0.00269✓
- MGE
- 0.01735
- MAE
- 0.00687
- Conn.
- 0.00668
- MGE
- 0.01370✓
- MAE
- 0.00627✓
- Conn.
- 0.00610✓
- MGE
- 0.03203
- MAE
- 0.01223
- Conn.
- 0.01087
- MGE
- 0.02480✓
- MAE
- 0.01061✓
- Conn.
- 0.00918✓
- MGE
- 0.01712✓
- MAE
- 0.01079✓
- Conn.
- 0.01024✓
- MGE
- 0.01942
- MAE
- 0.01082
- Conn.
- 0.01029
- MGE
- 0.06369
- MAE
- 0.01273
- Conn.
- 0.01265
- MGE
- 0.05280✓
- MAE
- 0.01033✓
- Conn.
- 0.01043✓
- MGE
- 0.02636
- MAE
- 0.00503
- Conn.
- 0.00479
- MGE
- 0.01234✓
- MAE
- 0.00296✓
- Conn.
- 0.00287✓
- MGE
- 0.01869✓
- MAE
- 0.00816✓
- Conn.
- 0.00786✓
- MGE
- 0.02320
- MAE
- 0.00840
- Conn.
- 0.00849
- MGE
- 0.02853
- MAE
- 0.00936
- Conn.
- 0.00923
- MGE
- 0.02596✓
- MAE
- 0.00885✓
- Conn.
- 0.00851✓
- MGE
- 0.04587
- MAE
- 0.01240
- Conn.
- 0.01258
- MGE
- 0.02603✓
- MAE
- 0.00683✓
- Conn.
- 0.00674✓
- MGE
- 0.01224
- MAE
- 0.00520
- Conn.
- 0.00515
- MGE
- 0.00681✓
- MAE
- 0.00344✓
- Conn.
- 0.00323✓
- MGE
- 0.03009
- MAE
- 0.01084
- Conn.
- 0.01069
- MGE
- 0.01785✓
- MAE
- 0.00705✓
- Conn.
- 0.00698✓
- MGE
- 0.04795
- MAE
- 0.01123
- Conn.
- 0.01103
- MGE
- 0.03575✓
- MAE
- 0.00888✓
- Conn.
- 0.00864✓
- MGE
- 0.01477
- MAE
- 0.00731
- Conn.
- 0.00697
- MGE
- 0.01188✓
- MAE
- 0.00560✓
- Conn.
- 0.00515✓
- MGE
- 0.01251✓
- MAE
- 0.00568✓
- Conn.
- 0.00480✓
- MGE
- 0.01875
- MAE
- 0.00926
- Conn.
- 0.00890
- MGE
- 0.05039
- MAE
- 0.02393
- Conn.
- 0.02378
- MGE
- 0.04310✓
- MAE
- 0.02258✓
- Conn.
- 0.02251✓
- MGE
- 0.03115
- MAE
- 0.01899
- Conn.
- 0.01896
- MGE
- 0.01629✓
- MAE
- 0.00464✓
- Conn.
- 0.00458✓
- MGE
- 0.37414
- MAE
- 0.49631
- Conn.
- 0.49210
- MGE
- 0.33352✓
- MAE
- 0.34456✓
- Conn.
- 0.35098✓
- MGE
- 0.02245
- MAE
- 0.00523
- Conn.
- 0.00503
- MGE
- 0.01895✓
- MAE
- 0.00451✓
- Conn.
- 0.00426✓
- MGE
- 0.00932
- MAE
- 0.00731
- Conn.
- 0.00723
- MGE
- 0.00709✓
- MAE
- 0.00649✓
- Conn.
- 0.00639✓
- MGE
- 0.01754✓
- MAE
- 0.00608
- Conn.
- 0.00528
- MGE
- 0.01788
- MAE
- 0.00606✓
- Conn.
- 0.00521✓
- MGE
- 0.03535
- MAE
- 0.00615
- Conn.
- 0.00610
- MGE
- 0.03314✓
- MAE
- 0.00544✓
- Conn.
- 0.00550✓
- MGE
- 0.01507
- MAE
- 0.02355✓
- Conn.
- 0.02418✓
- MGE
- 0.01489✓
- MAE
- 0.02831
- Conn.
- 0.02966
- MGE
- 0.01807
- MAE
- 0.00420
- Conn.
- 0.00401
- MGE
- 0.01238✓
- MAE
- 0.00266✓
- Conn.
- 0.00271✓
- MGE
- 0.01089
- MAE
- 0.00275
- Conn.
- 0.00248
- MGE
- 0.00947✓
- MAE
- 0.00208✓
- Conn.
- 0.00167✓
- MGE
- 0.01419
- MAE
- 0.00609
- Conn.
- 0.00537
- MGE
- 0.01028✓
- MAE
- 0.00472✓
- Conn.
- 0.00378✓
- MGE
- 0.02140
- MAE
- 0.00739
- Conn.
- 0.00718
- MGE
- 0.01861✓
- MAE
- 0.00706✓
- Conn.
- 0.00671✓
- MGE
- 0.03300
- MAE
- 0.01786✓
- Conn.
- 0.01614✓
- MGE
- 0.02155✓
- MAE
- 0.02638
- Conn.
- 0.02497
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- ?
- MAE
- ?
- Conn.
- ?
- MGE
- 0.06131✓
- MAE
- 0.09372✓
- Conn.
- 0.09310✓
- MGE
- 0.06565
- MAE
- 0.09469
- Conn.
- 0.09398
- MGE
- 0.09468
- MAE
- 0.01882
- Conn.
- 0.01849
- MGE
- 0.07565✓
- MAE
- 0.01517✓
- Conn.
- 0.01499✓
- MGE
- 0.04716
- MAE
- 0.24497✓
- Conn.
- 0.24520✓
- MGE
- 0.03932✓
- MAE
- 0.36117
- Conn.
- 0.36178
- MGE
- 0.01980
- MAE
- 0.00724
- Conn.
- 0.00659
- MGE
- 0.01547✓
- MAE
- 0.00542✓
- Conn.
- 0.00430✓
- MGE
- 0.02499✓
- MAE
- 0.01318✓
- Conn.
- 0.01269✓
- MGE
- 0.02804
- MAE
- 0.01535
- Conn.
- 0.01514
- MGE
- 0.01003
- MAE
- 0.00726
- Conn.
- 0.00712
- MGE
- 0.00929✓
- MAE
- 0.00502✓
- Conn.
- 0.00441✓
Methodology
- Alpha mattes are grayscale masks encoding per-pixel foreground probability. They capture fine edge detail (hair, fur, semi-transparent regions) that binary masks discard.
- Metrics are computed by comparing predicted mattes against a ground-truth reference: MGE measures edge sharpness, MAE measures pixel-level accuracy, and Connectivity penalises fragmented foreground regions. All three are lower-is-better.
- Scores are shown as ? when no ground-truth matte is available for that image. See the alpha matting evaluation benchmark for details on the evaluation methodology.
Photo Credits
Source images are courtesy of the photographers below via Unsplash.
Technical Specifications#
| Feature | Open Model | Pro Model (Cloud) |
|---|---|---|
| Status | Active (Open Source) | Active (Cloud API) |
| Availability | Apache 2.0 | API only |
| Pixel Accuracy | Excellent | Best Overall |
| Edge Quality | Excellent | Superior |
| Hardware | CPU / GPU | Managed (AWS Frankfurt) |
| Privacy | Images never leave your computer | Server-side processing (deleted after use) |
| Free Credits | Unlimited (run locally) | 50 credits on signup |
| Recommended Use | Privacy-sensitive, local processing | Highest quality requirements, production API |
Installation#
The Open Model runs locally; the cloud API is accessed via REST.
Open Model
Run instantly with Docker
docker run -p 80:80 withoutbg/app:latestPress the copy button to copy this command to your clipboard
Python
Install via pip
pip install withoutbgPress the copy button to copy this command to your clipboard
Cloud API
API Request
Process images via the cloud API
api
curl -X POST https://api.withoutbg.com/v1/remove-background \
-H 'Authorization: Bearer YOUR_API_KEY' \
-F 'image=@input.jpg' \
-o output.pngPress the copy button to copy this command to your clipboard
See the full API documentation for integration details.