LaMa Inpainting β€” ONNX (512Γ—512)

LaMa (Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022) exported to ONNX for object removal / inpainting. Fixed 512Γ—512 input.

I/O contract

  • Inputs
    • image β€” float32[1, 3, 512, 512], RGB, normalised /255
    • mask β€” float32[1, 1, 512, 512], 1 = region to erase, 0 = keep
  • Output
    • output β€” float32[1, 3, 512, 512], RGB already in [0, 255] (no *255 needed)

File

  • lama_fp32.onnx β€” SHA-256 1faef5301d78db7dda502fe59966957ec4b79dd64e16f03ed96913c7a4eb68d6

Credits & License

Released under the Apache License 2.0.

  • Original model: LaMa β€” advimman/lama (Apache-2.0).
  • ONNX export based on Carve/LaMa-ONNX (Apache-2.0).
  • Trained on the Places2 dataset (CC-BY 4.0) β€” attribution to the Places2 authors.

If you use this model, please cite the original LaMa paper:

@inproceedings{suvorov2022resolution,
  title     = {Resolution-robust Large Mask Inpainting with Fourier Convolutions},
  author    = {Suvorov, Roman and others},
  booktitle = {WACV},
  year      = {2022}
}
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