MI-GAN (ONNX) β object-removal inpainting
migan_pipeline_v2.onnx β an ONNX export of MI-GAN for image inpainting
(erasing a masked object and filling the hole). This "pipeline" variant takes a
full-size image + mask and returns the composited result, so it runs client-side
with onnxruntime-web on the WASM or WebGPU execution providers with no pre/post
resize step.
A verbatim mirror of
andraniksargsyan/migan's
migan_pipeline_v2.onnx, hosted so a single, immutable, CORS-enabled copy backs
the Edge Tools "Remove Object" tool.
Inputs / outputs
- Inputs:
imageuint8[1, 3, H, W],maskuint8[1, 1, H, W] - Output:
resultuint8[1, 3, H, W]β the inpainted image, already composited at the input resolution - RGB, channels-first (CHW).
HandWare dynamic (the graph resizes internally). Mask polarity:0= erase (the hole),255= keep.
Provenance & license
- Algorithm / weights: MI-GAN β MI-GAN: A Simple Baseline for Image Inpainting on Mobile Devices (Sargsyan et al., ICCV 2023), Picsart-AI-Research/MI-GAN. Code and weights are released under the MIT license.
- ONNX export:
andraniksargsyan/migan
(
migan_pipeline_v2.onnx). - The upstream MIT
LICENSE(Β© 2024 Picsart AI Research) is included in this repo.