| --- |
| license: mit |
| library_name: onnx |
| pipeline_tag: image-to-image |
| tags: |
| - migan |
| - inpainting |
| - object-removal |
| - onnx |
| - webgpu |
| --- |
| |
| # MI-GAN (ONNX) — object-removal inpainting |
|
|
| `migan_pipeline_v2.onnx` — 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`](https://huggingface.co/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:** `image` uint8 `[1, 3, H, W]`, `mask` uint8 `[1, 1, H, W]` |
| - **Output:** `result` uint8 `[1, 3, H, W]` — the inpainted image, already |
| composited at the input resolution |
| - RGB, channels-first (CHW). `H` and `W` are dynamic (the graph resizes |
| internally). **Mask polarity: `0` = erase (the hole), `255` = keep.** |
|
|
| ## Provenance & license |
|
|
| - **Algorithm / weights:** **MI-GAN** — *MI-GAN: A Simple Baseline for Image |
| Inpainting on Mobile Devices* (Sargsyan et al., ICCV 2023), |
| [Picsart-AI-Research/MI-GAN](https://github.com/Picsart-AI-Research/MI-GAN). |
| Code and weights are released under the **MIT license**. |
| - **ONNX export:** |
| [andraniksargsyan/migan](https://huggingface.co/andraniksargsyan/migan) |
| (`migan_pipeline_v2.onnx`). |
| - The upstream **MIT `LICENSE`** (© 2024 Picsart AI Research) is included in this |
| repo. |
|
|
