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| title: MAOAM | |
| emoji: π¨ | |
| colorFrom: yellow | |
| colorTo: pink | |
| sdk: gradio | |
| sdk_version: "5.29.0" | |
| app_file: app.py | |
| short_description: Object and Material Selection VLM | |
| python_version: "3.10" | |
| startup_duration_timeout: "600s" | |
| # MAOAM: Unified Object and Material Selection with Vision-Language Models | |
| This demo showcases **MAOAM** (Mask Any Object And Material), a unified selection framework that enables precise object- and material-level segmentation across both text- and click-based interactions. | |
| ## How to use | |
| 1. **Upload an image** β any RGB photo works. | |
| 2. **Choose a selection mode**: | |
| - **Material: click** β Place star markers on the material you want to segment. | |
| - **Material: text** β Describe the material in words (e.g., "shiny chrome metal"). | |
| - **Object: text** β Name an object (e.g., "the chair"). | |
| 3. **Click Submit** β The model produces a segmentation mask overlaid on your image. | |
| ## Model | |
| This Space uses the **MAOAM-Sa2VA** variant, based on Qwen2.5-VL-7B + SAM2 Hiera-L, fine-tuned for unified object and material selection. | |
| - Paper: [MAOAM: Unified Object and Material Selection with Vision-Language Models](https://arxiv.org/abs/2606.04880) | |
| - Code: [github.com/adobe-research/obj-and-mat-selection](https://github.com/adobe-research/obj-and-mat-selection) | |
| - Weights: [jpark677/maoam_ckpts](https://huggingface.co/jpark677/maoam_ckpts) |