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Download README.md from GamutPhoto/gamut-models: direct link, hf CLI and curl.
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https://huggingface.co/GamutPhoto/gamut-models/resolve/main/README.md
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hf download hf://GamutPhoto/gamut-models/README.md
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metadata
license: other
license_name: mixed
tags:
- onnx
- image-segmentation
- depth-estimation
Gamut — mask models
The on-device models behind Gamut's subject, sky and depth masks, kept here so every copy of Gamut downloads exactly the same, checksum-verified files. Gamut downloads a model only when someone chooses to use masks, and never sends a photograph anywhere: all of this runs on the person's own computer.
These are unmodified copies of the files named below. Each keeps its own licence and its authors' credit; nothing here is relicensed.
| File | What it does in Gamut | Model and authors | Copied from | Licence |
|---|---|---|---|---|
birefnet_lite.onnx |
Finds the subject | BiRefNet (lite), Peng Zheng et al. | onnx-community/BiRefNet_lite-ONNX (onnx/model.onnx), an ONNX conversion of ZhengPeng7/BiRefNet_lite |
MIT — LICENSE-BiRefNet.txt |
sam2.1_hiera_tiny_encoder.onnx, sam2.1_hiera_tiny_decoder.onnx |
Picks out the subject someone points at | Segment Anything 2.1 (Hiera tiny), Meta | vietanhdev/segment-anything-2.1-onnx-models (sam2.1_hiera_tiny_20260221.zip), exported with samexporter by Viet-Anh Nguyen |
Apache-2.0 — LICENSE-Apache-2.0.txt |
depth_anything_v2_small.onnx |
Near and far | Depth Anything V2 Small, Lihe Yang et al. | onnx-community/depth-anything-v2-small (onnx/model.onnx) |
Apache-2.0 — LICENSE-Apache-2.0.txt. Only the Small model is Apache-2.0; the Base, Large and Giant models are CC-BY-NC-4.0 and are not used. |
skyseg.onnx |
Finds the sky | Sky segmentation by xiongzhu666 (U²-Net architecture, Qin et al.) | JianyuanWang/skyseg, from xiongzhu666/Sky-Segmentation-and-Post-processing |
MIT — LICENSE-skyseg.txt |
Papers
- Zheng et al., Bilateral Reference for High-Resolution Dichotomous Image Segmentation, CAAI AIR 2024.
- Ravi et al., SAM 2: Segment Anything in Images and Videos, ICLR 2025.
- Yang et al., Depth Anything V2, NeurIPS 2024.
- Qin et al., U²-Net: Going Deeper with Nested U-Structure for Salient Object Detection, Pattern Recognition 2020.