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README.md

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+# SHARP ONNX — Apple's Single-Image 3D Gaussian Splatting
+
+ONNX export of [Apple's SHARP model](https://github.com/apple/ml-sharp) for use with [tortuise](https://github.com/buildoak/tortuise), a terminal-native 3D Gaussian Splatting viewer.
+
+## Files
+
+| File | Size | Description |
+|------|------|-------------|
+| `sharp.onnx` | 1.9 MB | Model structure (ONNX graph) |
+| `sharp.onnx.data` | 2.6 GB | Model weights (external data) |
+
+Both files are required. The model exceeds protobuf's 2GB limit, so weights are stored separately.
+
+## Usage
+
+These files are automatically downloaded by tortuise when you run:
+
+```bash
+cargo install tortuise --features sharp
+tortuise photo.jpg
+```
+
+Or manually place both files in `~/.tortuise/models/`.
+
+## Model Details
+
+- **Architecture:** DINOv2 ViT-Large encoder + Sliding Pyramid Network + DPT decoders
+- **Parameters:** 702M (340M trainable)
+- **Input:** Single RGB image (resized to 1536×1536 internally)
+- **Output:** ~1.2M 3D Gaussians (positions, scales, rotations, colors, opacities)
+- **ONNX opset:** 17
+- **Source checkpoint:** `sharp_2572gikvuh.pt` from [apple/Sharp](https://huggingface.co/apple/Sharp)
+
+## License
+
+The model weights are licensed under the [Apple Machine Learning Research Model License](LICENSE). This is a **research-only, non-commercial** license. See the LICENSE file for full terms.
+
+This ONNX conversion is a format transformation of Apple's original PyTorch checkpoint. No architectural modifications were made.
+
+## Attribution
+
+Based on Apple SHARP model. Copyright (C) 2025 Apple Inc. Licensed under the Apple Machine Learning Research Model License Agreement.
+
+Paper: [SHARP: Monocular View Synthesis in Less Than a Second](https://arxiv.org/abs/2512.10685)