Upload folder using huggingface_hub

.gitattributes

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LICENSE

@@ -0,0 +1,47 @@
+Copyright (C) 2025 Apple Inc. All Rights Reserved.
+
+Disclaimer: IMPORTANT:  This Apple software is supplied to you by Apple
+Inc. ("Apple") in consideration of your agreement to the following
+terms, and your use, installation, modification or redistribution of
+this Apple software constitutes acceptance of these terms.  If you do
+not agree with these terms, please do not use, install, modify or
+redistribute this Apple software.
+
+In consideration of your agreement to abide by the following terms, and
+subject to these terms, Apple grants you a personal, non-exclusive
+license, under Apple's copyrights in this original Apple software (the
+"Apple Software"), to use, reproduce, modify and redistribute the Apple
+Software, with or without modifications, in source and/or binary forms;
+provided that if you redistribute the Apple Software in its entirety and
+without modifications, you must retain this notice and the following
+text and disclaimers in all such redistributions of the Apple Software.
+Neither the name, trademarks, service marks or logos of Apple Inc. may
+be used to endorse or promote products derived from the Apple Software
+without specific prior written permission from Apple.  Except as
+expressly stated in this notice, no other rights or licenses, express or
+implied, are granted by Apple herein, including but not limited to any
+patent rights that may be infringed by your derivative works or by other
+works in which the Apple Software may be incorporated.
+
+The Apple Software is provided by Apple on an "AS IS" basis.  APPLE
+MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION
+THE IMPLIED WARRANTIES OF NON-INFRINGEMENT, MERCHANTABILITY AND FITNESS
+FOR A PARTICULAR PURPOSE, REGARDING THE APPLE SOFTWARE OR ITS USE AND
+OPERATION ALONE OR IN COMBINATION WITH YOUR PRODUCTS.
+
+IN NO EVENT SHALL APPLE BE LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL
+OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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+AND WHETHER UNDER THEORY OF CONTRACT, TORT (INCLUDING NEGLIGENCE),
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+POSSIBILITY OF SUCH DAMAGE.
+
+
+-------------------------------------------------------------------------------
+SOFTWARE DISTRIBUTED IN THIS REPOSITORY:
+
+This software includes a number of subcomponents with separate
+copyright notices and license terms - please see the file ACKNOWLEDGEMENTS.
+-------------------------------------------------------------------------------

LICENSE_MODEL

@@ -0,0 +1,88 @@
+Disclaimer: IMPORTANT: This Apple Machine Learning Research Model is
+specifically developed and released by Apple Inc. ("Apple") for the sole purpose
+of scientific research of artificial intelligence and machine-learning
+technology. “Apple Machine Learning Research Model” means the model, including
+but not limited to algorithms, formulas, trained model weights, parameters,
+configurations, checkpoints, and any related materials (including
+documentation).
+
+This Apple Machine Learning Research Model is provided to You by
+Apple in consideration of your agreement to the following terms, and your use,
+modification, creation of Model Derivatives, and or redistribution of the Apple
+Machine Learning Research Model constitutes acceptance of this Agreement. If You
+do not agree with these terms, please do not use, modify, create Model
+Derivatives of, or distribute this Apple Machine Learning Research Model or
+Model Derivatives.
+
+* License Scope: In consideration of your agreement to abide by the following
+  terms, and subject to these terms, Apple hereby grants you a personal,
+  non-exclusive, worldwide, non-transferable, royalty-free, revocable, and
+  limited license, to use, copy, modify, distribute, and create Model
+  Derivatives (defined below) of the Apple Machine Learning Research Model
+  exclusively for Research Purposes. You agree that any Model Derivatives You
+  may create or that may be created for You will be limited to Research Purposes
+  as well. “Research Purposes” means non-commercial scientific research and
+  academic development activities, such as experimentation, analysis, testing
+  conducted by You with the sole intent to advance scientific knowledge and
+  research. “Research Purposes” does not include any commercial exploitation,
+  product development or use in any commercial product or service.
+
+* Distribution of Apple Machine Learning Research Model and Model Derivatives:
+  If you choose to redistribute Apple Machine Learning Research Model or its
+  Model Derivatives, you must provide a copy of this Agreement to such third
+  party, and ensure that the following attribution notice be provided: “Apple
+  Machine Learning Research Model is licensed under the Apple Machine Learning
+  Research Model License Agreement.” Additionally, all Model Derivatives must
+  clearly be identified as such, including disclosure of modifications and
+  changes made to the Apple Machine Learning Research Model. The name,
+  trademarks, service marks or logos of Apple may not be used to endorse or
+  promote Model Derivatives or the relationship between You and Apple. “Model
+  Derivatives” means any models or any other artifacts created by modifications,
+  improvements, adaptations, alterations to the architecture, algorithm or
+  training processes of the Apple Machine Learning Research Model, or by any
+  retraining, fine-tuning of the Apple Machine Learning Research Model.
+
+* No Other License: Except as expressly stated in this notice, no other rights
+  or licenses, express or implied, are granted by Apple herein, including but
+  not limited to any patent, trademark, and similar intellectual property rights
+  worldwide that may be infringed by the Apple Machine Learning Research Model,
+  the Model Derivatives or by other works in which the Apple Machine Learning
+  Research Model may be incorporated.
+
+* Compliance with Laws: Your use of Apple Machine Learning Research Model must
+  be in compliance with all applicable laws and regulations.
+
+* Term and Termination: The term of this Agreement will begin upon your
+  acceptance of this Agreement or use of the Apple Machine Learning Research
+  Model and will continue until terminated in accordance with the following
+  terms. Apple may terminate this Agreement at any time if You are in breach of
+  any term or condition of this Agreement. Upon termination of this Agreement,
+  You must cease to use all Apple Machine Learning Research Models and Model
+  Derivatives and permanently delete any copy thereof. Sections 3, 6 and 7 will
+  survive termination.
+
+* Disclaimer and Limitation of Liability: This Apple Machine Learning Research
+  Model and any outputs generated by the Apple Machine Learning Research Model
+  are provided on an “AS IS” basis. APPLE MAKES NO WARRANTIES, EXPRESS OR
+  IMPLIED, INCLUDING WITHOUT LIMITATION THE IMPLIED WARRANTIES OF
+  NON-INFRINGEMENT, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE,
+  REGARDING THE APPLE MACHINE LEARNING RESEARCH MODEL OR OUTPUTS GENERATED BY
+  THE APPLE MACHINE LEARNING RESEARCH MODEL. You are solely responsible for
+  determining the appropriateness of using or redistributing the Apple Machine
+  Learning Research Model and any outputs of the Apple Machine Learning Research
+  Model and assume any risks associated with Your use of the Apple Machine
+  Learning Research Model and any output and results. IN NO EVENT SHALL APPLE BE
+  LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING
+  IN ANY WAY OUT OF THE USE, REPRODUCTION, MODIFICATION AND/OR DISTRIBUTION OF
+  THE APPLE MACHINE LEARNING RESEARCH MODEL AND ANY OUTPUTS OF THE APPLE MACHINE
+  LEARNING RESEARCH MODEL, HOWEVER CAUSED AND WHETHER UNDER THEORY OF CONTRACT,
+  TORT (INCLUDING NEGLIGENCE), STRICT LIABILITY OR OTHERWISE, EVEN IF APPLE HAS
+  BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+* Governing Law: This Agreement will be governed by and construed under the laws
+  of the State of California without regard to its choice of law principles. The
+  Convention on Contracts for the International Sale of Goods shall not apply to
+  the Agreement except that the arbitration clause and any arbitration hereunder
+  shall be governed by the Federal Arbitration Act, Chapters 1 and 2.
+
+Copyright (C) 2025 Apple Inc. All Rights Reserved.

README.md

@@ -0,0 +1,131 @@
+---
+license: apple-amlr
+library_name: ml-sharp
+pipeline_tag: image-to-3d
+base_model: apple/Sharp
+tags:
+- webgpu
+- onnx
+- transformers.js
+- gaussian-splatting
+- view-synthesis
+- apple-amlr
+---
+
+# ml-sharp-webgpu
+
+This repository contains a browser-oriented ONNX/WebGPU export of Apple's SHARP
+monocular view-synthesis model. It is a derived artifact of the official
+[`apple/Sharp`](https://huggingface.co/apple/Sharp) checkpoint, packaged for the
+`sharp_webgpu.html` browser runtime in
+[`apple/ml-sharp`](https://github.com/apple/ml-sharp).
+
+This is not the official Apple checkpoint repository and is not endorsed by
+Apple. The goal of this repo is to make the released research model easier to
+run in WebGPU-capable browsers through the SHARP WebGPU pipeline and
+Transformers.js v4.
+
+## Intended Use
+
+- Non-commercial scientific research and academic development.
+- Browser-side WebGPU inference for SHARP image-to-splat and panorama workflows.
+- Local validation of the staged ONNX export against the SHARP WebGPU runtime.
+
+## Not Intended For
+
+- Commercial exploitation.
+- Product development.
+- Use in a commercial product or service.
+- Any use outside the Apple Machine Learning Research Model License Agreement.
+
+## License
+
+The source code in the upstream SHARP project is covered by `LICENSE`.
+
+The model weights and derived model artifacts in this repository are covered by
+`LICENSE_MODEL`, the Apple Machine Learning Research Model License Agreement.
+That license limits use, modification, derivatives, and redistribution to
+research purposes and excludes commercial exploitation, product development, or
+commercial product/service use.
+
+This ONNX/WebGPU bundle is a derived artifact from the released SHARP model and
+should be treated as a model derivative for licensing purposes.
+
+Attribution required by `LICENSE_MODEL`:
+
+> Apple Machine Learning Research Model is licensed under the Apple Machine
+> Learning Research Model License Agreement.
+
+Modifications from the upstream `apple/Sharp` release:
+
+- Exported the PyTorch checkpoint to a staged ONNX layout for browser execution.
+- Split execution into `stage-1` through `stage-4` for ONNX Runtime WebGPU.
+- Applied the ONNX Runtime 1.26 compatibility export/patch that removes
+  `Cast(to=DOUBLE) -> IsInf` adapters emitted by PyTorch `nan_to_num`.
+- Added a `manifest.json` consumed by the SHARP WebGPU runtime.
+
+## Files
+
+```text
+README.md
+LICENSE
+LICENSE_MODEL
+.gitattributes
+config.json
+manifest.json
+sharp_stage_1.onnx
+sharp_stage_1.onnx.data
+sharp_stage_2.onnx
+sharp_stage_3.onnx
+sharp_stage_4.onnx
+SHA256SUMS
+```
+
+## Browser Usage
+
+Serve the SHARP WebGPU app and load this repository through Transformers.js:
+
+```text
+http://localhost:8000/sharp_webgpu.html?model=ml-sharp-webgpu
+```
+
+For local validation before upload, place this folder under `webgpu/models/` and
+open:
+
+```text
+http://localhost:8000/sharp_webgpu.html?model=ml-sharp-webgpu&local=1&localModelPath=./models/
+```
+
+## Validation
+
+This folder was prepared with:
+
+```bash
+./.venv/bin/python webgpu/prepare_hf_release.py --repo-id ml-sharp-webgpu
+```
+
+Before publishing, run:
+
+```bash
+./.venv/bin/python webgpu/prepare_hf_release.py \
+  --repo-id ml-sharp-webgpu \
+  --validate-only
+```
+
+The validation checks that all expected files are present, external ONNX data is
+available, SHA-256 hashes match, license markers exist in this model card, and
+`sharp_stage_1.onnx` no longer contains the ORT 1.26 double-cast export pattern.
+
+## Citation
+
+If you use this model, cite the upstream SHARP work:
+
+```bibtex
+@article{mescheder2025sharp,
+  title      = {Sharp Monocular View Synthesis in Less Than a Second},
+  author     = {Lars Mescheder and Wei Dong and Shiwei Li and Xuyang Bai and Marcel Santos and Peiyun Hu and Bruno Lecouat and Mingmin Zhen and Amael Delaunoy and Tian Fang and Yanghai Tsin and Stephan R. Richter and Vladlen Koltun},
+  journal    = {arXiv preprint arXiv:2512.10685},
+  year       = {2025},
+  url        = {https://arxiv.org/abs/2512.10685},
+}
+```

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config.json

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+{
+  "architectures": [
+    "SharpWebGpuStage"
+  ],
+  "model_type": "custom",
+  "transformers_js_model_type": "sharp-webgpu-stage"
+}

manifest.json

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+  "version": 1,
+  "opset": 17,
+  "precision": "mixed",
+  "internal_resolution": 1536,
+  "output_resolution": 768,
+  "stages": [
+    {
+      "name": "stage-1",
+      "file": "sharp_stage_1.onnx",
+      "inputs": [
+        "image",
+        "disparity_factor"
+      ],
+      "outputs": [
+        "depth",
+        "encoder_feature_0",
+        "encoder_feature_1",
+        "encoder_feature_2",
+        "encoder_feature_3",
+        "encoder_feature_4"
+      ]
+    },
+    {
+      "name": "stage-2",
+      "file": "sharp_stage_2.onnx",
+      "inputs": [
+        "image",
+        "depth"
+      ],
+      "outputs": [
+        "feature_input",
+        "base_mean_x_ndc",
+        "base_mean_y_ndc",
+        "base_mean_inverse_z_ndc",
+        "base_scales",
+        "base_quaternions",
+        "base_colors",
+        "base_opacities",
+        "global_scale"
+      ]
+    },
+    {
+      "name": "stage-3",
+      "file": "sharp_stage_3.onnx",
+      "inputs": [
+        "feature_input",
+        "encoder_feature_0",
+        "encoder_feature_1",
+        "encoder_feature_2",
+        "encoder_feature_3",
+        "encoder_feature_4"
+      ],
+      "outputs": [
+        "delta"
+      ]
+    },
+    {
+      "name": "stage-4",
+      "file": "sharp_stage_4.onnx",
+      "inputs": [
+        "delta",
+        "base_mean_x_ndc",
+        "base_mean_y_ndc",
+        "base_mean_inverse_z_ndc",
+        "base_scales",
+        "base_quaternions",
+        "base_colors",
+        "base_opacities",
+        "global_scale"
+      ],
+      "outputs": [
+        "mean_vectors",
+        "singular_values",
+        "quaternions",
+        "colors",
+        "opacities"
+      ]
+    }
+  ],
+  "ort_compatibility_patch": {
+    "stage-1": "removed Cast(to=DOUBLE)->IsInf adapters emitted by torch.nan_to_num"
+  }
+}

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