Publish q8 CorridorKey v2 MLX profiles, licenses and evidence

.gitattributes

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+licenses/LICENSE-NVIDIA-OPEN-MODEL.pdf filter=lfs diff=lfs merge=lfs -text

.gitignore

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+# macOS metadata, at the root or in any profile directory
+._*
+.DS_Store
+.AppleDouble/
+# Local Hugging Face transfer cache
+.cache/huggingface/

LICENSE

@@ -0,0 +1,597 @@
+CORRIDOR KEY LICENCE
+=======================================================================
+
+Version 2.0
+
+Copyright (c) Corridor Digital LLC. All rights reserved.
+
+
+ADDITIONAL TERMS AND CONDITIONS
+=======================================================================
+
+This work is licensed under the Creative Commons
+Attribution-NonCommercial-ShareAlike 4.0 International Public License
+(CC BY-NC-SA 4.0), the full text of which is included below, subject
+to the following additional terms and conditions. These additional
+terms supplement the CC BY-NC-SA 4.0 licence and take precedence
+where they conflict.
+
+"This tool" means the CorridorKey software in this repository and
+the CorridorKey model weights distributed for use with it.
+
+By exercising any rights to the Licensed Material, You accept and
+agree to be bound by both these Additional Terms and the
+CC BY-NC-SA 4.0 Public License.
+
+
+1. PERMITTED USE
+
+   a. You may use this tool for any lawful purpose, including for
+      processing images as part of a commercial project, provided
+      that such use complies with the restrictions set out below
+      and the terms of the CC BY-NC-SA 4.0 licence.
+
+   b. The images and video You produce with this tool are Yours.
+      The Licensor claims no rights in them, and You may use them
+      commercially.
+
+
+2. RESTRICTIONS
+
+   In addition to the restrictions set out in the CC BY-NC-SA 4.0
+   licence, the following restrictions apply:
+
+   a. NO REPACKAGING OR RESALE
+      You may not repackage, redistribute, sublicense, or sell
+      this tool, in whole or in part, as a standalone product or
+      as part of a competing product, and You may not charge for
+      access to this tool's code or model weights.
+
+   b. NO PAID API OR INFERENCE SERVICES
+      You may not use this tool to provide inference as a paid
+      API service, whether directly or indirectly. This includes,
+      but is not limited to, offering access to this tool behind
+      a paywall, subscription model, or usage-based billing
+      system.
+
+   c. DERIVATIVES MUST BE FREELY ACCESSIBLE
+      You may build on this tool, but any project, fork,
+      derivative work, or modified version that You release and
+      that incorporates this tool must be made available to the
+      public free of charge. Voluntary donations and
+      pay-what-you-want pricing are permitted, provided that
+      paying nothing is always an available option.
+
+   d. COMMERCIAL SOFTWARE INTEGRATION
+      If you operate a commercial software package or inference
+      service and wish to incorporate this tool into your
+      software, you must obtain a separate written agreement
+      from the Licensor. Please contact:
+
+          contact@corridordigital.com
+
+
+3. LARGE ORGANISATIONS
+
+   a. If You are, or are using this tool on behalf of, a Legal
+      Entity whose total gross revenue exceeded US $20,000,000
+      (twenty million US dollars) in its most recently completed
+      fiscal year, the permissions in Section 1 do not apply
+      unless that Legal Entity has purchased a seat of the
+      CorridorKey plugin from the Licensor for each individual
+      who uses this tool.
+
+   b. "Legal Entity" means the entity using this tool together
+      with all other entities that control, are controlled by,
+      or are under common control with it. Revenue is measured
+      across the whole Legal Entity.
+
+   c. Each seat of the CorridorKey plugin includes a licence
+      for one individual to download and use this tool and its
+      model weights. Seats are available at:
+
+          https://corridorkey.com
+
+
+4. ATTRIBUTION
+
+   a. In addition to the attribution requirements set out in
+      Section 3(a) of the CC BY-NC-SA 4.0 licence, You must
+      include the name "CorridorKey" in any attribution notice.
+
+   b. Any fork, derivative work, variation, improvement, or
+      subsequent release of this tool must retain the
+      "CorridorKey" name in a reasonably prominent position.
+
+   c. You may interchange "Corridor Key" for "CorridorKey" as
+      needed.
+
+
+5. SHARE-ALIKE
+
+   Any variations, improvements, derivative works, or modified
+   versions of this tool that are publicly released must be
+   distributed under this same licence, including these Additional
+   Terms, or a licence with substantially equivalent terms.
+
+
+6. THIRD-PARTY COMPONENTS
+
+   This tool depends on third-party code and model weights that
+   are not owned by the Licensor and are not covered by this
+   licence. Each remains under its own licence, as listed in
+   THIRD_PARTY_NOTICES.md.
+
+
+7. DISCLAIMER
+
+   This licence is provided on an "as-is" basis. The Licensor makes
+   no representations or warranties regarding the enforceability or
+   legal sufficiency of these terms. You are encouraged to seek
+   independent legal advice if you have questions about the scope
+   or applicability of this licence.
+
+
+8. CONTRIBUTIONS
+
+   By submitting any contribution (including source code,
+   documentation, or images) to this repository, You agree that:
+
+   a. Your contribution is provided under the terms of this
+      Corridor Key Licence.
+
+   b. You grant the Licensor (Corridor Digital LLC) a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free,
+      irrevocable license to use, reproduce, prepare derivative
+      works of, publicly display, and sublicense your
+      contribution, including for commercial purposes.
+
+   c. You represent that you are the legal owner of the
+      contribution or have the authority to submit it under
+      these terms.
+
+=======================================================================
+
+
+https://creativecommons.org/licenses/by-nc-sa/4.0/
+https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.txt
+
+=======================================================================
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+Attribution-NonCommercial-ShareAlike 4.0 International
+
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README.md

@@ -0,0 +1,241 @@
+---
+license: other
+license_name: corridor-key-licence-2.0
+license_link: https://huggingface.co/cdelta/CorridorKey-v2-MLX-8bit/blob/main/LICENSE
+base_model: nikopueringer/CorridorKey2.0
+base_model_relation: quantized
+library_name: mlx
+pipeline_tag: image-segmentation
+tags:
+  - mlx
+  - apple-silicon
+  - video-matting
+  - green-screen
+  - blue-screen
+  - chroma-key
+  - vfx
+  - fp32
+  - fp16
+  - quantized
+---
+
+<div align="center">
+
+# CorridorKey v2 · MLX · Q8 / 8-bit
+
+### Q8 / 8-bit matting profiles for Apple Silicon
+
+[Source & CLI](https://github.com/peterteravskis/corridorkey-v2-mlx) · [Original model](https://huggingface.co/nikopueringer/CorridorKey2.0) · [Original project](https://github.com/nikopueringer/CorridorKey2.0) · [License](https://huggingface.co/cdelta/CorridorKey-v2-MLX-8bit/blob/main/LICENSE)
+
+</div>
+
+This repository contains the **Q8 / 8-bit profiles** of CorridorKey 2.0 for Apple Silicon. It uses group-64 affine quantization for 445 linear matrices, with FP16 residual weights and activations. No fine-tuning or retraining was performed.
+
+[All variants](https://huggingface.co/collections/cdelta/corridorkey-v2-mlx-6ad84231314d2593c3799e34) · [FP32](https://huggingface.co/cdelta/CorridorKey-v2-MLX-fp32) · [FP16](https://huggingface.co/cdelta/CorridorKey-v2-MLX-fp16) · [Q8 / 8-bit](https://huggingface.co/cdelta/CorridorKey-v2-MLX-8bit) · [Combined bundle](https://huggingface.co/cdelta/CorridorKey-v2-MLX)
+
+**The original model was designed and trained by Zachary Harris in direct
+collaboration with Niko Pueringer and Corridor Digital.** Credit for the model,
+architecture, and training belongs to them. Peter Teravskis maintains this
+community MLX implementation and its Apple Silicon evaluation work.
+For the official supported plugins, visit [corridorkey.com](https://corridorkey.com).
+
+![Squirrel on green screen and redhead on blue screen: a centre stripe separates each input from its background-removed result](assets/screen-to-foreground.png)
+
+Actual FP32 results from the companion CLI, shown with a central split between
+the original screen and a checkerboard transparency preview. Fine fur, a
+blurred paw, flyaway hair, and translucent gauze remain visible. The plates
+are synthetic demonstration inputs, without ground-truth mattes.
+
+| Example | Original input | Transparent 16-bit PNG |
+| :--- | :--- | :--- |
+| Squirrel · green screen | [Input](assets/examples/squirrel-input.png) | [RGBA cutout](assets/examples/squirrel-cutout.png) |
+| Redhead · blue screen | [Input](assets/examples/redhead-input.png) | [RGBA cutout](assets/examples/redhead-cutout.png) |
+
+## Use with the companion runtime
+
+Install the [Apache 2.0 source and CLI](https://github.com/peterteravskis/corridorkey-v2-mlx):
+
+```bash
+git clone https://github.com/peterteravskis/corridorkey-v2-mlx.git
+cd corridorkey-v2-mlx
+python3.12 -m venv .venv
+source .venv/bin/activate
+python -m pip install '.[download]'
+
+hf download cdelta/CorridorKey-v2-MLX-8bit --local-dir /path/to/CorridorKey-v2-MLX
+
+corridorkey-mlx --precision q8 --compile --image-sequence \
+  --model-root /path/to/CorridorKey-v2-MLX \
+  --input /path/to/plate.png --output-dir outputs/plate \
+  --outputs alpha fg raw_fg checker cutout
+```
+
+Use an Apple Silicon Mac with Python 3.12. MLX 0.32.4 and PyTorch 2.9.1 are
+pinned by the source package. PyTorch is used for CPU preparation; the neural
+networks and output renderer execute on MLX. FFmpeg is required for video
+export. The profiles are custom MLX inference graphs, not an MLX-LM or
+Transformers checkpoint; use the companion runtime rather than `AutoModel`.
+
+## Profile contents
+
+| Profile | Components |
+| :--- | :--- |
+| `q8/1024x1536-t1`, `q8/768x1280-t1` | RVM, C-RADIO + MoGe foundations, stage 1, stage 2 |
+| `q8/1024x1536-t4`, `q8/768x1280-t4` | Four-frame stage 1 and an additional 768×1280 stage-two batch profile |
+| `q8/768x1280-t2` | Two-frame stage-two batch profile for API/research use |
+
+Each component contains `graph.json` and `weights.safetensors`. The single-frame
+profile also supplies normalization statistics. Profile names use **height ×
+width**. Inputs are padded to a multiple of 128, then cropped back to their
+native dimensions; the padded shape must match a profile.
+
+For temporal clips of four or more frames, use Hann window/stride **4/2** and
+stage-two batch one. Two- or three-frame clips require their own stage-one
+profiles or explicit **1/1** processing without temporal windows. Larger
+resolutions and other stage-one window lengths are not included in this bundle.
+The [CLI guide](https://github.com/peterteravskis/corridorkey-v2-mlx/blob/main/docs/CLI.md)
+documents input, output, hint, and scratch-storage behavior.
+
+Use this repository with `--precision q8`. Keep its folder layout intact; pass the downloaded repository root to `--model-root`, not its `q8/` subfolder.
+
+For native 1280 × 720 footage, add `--height 768 --width 1280`. Download another precision from the [Collection](https://huggingface.co/collections/cdelta/corridorkey-v2-mlx-6ad84231314d2593c3799e34), or use the [combined bundle](https://huggingface.co/cdelta/CorridorKey-v2-MLX) for all three.
+
+## Precision tradeoffs
+
+FP16 retains sensitive reductions and normalization in FP32. Q8 uses native
+MLX group-64 affine quantization on **445 linear matrices**, covering **74.47%**
+of floating-point parameters, with FP16 residual weights and activations.
+Convolutions and activations are not 8-bit. Output rendering stays FP32.
+
+FP16 and Q8 reduce memory use but change numerical results. The CLI measurements
+below report current time and memory. The retained [precision study](https://github.com/peterteravskis/corridorkey-v2-mlx/blob/main/docs/PRECISION.md)
+compares against FP32 and records larger localized Q8 transparency differences,
+including a maximum 6.885-percentage-point alpha difference on the blue-glass
+fixture. Numerical agreement and visible quality are separate questions.
+
+## Verified parent weights
+
+Direct byte comparisons cover the FP32 conversion inputs and both distributed
+FP32 single-frame profiles. FP16 rounding and Q8
+quantization intentionally change tensor values; their file hashes and source
+conversion hashes are retained separately in the profiles and model manifest.
+
+The official public checkpoint was checked at revision
+`cf44a8db3f024bb49fd59daa408848ccf05f7477` before adding the `base_model` link.
+
+| Check | Result |
+| :--- | :--- |
+| Learned tensors | **738 / 738 equal in direct byte comparisons and SHA-256** |
+| Foundation normalization tensors | **6 / 6 equal in direct byte comparisons and SHA-256** |
+| Tensor names, shapes, and dtypes | Exact match |
+| Distributed FP32 stage-one/stage-two tensors | **1,476 / 1,476 direct byte comparisons passed** across both resolutions |
+| Model configuration | Match after JSON sequence normalization |
+| Missing, extra, or changed learned tensors | None |
+
+The conversion inputs match the official release's tensor payloads byte for
+byte. Exported MLX files have different container hashes because graph export
+names and partitions tensors by component. The model manifest checks the exact
+bytes of the distributed MLX files separately.
+
+- [Current official checkpoint direct-byte verification](current-hf-bytecheck.json)
+- [Distributed FP32 tensor direct-byte verification](fp32-export-bytecheck.json)
+- [Original verification summary](weight-verification.json)
+- [Every tensor's paired SHA-256 hashes](weight-tensor-hashes.json)
+- [Packaged graph/weight file manifest](model-manifest.json)
+
+Official safetensors SHA-256:
+`c43596de98cc8866d577c8a9f9ea239acdf3f7a130ff24e25db4375a50590436`.
+
+## Measurements
+
+The comparison below covers all three companion precision releases. This repository contains Q8 / 8-bit profiles only.
+
+Fresh measurements of this packaged CLI on an **Apple M4 Pro with 48 GiB**, using
+the distributed FP32, FP16, and Q8 profiles. Each condition runs one complete
+warm-up followed by three measured workflows. Timings include input decoding,
+neural inference, rendering, four completed 16-bit PNG outputs per frame, and
+scratch cleanup. Initial model loading and compilation are reported separately.
+
+![CLI workflow time and physical memory](assets/cli-workflow.png)
+
+The table below measures **32 moving frames at native 1280 × 720**, padded to
+1280 × 768. Reference mode disables the custom graph rewrites and kernels;
+enabled mode uses the release defaults. Both use identical weights, precision,
+Hann windows/stride 4/2, and stage-two batch one.
+
+| Precision | Reference | Enabled | Less time | Enabled physical memory |
+| :--- | ---: | ---: | ---: | ---: |
+| FP32 | 50.465 s | 37.657 s | **25.4%** | 7.05 GiB |
+| FP16 | 42.975 s | 37.123 s | **13.6%** | 4.11 GiB |
+| Q8 | 46.088 s | 39.397 s | **14.5%** | 3.28 GiB |
+
+![CLI kernel optimization comparison with all timing samples](assets/cli-kernel-gains.png)
+
+**The speed optimizations ship enabled.** FP32 uses specialized reconstruction,
+reflection padding/layout, dense projection pairing, and paired 7×7 channel
+convolution. FP16/Q8 use the accepted half-precision paired-convolution path.
+Half-precision projection pairing remains disabled.
+
+![CLI time by processing stage](assets/cli-stage-times.png)
+
+All four stills and all 32 moving frames were compared with optimizations
+enabled and disabled at each precision. Every comparison passed the recorded
+numerical limits. FP16 and Q8 outputs match their own reference paths exactly.
+FP32 differs by at most **1/65535 in alpha** and **2/65535 in the checker output**.
+These checks do not establish FP16/Q8 equality with FP32 or accuracy against
+ground-truth mattes.
+
+![Saved output agreement for every fixture and precision](assets/cli-output-agreement.png)
+
+![Initial model load and first CLI workflow versus warmed execution](assets/cli-first-use.png)
+
+[Methodology and raw samples](https://github.com/peterteravskis/corridorkey-v2-mlx/blob/main/docs/BENCHMARKS.md) ·
+[Kernel implementation and isolated measurements](https://github.com/peterteravskis/corridorkey-v2-mlx/blob/main/docs/OPTIMIZATIONS.md) ·
+[Release validation](https://github.com/peterteravskis/corridorkey-v2-mlx/blob/main/docs/VALIDATION.md).
+
+The retained [MPS comparison](https://github.com/peterteravskis/corridorkey-v2-mlx/blob/main/docs/HISTORICAL_BENCHMARKS.md) and isolated
+operator studies use earlier measurement setups. Their ratios are not combined
+with these CLI results. These measurements describe the recorded Mac and
+fixtures, not a minimum-RAM requirement or a guarantee for other footage.
+
+## Intended use and limitations
+
+Use for green-/blue-screen foreground separation, matte review, and compositing.
+Fine hair, gauze, transparent objects, blur, and subject identity can still need
+artist review or hints. The port does not improve the original model's learned
+semantic decisions. It is a shape-specialized inference release; training and
+arbitrary-shape execution are outside its scope.
+
+The basic CLI accepts display-referred PNG/JPEG/video and produces SDR PNG/video
+exports. It does not expose the original model's HDR EXR workflow. Audio is
+not copied. Validation is specific to the recorded hardware and fixtures;
+other Macs and longer clips need their own evaluation. FP16/Q8 do not meet the
+strict FP32 agreement criteria and remain explicit opt-in choices.
+
+Upstream reports that the original training data was generated in-house using
+3D rendering. No additional training dataset was used for this conversion.
+No broad demographic or production-shot generalization evaluation is claimed.
+See the [original model card](https://huggingface.co/nikopueringer/CorridorKey2.0)
+for the publisher's training and intended-use information.
+
+## License and acknowledgements
+
+CorridorKey-derived weights and graphs retain the unchanged
+[Corridor Key Licence 2.0](https://huggingface.co/cdelta/CorridorKey-v2-MLX-8bit/blob/main/LICENSE), including its additional terms.
+The [Apache 2.0 source license](https://github.com/peterteravskis/corridorkey-v2-mlx/blob/main/LICENSE)
+applies to the separate runtime code and grants no additional rights to these
+model assets.
+
+The foundation components retain their own licenses:
+
+| Component | Publisher | License |
+| :--- | :--- | :--- |
+| [C-RADIOv4-SO400M](https://huggingface.co/nvidia/C-RADIOv4-SO400M) | NVIDIA | NVIDIA Open Model License |
+| [MoGe-2 ViT-B](https://huggingface.co/Ruicheng/moge-2-vitb-normal) | Microsoft / Ruicheng | MIT |
+| [RVM small](https://github.com/google-deepmind/representations4d) | Google DeepMind | CC BY 4.0 weights |
+
+Licensed by NVIDIA Corporation under the NVIDIA Open Model License.
+The foundation profiles are converted representations, not unmodified copies
+of their original file containers. [THIRD_PARTY_NOTICES.md](THIRD_PARTY_NOTICES.md)
+identifies those changes and the bundled license texts. Nothing here implies
+endorsement by the original authors or their organizations.

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THIRD_PARTY_NOTICES.md

@@ -0,0 +1,42 @@
+# Attribution and model licenses
+
+**CorridorKey 2.0** was designed and trained by Zachary Harris in collaboration
+with Niko Pueringer and Corridor Digital.
+
+- Original source: https://github.com/nikopueringer/CorridorKey2.0
+- Original weights: https://huggingface.co/nikopueringer/CorridorKey2.0
+- CorridorKey-derived weights and graphs: [Corridor Key Licence 2.0](LICENSE), unchanged.
+
+This repository contains MLX conversions by Peter Teravskis. The FP32 conversion
+preserves the learned parameter values; FP16 and Q8 variants apply rounding and
+quantization. The conversion exports shape-specialized component graphs and
+safetensors. It is a community conversion, without implied endorsement.
+
+## Foundation components
+
+| Component | Original source | Bundled license |
+| :--- | :--- | :--- |
+| NVIDIA C-RADIOv4-SO400M | https://huggingface.co/nvidia/C-RADIOv4-SO400M | [NVIDIA Open Model License](licenses/LICENSE-NVIDIA-OPEN-MODEL.pdf) |
+| Microsoft / Ruicheng MoGe-2 ViT-B | https://huggingface.co/Ruicheng/moge-2-vitb-normal | [MIT / MoGe notices](licenses/MoGe-LICENSE) |
+| Google DeepMind RVM small | https://github.com/google-deepmind/representations4d | [CC BY 4.0](licenses/LICENSE-CC-BY-4.0.txt) |
+
+Licensed by NVIDIA Corporation under the NVIDIA Open Model License.
+The NVIDIA notice is also retained in [licenses/NVIDIA-NOTICE](licenses/NVIDIA-NOTICE).
+
+RVM attribution: Copyright 2025 Google LLC. Associated work: *Recurrent Video
+Masked Autoencoders*, Daniel Zoran, Nikhil Parthasarathy, Yi Yang, Drew A. Hudson,
+Joao Carreira, and Andrew Zisserman. Reference source uses Apache 2.0; the
+checkpoint is CC BY 4.0. MLX export changes the graph/container representation.
+This is not an official Google product.
+
+The combined `foundations` profile contains C-RADIO and MoGe. The `rvm` profile
+contains the recurrent encoder; `stage1` and `stage2` contain CorridorKey's
+matting networks. Model-specific terms continue to apply within combined files.
+Identified DINOv2 source in the MoGe project is Apache 2.0; its notice is retained
+within the MoGe license text. No original foundation-model Python source is
+included in this model bundle.
+
+[UPSTREAM_THIRD_PARTY_NOTICES.md](UPSTREAM_THIRD_PARTY_NOTICES.md) preserves the
+original public project's notices verbatim. Its statement that foundation models
+are downloaded separately describes the upstream repository. This derivative
+bundle includes their converted profiles, under the licenses listed above.

UPSTREAM_THIRD_PARTY_NOTICES.md

@@ -0,0 +1,39 @@
+# Third-Party Notices
+
+CorridorKey v2 is licensed under the Corridor Key Licence (see `LICENSE`).
+It depends on the third-party components below, which are not owned by
+Corridor Digital LLC and remain under their own licenses.
+
+The three foundation models are not redistributed in this repository or in the
+CorridorKey Hugging Face repository. `scripts/download_weights.py` fetches them
+from their original publishers.
+
+## C-RADIOv4-SO400M
+
+- Publisher: NVIDIA Corporation
+- Source: https://huggingface.co/nvidia/C-RADIOv4-SO400M
+- License: [NVIDIA Open Model License](https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf)
+- Use: frozen visual feature extractor, downloaded to `vfms/cradio/`
+
+Licensed by NVIDIA Corporation under the NVIDIA Open Model License.
+
+## MoGe-2 ViT-B
+
+- Publisher: Microsoft Corporation
+- Source: https://github.com/microsoft/MoGe, weights at https://huggingface.co/Ruicheng/moge-2-vitb-normal
+- License: MIT (code and weights)
+- Use: frozen geometry feature extractor. The model code is vendored in
+  `third_party/MoGe/` with its license at `third_party/MoGe/LICENSE`; weights
+  are downloaded to `vfms/moge/`.
+
+The vendored MoGe code includes DINOv2 (Meta Platforms, Inc.), licensed under
+the Apache License 2.0, also reproduced in `third_party/MoGe/LICENSE`.
+
+## RVM (Recurrent Video MAE), small
+
+- Publisher: Google DeepMind
+- Source: https://github.com/google-deepmind/representations4d
+- License: Apache License 2.0 (code), Creative Commons Attribution 4.0 (weights)
+- Use: frozen recurrent video feature extractor. `corridorkey/rvm.py` is a
+  PyTorch port of the reference architecture; weights are downloaded to
+  `vfms/rvm/`.

assets/examples/manifest.json

@@ -0,0 +1,30 @@
+[
+  {
+    "file": "examples/squirrel-input.png",
+    "sha256": "0a721e992526212122e118c794d9f6e2476165b1164571a69a08a55c4cb41197",
+    "role": "synthetic demonstration input",
+    "precision": "fp32",
+    "screen": "green"
+  },
+  {
+    "file": "examples/squirrel-cutout.png",
+    "sha256": "3d9e3dbe9c0425bf16cc140f7000009841715e654956dadcc6a6ee311dd19b71",
+    "role": "unaltered 16-bit RGBA output from release CLI",
+    "precision": "fp32",
+    "screen": "green"
+  },
+  {
+    "file": "examples/redhead-input.png",
+    "sha256": "ef1e5b6a1daf2e29db36f0e03e5ed9b79966f4eedbafff6af6cf9e2a4f6e078e",
+    "role": "synthetic demonstration input",
+    "precision": "fp32",
+    "screen": "blue"
+  },
+  {
+    "file": "examples/redhead-cutout.png",
+    "sha256": "0386c30fba4a54596e3ec1ccc87ecd8318afd160b6369191187875924875a6dc",
+    "role": "unaltered 16-bit RGBA output from release CLI",
+    "precision": "fp32",
+    "screen": "blue"
+  }
+]

licenses/LICENSE-CC-BY-4.0.txt

@@ -0,0 +1,396 @@
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licenses/LICENSE-NVIDIA-OPEN-MODEL.pdf

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+version https://git-lfs.github.com/spec/v1
+oid sha256:396d7de220f6b0e6fcfe33836f1b99a9943769b97c56330444f8efe1b441f607
+size 151612

licenses/MoGe-LICENSE

@@ -0,0 +1,224 @@
+    MIT License
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+
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licenses/NVIDIA-NOTICE

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+Licensed by NVIDIA Corporation under the NVIDIA Open Model License

model-manifest.json

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