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+ +# 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) + +
+ +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. 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q8/768x1280-t4/stats.json +dfb814d9a0ac755ee660ee70715db9fd88bc8fc82c89db3726b6d6683794d52b weight-tensor-hashes.json +2fe68699e0144791d0874a5f3a8fa196b828ad064cc82036e17e3ed2e7e3462b weight-verification.json diff --git a/THIRD_PARTY_NOTICES.md b/THIRD_PARTY_NOTICES.md new file mode 100644 index 0000000000000000000000000000000000000000..71cfe8b3708c82298ff3d57de996fc1d92dc5ef5 --- /dev/null +++ b/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. diff --git a/UPSTREAM_THIRD_PARTY_NOTICES.md b/UPSTREAM_THIRD_PARTY_NOTICES.md new file mode 100644 index 0000000000000000000000000000000000000000..924012b75ffcf87f10880e152dd70a1d7b9dd730 --- /dev/null +++ b/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/`. diff --git a/assets/cli-first-use.png b/assets/cli-first-use.png new file mode 100644 index 0000000000000000000000000000000000000000..47ea9a0802e4b2c246ff8b47572958a4c2aa2515 Binary files /dev/null and b/assets/cli-first-use.png differ diff --git a/assets/cli-first-use.svg b/assets/cli-first-use.svg new file mode 100644 index 0000000000000000000000000000000000000000..a0f3e66b4a41d4ef08bef6544cfb0077e633f6ad --- /dev/null +++ b/assets/cli-first-use.svg @@ -0,0 +1,278 @@ + + + + + + + + 2026-10-20T23:05:48.187019 + image/svg+xml + + + Matplotlib v3.11.2, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + 0 + + + + + + + + + 10 + + + + + + + + + 20 + + + + + + + + + 30 + + + + + + + + + 40 + + + + seconds + + + + + + + FP32 + + + + + + FP16 + + + + + + Q8 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 42.1 s + + + 37.7 s + + + 37.3 s + + + 37.1 s + + + 41.6 s + + + 39.4 s + + + + CORRIDORKEY v2 / MLX + + + Initial model load and first CLI workflow + + + 32 moving frames · enabled kernels · first workflow includes graph compilation + + + First use is initial model construction plus the first complete workflow; Python interpreter/import startup is excluded. + Warmed comparison is the median of the next three runs in the same process. Every workflow writes all four PNG outputs. + + + + + + + + + + Initial model load + + + + + + First workflow / compile + + + + + + Warmed workflow + + + + + + + + + diff --git a/assets/cli-kernel-gains.png b/assets/cli-kernel-gains.png new file mode 100644 index 0000000000000000000000000000000000000000..03900a03c72d3600395dbf06f608d0ccf029cfc1 --- /dev/null +++ b/assets/cli-kernel-gains.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:db0427b6328967635e47fe8779ca69a754c550b980b38549fd94528ec9c00d1b +size 121105 diff --git a/assets/cli-kernel-gains.svg b/assets/cli-kernel-gains.svg new file mode 100644 index 0000000000000000000000000000000000000000..e6d08d09620fa05144030a2dd5234943d5d5635e --- /dev/null +++ b/assets/cli-kernel-gains.svg @@ -0,0 +1,338 @@ + + + + + + + + 2026-10-20T23:05:48.030890 + image/svg+xml + + + Matplotlib v3.11.2, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + 0 + + + + + + + + + 10 + + + + + + + + + 20 + + + + + + + + + 30 + + + + + + + + + 40 + + + + + + + + + 50 + + + + + + + + + 60 + + + + seconds / 32-frame CLI workflow + + + + + + + FP32 + + + + + + FP16 + + + + + + Q8 + + + + + + + + + + + + + + + + + + + + + + + 50.47 s + + + 37.66 s + + + 25.4% + + + less time + + + 42.98 s + + + 37.12 s + + + 13.6% + + + less time + + + 46.09 s + + + 39.40 s + + + 14.5% + + + less time + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + CORRIDORKEY v2 / MLX + + + CLI workflow with and without kernel optimizations + + + 32 moving frames · identical precision, input, temporal settings and completed outputs + + + Reference disables custom graph rewrites and kernels; enabled uses the release defaults. Bars: median; dots: all three measured runs. + One full warm-up per process. Includes decoding through completed PNG writing and scratch cleanup. Initial load and compilation excluded. + + + + + + + + + + Reference + + + + + + Enabled + + + + + + + + + diff --git a/assets/cli-output-agreement.png b/assets/cli-output-agreement.png new file mode 100644 index 0000000000000000000000000000000000000000..ee24d07cc50122eb902bdccfcce0c654d5bb26c6 --- /dev/null +++ b/assets/cli-output-agreement.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:579e2cf758ccef57a9a49644cbfb2d8b132c8793170a121a81fbef0a304d112a +size 144324 diff --git a/assets/cli-output-agreement.svg b/assets/cli-output-agreement.svg new file mode 100644 index 0000000000000000000000000000000000000000..e5d583a6dffb9baa55b93fc4cd19f73aea0a29a1 --- /dev/null +++ b/assets/cli-output-agreement.svg @@ -0,0 +1,303 @@ + + + + + + + + 2026-10-20T23:05:48.287914 + image/svg+xml + + + Matplotlib v3.11.2, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + FP32 + + + + + + FP16 + + + + + + Q8 + + + + + + + + Squirrel · green + + + + + + Redhead / gauze · blue + + + + + + Hair / gauze · green + + + + + + Fur / glass · blue + + + + + + Moving video · 32 frames + + + + + 1 + + + 0 + + + 0 + + + 1 + + + 0 + + + 0 + + + 1 + + + 0 + + + 0 + + + 1 + + + 0 + + + 0 + + + 1 + + + 0 + + + 0 + + + Alpha + + + + + + + + + + + + + + FP32 + + + + + + FP16 + + + + + + Q8 + + + + + + + + + + + + + + + + + + + + + + 2 + + + 0 + + + 0 + + + 2 + + + 0 + + + 0 + + + 2 + + + 0 + + + 0 + + + 1 + + + 0 + + + 0 + + + 2 + + + 0 + + + 0 + + + Checker composite + + + + CORRIDORKEY v2 / MLX + + + Output agreement after enabling kernel optimizations + + + Maximum absolute 16-bit code difference · each precision compared with its own reference path + + + All pixels and all frames compared for alpha and checker outputs; values are differences in the saved PNGs, not perceptual scores. + This does not compare FP16/Q8 against FP32. Visible foreground and RGBA checks, limits, and per-file hashes are in the raw receipts. + + + + + + + + + + Exact pixels + + + + + + Nonzero numerical difference + + + + + + + + + + + + diff --git a/assets/cli-stage-times.png b/assets/cli-stage-times.png new file mode 100644 index 0000000000000000000000000000000000000000..961107c44d523a81a0987814ad08afcc8415c718 --- /dev/null +++ b/assets/cli-stage-times.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:aad48eedd6516f2db534cf01327263bf5b3776668625e76cd47ff6cda399b8db +size 116416 diff --git a/assets/cli-stage-times.svg b/assets/cli-stage-times.svg new file mode 100644 index 0000000000000000000000000000000000000000..9d7b1c114f9a0b5edca22609d44696e70fea9d45 --- /dev/null +++ b/assets/cli-stage-times.svg @@ -0,0 +1,597 @@ + + + + + + + + 2026-10-20T23:05:48.117675 + image/svg+xml + + + Matplotlib v3.11.2, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + 0 + + + + + + + + + 10 + + + + + + + + + 20 + + + + + + + + + 30 + + + + + + + + + 40 + + + + + + + + + 50 + + + + seconds / 32-frame CLI workflow + + + + + + + FP32 · reference + + + + + + FP32 · enabled + + + + + + FP16 · reference + + + + + + FP16 · enabled + + + + + + Q8 · reference + + + + + + Q8 · enabled + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + CORRIDORKEY v2 / MLX + + + CLI time by processing stage + + + 32 moving frames · reference and enabled kernels · same input and precision in each pair + + + Breakdown uses the median-duration measured run in each condition. Calls include their CPU/MLX tensor bridges; rendering is evaluated. + Other includes decoding, preparation, feature staging, temporal blending, scheduling, and scratch cleanup. All output writes are included. + + + + + + + + + + RVM + + + + + + C-RADIO + MoGe + + + + + + Matting stage 1 + + + + + + Matting stage 2 + + + + + + Rendering + + + + + + PNG writes + + + + + + Other I/O / CPU + + + + + + + + + diff --git a/assets/cli-workflow.png b/assets/cli-workflow.png new file mode 100644 index 0000000000000000000000000000000000000000..78c183675cf965f88c330a88011d49e331de5368 --- /dev/null +++ b/assets/cli-workflow.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:614f86f4367ae5343169a7bbd9755cdffc9820682a122511adfcb56c9d8cde3c +size 128803 diff --git a/assets/cli-workflow.svg b/assets/cli-workflow.svg new file mode 100644 index 0000000000000000000000000000000000000000..69229c93dcd246457a26104a75d0fc9b1d2895d1 --- /dev/null +++ b/assets/cli-workflow.svg @@ -0,0 +1,602 @@ + + + + + + + + 2026-10-20T23:05:47.943086 + image/svg+xml + + + Matplotlib v3.11.2, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + 0.00 + + + + + + + + + 0.25 + + + + + + + + + 0.50 + + + + + + + + + 0.75 + + + + + + + + + 1.00 + + + + + + + + + 1.25 + + + + + + + + + 1.50 + + + + + + + + + 1.75 + + + + seconds / frame + + + + + + + Squirrel · green + + + + + + Redhead / gauze · blue + + + + + + Hair / gauze · green + + + + + + Fur / glass · blue + + + + + + Moving video · 32 frames + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Completed CLI workflow + + + + + + + + + + + + + + 0 + + + + + + + + + 1 + + + + + + + + + 2 + + + + + + + + + 3 + + + + + + + + + 4 + + + + + + + + + 5 + + + + + + + + + 6 + + + + + + + + + 7 + + + + GiB · warmed peak physical footprint + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Physical memory + + + + CORRIDORKEY v2 / MLX + + + CLI workflow time and physical memory + + + M4 Pro, 48 GiB · enabled kernels · one complete warm-up and three measured runs per condition + + + Actual CLI: decoding, neural inference, rendering, four 16-bit PNG writes, and scratch cleanup. Model loading and warm-up excluded. + Stills: 1536 × 1024. Video: native 1280 × 720, 32 moving frames; seconds divided by 32. Memory: sampled process physical footprint. + + + + + + + + + + FP32 + + + + + + FP16 + + + + + + Q8 + + + + + + + + + + + + diff --git a/assets/examples/manifest.json b/assets/examples/manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..fe74dff4d8132c82946a847dd186c39386d4f8f9 --- /dev/null +++ b/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" + } +] diff --git a/assets/examples/redhead-cutout.png b/assets/examples/redhead-cutout.png new file mode 100644 index 0000000000000000000000000000000000000000..ee544227de248164b73b0efdc5d9e45d41a23ae0 --- /dev/null +++ b/assets/examples/redhead-cutout.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0386c30fba4a54596e3ec1ccc87ecd8318afd160b6369191187875924875a6dc +size 9198287 diff --git a/assets/examples/redhead-input.png b/assets/examples/redhead-input.png new file mode 100644 index 0000000000000000000000000000000000000000..d068f6672b6f9e1a28de6c5a35fb147ea304d7d8 --- /dev/null +++ b/assets/examples/redhead-input.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ef1e5b6a1daf2e29db36f0e03e5ed9b79966f4eedbafff6af6cf9e2a4f6e078e +size 2380142 diff --git a/assets/examples/squirrel-cutout.png b/assets/examples/squirrel-cutout.png new file mode 100644 index 0000000000000000000000000000000000000000..4c98058c0d2f706b52dae445803535f446ed3a7b --- /dev/null +++ b/assets/examples/squirrel-cutout.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3d9e3dbe9c0425bf16cc140f7000009841715e654956dadcc6a6ee311dd19b71 +size 5075547 diff --git a/assets/examples/squirrel-input.png b/assets/examples/squirrel-input.png new file mode 100644 index 0000000000000000000000000000000000000000..6ef353eebdd1023e2a614dcfd1f388bf4e257235 --- /dev/null +++ b/assets/examples/squirrel-input.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0a721e992526212122e118c794d9f6e2476165b1164571a69a08a55c4cb41197 +size 1731395 diff --git a/assets/kernel-ablation.png b/assets/kernel-ablation.png new file mode 100644 index 0000000000000000000000000000000000000000..9d647de38d6d8e3e0cbed0ce6f80cc4a55c83133 --- /dev/null +++ b/assets/kernel-ablation.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c625ddd553c9028d3b674af11431fcc0d66d648f2c6da9eaed16ed2e67b126f5 +size 129766 diff --git a/assets/kernel-ablation.svg b/assets/kernel-ablation.svg new file mode 100644 index 0000000000000000000000000000000000000000..51225d11cbb0eb6e1b1c4476ab107b3ba03754bf --- /dev/null +++ b/assets/kernel-ablation.svg @@ -0,0 +1,515 @@ + + + + + + + + 2026-10-20T22:09:57.533172 + image/svg+xml + + + Matplotlib v3.11.2, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + 0 + + + + + + + + + 100 + + + + + + + + + 200 + + + + + + + + + 300 + + + + + + + + + 400 + + + + + + + + + 500 + + + + + + + + + 600 + + + + + + + + + 700 + + + + milliseconds / stage-two call + + + + + + + Baseline + + + + + + Projection pairing + + + + + + Paired convolution + + + + + + Both changes + + + + + + + + + + + + + + + + + 642.2 ms + + + 651.1 ms + + + 551.7 ms + + + 560.9 ms + + + FP16 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 0 + + + + + + + + + 100 + + + + + + + + + 200 + + + + + + + + + 300 + + + + + + + + + 400 + + + + + + + + + 500 + + + + + + + + + 600 + + + + + + + + + 700 + + + + milliseconds / stage-two call + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 663.6 ms + + + 672.3 ms + + + 576.8 ms + + + 582.3 ms + + + Q8 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + CORRIDORKEY v2 / MLX + + + Refinement-stage kernel ablation + + + 768 × 1280 · batch one · compiled stage 2 · two warm-ups, five measured runs with rotated order + + + Synthetic tensor inputs, fixed random seed; dots show all measured runs. Every candidate matches its precision baseline exactly. + Convolution alone is enabled for FP16/Q8. Projection pairing alone was slower, and adding it to convolution did not improve time. + + + + + + + + + + Control / other candidate + + + + + + Enabled candidate + + + + + + + + + + + + diff --git a/assets/kernel-latency.png b/assets/kernel-latency.png new file mode 100644 index 0000000000000000000000000000000000000000..42120e619f09b7c32bc5c1b9c516130ba26813a6 --- /dev/null +++ b/assets/kernel-latency.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:42a36a3fbe952bc8e082d1a342d8374e39a3ea78e6fdd95297e4ad6302624304 +size 158733 diff --git a/assets/kernel-latency.svg b/assets/kernel-latency.svg new file mode 100644 index 0000000000000000000000000000000000000000..b8f8c649dcae894fcece4e939abef64912331439 --- /dev/null +++ b/assets/kernel-latency.svg @@ -0,0 +1,744 @@ + + + + + + + + 2026-10-20T22:09:57.425858 + image/svg+xml + + + Matplotlib v3.11.2, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + 0 + + + + + + + + + 100 + + + + + + + + + 200 + + + + + + + + + 300 + + + + + + + + + 400 + + + + + + + + + 500 + + + + milliseconds / operator + + + + + + + Batch 1 + + + + + + Batch 4 + + + + + + + + + + + + + + + + + 110.67 + + + 8.21 + + + 404.73 + + + 42.01 + + + Reconstruction + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 0 + + + + + + + + + 2 + + + + + + + + + 4 + + + + + + + + + 6 + + + + + + + + + 8 + + + + + + + + + 10 + + + + milliseconds / operator + + + + + + + Channels 1280 + + + + + + Channels 3840 + + + + + + Small asymmetric + + + + + + + + + + + + + + + + + + + + + + + 1.45 + + + 0.31 + + + 8.44 + + + 0.81 + + + 0.59 + + + 0.55 + + + Reflection padding + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 0 + + + + + + + + + 10 + + + + + + + + + 20 + + + + + + + + + 30 + + + + + + + + + 40 + + + + + + + + + 50 + + + + milliseconds / operator + + + + + + + Small control + + + + + + Batch 1 · 1280 channels + + + + + + Batch 4 · 1280 channels + + + + + + + + + + + + + + + + + + + + + + + 0.18 + + + 0.15 + + + 10.55 + + + 2.86 + + + 40.35 + + + 10.27 + + + Paired 7×7 convolution + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + CORRIDORKEY v2 / MLX + + + Isolated FP32 kernel latency + + + Apple M4 Pro, 48 GiB · compiled operators · bars: median · dots: individual samples + + + Five alternating samples for reconstruction/padding; seven samples for convolution. Each panel has its own millisecond scale. + Maximum absolute output difference: reconstruction 9.54e−6; padding and convolution 0. Kernel ratios are not whole-workflow speedups. + + + + + + + + + + Reference operator + + + + + + Optimized kernel + + + + + + + + + + + + + + + diff --git a/assets/mlx-mps-performance.png b/assets/mlx-mps-performance.png new file mode 100644 index 0000000000000000000000000000000000000000..d8aece6e9ab6c3757a4f55051c91cf6e7adae9da --- /dev/null +++ b/assets/mlx-mps-performance.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:930c24da8934e4c4ca2e01f50572359a221e06ce00a7c5a0976b26f242082835 +size 114450 diff --git a/assets/mlx-mps-performance.svg b/assets/mlx-mps-performance.svg new file mode 100644 index 0000000000000000000000000000000000000000..fa66583084d0ac1f89192b96ece936a74e4836ef --- /dev/null +++ b/assets/mlx-mps-performance.svg @@ -0,0 +1,398 @@ + + + + + + + + 2026-10-20T22:09:57.140089 + image/svg+xml + + + Matplotlib v3.11.2, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + 0 + + + + + + + + + 1 + + + + + + + + + 2 + + + + + + + + + 3 + + + + + + + + + 4 + + + + seconds / frame + + + + + + + Hair / gauze + + + + + + Fur / blur + + + + + + + + + + + + + + + + + 3.60 + + + 2.39 + + + 3.50 + + + 2.30 + + + Still image + + + + + + + + + + + + + + 0 + + + + + + + + + 10 + + + + + + + + + 20 + + + + seconds / clip + + + + + + + MPS + + + + + + MLX + + + + + + + + + + + 21.92 + + + 15.53 + + + Six-frame clip + + + + + + + + + + + + + + 0 + + + + + + + + + 10 + + + + + + + + + 20 + + + + GiB · warmed peak + + + + + + + MPS + + + + + + MLX + + + + + + + + + + + 19.25 + + + 7.19 + + + Physical footprint + + + + CORRIDORKEY v2 / MLX + + + Matched backend comparison + + + Apple M4 Pro · 48 GiB · FP32 · warmed workflow · lower is better + + + Historical engine benchmark; includes four completed 16-bit PNG exports. New CLI timings are separate. + Stills: five samples/backend. Six-frame repeated-still clip: three samples/backend. Memory: separate physical-footprint probe. + + + + + + + + + + MPS + + + + + + MLX + + + + + + + + + + + + + + + diff --git a/assets/mlx-mps-quality.png b/assets/mlx-mps-quality.png new file mode 100644 index 0000000000000000000000000000000000000000..a089d8127c53e64d73d471cb3efb5290bcaabdec --- /dev/null +++ b/assets/mlx-mps-quality.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:68f7ea94d42339e1cb32a1309fce99afa2704dabdc342d3c6f1cf845c5701b1b +size 1526864 diff --git a/assets/optimization-gains.png b/assets/optimization-gains.png new file mode 100644 index 0000000000000000000000000000000000000000..79f8a36f7fbd89421887ab70bcbec634fd218850 --- /dev/null +++ b/assets/optimization-gains.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:36f46a0ba7a9ebca37cbafc67c479b9adf82d39c1ad3a64c99ab2e1a641c1796 +size 124387 diff --git a/assets/optimization-gains.svg b/assets/optimization-gains.svg new file mode 100644 index 0000000000000000000000000000000000000000..79f3427f918aa00e18984ebd215b701cb780cc08 --- /dev/null +++ b/assets/optimization-gains.svg @@ -0,0 +1,261 @@ + + + + + + + + 2026-10-20T22:09:57.215074 + image/svg+xml + + + Matplotlib v3.11.2, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + 0 + + + + + + + + + 10 + + + + + + + + + 20 + + + + + + + + + 30 + + + + + + + + + 40 + + + + seconds / 32-frame workflow + + + + + + + FP32 + + + + + + FP16 + + + + + + Q8 + + + + + + + + + + + + + + + + + + + + + + + 39.50 s + + + 33.15 s + + + 16.1% + + + less time + + + 40.98 s + + + 33.92 s + + + 17.2% + + + less time + + + 42.07 s + + + 34.31 s + + + 18.4% + + + less time + + + + CORRIDORKEY v2 / MLX + + + Workflow time before and after optimization + + + 32 moving frames · M4 Pro, 48 GiB · median of three warmed runs + + + Decode through uint16 rendering; PNG writing excluded. Separate before/after studies, not a cross-precision speed ranking. + Exact raw and rendered agreement with each preceding precision path across 36 frames per precision. 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