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ATTRIBUTION.md

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+# Attribution
+
+## Original model
+
+**ClearRealityV1** was created and released by **Kim2091**.
+
+Upstream repository:
+
+https://huggingface.co/Kim2091/ClearRealityV1
+
+Architecture: SPAN  
+Scale: 4×
+
+The source checkpoint used for this conversion is:
+
+`4x-ClearRealityV1.safetensors`
+
+Upstream SHA256:
+
+`83a9c8e279e3d07548e2b0d736dc2c73c1736a07072a748ed4fafbba99b44693`
+
+## Core AI conversion
+
+This repository contains an Apple Core AI conversion by **enginil**.
+
+Changes relative to the upstream artifact:
+
+- converted the original model weights to Apple Core AI `.aimodel` format;
+- froze Spandrel's own eval-time SPAN reparameterization before `torch.export`;
+- added Core AI inference and parity-validation scripts;
+- no additional model training was performed.
+
+The original model remains the work of Kim2091.
+
+## License
+
+At the time this release package was prepared, the current upstream Hugging Face
+repository declares the model under the Apache License 2.0.
+
+This repository includes a copy of the Apache License 2.0 in `LICENSE`.

LICENSE

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README.md

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 ---
 license: apache-2.0
+pipeline_tag: image-to-image
+base_model: Kim2091/ClearRealityV1
+tags:
+  - core-ai
+  - apple-core-ai
+  - super-resolution
+  - image-upscaling
+  - span
+  - apple-silicon
+  - pytorch
 ---
+
+# ClearRealityV1 4× — Apple Core AI Port
+
+Apple Core AI (`.aimodel`) port of **Kim2091's ClearRealityV1** 4× super-resolution model.
+
+> **Original model:** [Kim2091/ClearRealityV1](https://huggingface.co/Kim2091/ClearRealityV1)  
+> **Original author:** Kim2091  
+> **Architecture:** SPAN  
+> **Scale:** 4×  
+> **Port / conversion:** enginil  
+> **Format:** Apple Core AI `.aimodel`  
+> **License:** Apache-2.0, matching the current upstream model repository
+
+This repository does **not** claim authorship of the original ClearRealityV1 model.  
+The model was trained and released by **Kim2091**. This repository contains a
+conversion of the original weights to Apple's **Core AI** format plus conversion,
+inference, and validation scripts.
+
+## Model file
+
+The converted model is:
+
+```text
+ClearRealityV1_4x_CoreAI.aimodel
+```
+
+Source checkpoint used for the conversion:
+
+```text
+Kim2091/ClearRealityV1
+4x-ClearRealityV1.safetensors
+SHA256: 83a9c8e279e3d07548e2b0d736dc2c73c1736a07072a748ed4fafbba99b44693
+```
+
+## Requirements
+
+Running Core AI models requires current Apple Core AI platform support:
+
+- Apple silicon
+- macOS 27 or later
+- Python 3.11+ for the included Python inference script
+- `coreai-core`
+
+Install the small runtime environment:
+
+```bash
+uv venv -p 3.11 .venv
+source .venv/bin/activate
+uv pip install -r requirements-inference.txt
+```
+
+You can also use ordinary `pip`:
+
+```bash
+python3.11 -m venv .venv
+source .venv/bin/activate
+pip install -r requirements-inference.txt
+```
+
+## Inference
+
+The included `03_inference_coreai.py` performs full-image 4× upscaling with a
+fixed Core AI input tile of 512×512, 64-pixel overlap, and midpoint-discard
+stitching.
+
+### PNG output
+
+```bash
+python3.11 03_inference_coreai.py \
+  --model "ClearRealityV1_4x_CoreAI.aimodel" \
+  --input "/path/to/input.jpg" \
+  --output "/path/to/output.png"
+```
+
+PNG output is lossless.
+
+### JPEG output
+
+```bash
+python3.11 03_inference_coreai.py \
+  --model "ClearRealityV1_4x_CoreAI.aimodel" \
+  --input "/path/to/input.jpg" \
+  --output "/path/to/output.jpg"
+```
+
+Default inference parameters:
+
+```text
+model tile:     512  (fixed by the .aimodel input signature)
+overlap:         64  (adjustable)
+output-scale:     4  (default; optional final 2× mode available)
+```
+
+The model itself is always the original native 4× ClearRealityV1 model with a
+static `1×3×512×512` RGB input and `1×3×2048×2048` output. Therefore the tile
+size is **not user-configurable** for this exported `.aimodel`; only the overlap
+is adjustable. The inference script tiles larger images automatically.
+
+### Optional 2× final output
+
+For cases where 4× is unnecessary, the same native 4× model can produce a
+smaller final 2× image:
+
+```bash
+python3.11 03_inference_coreai.py   --model "ClearRealityV1_4x_CoreAI.aimodel"   --input "/path/to/input.jpg"   --output "/path/to/output_2x.png"   --output-scale 2
+```
+
+This is **not a separately trained native 2× model**. Core AI still runs the
+original 4× network, stitches the full 4× float output, and then performs one
+high-quality Lanczos downsample to the final 2× resolution. The default remains
+the original native 4× output.
+
+## Conversion method
+
+The original SPAN implementation in Spandrel performs eval-time
+reparameterization inside its Conv3XC-style modules. Exporting the raw Spandrel
+object directly with `torch.export` therefore mutates module state during graph
+capture.
+
+The conversion used here does **not** reimplement SPAN or manually derive fused
+weights. Instead it:
+
+1. loads the original checkpoint through Spandrel;
+2. lets Spandrel's own `update_params()` implementation materialize its exact
+   eval-time fused convolutions;
+3. freezes those exact `eval_conv` modules into a static inference graph;
+4. verifies the frozen graph against fresh real Spandrel output;
+5. exports the verified static graph with `torch.export`;
+6. applies the Core AI decomposition table;
+7. converts with `coreai_torch.TorchConverter`;
+8. optimizes and saves the resulting `.aimodel`;
+9. validates the saved Core AI model against the original Spandrel runtime.
+
+The conversion path is therefore:
+
+```text
+ClearRealityV1.safetensors
+        ↓
+Spandrel SPAN
+        ↓
+Spandrel's own eval-time reparameterization
+        ↓
+static verified PyTorch graph
+        ↓
+torch.export
+        ↓
+Core AI decompositions
+        ↓
+coreai-torch
+        ↓
+optimize()
+        ↓
+ClearRealityV1_4x_CoreAI.aimodel
+```
+
+## Validation
+
+The conversion was validated at multiple levels.
+
+### 1. Real Spandrel vs frozen export-safe graph
+
+```text
+max_abs_diff : 0
+mean_abs_diff: 0
+RMSE         : 0
+cosine       : 1
+```
+
+### 2. Real Spandrel vs `torch.export.ExportedProgram`
+
+```text
+max_abs_diff : 0
+mean_abs_diff: 0
+RMSE         : 0
+cosine       : 1
+```
+
+### 3. FP32 Spandrel vs saved Core AI model
+
+```text
+max_abs_diff : 0.0023136139
+mean_abs_diff: 0.000000906632
+RMSE         : 0.000005862728
+cosine       : 0.999999999935
+```
+
+### 4. Full-image end-to-end validation
+
+Input:
+
+```text
+854 × 1280
+```
+
+Output:
+
+```text
+3416 × 5120
+```
+
+Both paths used the same 512/64 tile geometry and midpoint-discard stitching:
+
+```text
+Spandrel MPS FP16 ↔ Core AI
+
+max_abs_diff : 0.0095030665
+mean_abs_diff: 0.0002444417
+RMSE         : 0.0003341608
+cosine       : 0.99999985751
+
+mean_abs ×255: 0.06233263
+RMSE ×255    : 0.08521101
+max_abs ×255 : 2.42328197
+```
+
+The numerical metrics are calculated on raw float outputs before JPEG encoding.
+
+To reproduce the full-image comparison:
+
+```bash
+python3.11 04_compare_full_image.py \
+  --weights "/path/to/4x-ClearRealityV1.safetensors" \
+  --aimodel "ClearRealityV1_4x_CoreAI.aimodel" \
+  --image "/path/to/input.jpg" \
+  --output-dir "./validation_output" \
+  --tile 512 \
+  --overlap 64 \
+  --visual-format jpg
+```
+
+This writes:
+
+```text
+spandrel_mps_fp16.jpg
+coreai.jpg
+difference_x20.png
+```
+
+## Files
+
+```text
+ClearRealityV1_4x_CoreAI.aimodel   converted model
+03_inference_coreai.py             standalone Core AI inference
+04_compare_full_image.py           full-image parity validation
+02_validate_real_crop.py           real-image crop validation
+01_convert_coreai.py               Core AI conversion
+00_probe_freeze_and_export.py      pre-conversion parity gate
+spandrel_source.py                 exact Spandrel loading/freezing helpers
+tiling.py                          shared tiling/stitching implementation
+requirements-inference.txt         minimal runtime dependencies
+requirements-conversion.txt        conversion/validation dependencies
+ATTRIBUTION.md                     upstream attribution and conversion notice
+LICENSE                            Apache License 2.0
+```
+
+## Original model notes
+
+Kim2091 describes ClearRealityV1 as a 4× SPAN model intended for realistic
+imagery, including faces, hair, foliage, trees, and buildings, with a softer,
+more natural target and reduced artifacts.
+
+The upstream author also notes that depth-of-field / bokeh regions can still
+produce artifacts. That limitation is inherited by this port; conversion to
+Core AI does not change the learned behavior of the original model.
+
+## License and attribution
+
+The current upstream Hugging Face repository declares **Apache-2.0**.
+
+Original model:
+
+- **ClearRealityV1**
+- **Author:** Kim2091
+- **Upstream:** https://huggingface.co/Kim2091/ClearRealityV1
+
+Core AI conversion:
+
+- **Port:** enginil
+- No additional training was performed.
+- The converted artifact remains derived from the original ClearRealityV1 model.
+
+See `ATTRIBUTION.md` and `LICENSE`.
+
+
+## Seam-resistant tiled inference
+
+The release runner now uses **balanced tile placement** plus **weighted overlap
+blending**. No `.aimodel` reconversion is required.
+
+```text
+model tile:   512×512 (fixed by this converted model)
+min overlap:  64 px (configurable)
+placement:    balanced
+blend:        cosine (configurable)
+```
+
+For a 1024-pixel axis, the default planner uses starts `[0, 256, 512]`,
+so the two actual overlaps are both 256 pixels. The old asymmetric
+`[0, 448, 512]` placement is no longer used.
+
+The recommended default is `--blend cosine`. `linear` and `uniform` are
+available for comparison.