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Prepare lean solver for hosted shipping

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This commit is contained in:
Meta Vens 2026-04-29 11:24:31 +01:00
commit 5f2a644906
35 changed files with 1839 additions and 1948 deletions
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77
scripts/generate_readme_previews.py
View file

@ -63,8 +63,8 @@ def _parse_args() -> argparse.Namespace:
)
parser.add_argument(
"--dense-phase-field-output",
default="tests/fixtures/real/dense-landscape-fixed-512.png",
help="Tracked fixed-lattice output used for the dense landscape row.",
default="",
help="Optional existing dense landscape output. If omitted, the dense row is regenerated with automatic lattice inference.",
)
parser.add_argument(
"--guard-cell-bbox",
@ -93,29 +93,30 @@ def _parse_args() -> argparse.Namespace:
type=int,
default=126,
help="Pinned target height for the canonical badge comparison.",
) parser.add_argument(
)
parser.add_argument(
"--dense-target-width",
type=int,
default=512,
help="Pinned target width for the dense landscape comparison.",
help="Fallback target width used only when --dense-phase-field-output is supplied.",
)
parser.add_argument(
"--dense-target-height",
type=int,
default=512,
help="Pinned target height for the dense landscape comparison.",
help="Fallback target height used only when --dense-phase-field-output is supplied.",
)
parser.add_argument(
"--dense-auto-inferred-width",
type=int,
default=418,
help="Current automatic lattice width guess for the dense landscape case.",
help="Deprecated display fallback for old fixed-output runs.",
)
parser.add_argument(
"--dense-auto-inferred-height",
type=int,
default=418,
help="Current automatic lattice height guess for the dense landscape case.",
help="Deprecated display fallback for old fixed-output runs.",
)
parser.add_argument("--steps", type=int, default=48, help="Optimizer step budget for both runs.")
parser.add_argument("--device", default="cpu", choices=("auto", "cpu", "cuda"), help="Torch device for generation.")
@ -369,7 +370,6 @@ def main() -> None:
source_input = Path(args.input)
dense_input = Path(args.dense_input)
dense_phase_field_output = Path(args.dense_phase_field_output)
out_sheet = Path(args.out_sheet)
out_guard_crop = Path(args.out_guard_crop)
out_sheet.parent.mkdir(parents=True, exist_ok=True)
@ -389,15 +389,43 @@ def main() -> None:
source_rgba = load_rgba(source_input)
lanczos = lanczos_resize_baseline(source_rgba, width=args.target_width, height=args.target_height)
dense_source_rgba = load_rgba(dense_input)
dense_phase_field_rgba = load_rgba(dense_phase_field_output)
if args.dense_phase_field_output:
dense_phase_field_output = Path(args.dense_phase_field_output)
dense_phase_field_rgba = load_rgba(dense_phase_field_output)
dense_target_width = int(dense_phase_field_rgba.shape[1])
dense_target_height = int(dense_phase_field_rgba.shape[0])
dense_phase_field_subtitle = f"tracked {dense_target_width}x{dense_target_height} output"
dense_title = (
f"Dense {dense_source_rgba.shape[1]}px pixel art -> tracked "
f"{dense_target_width}x{dense_target_height} output"
)
dense_output_summary = str(dense_phase_field_output)
else:
dense_phase_field_result = run_pipeline(
dense_input,
scratch_dir / "dense-landscape-phase-field-auto.png",
diagnostics_dir=scratch_dir / "dense-phase-field-auto-diag",
steps=args.steps,
device=args.device,
lattice_inference_mode="autocorr",
)
dense_phase_field_rgba = dense_phase_field_result.output_rgba
dense_target_width = int(dense_phase_field_result.inference.target_width)
dense_target_height = int(dense_phase_field_result.inference.target_height)
dense_phase_field_subtitle = f"{dense_target_width}x{dense_target_height} inferred lattice"
dense_title = (
f"Dense {dense_source_rgba.shape[1]}px pixel art -> "
f"{dense_target_width}x{dense_target_height} inferred lattice"
)
dense_output_summary = str(scratch_dir / "dense-landscape-phase-field-auto.png")
dense_lanczos = lanczos_resize_baseline(
dense_source_rgba,
width=args.dense_target_width,
height=args.dense_target_height,
width=dense_target_width,
height=dense_target_height,
)
save_rgba(scratch_dir / "badge-ai-lanczos.png", lanczos)
save_rgba(scratch_dir / "dense-landscape-lanczos-512.png", dense_lanczos)
save_rgba(scratch_dir / f"dense-landscape-lanczos-{dense_target_width}x{dense_target_height}.png", dense_lanczos)
panel_width = 320
panel_height = 360
@ -411,6 +439,13 @@ def main() -> None:
scale_x=0.5,
scale_y=0.5,
)
dense_focus_cell_bbox = (
int(round(args.dense_focus_cell_bbox[0] * dense_target_width / max(1, args.dense_target_width))),
int(round(args.dense_focus_cell_bbox[1] * dense_target_height / max(1, args.dense_target_height))),
int(round(args.dense_focus_cell_bbox[2] * dense_target_width / max(1, args.dense_target_width))),
int(round(args.dense_focus_cell_bbox[3] * dense_target_height / max(1, args.dense_target_height))),
)
rows = [
PreviewRow(
row_id="badge",
@ -427,20 +462,16 @@ def main() -> None:
),
PreviewRow(
row_id="dense-landscape",
title=(
"Dense 1254px pixel art -> auto inference "
f"{args.dense_auto_inferred_width}x{args.dense_auto_inferred_height}; "
f"fixed {args.dense_target_width}x{args.dense_target_height} shown"
),
title=dense_title,
source_rgba=dense_source_rgba,
source_subtitle=f"{dense_source_rgba.shape[1]}px source",
lanczos_rgba=dense_lanczos,
lanczos_subtitle=f"{args.dense_target_width}x{args.dense_target_height} baseline",
lanczos_subtitle=f"{dense_target_width}x{dense_target_height} baseline",
phase_field_rgba=dense_phase_field_rgba,
phase_field_subtitle=f"fixed {args.dense_target_width}x{args.dense_target_height} lattice",
target_width=args.dense_target_width,
target_height=args.dense_target_height,
focus_cell_bbox=tuple(args.dense_focus_cell_bbox),
phase_field_subtitle=dense_phase_field_subtitle,
target_width=dense_target_width,
target_height=dense_target_height,
focus_cell_bbox=dense_focus_cell_bbox,
),
]
built_rows: list[tuple[PreviewRow, list[RenderedPanel], tuple[int, int, int, int]]] = []
@ -501,7 +532,7 @@ def main() -> None:
],
"badge_input": str(source_input),
"dense_input": str(dense_input),
"dense_phase_field_output": str(dense_phase_field_output),
"dense_phase_field_output": dense_output_summary,
"guard_cell_bbox": list(args.guard_cell_bbox),
"guard_source_bbox": list(guard_bbox),
"out_sheet": str(out_sheet),

7
scripts/render_focus_crop.py
View file

@ -6,8 +6,7 @@ from pathlib import Path
import numpy as np
from PIL import Image, ImageDraw
from repixelizer.analysis import analyze_phase_field_source
from repixelizer.inference import infer_lattice
from repixelizer.inference import infer_autocorr_lattice
from repixelizer.io import load_rgba
from repixelizer.metrics import source_lattice_consistency_breakdown
from repixelizer.params import SolverHyperParams
@ -77,12 +76,10 @@ def _build_focus_states(
device: str,
) -> tuple[np.ndarray, np.ndarray, np.ndarray, tuple[float, float], dict[str, dict[str, float]]]:
source = load_rgba(input_path)
inference = infer_lattice(source, device=device)
analysis = analyze_phase_field_source(source, seed=7, device=device)
inference = infer_autocorr_lattice(source, device=device)
artifacts = optimize_phase_field(
source,
inference=inference,
analysis=analysis,
steps=steps,
seed=7,
device=device,