71 lines
3.1 KiB
Python
71 lines
3.1 KiB
Python
"""Package the existing SDR PNG and matching SVG as a backwards-compatible JPEG.
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Run: uv run python avatar_ultrahdr.py
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"""
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import argparse
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import io
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from pathlib import Path
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import numpy as np
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from PIL import Image
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from pyultrahdr import build_ultra_hdr
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from avatar_color import BT2020_Y, SRGB_Y, validate_peak
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from avatar_hdr import render_linear_hdr
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def export_ultrahdr(png_path, svg_path, output, peak_nits=400):
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validate_peak(peak_nits)
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with Image.open(png_path) as image:
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sdr = np.asarray(image.convert('RGB'))
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hdr = render_linear_hdr(Path(svg_path).read_text(encoding='utf-8'), peak_nits)
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if hdr.shape != sdr.shape:
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raise ValueError('The SDR PNG and SVG must have matching dimensions and content')
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encoded = sdr.astype(np.float64) / 255
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linear = np.where(encoded <= .04045, encoded / 12.92, ((encoded + .055) / 1.055) ** 2.4)
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sdr_white = 203.0
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sdr_y = linear @ np.asarray(SRGB_Y) * sdr_white
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hdr_y = hdr @ np.asarray(BT2020_Y)
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# A single-channel map scales RGB together, preserving the base chromaticity.
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# Keep SDR shadows rather than forcing the PQ version's darker black level.
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gain = np.log2(np.maximum(hdr_y / np.maximum(sdr_y, 1e-8), 1))
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gain_max = max(float(gain.max()), 1e-6)
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# The library's capacity argument is a reference-white brightness, not our
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# colored pixels' luminance. Full gain must wait for the full gain headroom.
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result = build_ultra_hdr(sdr, gain, 0.0, gain_max,
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sdr_white * 2 ** gain_max, sdr_white,
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base_quality=100, gainmap_quality=100)
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Path(output).write_bytes(result)
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return verify_ultrahdr(result, sdr)
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def verify_ultrahdr(result, sdr):
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with Image.open(io.BytesIO(result)) as image:
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decoded = np.asarray(image.convert('RGB'))
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directory = image._getmp()
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frames = directory[45057]
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entry = directory[45058][1]
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start = image.info['mpoffset'] + entry['DataOffset']
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with Image.open(io.BytesIO(result[start:start + entry['Size']])) as gain_image:
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gain_image.load()
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if gain_image.size != image.size or b'GainMapMax' not in gain_image.info['xmp']:
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raise ValueError('Missing full-resolution gain map or HDR metadata')
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error = np.abs(decoded.astype(float) - sdr)
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if frames != 2:
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raise ValueError('Ultra HDR output must contain a base and gain-map image')
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return {'size': list(sdr.shape[:2]), 'jpeg_frames': frames,
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'sdr_mean_absolute_error': float(error.mean()),
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'sdr_max_error': float(error.max())}
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument('--png', type=Path, default=Path('avatar.png'))
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parser.add_argument('--svg', type=Path, default=Path('avatar.svg'))
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parser.add_argument('--output', type=Path, default=Path('avatar-ultrahdr.jpg'))
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parser.add_argument('--peak-nits', type=float, default=400)
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args = parser.parse_args()
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print(export_ultrahdr(args.png, args.svg, args.output, args.peak_nits))
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print(f'Saved {args.output.resolve()}')
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