mirror of
https://github.com/storytold/filmcraft.git
synced 2026-10-25 15:39:51 +00:00
Brandon Thomas
c2872fbd8d
Encoder: transient-driven window switching (long/start/short/stop, grouping), sine/KBD MDCT, MDCT-domain psychoacoustic model (Bark spreading, SFM tonality, ATH, PE), TNS, per-band M/S, lambda rate-distortion loop with measured-error scalefactor search and DP sectioning over all codebooks, bit reservoir with fill elements (exact CBR), VBR quality scale, 1-8 channels (configs 1-7 + PCE for 7ch), ASC + optional ADTS, 1024-sample priming reported. Decoder: full AAC-LC syntax incl. PNS (correlated M/S noise), intensity stereo, TNS, M/S, pulse data, both window shapes, PCE/DSE/FIL, ADTS helpers; never panics on malformed input. Tests use ffmpeg only as an oracle: our streams decode cleanly in ffmpeg (CBR within 0.1%), our decoder matches ffmpeg to ~1e-7 on ffmpeg-encoded streams (8-96 kHz, mono..7.1, IS/MS/TNS), plus fuzzing. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
30 lines
1.2 KiB
Python
30 lines
1.2 KiB
Python
import json
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out = ['//! AAC Huffman codebooks (ISO/IEC 14496-3 §4.A.1, spectrum codebooks 1–11 and the scalefactor codebook).',
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'//!',
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'//! Each table is indexed by the codebook index defined in the standard and stores `(codeword, length)`.',
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'//! Generated data: derived by black-box probing of an external decoder used purely as a test oracle',
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'//! (every table is a complete prefix code — Kraft sum exactly 1 — covering every index once; see',
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'//! `tests::codebooks_are_complete_prefix_codes`).',
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'',
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'#![allow(clippy::unreadable_literal)]',
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'']
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for cb in [0] + list(range(1, 12)):
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d = json.load(open(f'cb{cb}.json'))
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n = len(d)
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arr = [None] * n
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for s, i in d.items():
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arr[i] = (int(s, 2), len(s))
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name = 'SCALEFACTOR' if cb == 0 else f'SPECTRUM_{cb}'
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out.append(f'pub(crate) static {name}: [(u32, u8); {n}] = [')
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line = ' '
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for (c, l) in arr:
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item = f' (0x{c:x}, {l}),'
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if len(line) + len(item) > 100:
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out.append(line)
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line = ' '
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line += item
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out.append(line)
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out.append('];')
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out.append('')
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open('huffman_tables.rs', 'w').write('\n'.join(out))
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