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swordpdfandClaude Opus 5.5
92449d681e
swordpdf relicenses src/, tests/, tools/, examples/ and docs/ from GPL-2.0-only to GPL-3.0-or-later, as PCSX2 and PS5SX2 are: every SPDX line, COPYING (the GPL 3 text, which GitHub reads) in place of LICENSES/GPL-2.0-only.txt, LICENSE.md and the README. The shaders stay MIT, stb public domain or MIT. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01DaNprJCmpBhrkpzRHVPLXM
82 lines
4.0 KiB
Python
Executable File
82 lines
4.0 KiB
Python
Executable File
#!/usr/bin/env python3
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# truth.py [--tests N] FG_TEST[,FG_TEST...] FRAME... : the frame generation measured on real frames of a game.
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#
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# FRAME...: consecutive frames of a game as PNG files, in order (a frame dump: the game's own frames, not the generated ones). The frame
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# generated between frame i and frame i+2 is compared with the real frame i+1 that was left out (the test has twice the motion of a
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# real use, which makes it harder, not easier). Each test also feeds the frames before, every other one, so that the history the
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# interpolation keeps (still pixels, the last frame's motion) is there.
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#
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# The game's motion is not even (a camera speeds up and slows down), so the real frame i+1 is not exactly where an interpolation puts
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# things: each 32x32 block of the result is compared with the real frame shifted by the best whole-pixel offset within 6 pixels. That
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# measures artifacts (specks, ghosts, smears, tears), not timing.
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#
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# Printed per fg-test build: the mean error (0-255, the mean of the 3 channels), the mean where frame i and i+2 differ (moving parts),
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# the pixels off by more than 40 ("bad"), the bad ones with no bad neighbours ("specks"), and the PSNR of the aligned error.
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#
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# Needs python3 with numpy and Pillow. FG_TEST: tools/build-fg-test.sh's result; VK_ICD_FILENAMES as for fg-test.
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#
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# SPDX-License-Identifier: GPL-3.0-or-later
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import os, subprocess, sys, tempfile
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import numpy as np
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from PIL import Image, ImageFilter
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def load(p):
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return np.asarray(Image.open(p).convert('RGB'), dtype=np.float32)
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def aligned_error(out, truth, B=32, R=6):
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h, w, _ = out.shape
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hb, wb = h // B, w // B
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o = out[:hb * B, :wb * B]
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best = np.full((hb, wb), 1e9, dtype=np.float32)
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emap = np.zeros((hb, B, wb, B), dtype=np.float32)
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tp = np.pad(truth, ((R, R), (R, R), (0, 0)), mode='edge')
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for dy in range(-R, R + 1):
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for dx in range(-R, R + 1):
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t = tp[R + dy:R + dy + hb * B, R + dx:R + dx + wb * B]
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e4 = (np.abs(o - t).sum(axis=2) * (1.0 / 3.0)).reshape(hb, B, wb, B)
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bm = e4.mean(axis=(1, 3))
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imp = bm < best
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if imp.any():
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best = np.where(imp, bm, best)
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emap = np.where(imp[:, None, :, None], e4, emap)
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return emap.reshape(hb * B, wb * B)
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def metrics(out, truth, a, b):
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e = aligned_error(out, truth)
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moving = (np.abs(a - b).mean(axis=2) > 12)[:e.shape[0], :e.shape[1]]
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big = e > 40
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med = np.asarray(Image.fromarray(np.clip(e, 0, 255).astype(np.uint8)).filter(ImageFilter.MedianFilter(5)), dtype=np.float32)
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speck = big & (med < 15)
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psnr = 10 * np.log10(255 ** 2 / np.mean(e ** 2 + 1e-6))
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return np.array([e.mean(), e[moving].mean() if moving.any() else 0.0, big.sum(), speck.sum(), psnr])
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def main():
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args = sys.argv[1:]
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tests = 4
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if len(args) >= 2 and args[0] == '--tests':
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tests = int(args[1])
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args = args[2:]
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if len(args) < 4:
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print(__doc__ if __doc__ else 'usage: truth.py [--tests N] FG_TEST[,FG_TEST...] FRAME FRAME FRAME ...')
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sys.exit(2)
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binaries = args[0].split(',')
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frames = args[1:]
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# the last `tests` frames i that have a frame i-1 to compare with and two frames of history (i-2, i-4) of their parity
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picks = [i for i in range(4, len(frames))][-tests:]
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tmp = tempfile.mkdtemp()
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for fg in binaries:
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total = np.zeros(5)
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for i in picks:
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seq = [frames[j] for j in range(i % 2, i + 1, 2)]
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out = os.path.join(tmp, 'out.png')
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p = subprocess.run([fg, '--seq', out] + seq, capture_output=True, text=True)
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if 'wrote' not in p.stdout:
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print(p.stdout[-400:], p.stderr[-400:])
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sys.exit(1)
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total += metrics(load(out), load(frames[i - 1]), load(frames[i - 2]), load(frames[i]))
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n = len(picks)
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print('%-40s error %.3f moving %.2f bad %7d specks %6d PSNR %.2f' % (fg[-40:], total[0] / n, total[1] / n, total[2], total[3], total[4] / n), flush=True)
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if __name__ == '__main__':
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main()
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