USER DECISION: drop the `sasi` profile. Not on bandwidth -- on capacity. A SASI volume is 40 MB, and the 22.8 min of unique scene footage on the source Blu-ray (streams 00000-00201, measured, not recalled) is 146 MiB at the LOWEST rate this codec makes -- more than the machine's whole 4-unit SASI space. `scsi` is the only profile now. FINDINGS 32. Then the user asked whether we were drawing the wrong conclusions about PIO vs DMA, and we were, more broadly than the question implied. Every CPU figure in FINDINGS 24-34 is scored against the full 833,333 cycles/frame with nothing subtracted for moving the bitstream off disk. Debiting the HD63450 cycle-steal at the long-standing 8 clk/word ESTIMATE, "1 frame of 120 misses" becomes 84 of 120, median 112.4%. PIO at the span rate is 99.8% of the machine. Spans buy cycles by spending bandwidth and the bandwidth returns as steal, so 31.6's "fits completely" becomes a worst frame of 114.3%. 10 fps absorbs it: median 93.7%, 1/120. FINDINGS 35. `11_cpu_budget.py` takes --io dma|pio|none, defaults to dma, and warns if asked for none. Also landed: - item 1 done: the cost model checked against the 68000 on a cost-aware container, -3.07% to +0.01%, whole-window mean -1.22%. FINDINGS 34. - item 4 done: the container carries its own 4-byte record alignment (DLX2). 94/120 record starts were on odd addresses -- an address error, not a slow read -- now 0/120 for 16 B/s. Re-encoding reproduces 31.1 exactly. FINDINGS 33. - a `scsi` window does not fit the 2 MB machine the rig emulates (2.84 MB of stream past a 0x200000 ceiling). The gate now verifies 80 of 120 frames and SAYS so, and fails loudly when the pass does not complete, instead of reporting a phantom 49,005-pixel diff. FINDINGS 36. Three near-misses this session had one shape: an unobservable run nearly produced a false finding. stdbuf -oL on any MAME job that prints progress -- a file is block-buffered too, and a run that is merely finishing looks exactly like one that is wedged. check.sh ALL GREEN. Claude-Session: https://claude.ai/code/session_01194oWYW8DQXK1SZ2DnChW6
117 lines
5.5 KiB
Python
117 lines
5.5 KiB
Python
#!/usr/bin/env python3
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"""Render what the codec is actually DOING, per block, per frame.
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Three panels at 12 fps: the palettised source (the real quality ceiling, not
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1080p -- FINDINGS 11), the decoded output, and a block-mode map.
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The mode map is not decoration. FINDINGS 24.5 makes the per-frame non-SKIP
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fraction the number that selects the decoder's inner loop, and a percentile
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cannot show you that the non-SKIP blocks are CLUSTERED (a moving character on a
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held background) rather than scattered. Clustering is what a run-length over
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the mode headers would exploit.
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SKIP left as the previous frame, costs the 68000 nothing
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V1 one 4x4 codeword, 1 byte
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V4 four 2x2 codewords, 4 bytes
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RAW 16 literal palette indices -- the escape that makes lam=0 pixel-exact
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Usage: python3 tools/analysis/08_mode_map.py <frames_dir> <out.webm>
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[--profile scsi] [--scale N] [--lossless] [--fixed-lam]
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--fixed-lam renders the pre-session-6 encoder (no rate control) instead.
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Output format follows the extension. Prefer .webm: GIF re-quantises to 256
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colours, which is a poor fit for output whose subject is colour fidelity.
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"""
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import sys, os
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sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "encoder"))
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import numpy as np
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from PIL import Image
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import vq as VQ, vq_hybrid as H, ratectl as RC
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MODE_RGB = np.array([[ 20, 22, 30], # SKIP - near black, costs nothing
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[ 60, 150, 230], # V1 - blue
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[ 80, 200, 120], # V4 - green
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[235, 90, 70]], # RAW - red, the expensive escape
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dtype=np.uint8)
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LABEL = ["SKIP", "V1", "V4", "RAW"]
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SCALE = 1
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LOSSLESS = False
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def main():
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global SCALE, LOSSLESS
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LOSSLESS = "--lossless" in sys.argv
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src, out = sys.argv[1], sys.argv[2]
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if "--scale" in sys.argv:
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SCALE = int(sys.argv[sys.argv.index("--scale")+1])
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prof = RC.PROFILES[sys.argv[sys.argv.index("--profile")+1]
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if "--profile" in sys.argv else "scsi"]
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m = H.build(src, k1=prof["k1"], k4=prof["k4"])
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# Rate-controlled by default, so the map shows the mode decisions that
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# actually ship. --fixed-lam renders the pre-session-6 encoder instead;
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# the difference is visible as V4/RAW collapsing to V1/SKIP on peak frames.
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if "--fixed-lam" in sys.argv:
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enc = H.encode(m, lam=prof["lam"])
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else:
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enc = RC.encode_rate_controlled(m, prof["kbps"],
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lam_lo=prof["lam"])
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pal, H_, W_ = m["pal"], m["H"], m["W"]
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nbx, nby = W_ // 4, H_ // 4
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frames, stats = [], []
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for f, (rec, mode) in enumerate(zip(enc["recon"], enc["modes"])):
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srcp = pal[m["idx"][f]]
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decp = pal[rec]
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mmap = MODE_RGB[mode.reshape(nby, nbx)].repeat(4, 0).repeat(4, 1)
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# tint the mode map with the decoded luma so the action stays legible
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luma = decp.mean(2, keepdims=True) / 255.0
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mmap = (mmap * (0.45 + 0.55 * luma)).astype(np.uint8)
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gap = np.full((H_, 3, 3), 60, np.uint8)
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panel = np.hstack([srcp, gap, decp, gap, mmap])
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im = Image.fromarray(panel)
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if SCALE != 1:
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im = im.resize((panel.shape[1]*SCALE, H_*SCALE), Image.NEAREST)
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frames.append(im)
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stats.append([(mode == i).mean() for i in range(4)])
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if out.endswith(".webm") or out.endswith(".mp4"):
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# Preferred. GIF would impose its own 256-colour palette on top of
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# output whose entire subject is colour fidelity, and costs ~4x the
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# bytes doing it. -lossless keeps the panels pixel-exact.
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import subprocess
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w, h = frames[0].size
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cmd = ["ffmpeg", "-v", "error", "-y", "-f", "rawvideo", "-pix_fmt", "rgb24",
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"-s", f"{w}x{h}", "-r", "12", "-i", "-"]
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# yuv444p, not 420: the mode map is flat saturated colour on a 4-pixel
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# grid, and chroma subsampling smears exactly those edges. Lossless is
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# available but runs larger than the GIF on this content; crf 18 in 444
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# is visually clean at a quarter the size.
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if out.endswith(".webm"):
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cmd += ["-c:v", "libvpx-vp9", "-pix_fmt", "yuv444p", "-row-mt", "1"]
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cmd += ["-lossless", "1"] if LOSSLESS else ["-crf", "18", "-b:v", "0"]
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else:
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cmd += ["-c:v", "libx264", "-crf", "12", "-pix_fmt", "yuv444p"]
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p = subprocess.Popen(cmd + [out], stdin=subprocess.PIPE)
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for f in frames:
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p.stdin.write(np.asarray(f.convert("RGB")).tobytes())
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p.stdin.close(); p.wait()
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else:
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# One shared adaptive palette: per-frame palettes are what make a naive
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# GIF of this enormous, and a stable palette also stops the mode-map
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# colours shimmering between frames.
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shared = frames[0].quantize(colors=192, method=Image.MEDIANCUT)
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q = [f.quantize(palette=shared, dither=Image.NONE) for f in frames]
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q[0].save(out, save_all=True, append_images=q[1:],
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duration=1000//12, loop=0, optimize=True)
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st = np.array(stats)
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print(f"{len(frames)} frames -> {out} ({os.path.getsize(out)/1024:.0f} KB)")
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print(" panels: palettised source | decoded | block mode map")
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for i, n in enumerate(LABEL):
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print(f" {n:4s} mean {100*st[:,i].mean():5.1f}% "
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f"per-frame range {100*st[:,i].min():5.1f}% .. {100*st[:,i].max():5.1f}%")
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ns = 100 * (1 - st[:, 0])
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print(f" non-SKIP: median {np.median(ns):.1f}% p90 {np.percentile(ns,90):.1f}%")
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if __name__ == "__main__":
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main()
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