dtourolle
ef99951360
Auto-match each named July frame by film+actor+class and re-extract it from the current learned-boundary flood replay, drawing GT-aware boxes: green TP, red FP, orange unknown, plus the blue off-screen/missed (X-Ray cast, no face) FN panel. Adds rematch_frames.py, the tool that does the matching. Zooey Deschanel is dropped: the current pipeline no longer makes that false identification, so the frame is removed and the July deep-dive notes the fix rather than showing a stale error.
117 lines
5.5 KiB
Python
117 lines
5.5 KiB
Python
#!/usr/bin/env python3
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"""
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rematch_frames.py — remake each named July frame example against the CURRENT
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pipeline. For a file named <film>_<...>_<actor>.jpg, find a second in this film's
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replay where that actor is drawn in the matching class (FP for *_fpi_*, TP for
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*_tp/perfect*), extract + annotate it, and write it over the doc asset. Reports
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which July examples no longer reproduce (honest — the config/model changed).
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Needs the per-film raw replay (experiments/dumps + replay --raw-out already run by
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regen_frame_examples.sh into the scratch predictions). Reads those.
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"""
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from __future__ import annotations
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import json, sys, subprocess, re
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from pathlib import Path
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sys.path.insert(0, "scripts/optimizer"); sys.path.insert(0, "scripts/validation")
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import dump_error_frames as D
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from second_score import load_second_timeline, _match
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SP = Path("/tmp/claude-1000/-home-dtourolle-Development-scene-actor-extraction/"
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"c579f8cf-2974-4cbd-be88-afec68dbbf58/scratchpad")
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ASSETS = Path("docs/assets/images")
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LUT = json.load(open("experiments/file-lut.json"))
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FILMS = json.load(open("experiments/manifests/films_LVFace_opencv5.json"))
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XR = {f["slug"]: f["xray"] for f in FILMS}
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# filename → (film slug, actor substring, class). class: "fp" | "tp".
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# actor substring is matched case-insensitively against drawn names.
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JOBS = {
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"lord_of_war_fpi_reddick.jpg": ("Lord_of_War", "reddick", "fp"),
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"lord_of_war_fpi_shumbris.jpg": ("Lord_of_War", "shumbris", "fp"),
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"lord_of_war_fpi_reagan_photo.jpg": ("Lord_of_War", "reagan", "fp"),
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"lovelace_fpi_sevigny.jpg": ("Lovelace", "sevigny", "fp"),
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"lovelace_robert_patrick_fpi.jpg": ("Lovelace", "patrick", "fp"),
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"lovelace_perfect_second.jpg": ("Lovelace", None, "tp"),
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"lovelace_polygraph_bridged.jpg": ("Lovelace", None, "tp"),
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"many_saints_fpi_deschanel.jpg": ("The_Many_Saints_of_Newark", "deschanel", "fp"),
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"many_saints_fpi_gardner.jpg": ("The_Many_Saints_of_Newark", "gardner", "fp"),
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"many_saints_fpi_yates.jpg": ("The_Many_Saints_of_Newark", "yates", "fp"),
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"many_saints_outofcast_fpi.jpg": ("The_Many_Saints_of_Newark", None, "fp"),
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"scarface_fpi_alley.jpg": ("Scarface", "alley", "fp"),
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"downton_crew_fn.jpg": ("Downton_Abbey__A_New_Era", None, "tp"),
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"downton_wedding_couple.jpg": ("Downton_Abbey__A_New_Era", None, "tp"),
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"downton_tp_example.jpg": ("Downton_Abbey__A_New_Era", None, "tp"),
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"valerian_screen_call.jpg": ("Valerian_and_the_City_of_a_Thousand_Plan", None, "tp"),
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"cafe_society_rapid_cut.jpg": ("Café_Society", None, "tp"),
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# germar_beats_xray / downton_funeral_19of20 are July-narrative-specific; skip.
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}
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def gt_keysets(slug):
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tl, _, _ = load_second_timeline(XR[slug])
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return tl
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def main():
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made, missing = [], []
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for fname, (slug, actor, cls) in JOBS.items():
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raw = SP / f"{slug}_raw.jsonl"
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if not raw.exists():
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missing.append((fname, "no raw replay")); continue
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tl = gt_keysets(slug)
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best = None # (t, actor_dict, fp_keys)
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for line in open(raw):
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d = json.loads(line)
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t = int(d["timestamp_sec"])
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drawn = [a for a in d.get("visible_actors", []) if a.get("actor_idx", -1) >= 0]
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if not drawn:
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continue
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gt = tl.get(t, [])
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fp_keys = {D._name_key(a["name"]) for a in drawn
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if not any(D._name_key(a["name"]) in g for g in gt)}
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for a in drawn:
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nk = D._name_key(a["name"]); is_fp = nk in fp_keys
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if actor and actor not in a["name"].lower():
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continue
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match = (is_fp if cls == "fp" else not is_fp)
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if not match:
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continue
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# prefer high similarity + a clean single-subject frame
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score = a["similarity"] - 0.05*len(drawn)
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if best is None or score > best[3]:
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best = (t, d, fp_keys, score)
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if best is None:
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missing.append((fname, f"no current {cls} for {actor or 'any'}")); continue
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t, d, fp_keys, _ = best
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# FN names at t: X-Ray scene cast whose keyset matches no drawn face.
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gt = tl.get(t, [])
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drawn_keys = [set(D._name_key(a["name"]).replace("name:", "") for _ in [0])
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for a in d.get("visible_actors", []) if a.get("actor_idx", -1) >= 0]
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drawn_ks = [D._name_key(a["name"]) for a in d.get("visible_actors", [])
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if a.get("actor_idx", -1) >= 0]
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fn_names = []
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for ga in gt:
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if not any(dk in ga for dk in drawn_ks):
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readable = sorted(x for x in ga
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if not x.startswith("imdb:") and not x.startswith("tmdb:")
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and not x.startswith("jf:"))
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if readable:
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fn_names.append(readable[0])
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out = ASSETS / fname
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try:
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D.extract_frame(LUT[slug], t, out)
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D.draw_annotations(out, d["visible_actors"], fp_keys=fp_keys,
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fn_names=fn_names)
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made.append((fname, slug, t))
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except subprocess.CalledProcessError:
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missing.append((fname, "ffmpeg failed"))
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print("=== remade ===")
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for f, s, t in made: print(f" {f} ({s} t={t}s)")
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print("=== no current equivalent (left as-is / flag in doc) ===")
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for f, why in missing: print(f" {f} — {why}")
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if __name__ == "__main__":
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main()
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