#!/usr/bin/env python3 """s34 전체 샷 스틸 런 (2026-07-12, 실험 전용·커밋 금지). v24i 체인: v24 i2 콘티(실사영화 스토리보드+REALIZE 원칙) 6장 → 그리드 크롭(백색 패널 제외, 28패널, panels24i/) → LLM이 샷별 '시각적 관련 앞쪽 샷' 판정(기존 판정 재사용, prev 참조) → nb2 스틸 순차 생성 (참조=콘티 패널[참조일 뿐, 그대로 실사화 금지 강조]+prev 스틸+VE 엔티티: 캐릭터 composite+소품 reference_face — 맵·배경 참조 없음, REALIZE 원칙 주입, stills24i/) → stills_run24i.html 새 갤러리. 이전 런(nb2 콘티 기반 panels24/stills24/stills_run24.html)은 보존. 사용: backend/.venv/bin/python s34_stillrun.py --only [--groups ...] """ import argparse import html as _html import json import subprocess import sys from pathlib import Path HERE = Path(__file__).parent sys.path.insert(0, str(HERE)) import forest_lib as F # noqa: E402 BASE = HERE CONTI_VER = "conti24" # 크롭 소스 콘티 시트 버전 CONTI_ENG = "i2" # 콘티 엔진 (i2 콘티 → nb2 실사) OUTP = BASE / "out" / "conti" / "panels24i" # v24s: LLM이 샷별 콘티 참조 필요 여부 판정 → 쉬운 구도는 콘티 제거. # 갤러리에 참조 구성·프롬프트 전문 기록. (v24i 산출물은 보존) OUTS = BASE / "out" / "conti" / "stills24s" PAGE = BASE / "stills_run24s.html" PLAN_CONTI = "s34_conti_v2" PLAN_RUN = "s34_stillrun_v1" P5 = "8ad94c03-5b33-4d51-83d0-a6e4106e9c02" DATA = json.load(open(BASE / "pipeline_doc" / "shot_loc_data.json")) SHOT = {(s["scene"], s["shot"]): s for s in DATA["shots"]} GROUPS = json.loads(json.dumps({ # (표시명, 샷 목록) — s34 콘티와 동일 "forest": ["S1sh1", "S1sh4", "S3sh3"], "busstop": ["S15sh2", "S15sh6"], "rooftop_ext": ["S10sh6", "S10sh7", "S11sh4", "S11sh5", "S13sh4", "S13sh6"], "rooftop_int": ["S12sh11", "S12sh21", "S14sh5", "S18sh11", "S25sh1", "S25sh5"], "mart": ["S8sh3", "S8sh5", "S19sh5", "S19sh6", "S20sh1", "S20sh3"], "police": ["S16sh3", "S21sh7", "S21sh10", "S21sh12", "S22sh1"], })) GRID = {"forest": (2, 2), "busstop": (2, 1), "rooftop_ext": (3, 2), "rooftop_int": (3, 2), "mart": (3, 2), "police": (3, 2)} # 그룹 장소 서술(콘티 v24와 동일) — 콘티 제거 샷의 장소 앵커. # 스틸 프롬프트에 장소 텍스트가 없으면 콘티 패널이 유일한 장소 단서라, # 콘티 제거 시 장소 이탈 실측(S3sh3 숲→도시 거리) → LOCATION lock 상시 주입. PLACE = { "forest": "a dense Korean mountain forest with thick undergrowth", "busstop": "a small seaside bus stop with a bench facing the sea at" " night on a quiet Korean coastal road", "rooftop_ext": "the exterior of an old Korean multi-family villa:" " narrow alley and small yard at ground level, an added" " exterior steel staircase climbing the wall, and a" " rooftop with a small rooftop room (steel front door," " one lit window), a water tank, a clothesline and a" " low parapet", "rooftop_int": "the interior of a small Korean rooftop home: living" " room with a small window, kitchenette and dining" " table; a bedroom with a bed against one wall and a" " curtained window; a tiny tiled bathroom with a mirror", "mart": "a mid-size Korean supermarket: shelved sales floor inside;" " the entrance area outside with a bicycle rack and one" " wall-mounted CCTV camera above; a small back security" " office with CCTV monitors", "police": "a modest Korean provincial police station: a detectives'" " office with desks, monitors and a doorway; and the street" " right in front of the building", } def _key(tag): si, shi = tag[1:].split("sh") return (int(si), int(shi)) def _time_of(tag): h = SHOT[_key(tag)]["heading"] or "" if "/ N" in h or "밤" in h: return "night" if "해질" in h or "해 질" in h: return "dusk, just after sunset" if "동틀" in h: return "dawn" if "소나기" in h: return "heavy rain shower, daytime" if "실내" in h: return "interior ambient light" return "daytime" def stage_judge(groups_filter): plan = F.load_plan(PLAN_RUN) if (BASE / "plans" / f"{PLAN_RUN}.json").exists() else {} prev_map = plan.setdefault("prev", {}) SYS = "\n".join([ "당신은 콘티 연속성 판정가다. 같은 장소 그룹의 샷 목록(순서대로)과", "씬 원문을 보고, 각 샷마다 '시각적으로 관련된 앞쪽 샷'이 있는지", "판정하라. 시각적 관련 = 같은 공간·연속된 액션·같은 인물 구도가", "이어져 앞 샷의 생성 이미지를 참조로 붙이면 일관성에 도움이 되는", "경우. 다른 시간대·다른 서브 공간·연결 단서가 없으면 null.", "앞쪽 샷은 반드시 목록에서 자기보다 앞에 있는 샷이어야 한다.", "각 샷마다 prev(태그 또는 null)와 reason_ko(한 구절)를 반환.", ]) SCHEMA = {"type": "object", "properties": {"items": {"type": "array", "items": {"type": "object", "properties": { "shot": {"type": "string"}, "prev": {"type": ["string", "null"]}, "reason_ko": {"type": "string"}}, "required": ["shot", "prev", "reason_ko"]}}}, "required": ["items"]} for gkey, tags in GROUPS.items(): if groups_filter and gkey not in groups_filter: continue scene_ids = sorted({_key(t)[0] for t in tags}) scenes_txt = "\n\n".join( f"[씬 {si}] {DATA['scenes'][str(si)]['heading']}\n" + DATA['scenes'][str(si)]['text'] for si in scene_ids) shots_txt = "\n".join( f"{t}: {SHOT[_key(t)]['desc']}" for t in tags) res = F.llm(f"s34run_prev_{gkey}", SYS, f"씬 원문:\n{scenes_txt}\n\n샷 목록(순서):\n{shots_txt}", SCHEMA) prev_map[gkey] = {it["shot"]: {"prev": it["prev"], "reason": it["reason_ko"]} for it in res["items"]} print(f"[judge] {gkey}:", {k: v["prev"] for k, v in prev_map[gkey].items()}) F.save_plan(PLAN_RUN, plan) def stage_conti_need(groups_filter): """LLM 판정: 샷별로 콘티(구도) 참조가 필요한지 — 쉬운 구도는 제거.""" plan = F.load_plan(PLAN_RUN) need_map = plan.setdefault("conti_need", {}) mv_all = F.load_plan(PLAN_CONTI)["movement"] SYS = "\n".join([ "당신은 촬영 현장의 콘티 운용 판정가다. 각 샷의 텍스트와 동선", "분석을 보고, 이미지 생성 시 스토리보드(콘티) 패널을 구도", "참조로 첨부할 필요가 있는지 판정하라.", "콘티 필요(true) = 구도를 글만으로 오해하기 쉬운 경우: 여러", "인물의 동선·위치 관계가 얽힘, 특수한 카메라 각도/깊이 관계,", "연속 액션의 방향 유지가 중요, 프레임 내 배치가 스토리텔링에", "결정적.", "콘티 불필요(false) = 글만으로 충분히 명확한 쉬운 구도: 단일", "인물 클로즈업/상반신, 단순 인서트(손·사물), 정적인 단순 배치,", "표준적인 대화 구도 등.", "각 샷마다 need_conti(bool)와 reason_ko(한 구절)를 반환하라.", ]) SCHEMA = {"type": "object", "properties": {"items": {"type": "array", "items": {"type": "object", "properties": { "shot": {"type": "string"}, "need_conti": {"type": "boolean"}, "reason_ko": {"type": "string"}}, "required": ["shot", "need_conti", "reason_ko"]}}}, "required": ["items"]} for gkey, tags in GROUPS.items(): if groups_filter and gkey not in groups_filter: continue lines = [] for t in tags: m = mv_all.get(gkey, {}).get(t, {}) if isinstance(m, str): m = {"movement": m} lines.append(f"{t}: {SHOT[_key(t)]['desc']}\n 동선: " + m.get("movement", "(없음)")) res = F.llm(f"s34run24s_contineed_{gkey}", SYS, "샷 목록:\n" + "\n".join(lines), SCHEMA) need_map[gkey] = {it["shot"]: {"need": it["need_conti"], "reason": it["reason_ko"]} for it in res["items"]} print(f"[conti_need] {gkey}:", {k: v["need"] for k, v in need_map[gkey].items()}) F.save_plan(PLAN_RUN, plan) # 시트 이상 레이아웃 수동 오버라이드 (육안 매핑) # conti24 i2: 6장 전부 등분 준수 — 단 forest는 수풀 질감을 거터로 # 오인(h=289)해 등분 강제(equal) SHEET_OVERRIDES = { "forest": {"grid": (2, 2), "equal": True, "cells": { "S1sh1": (0, 0), "S1sh4": (1, 0), "S3sh3": (0, 1)}}, } def stage_crop(): from PIL import Image OUTP.mkdir(parents=True, exist_ok=True) for gkey, tags in GROUPS.items(): sheet = Image.open( BASE / "out" / "conti" / f"{CONTI_VER}_{gkey}_{CONTI_ENG}.png").convert("RGB") # nb2 여백 자동 트림 (거의-흰색 마진 제거 후 그리드 크롭 — 대충) mask = sheet.convert("L").point(lambda v: 255 if v < 242 else 0) bbox = mask.getbbox() if bbox: pad = 4 bbox = (max(0, bbox[0] - pad), max(0, bbox[1] - pad), min(sheet.size[0], bbox[2] + pad), min(sheet.size[1], bbox[3] + pad)) sheet = sheet.crop(bbox) W, H = sheet.size ov = SHEET_OVERRIDES.get(gkey) cols, rows = ov["grid"] if ov else GRID[gkey] # 거터 라인 감지: 시트를 가로/세로로 관통하는 어두운 직선 탐색. # 실패 시 등분 fallback (대충 크롭 허용). import numpy as np arr = np.asarray(sheet.convert("L")) dark = arr < 120 def _lines(profile, n_expect, total): # profile: 축별 어두운 픽셀 비율. 0.55+ 구간을 라인 후보로. cand = [i for i, v in enumerate(profile) if v > 0.55] groups = [] for i in cand: if groups and i - groups[-1][-1] <= 6: groups[-1].append(i) else: groups.append([i]) centers = [sum(g) // len(g) for g in groups if total * 0.05 < sum(g) / len(g) < total * 0.95] if len(centers) == n_expect: return centers return [total * (k + 1) // (n_expect + 1) for k in range(n_expect)] # 등분 fallback if ov and ov.get("equal"): v_lines = [W * (k + 1) // cols for k in range(cols - 1)] h_lines = [H * (k + 1) // rows for k in range(rows - 1)] else: v_lines = _lines(dark.mean(axis=0), cols - 1, W) if cols > 1 else [] h_lines = _lines(dark.mean(axis=1), rows - 1, H) if rows > 1 else [] xs = [0] + v_lines + [W] ys = [0] + h_lines + [H] for i, tag in enumerate(tags): if ov: c, r = ov["cells"][tag] else: c, r = i % cols, i // cols box = (xs[c] + 3, ys[r] + 3, xs[c + 1] - 3, ys[r + 1] - 3) sheet.crop(box).save(OUTP / f"{tag}.png") print(f"[crop] {gkey}: {len(tags)}패널 v={v_lines} h={h_lines}" + (" (override)" if ov else "")) def _psql(sql): return subprocess.run( ["psql", "-h", "localhost", "-U", "theroad", "-d", "theroad", "-tAc", sql], capture_output=True, text=True, check=True, env={"PGPASSWORD": "theroad_dev_2026", "PATH": "/usr/bin:/bin:/opt/homebrew/bin:/usr/local/bin"}).stdout def _char_refs(): """5회차 VE 캐릭터 → composite 경로 (DB read-only).""" sql = ("SELECT DISTINCT ON (ec.short_id) ec.short_id, ec.name," " ia.file_path FROM image_asset ia " "JOIN entity_canon ec ON ec.id::text=ia.entity_id::text " f"WHERE ia.project_id='{P5}' AND ec.entity_type='character' " "AND ia.pipeline_role='reference_composite' " "ORDER BY ec.short_id, ia.created_at DESC") m = {} for line in _psql(sql).strip().split("\n"): if not line: continue sid, name, path = line.split("|") m[sid] = (name, Path("/Users/manta/Documents/Projects/TheRoad-I1") / path) return m def _prop_refs(): """5회차 VE 소품 → reference_face 경로 (DB read-only).""" sql = ("SELECT DISTINCT ON (ec.short_id) ec.short_id, ec.name," " ia.file_path FROM image_asset ia " "JOIN entity_canon ec ON ec.id::text=ia.entity_id::text " f"WHERE ia.project_id='{P5}' AND ec.entity_type='prop' " "AND ia.pipeline_role='reference_face' " "ORDER BY ec.short_id, ia.created_at DESC") m = {} for line in _psql(sql).strip().split("\n"): if not line: continue sid, name, path = line.split("|") m[sid] = (name, Path("/Users/manta/Documents/Projects/TheRoad-I1") / path) return m def _ve_ids(): """샷별 VE — 배경(L) 제외 전 엔티티(C/P) short_id 목록.""" sql = ("SELECT scene_index, shot_index, visible_entities_json FROM" f" scene_still WHERE project_id='{P5}' AND is_selected") m = {} for line in _psql(sql).strip().split("\n"): if not line: continue si, shi, ve = line.split("|", 2) try: ids = [e["short_id"] for e in json.loads(ve) if str(e.get("short_id", ""))[:1] in ("C", "P")] except Exception: ids = [] m[(int(si), int(shi))] = ids return m # Gemini IMAGE_SAFETY 우회 — 명시 고어 어휘만 완곡화 (시각 의도 유지) _SOFTEN = [("피투성이가 된", "힘없이 무너져 미동이 없는"), ("핏자국", "어두운 얼룩"), ("피 묻은", "얼룩진"), ("피로 그린 듯한", "짙은 붉은"), ("blood-soaked", "dark-stained"), ("bloodied", "dark-stained"), ("bloodstained", "stained"), ("bloody", "dark-stained"), ("blood", "dark stains"), ("lifeless", "utterly motionless, collapsed"), ("corpse", "motionless figure")] def _soften(t): for a, b in _SOFTEN: t = t.replace(a, b) return t REALIZE_STILL = "\n".join([ "REALIZE FIGURATIVE LANGUAGE AS A LIVE-ACTION SHOT: the Korean shot", "text may describe characters metaphorically, figuratively or with", "exaggeration. Photograph what a real movie camera would actually", "record on a physical set — exaggerated or figurative impressions", "become realistic staging choices (lighting, distance, angle,", "wardrobe), not literal fantasy imagery.", "EVERY CHARACTER IS A HUMAN BEING: unless the story explicitly", "features non-human or virtual beings (as in science fiction or", "fantasy), every character — however indirectly, vaguely or", "figuratively the text describes them — IS a real human. When the", "text gives no direct visual description of a person, IMAGINE one", "and still show them as a concrete, fully-formed human being:", "always render the human form to the maximum extent — build,", "posture, face, hands, clothing — never reduce a person to a shape,", "blob, solid silhouette or abstract mass.", ]) def stage_gen(groups_filter): plan = F.load_plan(PLAN_RUN) prev_map = plan["prev"] need_map = plan.get("conti_need", {}) meta = plan.setdefault("gen_meta", {}) mv_all = F.load_plan(PLAN_CONTI)["movement"] chars = _char_refs() props = _prop_refs() ve = _ve_ids() # VE 공백 fallback: 같은 씬 선택 샷들의 VE 합집합 scene_union = {} for (si, shi), ids in ve.items(): scene_union.setdefault(si, set()).update(ids) OUTS.mkdir(parents=True, exist_ok=True) for gkey, tags in GROUPS.items(): if groups_filter and gkey not in groups_filter: continue for tag in tags: out = OUTS / f"{tag}_nb2.png" if out.exists(): print(f"[gen] {tag} skip(exists)") continue s = SHOT[_key(tag)] m = mv_all.get(gkey, {}).get(tag, {}) if isinstance(m, str): m = {"movement": m, "figures": ""} pj = prev_map.get(gkey, {}).get(tag, {}) prev_tag = pj.get("prev") nd = need_map.get(gkey, {}).get(tag, {"need": True, "reason": "판정 없음"}) refs = [] if nd["need"]: refs.append(( "STORYBOARD PANEL — a REFERENCE ONLY, never the" " target: use it loosely for camera framing, figure" " placement and depth order. Do NOT photorealize" " this drawing as-is — the SHOT TEXT and the other" " references are authoritative; re-stage the moment" " naturally as a real photograph. Never copy the" " sketch's line style, paper texture, borders," " simplified geometry or drawing errors.", OUTP / f"{tag}.png")) prev_used = None if prev_tag and (OUTS / f"{prev_tag}_nb2.png").exists(): prev_used = prev_tag refs.append(( "PREVIOUS SHOT STILL — a visually related earlier shot" " of this same place: the location's look, materials," " fixed features, lighting mood and each person's" " clothing are LOCKED to this photo; never copy its" " camera framing.", OUTS / f"{prev_tag}_nb2.png")) ve_ids = ve.get(_key(tag), []) if not ve_ids: ve_ids = sorted(scene_union.get(_key(tag)[0], set())) char_names, prop_names = [], [] for cid in ve_ids: if cid in chars: name, p = chars[cid] if p.exists(): char_names.append(name) refs.append(( f"CHARACTER REFERENCE — {name}: the exact" " person appearing in this shot; match face," " hair and build exactly.", p)) elif cid in props: name, p = props[cid] if p.exists(): prop_names.append(name) refs.append(( f"PROP REFERENCE — {name}: the exact object" " appearing in this shot; match its look," " material and wear exactly.", p)) parts = [ "Create ONE FINAL photorealistic live-action film still of" " the moment below — contemporary South Korea, 2026; all" " people are Korean unless stated. TIME OF DAY (lock): " + _time_of(tag) + ".", f"SHOT TEXT (authoritative, Korean): {_soften(s['desc'])}", f"LOCATION (lock): {PLACE[gkey]}. The shot takes place" " here — pick the sub-area of this location that the shot" " text implies.", ] if nd["need"]: parts.append("\n".join([ "THE STORYBOARD PANEL IS ONLY A REFERENCE: it is a", "rough pre-production sketch, not the image to", "reproduce. Take from it only the shot's rough", "composition — framing, where figures sit, near/far", "order. Everything else (real-world detail, materials,", "light, anatomy, environment richness) must come from", "the shot text and the photographic references,", "re-staged as if actually filmed on a real set. If the", "sketch conflicts with the shot text or looks", "simplified/wrong, FOLLOW THE TEXT, not the sketch.", ])) parts.append(REALIZE_STILL) if m.get("movement"): parts.append("MOVEMENT (follow exactly): " + _soften(m["movement"])) if m.get("figures"): parts.append("FIGURES — size & depth (follow exactly): " + _soften(m["figures"])) if char_names: parts.append( "PEOPLE: the SHOT TEXT alone decides whether any person" " is visible in this shot. IF a person appears, they" " must be one of the referenced people (" + ", ".join(char_names) + ") matched exactly to their reference photo — never" " anyone else, and never add a person the shot text" " does not show.") else: parts.append("No people appear unless the shot text itself" " says so.") parts.append("No text, captions, watermarks or annotations" " anywhere.") prompt_full = "\n\n".join(parts) F.img_nb2(f"s34run24s_{tag}_nb2", prompt_full, refs, aspect_ratio="16:9", out_path=out) meta[tag] = { "conti_used": nd["need"], "conti_reason": nd["reason"], "prev_used": prev_used, "prompt": prompt_full, "refs": [{"label": lab, "path": (str(p.relative_to(BASE)) if str(p).startswith(str(BASE)) else str(p))} for lab, p in refs], } F.save_plan(PLAN_RUN, plan) print(f"[gen] {tag} 완료 (conti={nd['need']}," f" prev={prev_used}, chars={char_names}," f" props={prop_names})") def stage_html(): import shutil plan = F.load_plan(PLAN_RUN) prev_map = plan.get("prev", {}) need_map = plan.get("conti_need", {}) meta = plan.get("gen_meta", {}) REFD = BASE / "out" / "conti" / "refs24s" REFD.mkdir(parents=True, exist_ok=True) def esc(t): return _html.escape(t or "") def _ref_kind(label): if label.startswith("STORYBOARD"): return "콘티 패널 (구도 참조 전용)" if label.startswith("PREVIOUS"): return "PREV 스틸 (장소 룩·의상 잠금)" if label.startswith("CHARACTER"): return "캐릭터 " + label.split("—", 1)[1].split(":", 1)[0].strip() if label.startswith("PROP"): return "소품 " + label.split("—", 1)[1].split(":", 1)[0].strip() return label[:30] def _ref_rel(path_s): if not path_s.startswith("/"): return path_s # 이미 BASE 상대 src = Path(path_s) dst = REFD / src.name if not dst.exists(): shutil.copy(src, dst) return f"out/conti/refs24s/{src.name}" secs = [] NAME = {"forest": "숲속", "busstop": "해안가 버스정류장", "rooftop_ext": "옥탑 단지 외부", "rooftop_int": "옥탑방 내부", "mart": "대형마트", "police": "경찰서"} for gkey, tags in GROUPS.items(): figs = "" for tag in tags: pj = prev_map.get(gkey, {}).get(tag, {}) nd = need_map.get(gkey, {}).get(tag, {}) mt = meta.get(tag, {}) still_rel = f"out/conti/stills24s/{tag}_nb2.png" conti_used = mt.get("conti_used", nd.get("need")) badge = ("콘티 사용" if conti_used else "콘티 제거") ref_items = "" for r in mt.get("refs", []): rel = _ref_rel(r["path"]) ref_items += ( f"
" f"
" f"{esc(_ref_kind(r['label']))}
") if not ref_items: ref_items = "참조 이미지 없음" ref_details = "".join( f"
  • {esc(_ref_kind(r['label']))} — " f"{esc(r['label'])} " f"{esc(r['path'])}
    • " for r in mt.get("refs", [])) figs += ( f"

    {tag} {badge}" f" — 콘티 판정: {esc(nd.get('reason', ''))}" f" · prev: {esc(str(pj.get('prev') or '없음'))}" + (f" ({esc(pj.get('reason', ''))})" if pj.get("prev") else "") + "

    " f"
    " f"{esc(SHOT[_key(tag)]['desc'])}
    " f"
    " f"
    nb2 스틸
    " f"
    참조 이미지" f" ({len(mt.get('refs', []))}장):
    " f"
    {ref_items}
    " f"
    참조 상세 + 프롬프트 전문" f"
      {ref_details}
    " f"
    {esc(mt.get('prompt', '(기록 없음)'))}
    " f"
    ") secs.append(f"

    {esc(NAME[gkey])} " f"({gkey})

    {figs}
    ") PAGE.write_text(f""" s34 v24s 스틸 런 — LLM 콘티 선별+참조·프롬프트 전문 기록

    s34 v24s 스틸 런 — 28샷 (LLM 콘티 선별: 쉬운 구도는 콘티 참조 제거 → nb2 스틸)

    콘티 선별: 샷별로 LLM(GPT-5.6 Sol)이 "구도를 글만으로 오해하기 쉬운가"를 판정 — 다인물 동선·특수 앵글·깊이 관계는 콘티 사용, 단일 인물 클로즈업·단순 인서트·정적 배치는 콘티 제거. 나머지 참조는 동일: prev 스틸 (시각 관련 앞쪽 샷, 장소 룩·의상 잠금) + VE 전 엔티티(캐릭터 composite + 소품 reference_face, 배경 L 제외) + REALIZE 원칙 + 씬 헤딩 시간 잠금. 각 샷 카드에 사용된 참조 이미지 전부와 프롬프트 전문을 기록. 비교: v24i(전샷 콘티) · v24(nb2 콘티).
    {''.join(secs)} """) print(f"[html] {PAGE}") if __name__ == "__main__": ap = argparse.ArgumentParser() ap.add_argument("--only", required=True, choices=["judge", "conti_need", "crop", "gen", "html"]) ap.add_argument("--groups", default="") a = ap.parse_args() gf = [g for g in a.groups.split(",") if g] if a.only == "judge": stage_judge(gf) elif a.only == "conti_need": stage_conti_need(gf) elif a.only == "crop": stage_crop() elif a.only == "gen": stage_gen(gf) else: stage_html()