Major: smart selection pipeline (analyze.py) + audio fade + multi-lang auto-detect

- New analyze.py: full transcript + energy + structural analysis
- Smart clip range: includes pre-chorus, can exceed 30s up to max_duration (default 45s)
- Audio fade in/out: auto-detected from vocal boundaries
- Instrumental detection: auto-disables subs if vocals < 10% of duration
- Multi-language: auto-detect via Whisper or explicit (DE/SL/HR/BS/SR/EN/IT/ES/FR)
- Frontend: cleaner UX, added bs language, smart selection description
- reframe.py: --fade-in --fade-out args
- clip.py: propagates fade params
- app/main.py: replaces find_chorus.py call with analyze.py
This commit is contained in:
Sebastjan Artič 2026-04-29 06:21:35 +00:00
parent 81edd24ca3
commit 8512076b91
5 changed files with 572 additions and 36 deletions

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@ -154,37 +154,57 @@ def process_job(job_id):
else:
input_path = Path(job["input_path"])
# ── 2. Find chorus (če auto) ──────────────────────────
# ── 2. Smart analysis (če auto_chorus) ──────────────────────────
if job.get("auto_chorus"):
update_job(job_id, current_step="Iščem refren (Whisper + energy)")
update_job(job_id, current_step="Analiza pesmi (transkript + energija)")
analysis_path = OUTPUT_DIR / f"{job_id}.analysis.json"
cmd = [
"python3", str(SCRIPTS_DIR / "find_chorus.py"),
"python3", str(SCRIPTS_DIR / "analyze.py"),
str(input_path),
"--duration", str(job.get("duration", 30)),
"--json",
"--target-duration", str(job.get("duration", 30)),
"--max-duration", str(job.get("max_duration", 45)),
"--min-duration", str(job.get("min_duration", 20)),
"--output", str(analysis_path),
]
if job.get("lang"):
# lang: če None ali 'auto', pusti analyze.py auto-detect
if job.get("lang") and job["lang"] not in ("auto", ""):
cmd += ["--lang", job["lang"]]
cmd += ["--model", job.get("whisper_model", "small")]
proc = subprocess.run(cmd, capture_output=True, text=True)
if proc.returncode == 0:
if proc.returncode == 0 and analysis_path.exists():
try:
chorus = json.loads(proc.stdout)
if chorus.get("candidates"):
best = chorus["candidates"][0]
update_job(
job_id,
chorus_detection=chorus,
start=best["start"],
duration=best["duration"],
)
# KLJUČNO: reload local job dict, da nove vrednosti pridejo v reframe call
job = load_job(job_id)
except json.JSONDecodeError:
update_job(job_id, chorus_error="JSON decode failed")
with open(analysis_path, "r", encoding="utf-8") as f:
analysis = json.load(f)
cr = analysis["clip_range"]
fade = analysis["fade"]
update_job(
job_id,
analysis_summary={
"language": analysis["language"],
"language_probability": analysis["language_probability"],
"instrumental": analysis["instrumental"],
"clip_range": cr,
"fade": fade,
"chorus_preview": analysis["chorus"]["best"]["text_preview"]
if analysis.get("chorus") and analysis["chorus"].get("best") else None,
},
start=cr["start"],
duration=cr["duration"],
fade_in=fade["fade_in"],
fade_out=fade["fade_out"],
detected_language=analysis["language"],
is_instrumental=analysis["instrumental"],
)
# Auto-disable subs za instrumental
if analysis["instrumental"] and not job.get("no_subs"):
update_job(job_id, no_subs=True, auto_disabled_subs=True)
# Reload local dict
job = load_job(job_id)
except (json.JSONDecodeError, KeyError) as e:
update_job(job_id, chorus_error=f"Analysis parse: {e}")
else:
update_job(job_id, chorus_error=proc.stderr[-300:])
update_job(job_id, chorus_error=(proc.stderr or "")[-500:])
# ── 3. Reframe + subtitles (clip.py orchestrator) ─────
output_path = OUTPUT_DIR / f"{job_id}.mp4"
@ -201,8 +221,16 @@ def process_job(job_id):
cmd += ["--start", str(job["start"])]
if job.get("duration") is not None:
cmd += ["--duration", str(job["duration"])]
if job.get("lang"):
cmd += ["--lang", job["lang"]]
if job.get("fade_in", 0) > 0:
cmd += ["--fade-in", str(job["fade_in"])]
if job.get("fade_out", 0) > 0:
cmd += ["--fade-out", str(job["fade_out"])]
# lang: prefer detected_language če auto
chosen_lang = job.get("lang")
if chosen_lang in (None, "auto", ""):
chosen_lang = job.get("detected_language")
if chosen_lang:
cmd += ["--lang", chosen_lang]
if job.get("no_subs"):
cmd += ["--no-subs"]
cmd += ["--model", job.get("whisper_model", "small")]
@ -269,10 +297,12 @@ class YouTubeJobIn(BaseModel):
class StartJobIn(BaseModel):
job_id: str
mode: str = "track"
lang: Optional[str] = None
lang: Optional[str] = None # None/auto = Whisper auto-detect
auto_chorus: bool = True
start: Optional[float] = None
duration: Optional[float] = 30
max_duration: Optional[float] = 45 # Smart selection lahko gre do 45s
min_duration: Optional[float] = 20
no_subs: bool = False
subtitle_style: str = "reels"
whisper_model: str = "small"
@ -373,6 +403,8 @@ async def start_processing(
auto_chorus=payload.auto_chorus,
start=payload.start,
duration=payload.duration,
max_duration=payload.max_duration,
min_duration=payload.min_duration,
no_subs=payload.no_subs,
subtitle_style=payload.subtitle_style,
whisper_model=payload.whisper_model,

467
scripts/analyze.py Normal file
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@ -0,0 +1,467 @@
#!/usr/bin/env python3
"""
analyze.py Predhodna analiza CELEGA videa pred trim-anjem.
Naredi:
1. Whisper transcript celega videa (auto-detect jezika ali user-specified)
2. Energy profile (RMS dB na 1s windows)
3. Structural detection (vocal/instrumental sections, energy peaks)
4. Pametno izbere clip range (lahko >30s, vključi pre-chorus)
5. Detekcija instrumentalnih pesmi (no_subs auto)
Output: JSON s podatki za clip.py
"""
import argparse
import json
import os
import re
import subprocess
import sys
import tempfile
from pathlib import Path
def get_video_duration(path):
r = subprocess.run(
["ffprobe", "-v", "error", "-show_entries", "format=duration",
"-of", "default=nw=1:nokey=1", str(path)],
capture_output=True, text=True
)
try:
return float(r.stdout.strip())
except ValueError:
return 0.0
def extract_audio(video_path):
"""Extract avdio v 16kHz mono WAV za Whisper + energy."""
audio = tempfile.NamedTemporaryFile(suffix=".wav", delete=False)
audio.close()
subprocess.run(
["ffmpeg", "-y", "-i", str(video_path), "-vn",
"-ac", "1", "-ar", "16000", "-c:a", "pcm_s16le", audio.name],
check=True, capture_output=True
)
return audio.name
def transcribe_full(audio_path, lang=None, model_size="small"):
"""Whisper transcript celega avdia. lang=None → auto-detect."""
from faster_whisper import WhisperModel
print(f"🧠 Whisper {model_size}, lang={lang or 'auto'}", file=sys.stderr)
m = WhisperModel(model_size, device="cpu", compute_type="int8")
segs, info = m.transcribe(
audio_path,
language=lang,
word_timestamps=True,
vad_filter=True,
)
detected_lang = info.language
detected_prob = info.language_probability
print(f" Detekcija: {detected_lang} (p={detected_prob:.2f})", file=sys.stderr)
segments = []
for s in segs:
words = []
if s.words:
for w in s.words:
words.append({
"start": w.start,
"end": w.end,
"text": w.word,
})
segments.append({
"start": s.start,
"end": s.end,
"text": s.text.strip(),
"words": words,
})
return {
"language": detected_lang,
"language_probability": detected_prob,
"segments": segments,
}
def compute_energy_profile(audio_path, window_sec=1.0):
"""RMS dB na window_sec sekund. Vrne list (timestamp, rms_db)."""
cmd = [
"ffmpeg", "-i", audio_path,
"-af", f"asetnsamples=n={int(16000 * window_sec)}:p=0,"
f"astats=metadata=1:reset={window_sec},"
f"ametadata=print:key=lavfi.astats.Overall.RMS_level:file=-",
"-f", "null", "-",
]
result = subprocess.run(cmd, capture_output=True, text=True)
output = result.stdout + "\n" + result.stderr
energies = []
current_pts = 0.0
for line in output.split("\n"):
line = line.strip()
m = re.search(r"pts_time:(\S+)", line)
if m:
try:
current_pts = float(m.group(1))
except ValueError:
pass
continue
if "RMS_level=" in line:
val = line.split("RMS_level=")[-1].strip()
try:
rms = float(val)
# -inf zamenjamo z -90
if rms < -90 or rms != rms: # NaN check
rms = -90.0
energies.append((current_pts, rms))
current_pts += window_sec
except ValueError:
pass
return energies
def detect_vocal_sections(segments, max_gap=3.0):
"""Združi consecutive segmente v "vokalne sekcije"."""
if not segments:
return []
sections = []
current = {
"start": segments[0]["start"],
"end": segments[0]["end"],
"segments": [segments[0]],
"text": segments[0]["text"],
}
for seg in segments[1:]:
if seg["start"] - current["end"] > max_gap:
sections.append(current)
current = {
"start": seg["start"],
"end": seg["end"],
"segments": [seg],
"text": seg["text"],
}
else:
current["end"] = seg["end"]
current["segments"].append(seg)
current["text"] += " " + seg["text"]
sections.append(current)
return sections
def avg_energy_in_range(energies, start, end):
"""Povprečna RMS v rangeu."""
vals = [r for (t, r) in energies if start <= t <= end]
if not vals:
return -90.0
return sum(vals) / len(vals)
def score_section_as_chorus(section, all_sections, energies, avg_rms):
"""Score sekcijo kot kandidat za refren.
Faktorji:
- Ponavljajoče besede (low unique-word-ratio) = refren
- Visoka energija
- Sekcija se pojavi večkrat v pesmi (refren se ponovi)
- Krajše vrstice (3-8 besed)
"""
text = section["text"].lower()
words = re.findall(r"\b\w+\b", text)
if not words:
return 0
unique_ratio = len(set(words)) / len(words)
# Refren = nizko unique ratio (ponovitve)
chorus_signal = max(0, (1.0 - unique_ratio) * 30)
# Energija
sec_energy = avg_energy_in_range(energies, section["start"], section["end"])
energy_above = max(0, sec_energy - avg_rms)
energy_score = energy_above * 8
# Kako pogosto se pojavi podobno besedilo
repeat_count = 0
for other in all_sections:
if other is section:
continue
other_text = other["text"].lower()
other_words = set(re.findall(r"\b\w+\b", other_text))
common = set(words) & other_words
# Če imata >50% besed skupnih, je verjetno isti refren
if len(common) >= len(set(words)) * 0.5 and len(common) >= 3:
repeat_count += 1
repeat_score = repeat_count * 25
# Dolžina vrstice
duration = section["end"] - section["start"]
if 3 <= duration <= 25:
length_score = 10
elif duration > 25:
length_score = 5
else:
length_score = 2
return chorus_signal + energy_score + repeat_score + length_score
def find_chorus(transcript, energies, video_duration):
"""Najde najbolj verjeten refren."""
sections = detect_vocal_sections(transcript["segments"])
if not sections:
return None
avg_rms = sum(r for (_, r) in energies) / len(energies) if energies else -30.0
candidates = []
for sec in sections:
score = score_section_as_chorus(sec, sections, energies, avg_rms)
candidates.append({
"start": sec["start"],
"end": sec["end"],
"duration": sec["end"] - sec["start"],
"text_preview": sec["text"][:80],
"score": round(score, 2),
"avg_rms": round(avg_energy_in_range(energies, sec["start"], sec["end"]), 2),
})
# Sort by score descending
candidates.sort(key=lambda c: -c["score"])
if not candidates:
return None
return {
"best": candidates[0],
"all_candidates": candidates[:10],
"avg_rms_total": round(avg_rms, 2),
}
def smart_clip_range(chorus, transcript, video_duration,
target_duration=30, max_duration=45, min_duration=20):
"""Inteligentno določi clip range.
Logika:
1. Začni z refrenom kot core
2. Če je krajši od min_duration, razširi na obeh straneh
3. Če imamo prostor, dodaj pre-chorus pred refrenom
4. Cap na max_duration
"""
if not chorus or not chorus.get("best"):
# Fallback: vzemi sredino videa
mid = video_duration / 2
start = max(0, mid - target_duration / 2)
return {
"start": start,
"end": min(video_duration, start + target_duration),
"reason": "fallback_middle",
}
best = chorus["best"]
sections = detect_vocal_sections(transcript["segments"])
actual_start = best["start"]
actual_end = best["end"]
# 1. Če je core refren prekratek, razširi
if actual_end - actual_start < min_duration:
# Najdi naslednjo sekcijo (verjetno se refren ponovi)
for sec in sections:
if sec["start"] > actual_end and sec["start"] - actual_end < 5:
# Sekcija blizu, dodaj jo
if sec["end"] - actual_start <= max_duration:
actual_end = sec["end"]
if actual_end - actual_start >= min_duration:
break
# 2. Dodaj pre-chorus pred refrenom (build-up)
pre_section = None
for sec in sections:
if sec["end"] <= actual_start and actual_start - sec["end"] < 8:
pre_section = sec # zadnja pred refrenom
if pre_section:
candidate_start = pre_section["start"]
if actual_end - candidate_start <= max_duration:
actual_start = candidate_start
# 3. Če je res prekratek, razširi simetrično
if actual_end - actual_start < min_duration:
deficit = min_duration - (actual_end - actual_start)
actual_start = max(0, actual_start - deficit / 2)
actual_end = min(video_duration, actual_end + deficit / 2)
# 4. Trim na max
if actual_end - actual_start > max_duration:
actual_end = actual_start + max_duration
# Snap to video bounds
actual_start = max(0, actual_start)
actual_end = min(video_duration, actual_end)
return {
"start": round(actual_start, 2),
"end": round(actual_end, 2),
"duration": round(actual_end - actual_start, 2),
"reason": "smart_chorus_with_prebuild",
"chorus_start": round(best["start"], 2),
"chorus_end": round(best["end"], 2),
}
def detect_audio_fade(clip_range, transcript):
"""Določi fade-in/fade-out trajanje.
Logika:
- Če clip začne sredi vokala 0.5s fade in
- Če se konča sredi vokala 1.0s fade out
- Sicer manj fade
"""
cs, ce = clip_range["start"], clip_range["end"]
# Vokal pri začetku?
starts_in_vocal = False
ends_in_vocal = False
for seg in transcript["segments"]:
# Začetek clip-a znotraj segmenta
if seg["start"] <= cs <= seg["end"]:
starts_in_vocal = True
# Konec clip-a znotraj segmenta
if seg["start"] <= ce <= seg["end"]:
ends_in_vocal = True
fade_in = 0.5 if starts_in_vocal else 0.2
fade_out = 1.5 if ends_in_vocal else 0.3
return {"fade_in": fade_in, "fade_out": fade_out}
def is_instrumental(transcript, video_duration, threshold=0.1):
"""Detekcija ali je pesem instrumentalna.
Če je vsota trajanja vokalnih segmentov < threshold * video_duration,
je pesem instrumentalna.
"""
if not transcript.get("segments"):
return True
vocal_duration = sum(
s["end"] - s["start"] for s in transcript["segments"]
)
ratio = vocal_duration / max(video_duration, 1)
return ratio < threshold
def main():
ap = argparse.ArgumentParser()
ap.add_argument("video", help="Vhod video file")
ap.add_argument("--lang", default=None, help="ISO 639-1 ali 'auto' (default: auto)")
ap.add_argument("--model", default="small", help="Whisper model")
ap.add_argument("--target-duration", type=float, default=30.0)
ap.add_argument("--max-duration", type=float, default=45.0)
ap.add_argument("--min-duration", type=float, default=20.0)
ap.add_argument("--json", action="store_true", help="Output JSON")
ap.add_argument("--output", help="Path za JSON output")
args = ap.parse_args()
video = Path(args.video)
if not video.exists():
print(f"❌ Video ne obstaja: {video}", file=sys.stderr)
sys.exit(1)
duration = get_video_duration(video)
print(f"📹 Video: {video.name}, {duration:.1f}s", file=sys.stderr)
# 1. Extract avdio
audio = extract_audio(video)
try:
# 2. Whisper transcript
lang = None if args.lang in (None, "auto", "") else args.lang
transcript = transcribe_full(audio, lang=lang, model_size=args.model)
print(f" Transkripcija: {len(transcript['segments'])} segmentov", file=sys.stderr)
# 3. Energy profile
print(f"⚡ Energy profile...", file=sys.stderr)
energies = compute_energy_profile(audio)
print(f" Energy samples: {len(energies)}", file=sys.stderr)
# 4. Instrumental detection
instrumental = is_instrumental(transcript, duration)
print(f"🎵 Instrumentalna: {instrumental}", file=sys.stderr)
# 5. Find chorus (samo če ni instrumental)
if not instrumental:
chorus = find_chorus(transcript, energies, duration)
else:
# Za instrumentalne: najdi sekcijo z najvišjo energijo
window = args.target_duration
best_start = 0
best_avg = -100
t = 0
while t + window <= duration:
avg = avg_energy_in_range(energies, t, t + window)
if avg > best_avg:
best_avg = avg
best_start = t
t += 5 # step 5s
chorus = {
"best": {
"start": best_start,
"end": best_start + window,
"duration": window,
"text_preview": "(instrumental — energy peak)",
"score": 0,
"avg_rms": round(best_avg, 2),
},
"all_candidates": [],
"avg_rms_total": round(
sum(r for (_, r) in energies) / len(energies) if energies else -30, 2
),
}
# 6. Smart clip range
clip_range = smart_clip_range(
chorus, transcript, duration,
target_duration=args.target_duration,
max_duration=args.max_duration,
min_duration=args.min_duration,
)
print(f"✂ Clip range: {clip_range['start']:.1f}s - {clip_range['end']:.1f}s "
f"(duration: {clip_range['duration']}s)", file=sys.stderr)
# 7. Fade params
fade = detect_audio_fade(clip_range, transcript)
print(f"🎚 Fade: in={fade['fade_in']}s, out={fade['fade_out']}s", file=sys.stderr)
result = {
"video": str(video),
"video_duration": duration,
"language": transcript["language"],
"language_probability": transcript["language_probability"],
"instrumental": instrumental,
"transcript": transcript,
"chorus": chorus,
"clip_range": clip_range,
"fade": fade,
}
if args.output:
with open(args.output, "w", encoding="utf-8") as f:
json.dump(result, f, ensure_ascii=False, indent=2)
print(f"💾 Saved: {args.output}", file=sys.stderr)
if args.json:
print(json.dumps(result, ensure_ascii=False))
finally:
try:
os.unlink(audio)
except Exception:
pass
if __name__ == "__main__":
main()

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@ -45,9 +45,11 @@ def parse_clips(spec):
SCRIPT_DIR = Path(__file__).parent
def run_clip(src, dst, start, duration, mode, lang, model, style, no_subs, quality):
def run_clip(src, dst, start, duration, mode, lang, model, style, no_subs, quality,
fade_in=0.0, fade_out=0.0):
"""Naredi en klip src → dst."""
print(f"🎯 run_clip args: src={src}, dst={dst}, start={start!r}, duration={duration!r}, mode={mode}", file=sys.stderr)
print(f"🎯 run_clip args: src={src}, dst={dst}, start={start!r}, duration={duration!r}, "
f"mode={mode}, fade_in={fade_in}, fade_out={fade_out}", file=sys.stderr)
tmp = tempfile.mkdtemp(prefix="reel_")
try:
reframed = Path(tmp) / "reframed.mp4"
@ -63,6 +65,10 @@ def run_clip(src, dst, start, duration, mode, lang, model, style, no_subs, quali
cmd += ["--start", str(start)]
if duration is not None:
cmd += ["--duration", str(duration)]
if fade_in > 0:
cmd += ["--fade-in", str(fade_in)]
if fade_out > 0:
cmd += ["--fade-out", str(fade_out)]
print(f"🔧 REFRAME CMD: {' '.join(cmd)}", file=sys.stderr)
print(f"\n▶ Klip: {dst.name}")
r = subprocess.run(cmd)
@ -97,6 +103,8 @@ def main():
ap.add_argument("output", help="Datoteka (en klip) ali mapa (več klipov)")
ap.add_argument("--start", type=str, default=None, help="Začetek (s ali mm:ss)")
ap.add_argument("--duration", type=float, default=None, help="Trajanje v s")
ap.add_argument("--fade-in", type=float, default=0.0, help="Audio fade in (s)")
ap.add_argument("--fade-out", type=float, default=0.0, help="Audio fade out (s)")
ap.add_argument("--clips", type=str, default=None,
help="Več klipov: '0:30-1:00,2:15-2:45'")
ap.add_argument("--mode", default="track", choices=["track", "center", "blur"])
@ -127,7 +135,8 @@ def main():
else:
start = parse_ts(args.start) if args.start else None
run_clip(src, Path(args.output), start, args.duration, args.mode,
args.lang, args.model, args.style, args.no_subs, args.quality)
args.lang, args.model, args.style, args.no_subs, args.quality,
fade_in=args.fade_in, fade_out=args.fade_out)
if __name__ == "__main__":

View File

@ -213,6 +213,8 @@ def main():
ap.add_argument("--target-height", type=int, default=1920)
ap.add_argument("--start", type=float, default=None, help="Začetek (s)")
ap.add_argument("--duration", type=float, default=None, help="Trajanje (s)")
ap.add_argument("--fade-in", type=float, default=0.0, help="Audio fade in (s)")
ap.add_argument("--fade-out", type=float, default=0.0, help="Audio fade out (s)")
ap.add_argument("--quality", default="medium", choices=["fast", "medium", "high"])
args = ap.parse_args()
@ -268,6 +270,16 @@ def main():
preset = {"fast": "veryfast", "medium": "medium", "high": "slow"}[args.quality]
crf = {"fast": "26", "medium": "21", "high": "18"}[args.quality]
# Audio fade filter (afade)
audio_filter = []
if args.fade_in > 0:
audio_filter.append(f"afade=t=in:st=0:d={args.fade_in}")
if args.fade_out > 0:
clip_dur = info["duration"]
fade_start = max(0, clip_dur - args.fade_out)
audio_filter.append(f"afade=t=out:st={fade_start}:d={args.fade_out}")
audio_filter_str = ",".join(audio_filter) if audio_filter else None
if args.mode == "blur":
# blur uporablja filter_complex
cmd = [
@ -275,18 +287,20 @@ def main():
"-filter_complex", vfilter,
"-c:v", "libx264", "-preset", preset, "-crf", crf,
"-c:a", "aac", "-b:a", "128k",
"-movflags", "+faststart",
str(dst),
]
if audio_filter_str:
cmd += ["-af", audio_filter_str]
cmd += ["-movflags", "+faststart", str(dst)]
else:
cmd = [
"ffmpeg", "-y", "-i", str(work_input),
"-vf", vfilter,
"-c:v", "libx264", "-preset", preset, "-crf", crf,
"-c:a", "aac", "-b:a", "128k",
"-movflags", "+faststart",
str(dst),
]
if audio_filter_str:
cmd += ["-af", audio_filter_str]
cmd += ["-movflags", "+faststart", str(dst)]
print(f"🎬 Render ({args.mode})...")
result = subprocess.run(cmd, capture_output=True, text=True)

View File

@ -216,12 +216,16 @@
<div>
<label>Jezik podnapisov</label>
<select id="lang">
<option value="">Auto detect</option>
<option value="">Auto detect (Whisper)</option>
<option value="sl">Slovenščina</option>
<option value="de">Deutsch</option>
<option value="en">English</option>
<option value="hr">Hrvatski</option>
<option value="bs">Bosanski</option>
<option value="sr">Српски</option>
<option value="it">Italiano</option>
<option value="es">Español</option>
<option value="fr">Français</option>
</select>
</div>
<div>
@ -238,8 +242,13 @@
<label class="toggle" style="margin-top: 16px;">
<input type="checkbox" id="auto-chorus" checked>
Avto-detekcija refrena (priporočeno za glasbo)
Pametna izbira odseka (Whisper + energy → najde refren)
</label>
<div style="font-size: 12px; color: var(--text-dim); margin-top: 4px; margin-left: 26px;">
Sistem analizira celoten video, najde refren ter pre-chorus build-up.
Lahko traja malo dlje (do 1.5×) če to bolje prikazuje pesem.
Audio fade in/out je avtomatsko dodan.
</div>
<div id="manual-times" class="row hidden">
<div>
@ -353,13 +362,18 @@
// ─── Settings collector ─────────────────────────
function collectSettings() {
const auto = $("#auto-chorus").checked;
const duration = parseFloat($("#duration").value) || 30;
return {
mode: $("#mode").value,
lang: $("#lang").value || null,
whisper_model: $("#model").value,
auto_chorus: $("#auto-chorus").checked,
start: !$("#auto-chorus").checked && $("#start").value ? parseTimestamp($("#start").value) : null,
duration: parseFloat($("#duration").value) || 30,
auto_chorus: auto,
start: !auto && $("#start").value ? parseTimestamp($("#start").value) : null,
duration: duration,
// Smart selection: max do 1.5x ciljno trajanje, min 0.7x
max_duration: auto ? Math.round(duration * 1.5) : duration,
min_duration: auto ? Math.round(duration * 0.7) : duration,
subtitle_style: $("#subtitle-style").value,
quality: $("#quality").value,
no_subs: $("#no-subs").checked,