Files
twitch-highlight-detector/two_game_extractor.py
renato97 00180d0b1c Sistema completo de detección de highlights con VLM y análisis de gameplay
- Implementación de detector híbrido (Whisper + Chat + Audio + VLM)
- Sistema de detección de gameplay real vs hablando
- Scene detection con FFmpeg
- Soporte para RTX 3050 y RX 6800 XT
- Guía completa en 6800xt.md para próxima IA
- Scripts de filtrado visual y análisis de contexto
- Pipeline automatizado de generación de videos
2026-02-19 17:38:14 +00:00

209 lines
6.3 KiB
Python

#!/usr/bin/env python3
"""
TWO-GAME HIGHLIGHT EXTRACTOR
Extrae múltiples highlights de los 2 juegos: Diana y Mundo
"""
import json
import re
def extract_game_highlights():
"""Extrae highlights de Diana y Mundo por separado."""
print("=" * 60)
print("TWO-GAME HIGHLIGHT EXTRACTOR")
print("=" * 60)
with open("transcripcion_rage.json", "r") as f:
trans = json.load(f)
# Identificar segmentos por campeón
diana_segments = []
mundo_segments = []
for seg in trans["segments"]:
text = seg["text"].lower()
if "diana" in text:
diana_segments.append(seg)
elif "mundo" in text or "warwick" in text:
mundo_segments.append(seg)
print(f"Segmentos mencionando Diana: {len(diana_segments)}")
print(f"Segmentos mencionando Mundo/Warwick: {len(mundo_segments)}")
# Encontrar rangos de tiempo
if diana_segments:
diana_start = min(s["start"] for s in diana_segments)
diana_end = max(s["end"] for s in diana_segments)
print(f"\nJuego Diana: {diana_start / 60:.0f}m - {diana_end / 60:.0f}m")
else:
diana_start, diana_end = 0, 0
if mundo_segments:
mundo_start = min(s["start"] for s in mundo_segments)
mundo_end = max(s["end"] for s in mundo_segments)
print(f"Juego Mundo: {mundo_start / 60:.0f}m - {mundo_end / 60:.0f}m")
else:
mundo_start, mundo_end = 0, 0
# Buscar momentos épicos en cada juego
def find_moments_in_range(segments, game_name, start_time, end_time, min_score=6):
"""Busca momentos épicos en un rango específico."""
moments = []
rage_patterns = [
(r"\bputa\w*", 10, "EXTREME"),
(r"\bme mataron\b", 12, "DEATH"),
(r"\bme mori\b", 12, "DEATH"),
(r"\bmierda\b", 8, "RAGE"),
(r"\bjoder\b", 8, "RAGE"),
(r"\bretrasad\w*", 9, "INSULT"),
(r"\bimbecil\b", 9, "INSULT"),
(r"\bla cague\b", 8, "FAIL"),
(r"\bnooo+\b", 6, "FRUSTRATION"),
]
for seg in segments:
if seg["start"] < start_time or seg["end"] > end_time:
continue
text = seg["text"].lower()
score = 0
reasons = []
for pattern, points, reason in rage_patterns:
if re.search(pattern, text, re.IGNORECASE):
score += points
if reason not in reasons:
reasons.append(reason)
if score >= min_score:
moments.append(
{
"start": seg["start"],
"end": seg["end"],
"score": score,
"text": seg["text"][:70],
"reasons": reasons,
"game": game_name,
}
)
return moments
# Buscar en Diana
print(f"\n=== JUEGO DIANA ===")
diana_moments = find_moments_in_range(
trans["segments"],
"Diana",
max(455, diana_start - 300), # 5 min antes de primera mención
diana_end + 300, # 5 min después
min_score=5,
)
print(f"Momentos encontrados: {len(diana_moments)}")
# Buscar en Mundo
print(f"\n=== JUEGO MUNDO ===")
mundo_moments = find_moments_in_range(
trans["segments"],
"Mundo",
max(455, mundo_start - 300),
mundo_end + 300,
min_score=5,
)
print(f"Momentos encontrados: {len(mundo_moments)}")
# Ordenar por score
diana_moments.sort(key=lambda x: -x["score"])
mundo_moments.sort(key=lambda x: -x["score"])
# Tomar top 6 de cada juego
best_diana = diana_moments[:6]
best_mundo = mundo_moments[:6]
print(f"\nMejores momentos Diana: {len(best_diana)}")
for i, m in enumerate(best_diana, 1):
mins = int(m["start"]) // 60
secs = int(m["start"]) % 60
print(
f" {i}. {mins:02d}:{secs:02d} [Score: {m['score']}] {'/'.join(m['reasons'])}"
)
print(f"\nMejores momentos Mundo: {len(best_mundo)}")
for i, m in enumerate(best_mundo, 1):
mins = int(m["start"]) // 60
secs = int(m["start"]) % 60
print(
f" {i}. {mins:02d}:{secs:02d} [Score: {m['score']}] {'/'.join(m['reasons'])}"
)
# Combinar y crear clips
all_moments = best_diana + best_mundo
# Crear clips extendidos
clips = []
for m in all_moments:
start = max(455, int(m["start"]) - 10)
end = min(8237, int(m["end"]) + 15)
if end - start >= 15:
clips.append(
{
"start": start,
"end": end,
"score": m["score"],
"reasons": m["reasons"],
"game": m["game"],
}
)
# Eliminar solapamientos
clips.sort(key=lambda x: x["start"])
filtered = []
for clip in clips:
if not filtered:
filtered.append(clip)
else:
last = filtered[-1]
if clip["start"] <= last["end"] + 5:
# Fusionar
last["end"] = max(last["end"], clip["end"])
last["score"] = max(last["score"], clip["score"])
last["reasons"] = list(set(last["reasons"] + clip["reasons"]))
if clip["game"] not in last["game"]:
last["game"] += "/" + clip["game"]
else:
filtered.append(clip)
# Ordenar por tiempo
filtered.sort(key=lambda x: x["start"])
print(f"\n{'=' * 60}")
print(f"TOTAL: {len(filtered)} clips")
total_dur = sum(c["end"] - c["start"] for c in filtered)
print(f"Duración: {total_dur}s ({total_dur // 60}m {total_dur % 60}s)")
print(f"{'=' * 60}")
print(f"\nTimeline final:")
for i, c in enumerate(filtered, 1):
mins, secs = divmod(c["start"], 60)
dur = c["end"] - c["start"]
print(
f"{i:2d}. {mins:02d}:{secs:02d} - {dur}s [{c['game']}] {'/'.join(c['reasons'])}"
)
return filtered
if __name__ == "__main__":
clips = extract_game_highlights()
# Guardar
highlights = [[c["start"], c["end"]] for c in clips]
with open("highlights_two_games.json", "w") as f:
json.dump(highlights, f)
print(f"\nGuardado en highlights_two_games.json")