fb8b390740
- New 2-of-3 detection system (chat + audio + color) - GPU support (PyTorch ROCm/CUDA ready) - Draft mode (360p) for fast testing - HD mode (1080p) for final render - Auto download video + chat - CLI pipeline script - Documentation in Spanish
96 lines
2.7 KiB
Python
96 lines
2.7 KiB
Python
import sys
|
|
import re
|
|
import json
|
|
import logging
|
|
import numpy as np
|
|
from datetime import datetime
|
|
|
|
logging.basicConfig(level=logging.INFO)
|
|
logger = logging.getLogger(__name__)
|
|
|
|
def detect_highlights(chat_file, min_duration=10, threshold=2.0):
|
|
"""Detecta highlights por chat saturado"""
|
|
|
|
logger.info("Analizando picos de chat...")
|
|
|
|
# Leer mensajes
|
|
messages = []
|
|
with open(chat_file, 'r', encoding='utf-8') as f:
|
|
for line in f:
|
|
match = re.match(r'\[(\d{4}-\d{2}-\d{2}T[\d:.]+Z?)\]', line)
|
|
if match:
|
|
timestamp_str = match.group(1).replace('Z', '+00:00')
|
|
try:
|
|
timestamp = datetime.fromisoformat(timestamp_str)
|
|
messages.append((timestamp, line))
|
|
except:
|
|
pass
|
|
|
|
if not messages:
|
|
logger.error("No se encontraron mensajes")
|
|
return []
|
|
|
|
start_time = messages[0][0]
|
|
end_time = messages[-1][0]
|
|
duration = (end_time - start_time).total_seconds()
|
|
|
|
logger.info(f"Chat: {len(messages)} mensajes, duración: {duration:.1f}s")
|
|
|
|
# Agrupar por segundo
|
|
time_buckets = {}
|
|
for timestamp, _ in messages:
|
|
second = int((timestamp - start_time).total_seconds())
|
|
time_buckets[second] = time_buckets.get(second, 0) + 1
|
|
|
|
# Calcular estadísticas
|
|
counts = list(time_buckets.values())
|
|
mean_count = np.mean(counts)
|
|
std_count = np.std(counts)
|
|
|
|
logger.info(f"Stats: media={mean_count:.1f}, std={std_count:.1f}")
|
|
|
|
# Detectar picos
|
|
peak_seconds = []
|
|
for second, count in time_buckets.items():
|
|
if std_count > 0:
|
|
z_score = (count - mean_count) / std_count
|
|
if z_score > threshold:
|
|
peak_seconds.append(second)
|
|
|
|
logger.info(f"Picos encontrados: {len(peak_seconds)}")
|
|
|
|
# Unir segundos consecutivos
|
|
if not peak_seconds:
|
|
return []
|
|
|
|
intervals = []
|
|
start = peak_seconds[0]
|
|
prev = peak_seconds[0]
|
|
|
|
for second in peak_seconds[1:]:
|
|
if second - prev > 1:
|
|
if second - start >= min_duration:
|
|
intervals.append((start, prev))
|
|
start = second
|
|
prev = second
|
|
|
|
if prev - start >= min_duration:
|
|
intervals.append((start, prev))
|
|
|
|
return intervals
|
|
|
|
|
|
if __name__ == "__main__":
|
|
chat_file = "chat.txt"
|
|
|
|
highlights = detect_highlights(chat_file)
|
|
|
|
print(f"\nHighlights encontrados: {len(highlights)}")
|
|
for i, (start, end) in enumerate(highlights):
|
|
print(f" {i+1}. {start}s - {end}s (duración: {end-start}s)")
|
|
|
|
# Guardar JSON
|
|
with open("highlights.json", "w") as f:
|
|
json.dump(highlights, f)
|
|
print(f"\nGuardado en highlights.json")
|