222 lines
6.5 KiB
Python
222 lines
6.5 KiB
Python
#!/usr/bin/env python3
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"""
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场景拆分器 - 将口播文本拆分成细镜头
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基于时间戳对齐图片和字幕
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"""
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import json
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import re
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import argparse
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from pathlib import Path
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from typing import List, Dict
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def split_by_sentence_timestamps(timestamps: List[Dict]) -> List[Dict]:
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"""
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直接使用 TTS 的 SentenceBoundary 时间戳作为镜头分割
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Args:
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timestamps: TTS 输出的时间戳（包含 sentence 类型）
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Returns:
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每个镜头的信息：text, start, end, duration
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"""
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shots = []
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for ts in timestamps:
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if ts.get("type") == "sentence":
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shots.append({
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"text": ts["text"],
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"start": ts["start"],
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"end": ts["end"],
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"duration": round(ts["end"] - ts["start"], 2)
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})
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if not shots and timestamps:
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total_start = timestamps[0]["start"]
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total_end = timestamps[-1]["end"]
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full_text = "".join(ts["text"] for ts in timestamps)
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shots.append({
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"text": full_text,
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"start": total_start,
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"end": total_end,
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"duration": round(total_end - total_start, 2)
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})
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return shots
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def split_long_shots(shots: List[Dict], max_duration: float = 6.0) -> List[Dict]:
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"""
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将过长的镜头按标点符号进一步拆分
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Args:
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shots: 镜头列表
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max_duration: 最大镜头时长
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Returns:
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拆分后的镜头列表
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"""
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result = []
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for shot in shots:
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if shot["duration"] <= max_duration:
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result.append(shot)
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continue
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text = shot["text"]
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splits = re.split(r'([，。！？,!?])', text)
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sub_texts = []
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current = ""
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for i, part in enumerate(splits):
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current += part
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if i % 2 == 1 and current.strip():
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sub_texts.append(current.strip())
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current = ""
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if current.strip():
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sub_texts.append(current.strip())
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if len(sub_texts) <= 1:
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result.append(shot)
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continue
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total_chars = sum(len(t) for t in sub_texts)
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current_time = shot["start"]
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for sub_text in sub_texts:
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ratio = len(sub_text) / total_chars
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sub_duration = shot["duration"] * ratio
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result.append({
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"text": sub_text,
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"start": round(current_time, 2),
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"end": round(current_time + sub_duration, 2),
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"duration": round(sub_duration, 2)
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})
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current_time += sub_duration
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return result
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def merge_short_shots(shots: List[Dict], min_duration: float = 2.5) -> List[Dict]:
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"""合并过短的镜头"""
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if not shots:
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return shots
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merged = []
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current = shots[0].copy()
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for shot in shots[1:]:
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if current["duration"] < min_duration:
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current["text"] += shot["text"]
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current["end"] = shot["end"]
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current["duration"] = round(current["end"] - current["start"], 2)
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else:
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merged.append(current)
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current = shot.copy()
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merged.append(current)
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return merged
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def generate_shot_prompts(shots: List[Dict], style: str, context: str = "") -> List[Dict]:
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"""
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为每个镜头生成图片提示词
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Args:
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shots: 镜头列表
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style: 画风描述
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context: 上下文（如角色描述）
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Returns:
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带有图片提示词的镜头列表
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"""
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for i, shot in enumerate(shots):
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shot["image_prompt"] = f"{style}，{context}，画面：{shot['text']}。禁止出现任何文字"
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shot["index"] = i + 1
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return shots
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def generate_srt(shots: List[Dict], output_path: str):
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"""生成 SRT 字幕文件"""
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def format_time(seconds: float) -> str:
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hours = int(seconds // 3600)
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minutes = int((seconds % 3600) // 60)
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secs = int(seconds % 60)
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millis = int((seconds % 1) * 1000)
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return f"{hours:02d}:{minutes:02d}:{secs:02d},{millis:03d}"
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with open(output_path, "w", encoding="utf-8") as f:
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for i, shot in enumerate(shots, 1):
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f.write(f"{i}\n")
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f.write(f"{format_time(shot['start'])} --> {format_time(shot['end'])}\n")
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f.write(f"{shot['text']}\n\n")
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print(f" ✓ 字幕: {output_path}")
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def process_scene(text: str, timestamps_path: str, style: str, context: str = "", output_dir: str = ".") -> Dict:
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"""
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处理单个场景，输出镜头配置
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Args:
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text: 场景口播文本
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timestamps_path: TTS 时间戳 JSON 文件
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style: 画风
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context: 上下文
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output_dir: 输出目录
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Returns:
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场景配置字典
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"""
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with open(timestamps_path, "r", encoding="utf-8") as f:
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timestamps = json.load(f)
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shots = split_by_sentence_timestamps(timestamps)
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shots = split_long_shots(shots, max_duration=6.0)
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shots = merge_short_shots(shots, min_duration=2.5)
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shots = generate_shot_prompts(shots, style, context)
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output_path = Path(output_dir)
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output_path.mkdir(parents=True, exist_ok=True)
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srt_path = output_path / "subtitles.srt"
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generate_srt(shots, str(srt_path))
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config_path = output_path / "shots.json"
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with open(config_path, "w", encoding="utf-8") as f:
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json.dump(shots, f, ensure_ascii=False, indent=2)
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print(f" ✓ 镜头配置: {config_path}")
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return {"shots": shots, "srt_path": str(srt_path)}
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def main():
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parser = argparse.ArgumentParser(description='场景拆分器')
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parser.add_argument('--text', type=str, required=True, help='口播文本')
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parser.add_argument('--timestamps', type=str, required=True, help='TTS时间戳JSON文件')
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parser.add_argument('--style', type=str, default='', help='画风描述')
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parser.add_argument('--context', type=str, default='', help='上下文（角色等）')
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parser.add_argument('--output-dir', type=str, default='.', help='输出目录')
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args = parser.parse_args()
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result = process_scene(
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text=args.text,
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timestamps_path=args.timestamps,
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style=args.style,
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context=args.context,
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output_dir=args.output_dir
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)
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print(f"\n拆分完成，共 {len(result['shots'])} 个镜头：")
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for shot in result["shots"]:
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print(f" [{shot['duration']:.1f}s] {shot['text']}")
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if __name__ == "__main__":
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main()
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