feat(worker): 参考视频风格分析模块 video_analyzer (#2051)
实现 v1.3 爆款视频参考风格分析 6 步管线： ① FFmpeg 抽关键帧（每 2s 一帧 + 场景切换帧） ② PySceneDetect ContentDetector(threshold=27) 镜头分割 ③ OpenCV Farneback 光流运镜检测（推/拉/摇/移/zoom/static + 强度） ④ librosa BPM 分析（>110 fast_cut / 80-110 medium / <80 slow_cinematic） ⑤ OSS 上传关键帧 + 豆包 VLM 色调/构图/光线分析 ⑥ 豆包 LLM 整合 style_guide JSON（失败走规则合成降级） 新增渲染参数映射： - 运镜 → ken_burns 参数（push_in→zoom_in_slow、tilt_up→pan+zoom 等 11 种） - 转场 → TransitionEngine xfade 名称（hard_cut→cut/dissolve/wipeleft 等） - 色调 → FFmpeg eq + colorchannelmixer 预设（5 套：warm_vintage/cool_fresh/high_contrast/soft_pastel/dramatic_cinematic） - BPM → BGM 选曲 BPM±5 提示 - build_render_params_for_clip() 按镜头索引聚合可直接喂 URS 的参数 降级链： - FFmpeg 抽帧失败 → VLM 路径；OpenCV 不可用 → static/low；librosa 不可用 → VLM 估计； - LLM/VLM 不可用 → 规则合成 style_guide；任意子步骤异常不抛，best-effort 返回最小可用 style_guide。 资源约束：参考视频 ≤60s/≤100MB，总超时 60s，临时帧 try/finally 清理。 依赖新增：scenedetect==0.6.4、librosa==0.10.2.post1、soundfile==0.12.1（requirements-worker.txt）。 orchestrator 改为从 apps.worker.viral_video.video_analyzer 导入 analyze_video_style， 传入 style_strength 透传 light/medium/strict 三档。 单测 48 条覆盖：映射函数/光流运镜判定/BPM 档位/规则合成/聚合输出/降级/临时文件清理。
This commit is contained in:
xiaoxia
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"""爆款视频 Worker 侧模块（#2039/#2040/#2051）。
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video_analyzer（#2051）：参考视频风格分析 6 步管线，输出 style_guide + clips 渲染参数映射。
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#2040 的 prompt 系统（prompts/prompt_store/llm_runner）由 #2040 分支提供，本文件不依赖它。
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"""
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from __future__ import annotations
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from apps.worker.viral_video.video_analyzer import (
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DEFAULT_ANALYSIS_TIMEOUT,
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MAX_REFERENCE_DURATION_SEC,
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MAX_REFERENCE_SIZE_MB,
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STYLE_GUIDE_SCHEMA,
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analyze_video_style,
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build_render_params_for_clip,
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map_bgm_bpm,
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map_camera_to_ken_burns,
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map_color_to_video_filter,
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map_transition_to_xfade,
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)
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__all__ = [
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"DEFAULT_ANALYSIS_TIMEOUT",
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"MAX_REFERENCE_DURATION_SEC",
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"MAX_REFERENCE_SIZE_MB",
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"STYLE_GUIDE_SCHEMA",
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"analyze_video_style",
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"build_render_params_for_clip",
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"map_bgm_bpm",
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"map_camera_to_ken_burns",
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"map_color_to_video_filter",
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"map_transition_to_xfade",
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]
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"""参考爆款视频风格分析模块（#2051，v1.3）。
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管线（analyze_video_style）：
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① FFmpeg 抽关键帧（每 2s 1 帧 + 场景切换帧）到临时目录
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② PySceneDetect ContentDetector(threshold=27) 镜头分割
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③ OpenCV Farneback 光流运镜检测（推/拉/摇/移/zoom/static + 强度）
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④ librosa BPM 分析（>110 fast_cut / 80-110 medium / <80 slow_cinematic）
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⑤ OSS 上传关键帧 + 豆包 VLM 分析色调/构图/光线
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⑥ 豆包 LLM 整合输出完整 style_guide JSON
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降级链：
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- FFmpeg 抽帧失败 → VLM 均匀采样 3 帧（跳步骤 ②③④ 的精确值，给粗粒度估计）
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- OpenCV 光流失败 → BPM+VLM 估算运镜
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- librosa BPM 失败 → VLM 判断节奏
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- 任何子步骤异常不阻断整体，以 best-effort 填充 style_guide。
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资源约束：
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- 参考视频 ≤60s 且 ≤100MB；分析总超时 ≤60s；临时帧 try/finally 清理。
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"""
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from __future__ import annotations
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import json
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import logging
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import math
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import shutil
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import subprocess
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import tempfile
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import uuid
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Any, Optional
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logger = logging.getLogger(__name__)
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# ── 资源约束 ─────────────────────────────────────────────────────────────
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MAX_REFERENCE_DURATION_SEC = 60
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MAX_REFERENCE_SIZE_MB = 100
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DEFAULT_ANALYSIS_TIMEOUT = 60 # 秒
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KEYFRAME_INTERVAL_SEC = 2
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SCENEDETECT_THRESHOLD = 27
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VLM_SAMPLE_FRAMES = 5 # 上传给 VLM 的关键帧上限
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FARNEBACK_PARAMS = dict(pyr_scale=0.5, levels=3, winsize=15, iterations=3, poly_n=5, poly_sigma=1.2, flags=0)
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# ── style_guide 输出 schema（最小校验参考，不强制 jsonschema 依赖） ───────
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STYLE_GUIDE_SCHEMA: dict[str, Any] = {
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"style_name": str,
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"avg_shot_duration": float,
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"shot_count": int,
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"pace": str, # fast_cut | medium | slow_cinematic
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"bpm": int,
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"camera_movements": list,
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"transitions": list,
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"color_palette": list,
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"color_tone": str, # warm | cool | high_sat | low_sat | vintage | fresh | dramatic | bright
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"color_filter": str, # none | warm_vintage | cool_fresh | high_contrast | soft_pastel | dramatic_cinematic
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"composition": dict,
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"lighting": str,
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"mood": str,
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"visual_keywords": list,
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"ken_burns_params": dict,
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"transition_map": dict,
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"video_filter_eq_params": dict,
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"ken_burns_direction_hint": str,
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}
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# ── 数据结构 ─────────────────────────────────────────────────────────────
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@dataclass
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class ShotBoundary:
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"""一段镜头（帧号区间）。"""
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index: int
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start_sec: float
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end_sec: float
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movement: str = (
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"static" # push_in | pull_out | pan_left | pan_right | tilt_up | tilt_down | static | zoom_in | zoom_out
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)
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intensity: str = "low" # low | medium | high
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transition: str = "hard_cut" # 到下一个镜头的转场
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@dataclass
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class AnalysisArtifacts:
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"""中间产物（降级路径用）。"""
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frames_dir: Path
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frame_paths: list[Path] = field(default_factory=list)
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shots: list[ShotBoundary] = field(default_factory=list)
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bpm: int = 0
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vlm_descriptions: list[str] = field(default_factory=list)
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def _strip_code_fence(text: str) -> str:
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"""移除 markdown 代码块围栏，返回纯文本。"""
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t = text.strip()
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for fence in ("```json", "```JSON", "```"):
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if t.startswith(fence):
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t = t[len(fence) :].lstrip()
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if t.endswith("```"):
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t = t[:-3].rstrip()
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return t
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# ── FFmpeg / ffprobe ─────────────────────────────────────────────────────
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def _ffmpeg_bin() -> str:
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return shutil.which("ffmpeg") or "ffmpeg"
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def _ffprobe_bin() -> str:
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return shutil.which("ffprobe") or "ffprobe"
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def _probe_duration(video_path: str | Path) -> float:
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"""用 ffprobe 取视频时长（秒）；失败返回 0。"""
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try:
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out = subprocess.check_output(
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[
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_ffprobe_bin(),
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"-v",
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"error",
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"-show_entries",
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"format=duration",
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"-of",
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"default=noprint_wrappers=1:nokey=1",
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str(video_path),
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],
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stderr=subprocess.DEVNULL,
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timeout=10,
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text=True,
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)
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return float(out.strip() or 0)
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except Exception as exc: # noqa: BLE001
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logger.warning("ffprobe 时长探测失败 %s: %s", video_path, exc)
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return 0.0
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def _extract_keyframes(video_path: Path, out_dir: Path, interval: int = KEYFRAME_INTERVAL_SEC) -> list[Path]:
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"""按固定间隔抽帧；同时检测场景切换帧（select='gt(scene,...)'）。"""
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out_dir.mkdir(parents=True, exist_ok=True)
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# 固定间隔
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fixed_tpl = str(out_dir / "f_%04d.jpg")
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cmd_fixed = [
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_ffmpeg_bin(),
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"-y",
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"-i",
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str(video_path),
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"-vf",
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f"fps=1/{interval}",
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"-q:v",
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"3",
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fixed_tpl,
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]
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subprocess.run(
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cmd_fixed, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, timeout=DEFAULT_ANALYSIS_TIMEOUT, check=False
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)
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# 场景切换帧（独立命名，scene_ 前缀）
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scene_tpl = str(out_dir / "scene_%04d.jpg")
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cmd_scene = [
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_ffmpeg_bin(),
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"-y",
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"-i",
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str(video_path),
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"-vf",
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"select='gt(scene,0.35)',showinfo",
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"-vsync",
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"vfr",
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"-q:v",
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"3",
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scene_tpl,
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]
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subprocess.run(
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cmd_scene, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, timeout=DEFAULT_ANALYSIS_TIMEOUT, check=False
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)
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frames = sorted(out_dir.glob("f_*.jpg")) + sorted(out_dir.glob("scene_*.jpg"))
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# 去重（时间点相近时 scene 帧和 fixed 帧可能重复，简单按文件名存在性保留）
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seen: set[str] = set()
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unique: list[Path] = []
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for p in frames:
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if p.name not in seen:
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seen.add(p.name)
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unique.append(p)
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return unique
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# ── ② 镜头分割（PySceneDetect，失败降级） ────────────────────────────────
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def _detect_shots(video_path: Path, frames_dir: Path) -> list[ShotBoundary]:
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try:
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from scenedetect import ContentDetector, SceneManager, open_video
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video = open_video(str(video_path))
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sm = SceneManager()
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sm.add_detector(ContentDetector(threshold=SCENEDETECT_THRESHOLD))
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sm.detect_scenes(video)
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scenes = sm.get_scene_list()
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shots: list[ShotBoundary] = []
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for i, (start, end) in enumerate(scenes):
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shots.append(
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ShotBoundary(
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index=i,
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start_sec=start.get_seconds(),
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end_sec=end.get_seconds(),
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)
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)
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if shots:
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return shots
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except Exception as exc: # noqa: BLE001
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logger.warning("PySceneDetect 镜头分割失败，使用均匀分段降级: %s", exc)
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# 降级：按固定间隔每 3 秒一镜头
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duration = _probe_duration(video_path) or 15.0
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dur = max(3.0, min(duration, float(MAX_REFERENCE_DURATION_SEC)))
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shots = []
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seg = 3.0
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i = 0
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t = 0.0
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while t < dur - 0.1:
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shots.append(ShotBoundary(index=i, start_sec=t, end_sec=min(t + seg, dur)))
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i += 1
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t += seg
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return shots
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# ── ③ 运镜检测（OpenCV Farneback 光流） ──────────────────────────────────
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# 光流向量到运镜映射
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_FLOW_THRESHOLD_LOW = 0.3
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_FLOW_THRESHOLD_HIGH = 1.2
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def _detect_camera_movement(flow, w: int, h: int) -> tuple[str, str]:
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"""从平均光流向量判断运镜类型和强度。"""
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import numpy as np # noqa: PLC0415 - numpy 已在 requirements 中
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fx = float(np.median(flow[..., 0]))
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fy = float(np.median(flow[..., 1]))
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trans_mag = math.hypot(fx, fy)
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# 发散/收敛判断 zoom：比较边缘流沿径向外指的平均分量（稳健版）
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cx, cy = w / 2.0, h / 2.0
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ys, xs = np.mgrid[0:h, 0:w].astype(np.float32)
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rx, ry = (xs - cx) / max(cx, 1.0), (ys - cy) / max(cy, 1.0)
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rmag = np.sqrt(rx * rx + ry * ry) + 1e-6
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# 径向分量：(fx*rx + fy*ry)/rmag —— 正=外扩(zoom in)，负=内收(zoom out)
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radial = (flow[..., 0] * rx + flow[..., 1] * ry) / rmag
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# 只看边缘带（|r|>0.5），且减去平移贡献：径向减去平均平移投影
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edge_mask = (rmag > 0.5).astype(np.float32)
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if edge_mask.sum() > 10:
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trans_radial = (fx * rx + fy * ry) / rmag
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zoom_signal = float(np.mean((radial - trans_radial)[edge_mask > 0]))
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else:
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zoom_signal = 0.0
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abs_fx, abs_fy = abs(fx), abs(fy)
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# 综合运动幅度：平移 + |zoom| 投影到像素
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total_mag = trans_mag + abs(zoom_signal) * max(w, h) * 0.3
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if total_mag < _FLOW_THRESHOLD_LOW:
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return "static", "low"
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intensity = "high" if total_mag > _FLOW_THRESHOLD_HIGH else "medium"
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# zoom 判定需要边缘径向分量明显大过整体平移
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zoom_dominant = abs(zoom_signal) > 0.6 and abs(zoom_signal) * max(w, h) * 0.3 > trans_mag * 1.2
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if zoom_dominant and zoom_signal > 0:
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return "zoom_in", intensity
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if zoom_dominant and zoom_signal < 0:
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return "zoom_out", intensity
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# 平摇/tilt
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if abs_fx > abs_fy * 1.5:
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return "pan_right" if fx > 0 else "pan_left", intensity
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if abs_fy > abs_fx * 1.5:
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return "tilt_down" if fy > 0 else "tilt_up", intensity
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# 轨道/跟拍：以主轴为主
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if abs_fx >= abs_fy:
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return "pan_right" if fx > 0 else "pan_left", intensity
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return "tilt_down" if fy > 0 else "tilt_up", intensity
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def _analyze_movements(video_path: Path, shots: list[ShotBoundary]) -> None:
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"""对每个 shot 的首尾帧算光流，填充 movement/intensity。失败时静默降级为 static/low。"""
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try:
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import cv2 # noqa: PLC0415 - opencv-python-headless 已在 worker requirements 中
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except Exception as exc: # noqa: BLE001
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logger.warning("OpenCV 不可用，运镜检测降级为 static/low: %s", exc)
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return
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try:
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cap = cv2.VideoCapture(str(video_path))
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for shot in shots:
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mid_t = (shot.start_sec + shot.end_sec) / 2.0
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dt = max(0.2, min(0.5, (shot.end_sec - shot.start_sec) / 4.0))
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cap.set(cv2.CAP_PROP_POS_MSEC, max(0.0, (mid_t - dt)) * 1000)
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ok1, f1 = cap.read()
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cap.set(cv2.CAP_PROP_POS_MSEC, min(mid_t + dt, shot.end_sec - 0.05) * 1000)
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ok2, f2 = cap.read()
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if not (ok1 and ok2):
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continue
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g1 = cv2.cvtColor(f1, cv2.COLOR_BGR2GRAY)
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g2 = cv2.cvtColor(f2, cv2.COLOR_BGR2GRAY)
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h, w = g1.shape
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# 降采样加速
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scale = 360.0 / h if h > 360 else 1.0
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if scale < 1.0:
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g1 = cv2.resize(g1, (int(w * scale), int(h * scale)))
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g2 = cv2.resize(g2, (int(w * scale), int(h * scale)))
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flow = cv2.calcOpticalFlowFarneback(g1, g2, None, **FARNEBACK_PARAMS)
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move, inten = _detect_camera_movement(flow, g1.shape[1], g1.shape[0])
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shot.movement = move
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shot.intensity = inten
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||||
cap.release()
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except Exception as exc: # noqa: BLE001
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||||
logger.warning("运镜检测异常，已降级: %s", exc)
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||||
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||||
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||||
# ── ④ librosa BPM ────────────────────────────────────────────────────────
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||||
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||||
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||||
def _detect_bpm(video_path: Path) -> int:
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"""提取音轨并估算 BPM；失败返回 0。"""
|
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tmp_wav: Optional[Path] = None
|
||||
try:
|
||||
import librosa # noqa: PLC0415
|
||||
|
||||
tmp_wav = Path(tempfile.mkstemp(suffix=".wav")[1])
|
||||
# ffmpeg 抽 22050Hz 单声道 wav
|
||||
subprocess.run(
|
||||
[_ffmpeg_bin(), "-y", "-i", str(video_path), "-vn", "-ac", "1", "-ar", "22050", "-f", "wav", str(tmp_wav)],
|
||||
stdout=subprocess.DEVNULL,
|
||||
stderr=subprocess.DEVNULL,
|
||||
timeout=20,
|
||||
check=False,
|
||||
)
|
||||
if not tmp_wav.exists() or tmp_wav.stat().st_size < 1024:
|
||||
return 0
|
||||
y, sr = librosa.load(str(tmp_wav), sr=22050, mono=True)
|
||||
if len(y) < sr * 2:
|
||||
return 0
|
||||
tempo, _ = librosa.beat.beat_track(y=y, sr=sr)
|
||||
try:
|
||||
bpm = int(round(float(tempo)))
|
||||
except Exception: # noqa: BLE001
|
||||
bpm = int(round(float(tempo[0]))) if len(tempo) else 0
|
||||
return max(40, min(bpm, 220))
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("librosa BPM 分析失败: %s", exc)
|
||||
return 0
|
||||
finally:
|
||||
if tmp_wav and tmp_wav.exists():
|
||||
try:
|
||||
tmp_wav.unlink()
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
|
||||
def _pace_from_bpm(bpm: int) -> str:
|
||||
if bpm >= 110:
|
||||
return "fast_cut"
|
||||
if bpm >= 80:
|
||||
return "medium"
|
||||
if bpm > 0:
|
||||
return "slow_cinematic"
|
||||
return "medium"
|
||||
|
||||
|
||||
# ── ⑤ VLM 帧分析 ─────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def _sample_frames(frame_paths: list[Path], shots: list[ShotBoundary], k: int = VLM_SAMPLE_FRAMES) -> list[Path]:
|
||||
"""从全量帧中均匀选 k 张代表性帧（优先场景帧）。"""
|
||||
if not frame_paths:
|
||||
return []
|
||||
scene_frames = sorted(p for p in frame_paths if p.name.startswith("scene_"))
|
||||
fixed_frames = sorted(p for p in frame_paths if p.name.startswith("f_"))
|
||||
picks: list[Path] = list(scene_frames[: max(1, k // 2)])
|
||||
remaining = k - len(picks)
|
||||
if remaining > 0 and fixed_frames:
|
||||
step = max(1, len(fixed_frames) // remaining)
|
||||
picks += fixed_frames[::step][:remaining]
|
||||
# 去重保持顺序
|
||||
seen: set[str] = set()
|
||||
uniq: list[Path] = []
|
||||
for p in picks:
|
||||
if p.name not in seen and p.exists():
|
||||
seen.add(p.name)
|
||||
uniq.append(p)
|
||||
return uniq[:k]
|
||||
|
||||
|
||||
def _upload_frames_to_oss(frame_paths: list[Path]) -> list[str]:
|
||||
"""把帧上传 OSS，返回公网 URL 列表。失败时降级为 data URI。"""
|
||||
urls: list[str] = []
|
||||
try:
|
||||
from video_processing.oss_helpers import upload_to_oss
|
||||
|
||||
for p in frame_paths:
|
||||
try:
|
||||
key = f"viral-video/analysis/{uuid.uuid4().hex}/{p.name}"
|
||||
url = upload_to_oss(p, key)
|
||||
if url:
|
||||
urls.append(url)
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("单帧 OSS 上传失败 %s: %s", p.name, exc)
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("OSS 上传模块不可用，降级为 base64 data URI: %s", exc)
|
||||
if len(urls) < len(frame_paths):
|
||||
# 降级：base64 data URI（小图，单张 ≤100KB 才走此路）
|
||||
import base64
|
||||
|
||||
for p in frame_paths[len(urls) :]:
|
||||
try:
|
||||
if p.stat().st_size > 120_000:
|
||||
continue
|
||||
b64 = base64.b64encode(p.read_bytes()).decode("ascii")
|
||||
urls.append(f"data:image/jpeg;base64,{b64}")
|
||||
except Exception: # noqa: BLE001
|
||||
continue
|
||||
return urls
|
||||
|
||||
|
||||
def _vlm_analyze_frames(image_urls: list[str]) -> dict[str, Any]:
|
||||
"""调豆包 VLM 分析色调/构图/光线/转场观感。"""
|
||||
if not image_urls:
|
||||
return {}
|
||||
try:
|
||||
from packages.shared.ai_client import get_doubao_client
|
||||
|
||||
client = get_doubao_client()
|
||||
if not client.is_available:
|
||||
raise RuntimeError("豆包客户端未配置")
|
||||
sys_prompt = (
|
||||
"你是资深短视频导演和调色师。根据用户给出的同一支短视频的多张关键帧，"
|
||||
"分析其视觉风格并严格输出 JSON（不要 markdown，不要解释）：\n"
|
||||
"{"
|
||||
'"color_palette": ["#主色1","#主色2","#主色3","#辅色","#点缀色"],'
|
||||
'"color_tone": "warm|cool|high_sat|low_sat|vintage|fresh|dramatic|bright",'
|
||||
'"color_filter": "none|warm_vintage|cool_fresh|high_contrast|soft_pastel|dramatic_cinematic",'
|
||||
'"lighting": "natural|studio|backlit|soft|dramatic|bright_even",'
|
||||
'"composition": {"closeup_ratio":0.0,"medium_ratio":0.0,"wide_ratio":0.0,'
|
||||
'"angle":"eye_level|low_angle|high_angle|dutch"},'
|
||||
'"mood": "整体情绪（1-4字）",'
|
||||
'"visual_keywords": ["3-5个视觉关键词"],'
|
||||
'"transitions_observed": ["hard_cut|cross_dissolve|zoom_whip|fade_black"],'
|
||||
'"pace_guess": "fast_cut|medium|slow_cinematic"'
|
||||
"}"
|
||||
)
|
||||
raw = client.vision_completion(
|
||||
messages=[
|
||||
{"role": "system", "content": sys_prompt},
|
||||
{"role": "user", "content": "请分析这支参考视频的风格。"},
|
||||
],
|
||||
images=image_urls,
|
||||
temperature=0.2,
|
||||
max_tokens=2048,
|
||||
)
|
||||
if not raw:
|
||||
return {}
|
||||
raw = _strip_code_fence(raw)
|
||||
# 容忍模型可能前后加文本
|
||||
i, j = raw.find("{"), raw.rfind("}")
|
||||
if i >= 0 and j > i:
|
||||
return json.loads(raw[i : j + 1])
|
||||
return {}
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("VLM 帧分析失败: %s", exc)
|
||||
return {}
|
||||
|
||||
|
||||
# ── ⑥ LLM 整合 style_guide ──────────────────────────────────────────────
|
||||
|
||||
|
||||
def _llm_synthesize(
|
||||
shots: list[ShotBoundary],
|
||||
bpm: int,
|
||||
vlm: dict[str, Any],
|
||||
style_strength: str,
|
||||
) -> dict[str, Any]:
|
||||
"""把结构化信号整合成 style_guide；LLM 不可用时走规则合成。"""
|
||||
payload = {
|
||||
"style_strength": style_strength,
|
||||
"shot_count": len(shots),
|
||||
"shots": [
|
||||
{
|
||||
"index": s.index,
|
||||
"start_sec": round(s.start_sec, 2),
|
||||
"end_sec": round(s.end_sec, 2),
|
||||
"movement": s.movement,
|
||||
"intensity": s.intensity,
|
||||
"transition": s.transition,
|
||||
}
|
||||
for s in shots
|
||||
],
|
||||
"bpm": bpm,
|
||||
"pace_guess": _pace_from_bpm(bpm),
|
||||
"vlm": vlm,
|
||||
}
|
||||
try:
|
||||
from packages.shared.ai_client import get_doubao_client
|
||||
|
||||
client = get_doubao_client()
|
||||
if not client.is_available:
|
||||
raise RuntimeError("豆包客户端未配置")
|
||||
sys_prompt = (
|
||||
"你是资深短视频导演。根据参考视频的结构化分析数据（镜头分割/运镜/BPM/关键帧VLM描述），"
|
||||
"整合输出一份 style_guide JSON，字段必须包含："
|
||||
"style_name,avg_shot_duration,shot_count,pace,bpm,camera_movements,transitions,"
|
||||
"color_palette,color_tone,color_filter,composition,lighting,mood,visual_keywords,"
|
||||
"ken_burns_direction_hint,ken_burns_params,transition_map,video_filter_eq_params。"
|
||||
"严格输出一个合法 JSON 对象，不要 markdown/解释。"
|
||||
)
|
||||
user_text = "分析数据：\n" + json.dumps(payload, ensure_ascii=False)
|
||||
raw = client.chat_completion(
|
||||
[{"role": "system", "content": sys_prompt}, {"role": "user", "content": user_text}],
|
||||
temperature=0.3,
|
||||
max_tokens=4096,
|
||||
)
|
||||
if raw:
|
||||
raw = _strip_code_fence(raw)
|
||||
i, j = raw.find("{"), raw.rfind("}")
|
||||
if i >= 0 and j > i:
|
||||
result = json.loads(raw[i : j + 1])
|
||||
if isinstance(result, dict) and result.get("style_name"):
|
||||
return result
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("LLM 合成 style_guide 失败，走规则降级: %s", exc)
|
||||
return _rule_based_style_guide(shots, bpm, vlm)
|
||||
|
||||
|
||||
def _rule_based_style_guide(shots: list[ShotBoundary], bpm: int, vlm: dict[str, Any]) -> dict[str, Any]:
|
||||
"""LLM 不可用时，用规则拼出可用 style_guide。"""
|
||||
durations = [s.end_sec - s.start_sec for s in shots] or [3.0]
|
||||
avg_dur = round(sum(durations) / len(durations), 2)
|
||||
pace = _pace_from_bpm(bpm)
|
||||
movements = []
|
||||
for s in shots:
|
||||
movements.append(
|
||||
{
|
||||
"shot_index": s.index + 1,
|
||||
"movement": s.movement,
|
||||
"intensity": s.intensity,
|
||||
"duration": round(s.end_sec - s.start_sec, 2),
|
||||
"subject_hint": _default_subject_hint(s.movement),
|
||||
}
|
||||
)
|
||||
transitions = []
|
||||
for i in range(len(shots) - 1):
|
||||
transitions.append({"between_shot": [i + 1, i + 2], "type": shots[i].transition})
|
||||
color_palette = vlm.get("color_palette") or ["#E0E0E0", "#333333", "#F5F5F5", "#888888", "#FF6B35"]
|
||||
color_tone = vlm.get("color_tone") or "bright"
|
||||
color_filter = vlm.get("color_filter") or "none"
|
||||
lighting = vlm.get("lighting") or "bright_even"
|
||||
composition = vlm.get("composition") or {
|
||||
"closeup_ratio": 0.4,
|
||||
"medium_ratio": 0.4,
|
||||
"wide_ratio": 0.2,
|
||||
"angle": "eye_level",
|
||||
}
|
||||
mood = vlm.get("mood") or "明快"
|
||||
vk = vlm.get("visual_keywords") or ["节奏明快", "清晰", "真实"]
|
||||
dominant = _dominant_movement(shots)
|
||||
default_kb = map_camera_to_ken_burns(dominant)
|
||||
# 每镜头独立 ken_burns 参数（key 为 shot_index 字符串）+ 默认值
|
||||
kb_params: dict[str, Any] = {"default": default_kb}
|
||||
for m in movements:
|
||||
kb_params[str(m["shot_index"])] = map_camera_to_ken_burns(m["movement"])
|
||||
trans_map = _build_transition_map(transitions)
|
||||
eq_params = map_color_to_video_filter(color_filter)
|
||||
direction_hint = {
|
||||
"push_in": "zoom_in_slow",
|
||||
"zoom_in": "zoom_in_medium",
|
||||
"pull_out": "zoom_out_slow",
|
||||
"zoom_out": "zoom_out_medium",
|
||||
"pan_left": "pan_left_slow",
|
||||
"pan_right": "pan_right_slow",
|
||||
"tilt_up": "diagonal_push",
|
||||
"tilt_down": "diagonal_push",
|
||||
"track_left": "pan_left_slow",
|
||||
"track_right": "pan_right_slow",
|
||||
"static": "static",
|
||||
}.get(dominant, "static")
|
||||
return {
|
||||
"style_name": f"{pace}节奏-{color_tone}色调",
|
||||
"avg_shot_duration": avg_dur,
|
||||
"shot_count": len(shots),
|
||||
"pace": pace,
|
||||
"bpm": bpm or (120 if pace == "fast_cut" else 90 if pace == "medium" else 70),
|
||||
"camera_movements": movements,
|
||||
"transitions": transitions,
|
||||
"color_palette": color_palette,
|
||||
"color_tone": color_tone,
|
||||
"color_filter": color_filter,
|
||||
"composition": composition,
|
||||
"lighting": lighting,
|
||||
"mood": mood,
|
||||
"visual_keywords": vk,
|
||||
"ken_burns_direction_hint": direction_hint,
|
||||
"ken_burns_params": kb_params,
|
||||
"transition_map": trans_map,
|
||||
"video_filter_eq_params": eq_params,
|
||||
}
|
||||
|
||||
|
||||
def _default_subject_hint(movement: str) -> str:
|
||||
return {
|
||||
"push_in": "产品特写或细节展示",
|
||||
"pull_out": "从细节拉到全景环境",
|
||||
"zoom_in": "产品细节放大",
|
||||
"zoom_out": "全景交代",
|
||||
"pan_left": "横向展示环境/产品线",
|
||||
"pan_right": "横向展示环境/产品线",
|
||||
"tilt_up": "从细节抬到整体/人物表情",
|
||||
"tilt_down": "从整体俯冲到产品细节",
|
||||
"track_left": "跟拍/横向移动",
|
||||
"track_right": "跟拍/横向移动",
|
||||
"static": "稳定构图画面",
|
||||
}.get(movement, "产品展示")
|
||||
|
||||
|
||||
def _dominant_movement(shots: list[ShotBoundary]) -> str:
|
||||
if not shots:
|
||||
return "static"
|
||||
counts: dict[str, int] = {}
|
||||
for s in shots:
|
||||
counts[s.movement] = counts.get(s.movement, 0) + 1
|
||||
return max(counts, key=counts.get)
|
||||
|
||||
|
||||
def _build_transition_map(transitions: list[dict[str, Any]]) -> dict[str, str]:
|
||||
"""统计转场类型分布，返回 shot_index→transition 类型映射（字符串键）。"""
|
||||
m: dict[str, str] = {}
|
||||
for t in transitions:
|
||||
pair = t.get("between_shot") or [0, 0]
|
||||
if len(pair) >= 2:
|
||||
m[f"{pair[0]}-{pair[1]}"] = t.get("type", "hard_cut")
|
||||
return m
|
||||
|
||||
|
||||
# ── ③' 色调/滤镜预设（FFmpeg eq + colorchannelmixer 参数） ──────────────
|
||||
|
||||
#: color_filter → FFmpeg 滤镜参数字典（直接可拼到 eq=.../colorchannelmixer=...）
|
||||
COLOR_FILTER_PRESETS: dict[str, dict[str, Any]] = {
|
||||
"none": {},
|
||||
"warm_vintage": {
|
||||
"eq": {"brightness": 0.02, "contrast": 1.05, "saturation": 0.9, "gamma": 1.05},
|
||||
"colorchannelmixer": {"rr": 1.1, "gg": 0.98, "bb": 0.82, "ra": 0, "ga": 0, "ba": 0, "aa": 1},
|
||||
},
|
||||
"cool_fresh": {
|
||||
"eq": {"brightness": 0.03, "contrast": 1.08, "saturation": 1.05},
|
||||
"colorchannelmixer": {"rr": 0.9, "gg": 1.0, "bb": 1.12, "ra": 0, "ga": 0, "ba": 0, "aa": 1},
|
||||
},
|
||||
"high_contrast": {
|
||||
"eq": {"brightness": 0.0, "contrast": 1.3, "saturation": 1.2},
|
||||
"colorchannelmixer": {},
|
||||
},
|
||||
"soft_pastel": {
|
||||
"eq": {"brightness": 0.05, "contrast": 0.92, "saturation": 0.85},
|
||||
"colorchannelmixer": {"rr": 1.05, "gg": 1.03, "bb": 1.05, "ra": 0, "ga": 0, "ba": 0, "aa": 1},
|
||||
},
|
||||
"dramatic_cinematic": {
|
||||
"eq": {"brightness": -0.03, "contrast": 1.2, "saturation": 0.85},
|
||||
"colorchannelmixer": {"rr": 1.05, "gg": 0.98, "bb": 0.9, "ra": 0, "ga": 0, "ba": 0, "aa": 1},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def map_color_to_video_filter(color_filter: str) -> dict[str, Any]:
|
||||
"""color_filter 枚举 → FFmpeg eq/colorchannelmixer 参数字典（渲染端直接使用）。"""
|
||||
preset = COLOR_FILTER_PRESETS.get(color_filter) or COLOR_FILTER_PRESETS["none"]
|
||||
# 返回深拷贝防污染
|
||||
return json.loads(json.dumps(preset))
|
||||
|
||||
|
||||
# ── ③'' 运镜 → ken_burns 参数映射 ───────────────────────────────────────
|
||||
|
||||
#: 运镜类型 → URS 可直接消费的 ken_burns 参数字典
|
||||
CAMERA_TO_KEN_BURNS: dict[str, dict[str, Any]] = {
|
||||
"static": {
|
||||
"type": "static",
|
||||
"zoom_start": 1.0,
|
||||
"zoom_end": 1.0,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"push_in": {
|
||||
"type": "zoom",
|
||||
"zoom_start": 1.0,
|
||||
"zoom_end": 1.12,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"zoom_in": {
|
||||
"type": "zoom",
|
||||
"zoom_start": 1.0,
|
||||
"zoom_end": 1.18,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"pull_out": {
|
||||
"type": "zoom",
|
||||
"zoom_start": 1.12,
|
||||
"zoom_end": 1.0,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"zoom_out": {
|
||||
"type": "zoom",
|
||||
"zoom_start": 1.18,
|
||||
"zoom_end": 1.0,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"pan_left": {
|
||||
"type": "pan",
|
||||
"zoom_start": 1.05,
|
||||
"zoom_end": 1.05,
|
||||
"pan_x": -0.08,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"pan_right": {
|
||||
"type": "pan",
|
||||
"zoom_start": 1.05,
|
||||
"zoom_end": 1.05,
|
||||
"pan_x": 0.08,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"tilt_up": {
|
||||
"type": "pan+zoom",
|
||||
"zoom_start": 1.08,
|
||||
"zoom_end": 1.14,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": -0.05,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"tilt_down": {
|
||||
"type": "pan+zoom",
|
||||
"zoom_start": 1.14,
|
||||
"zoom_end": 1.08,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": 0.05,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"track_left": {
|
||||
"type": "pan",
|
||||
"zoom_start": 1.05,
|
||||
"zoom_end": 1.05,
|
||||
"pan_x": -0.10,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"track_right": {
|
||||
"type": "pan",
|
||||
"zoom_start": 1.05,
|
||||
"zoom_end": 1.05,
|
||||
"pan_x": 0.10,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def map_camera_to_ken_burns(movement: str) -> dict[str, Any]:
|
||||
"""运镜类型 → URS ken_burns 参数字典。未知类型回退 static。"""
|
||||
preset = CAMERA_TO_KEN_BURNS.get(movement) or CAMERA_TO_KEN_BURNS["static"]
|
||||
return json.loads(json.dumps(preset))
|
||||
|
||||
|
||||
# ── 转场 → xfade transition 名称 ────────────────────────────────────────
|
||||
|
||||
TRANSITION_TO_XFADE: dict[str, str] = {
|
||||
"hard_cut": "cut",
|
||||
"cross_dissolve": "dissolve",
|
||||
"fade_black": "fadeblack",
|
||||
"fade": "fade",
|
||||
"zoom_whip": "zoom",
|
||||
"slide_left": "slideright", # 画面左移 = 新画面从右滑入
|
||||
"slide_right": "slideleft",
|
||||
"wipe_left": "wipeleft",
|
||||
"wipe_right": "wiperight",
|
||||
}
|
||||
|
||||
|
||||
def map_transition_to_xfade(transition_type: str) -> str:
|
||||
"""转场枚举 → TransitionEngine 支持的 xfade 名称；未知回退 cut。"""
|
||||
return TRANSITION_TO_XFADE.get(transition_type, "cut")
|
||||
|
||||
|
||||
# ── BPM → BGM 推荐 BPM ──────────────────────────────────────────────────
|
||||
|
||||
|
||||
def map_bgm_bpm(bpm: int) -> int:
|
||||
"""BGM 选曲 BPM：参考视频 BPM ±5。bpm=0 返回 90（默认 medium）。"""
|
||||
if bpm <= 0:
|
||||
return 90
|
||||
return max(60, min(bpm, 180))
|
||||
|
||||
|
||||
# ── 单 clip 渲染参数聚合（给 URS build_render_plan 使用） ───────────────
|
||||
|
||||
|
||||
def build_render_params_for_clip(
|
||||
clip_index: int,
|
||||
style_guide: dict[str, Any],
|
||||
*,
|
||||
duration_sec: Optional[float] = None,
|
||||
) -> dict[str, Any]:
|
||||
"""根据 style_guide 为第 clip_index 个 clip 生成可直接喂给 URS 的渲染参数。"""
|
||||
shot_idx = clip_index + 1
|
||||
movements = style_guide.get("camera_movements") or []
|
||||
movement = "static"
|
||||
intensity = "low"
|
||||
for m in movements:
|
||||
if m.get("shot_index") == shot_idx:
|
||||
movement = m.get("movement", "static")
|
||||
intensity = m.get("intensity", "low")
|
||||
break
|
||||
ken = map_camera_to_ken_burns(movement)
|
||||
if intensity == "high":
|
||||
ken["zoom_end"] = round(ken.get("zoom_end", 1.0) * 1.08, 3)
|
||||
for k in ("pan_x", "pan_y"):
|
||||
ken[k] = round(ken.get(k, 0.0) * 1.3, 3)
|
||||
elif intensity == "low":
|
||||
for k in ("pan_x", "pan_y"):
|
||||
ken[k] = round(ken.get(k, 0.0) * 0.6, 3)
|
||||
transitions = style_guide.get("transitions") or []
|
||||
trans_type = "hard_cut"
|
||||
for t in transitions:
|
||||
pair = t.get("between_shot") or []
|
||||
if len(pair) >= 2 and pair[0] == shot_idx:
|
||||
trans_type = t.get("type", "hard_cut")
|
||||
break
|
||||
xfade = map_transition_to_xfade(trans_type)
|
||||
eq = map_color_to_video_filter(style_guide.get("color_filter", "none"))
|
||||
return {
|
||||
"ken_burns": ken,
|
||||
"transition": {"type": xfade, "duration": 0.3 if xfade != "cut" else 0.0},
|
||||
"video_filter": eq,
|
||||
"bgm_bpm_hint": map_bgm_bpm(int(style_guide.get("bpm") or 0)),
|
||||
"duration_sec": duration_sec,
|
||||
}
|
||||
|
||||
|
||||
# ── 素材本地化（URL/OSS key → 本地临时文件） ────────────────────────────
|
||||
|
||||
|
||||
def _ensure_local_video(reference: str, work_dir: Path) -> Optional[Path]:
|
||||
"""把 reference（URL/OSS key/本地路径）落到 work_dir 下的本地文件。"""
|
||||
p = Path(reference)
|
||||
if p.exists() and p.is_file():
|
||||
return p
|
||||
try:
|
||||
from video_processing.oss_helpers import download_asset
|
||||
|
||||
target = work_dir / f"ref_{uuid.uuid4().hex}.mp4"
|
||||
ok = download_asset(reference, target)
|
||||
if ok and target.exists() and target.stat().st_size > 0:
|
||||
return target
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("download_asset 失败，尝试 http 直连: %s", exc)
|
||||
if reference.startswith(("http://", "https://")):
|
||||
try:
|
||||
import urllib.request
|
||||
|
||||
target = work_dir / f"ref_{uuid.uuid4().hex}.mp4"
|
||||
with urllib.request.urlopen(reference, timeout=20) as r, open(target, "wb") as f:
|
||||
shutil.copyfileobj(r, f)
|
||||
if target.exists() and target.stat().st_size > 0:
|
||||
return target
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("HTTP 下载参考视频失败: %s", exc)
|
||||
return None
|
||||
|
||||
|
||||
# ── 入口 ─────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def analyze_video_style(
|
||||
reference_video_path: str | Path,
|
||||
style_strength: str = "medium",
|
||||
*,
|
||||
timeout_sec: int = DEFAULT_ANALYSIS_TIMEOUT,
|
||||
) -> dict[str, Any]:
|
||||
"""分析参考视频风格，返回 style_guide dict。
|
||||
|
||||
Args:
|
||||
reference_video_path: 本地路径、HTTP(S) URL 或 OSS storage key。
|
||||
style_strength: light | medium | strict。
|
||||
timeout_sec: 单步超时（秒），默认 60。
|
||||
|
||||
Returns:
|
||||
style_guide dict，详见 STYLE_GUIDE_SCHEMA。任何子步骤失败都会降级，不抛异常。
|
||||
"""
|
||||
style_strength = style_strength if style_strength in ("light", "medium", "strict") else "medium"
|
||||
frames_dir: Optional[Path] = None
|
||||
local_path: Optional[Path] = None
|
||||
try:
|
||||
frames_dir = Path(tempfile.mkdtemp(prefix="vstyle_"))
|
||||
work_dir = frames_dir # 同一临时根
|
||||
local_path = _ensure_local_video(str(reference_video_path), work_dir)
|
||||
if local_path is None:
|
||||
logger.error("[video_analyzer] 无法获取参考视频: %s", reference_video_path)
|
||||
return _rule_based_style_guide([], 0, {})
|
||||
# 资源约束：大小 / 时长
|
||||
try:
|
||||
size_mb = local_path.stat().st_size / (1024 * 1024)
|
||||
if size_mb > MAX_REFERENCE_SIZE_MB:
|
||||
logger.warning(
|
||||
"[video_analyzer] 参考视频 %.1fMB 超上限，按前 %ds 分析", size_mb, MAX_REFERENCE_DURATION_SEC
|
||||
)
|
||||
except OSError:
|
||||
pass
|
||||
duration = _probe_duration(local_path)
|
||||
if duration > MAX_REFERENCE_DURATION_SEC:
|
||||
duration = MAX_REFERENCE_DURATION_SEC
|
||||
# ① 抽帧
|
||||
try:
|
||||
frame_paths = _extract_keyframes(local_path, frames_dir / "frames")
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("FFmpeg 抽帧失败: %s，降级为 VLM 均匀采样", exc)
|
||||
frame_paths = []
|
||||
# ② 镜头分割
|
||||
shots = _detect_shots(local_path, frames_dir)
|
||||
# ③ 运镜检测（有帧才跑）
|
||||
if frame_paths or shots:
|
||||
_analyze_movements(local_path, shots)
|
||||
# ④ BPM
|
||||
bpm = _detect_bpm(local_path)
|
||||
# ⑤ 选帧→OSS→VLM
|
||||
sampled = _sample_frames(frame_paths, shots)
|
||||
image_urls = _upload_frames_to_oss(sampled) if sampled else []
|
||||
vlm = _vlm_analyze_frames(image_urls) if image_urls else {}
|
||||
# ⑥ 合成
|
||||
style_guide = _llm_synthesize(shots, bpm, vlm, style_strength)
|
||||
# 兜底字段校验
|
||||
style_guide.setdefault("style_strength", style_strength)
|
||||
style_guide.setdefault("pace", _pace_from_bpm(bpm))
|
||||
style_guide.setdefault("bpm", bpm)
|
||||
style_guide.setdefault("shot_count", len(shots))
|
||||
if shots and "avg_shot_duration" not in style_guide:
|
||||
durs = [s.end_sec - s.start_sec for s in shots]
|
||||
style_guide["avg_shot_duration"] = round(sum(durs) / len(durs), 2)
|
||||
return style_guide
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.exception("[video_analyzer] 整体分析异常，返回最小占位 style_guide: %s", exc)
|
||||
return _rule_based_style_guide([], 0, {"mood": "未知"})
|
||||
finally:
|
||||
# 临时帧清理
|
||||
if frames_dir and frames_dir.exists():
|
||||
shutil.rmtree(frames_dir, ignore_errors=True)
|
||||
@@ -110,19 +110,22 @@ def _step_video_analysis(job: ViralVideoJob) -> dict | None:
|
||||
return None
|
||||
|
||||
try:
|
||||
# 尝试导入 video_analyzer（由 #2051 提供）
|
||||
from worker_app.tasks.viral_video_analyzer import analyze_video_style
|
||||
# 尝试导入 video_analyzer（由 #2051 提供，位于 apps/worker/viral_video/）
|
||||
from apps.worker.viral_video.video_analyzer import analyze_video_style
|
||||
|
||||
style_guide = analyze_video_style(job.reference_video_url)
|
||||
style_guide = analyze_video_style(
|
||||
job.reference_video_url,
|
||||
style_strength=job.style_strength or "medium",
|
||||
)
|
||||
return style_guide
|
||||
except ImportError:
|
||||
logger.info("[爆款视频] video_analyzer 模块未就绪，使用占位风格分析")
|
||||
except ImportError as e:
|
||||
logger.info("[爆款视频] video_analyzer 模块未就绪(%s)，使用占位风格分析", e)
|
||||
return {
|
||||
"cut_speed": "medium",
|
||||
"transition": "cross_dissolve",
|
||||
"energy": "medium",
|
||||
"color_grade": "neutral",
|
||||
"narrative": False,
|
||||
"pace": "medium",
|
||||
"color_filter": "none",
|
||||
"ken_burns_params": {"type": "static"},
|
||||
"transition_map": {},
|
||||
"video_filter_eq_params": {},
|
||||
"source": "placeholder",
|
||||
}
|
||||
except Exception as e:
|
||||
|
||||
@@ -15,3 +15,8 @@ Pillow==10.4.0
|
||||
|
||||
# FFmpeg Python 绑定
|
||||
ffmpeg-python==0.2.0
|
||||
|
||||
# v1.3 参考视频风格分析（#2051）
|
||||
scenedetect==0.6.4
|
||||
librosa==0.10.2.post1
|
||||
soundfile==0.12.1
|
||||
|
||||
@@ -0,0 +1,360 @@
|
||||
"""video_analyzer（#2051）单元测试。
|
||||
|
||||
覆盖：
|
||||
- 映射函数（运镜→ken_burns、转场→xfade、色调→video_filter、BPM→BGM）
|
||||
- schema 常量与导出
|
||||
- Farneback 光流运镜判定（合成光流场）
|
||||
- BPM 档位映射
|
||||
- 降级路径（ffmpeg/cv2/librosa 不可用）
|
||||
- 临时目录清理
|
||||
- analyze_video_style 入口在无素材时返回最小 style_guide 不抛
|
||||
- build_render_params_for_clip 聚合输出
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import os
|
||||
import tempfile
|
||||
from pathlib import Path
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
# ── 映射函数 ──────────────────────────────────────────────────────────
|
||||
|
||||
from apps.worker.viral_video.video_analyzer import ( # noqa: E402
|
||||
COLOR_FILTER_PRESETS,
|
||||
DEFAULT_ANALYSIS_TIMEOUT,
|
||||
MAX_REFERENCE_DURATION_SEC,
|
||||
MAX_REFERENCE_SIZE_MB,
|
||||
STYLE_GUIDE_SCHEMA,
|
||||
TRANSITION_TO_XFADE,
|
||||
ShotBoundary,
|
||||
_detect_camera_movement,
|
||||
_pace_from_bpm,
|
||||
_rule_based_style_guide,
|
||||
analyze_video_style,
|
||||
build_render_params_for_clip,
|
||||
map_bgm_bpm,
|
||||
map_camera_to_ken_burns,
|
||||
map_color_to_video_filter,
|
||||
map_transition_to_xfade,
|
||||
)
|
||||
|
||||
|
||||
def test_constants_exported():
|
||||
assert MAX_REFERENCE_DURATION_SEC == 60
|
||||
assert MAX_REFERENCE_SIZE_MB == 100
|
||||
assert DEFAULT_ANALYSIS_TIMEOUT == 60
|
||||
assert "style_name" in STYLE_GUIDE_SCHEMA
|
||||
assert "ken_burns_params" in STYLE_GUIDE_SCHEMA
|
||||
assert "video_filter_eq_params" in STYLE_GUIDE_SCHEMA
|
||||
|
||||
|
||||
# ── 运镜→ken_burns ────────────────────────────────────────────────────
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"movement,expected_type",
|
||||
[
|
||||
("static", "static"),
|
||||
("push_in", "zoom"),
|
||||
("zoom_in", "zoom"),
|
||||
("pull_out", "zoom"),
|
||||
("pan_left", "pan"),
|
||||
("pan_right", "pan"),
|
||||
("tilt_up", "pan+zoom"),
|
||||
("track_left", "pan"),
|
||||
],
|
||||
)
|
||||
def test_map_camera_to_ken_burns_types(movement, expected_type):
|
||||
kb = map_camera_to_ken_burns(movement)
|
||||
assert kb["type"] == expected_type
|
||||
# zoom/pan 类必须有 zoom_start/zoom_end
|
||||
assert 0.8 <= kb["zoom_start"] <= 1.3
|
||||
assert 0.8 <= kb["zoom_end"] <= 1.3
|
||||
|
||||
|
||||
def test_map_camera_unknown_falls_back_to_static():
|
||||
kb = map_camera_to_ken_burns("unknown_movement_xyz")
|
||||
assert kb["type"] == "static"
|
||||
assert kb["zoom_start"] == kb["zoom_end"] == 1.0
|
||||
|
||||
|
||||
def test_map_camera_isolation_no_mutation():
|
||||
a = map_camera_to_ken_burns("push_in")
|
||||
a["zoom_end"] = 9.99
|
||||
b = map_camera_to_ken_burns("push_in")
|
||||
assert b["zoom_end"] != 9.99
|
||||
|
||||
|
||||
# ── 转场→xfade ────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"ttype,expected",
|
||||
[
|
||||
("hard_cut", "cut"),
|
||||
("cross_dissolve", "dissolve"),
|
||||
("fade", "fade"),
|
||||
("fade_black", "fadeblack"),
|
||||
("zoom_whip", "zoom"),
|
||||
("wipe_left", "wipeleft"),
|
||||
("slide_right", "slideleft"),
|
||||
],
|
||||
)
|
||||
def test_map_transition(ttype, expected):
|
||||
assert map_transition_to_xfade(ttype) == expected
|
||||
|
||||
|
||||
def test_map_transition_unknown_falls_back_to_cut():
|
||||
assert map_transition_to_xfade("some_random_transition") == "cut"
|
||||
|
||||
|
||||
# ── 色调→video_filter ─────────────────────────────────────────────────
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"name", ["none", "warm_vintage", "cool_fresh", "high_contrast", "soft_pastel", "dramatic_cinematic"]
|
||||
)
|
||||
def test_map_color_presets_available(name):
|
||||
p = map_color_to_video_filter(name)
|
||||
assert isinstance(p, dict)
|
||||
# 所有预设必须能被 FFmpeg eq/colorchannelmixer 消费：eq 是 dict，ccm 是 dict
|
||||
assert "eq" in p or p == {} or "colorchannelmixer" in p
|
||||
|
||||
|
||||
def test_map_color_unknown_is_none_preset():
|
||||
p = map_color_to_video_filter("not_a_real_filter")
|
||||
assert p == {}
|
||||
|
||||
|
||||
def test_map_color_isolation():
|
||||
a = map_color_to_video_filter("warm_vintage")
|
||||
a["eq"]["brightness"] = 9.99
|
||||
b = map_color_to_video_filter("warm_vintage")
|
||||
assert b["eq"]["brightness"] != 9.99
|
||||
|
||||
|
||||
# ── BPM → BGM ─────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"bpm,expected",
|
||||
[
|
||||
(0, 90),
|
||||
(70, 70),
|
||||
(120, 120),
|
||||
(200, 180),
|
||||
(30, 60),
|
||||
],
|
||||
)
|
||||
def test_map_bgm_bpm(bpm, expected):
|
||||
assert map_bgm_bpm(bpm) == expected
|
||||
|
||||
|
||||
def test_pace_from_bpm_buckets():
|
||||
assert _pace_from_bpm(120) == "fast_cut"
|
||||
assert _pace_from_bpm(110) == "fast_cut"
|
||||
assert _pace_from_bpm(90) == "medium"
|
||||
assert _pace_from_bpm(80) == "medium"
|
||||
assert _pace_from_bpm(60) == "slow_cinematic"
|
||||
assert _pace_from_bpm(0) == "medium"
|
||||
|
||||
|
||||
# ── Farneback 光流→运镜（合成光流） ───────────────────────────────────
|
||||
|
||||
|
||||
def _make_flow(dx: float, dy: float, w: int = 60, h: int = 40, zoom: float = 0.0):
|
||||
"""构造一个合成光流场：整体平移(dx,dy)+径向发散(zoom>0=zoom in,<0=out)。"""
|
||||
ys, xs = np.mgrid[0:h, 0:w].astype(np.float32)
|
||||
cx, cy = w / 2.0, h / 2.0
|
||||
fx = dx + (xs - cx) * zoom
|
||||
fy = dy + (ys - cy) * zoom
|
||||
return np.stack([fx, fy], axis=-1).astype(np.float32)
|
||||
|
||||
|
||||
def test_detect_movement_static():
|
||||
flow = _make_flow(0.0, 0.0, zoom=0.0)
|
||||
m, i = _detect_camera_movement(flow, 60, 40)
|
||||
assert m == "static"
|
||||
assert i == "low"
|
||||
|
||||
|
||||
def test_detect_movement_pan_right():
|
||||
flow = _make_flow(2.0, 0.0)
|
||||
m, i = _detect_camera_movement(flow, 60, 40)
|
||||
assert m == "pan_right"
|
||||
assert i in ("medium", "high")
|
||||
|
||||
|
||||
def test_detect_movement_pan_left():
|
||||
flow = _make_flow(-2.0, 0.0)
|
||||
m, _ = _detect_camera_movement(flow, 60, 40)
|
||||
assert m == "pan_left"
|
||||
|
||||
|
||||
def test_detect_movement_tilt_down():
|
||||
flow = _make_flow(0.0, 2.0)
|
||||
m, _ = _detect_camera_movement(flow, 60, 40)
|
||||
assert m == "tilt_down"
|
||||
|
||||
|
||||
def test_detect_movement_zoom_in_radial():
|
||||
# 径向向外发散 = zoom in
|
||||
flow = _make_flow(0.0, 0.0, zoom=0.08)
|
||||
m, _ = _detect_camera_movement(flow, 60, 40)
|
||||
assert m == "zoom_in"
|
||||
|
||||
|
||||
def test_detect_movement_zoom_out_radial():
|
||||
flow = _make_flow(0.0, 0.0, zoom=-0.08)
|
||||
m, _ = _detect_camera_movement(flow, 60, 40)
|
||||
assert m == "zoom_out"
|
||||
|
||||
|
||||
# ── 规则合成 style_guide ──────────────────────────────────────────────
|
||||
|
||||
|
||||
def _sample_shots(n=4):
|
||||
return [
|
||||
ShotBoundary(
|
||||
index=i,
|
||||
start_sec=float(i * 3),
|
||||
end_sec=float((i + 1) * 3),
|
||||
movement=["static", "push_in", "pan_left", "zoom_in"][i],
|
||||
intensity=["low", "medium", "low", "high"][i],
|
||||
transition="hard_cut",
|
||||
)
|
||||
for i in range(n)
|
||||
]
|
||||
|
||||
|
||||
CAMERA_TO_KEN_BURNS_DIRS = {
|
||||
"zoom_in_slow",
|
||||
"zoom_out_slow",
|
||||
"pan_left_slow",
|
||||
"pan_right_slow",
|
||||
"zoom_in_medium",
|
||||
"zoom_out_medium",
|
||||
"diagonal_push",
|
||||
"static",
|
||||
}
|
||||
|
||||
|
||||
def test_rule_based_style_guide_structure():
|
||||
shots = _sample_shots()
|
||||
sg = _rule_based_style_guide(shots, bpm=120, vlm={"color_filter": "warm_vintage"})
|
||||
# 关键字段存在且类型正确
|
||||
assert sg["shot_count"] == 4
|
||||
assert sg["pace"] == "fast_cut"
|
||||
assert sg["bpm"] == 120
|
||||
assert sg["avg_shot_duration"] == 3.0
|
||||
assert len(sg["camera_movements"]) == 4
|
||||
assert sg["color_filter"] == "warm_vintage"
|
||||
assert "eq" in sg["video_filter_eq_params"]
|
||||
assert "default" in sg["ken_burns_params"]
|
||||
assert isinstance(sg["transition_map"], dict)
|
||||
assert isinstance(sg["ken_burns_direction_hint"], str) and sg["ken_burns_direction_hint"]
|
||||
|
||||
|
||||
# ── build_render_params_for_clip 聚合 ─────────────────────────────────
|
||||
|
||||
|
||||
def test_build_render_params_for_clip_shape():
|
||||
sg = _rule_based_style_guide(_sample_shots(), bpm=95, vlm={"color_filter": "cool_fresh"})
|
||||
p0 = build_render_params_for_clip(0, sg, duration_sec=3.0)
|
||||
assert "ken_burns" in p0
|
||||
assert "transition" in p0
|
||||
assert "video_filter" in p0
|
||||
assert p0["bgm_bpm_hint"] == 95
|
||||
assert p0["duration_sec"] == 3.0
|
||||
# clip 1 是 push_in → zoom
|
||||
p1 = build_render_params_for_clip(1, sg)
|
||||
assert p1["ken_burns"]["type"] == "zoom"
|
||||
|
||||
|
||||
def test_build_render_params_high_intensity_amplifies():
|
||||
shots = _sample_shots() # shot 3 = zoom_in/high
|
||||
sg = _rule_based_style_guide(shots, bpm=120, vlm={})
|
||||
p3 = build_render_params_for_clip(3, sg)
|
||||
base = map_camera_to_ken_burns("zoom_in")
|
||||
assert p3["ken_burns"]["zoom_end"] > base["zoom_end"]
|
||||
|
||||
|
||||
# ── 降级与容错 ────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_analyze_with_nonexistent_file_returns_minimum_guide():
|
||||
sg = analyze_video_style("/nonexistent/path/fake_video.mp4")
|
||||
assert isinstance(sg, dict)
|
||||
assert "style_name" in sg
|
||||
assert sg["shot_count"] == 0
|
||||
# 不抛异常且字段完整
|
||||
|
||||
|
||||
def test_analyze_invalid_style_strength_defaults_to_medium():
|
||||
# 即使视频不存在，也应被规范化为 medium 并写入返回值
|
||||
with patch("apps.worker.viral_video.video_analyzer._ensure_local_video", return_value=None):
|
||||
sg = analyze_video_style("fake", style_strength="banana")
|
||||
assert sg.get("style_strength", "medium") == "medium"
|
||||
|
||||
|
||||
def test_temp_dir_cleaned_up_after_run():
|
||||
"""用临时真实空文件模拟本地路径，确认 frames 临时目录被清理。"""
|
||||
with tempfile.TemporaryDirectory() as td:
|
||||
fake = Path(td) / "fake.mp4"
|
||||
fake.write_bytes(b"")
|
||||
# 抽帧会失败（ffmpeg 对空文件失败），但应全程不抛且临时目录 rmtree
|
||||
# 直接 mock _ensure_local_video 回传不存在的文件，走 _probe_duration=0 降级路径
|
||||
with patch("apps.worker.viral_video.video_analyzer._ensure_local_video", return_value=None):
|
||||
sg = analyze_video_style("proto://fake", style_strength="light")
|
||||
assert "style_name" in sg
|
||||
|
||||
|
||||
def test_ffmpeg_failure_falls_back_to_vlm_only_path():
|
||||
"""模拟 ffmpeg 抽帧失败，仍能返回 style_guide。"""
|
||||
with tempfile.TemporaryDirectory() as td:
|
||||
fake = Path(td) / "ref.mp4"
|
||||
fake.write_bytes(b"not a real video")
|
||||
with patch(
|
||||
"apps.worker.viral_video.video_analyzer._extract_keyframes", side_effect=RuntimeError("ffmpeg exploded")
|
||||
):
|
||||
with patch("apps.worker.viral_video.video_analyzer._detect_shots") as mock_shots:
|
||||
mock_shots.return_value = [ShotBoundary(0, 0.0, 3.0)]
|
||||
with patch("apps.worker.viral_video.video_analyzer._analyze_movements"):
|
||||
with patch("apps.worker.viral_video.video_analyzer._detect_bpm", return_value=90):
|
||||
with patch(
|
||||
"apps.worker.viral_video.video_analyzer._vlm_analyze_frames",
|
||||
return_value={"color_filter": "none"},
|
||||
):
|
||||
with patch(
|
||||
"apps.worker.viral_video.video_analyzer._llm_synthesize",
|
||||
side_effect=lambda shots, bpm, vlm, ss: _rule_based_style_guide(shots, bpm, vlm),
|
||||
):
|
||||
sg = analyze_video_style(str(fake))
|
||||
assert sg["bpm"] == 90
|
||||
assert sg["shot_count"] == 1
|
||||
|
||||
|
||||
# ── 转场映射完整性 ────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_transition_map_covers_observed_types():
|
||||
for t in ("hard_cut", "cross_dissolve", "fade_black", "zoom_whip"):
|
||||
assert t in TRANSITION_TO_XFADE
|
||||
|
||||
|
||||
# ── 预设完整性 ────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_color_filter_preset_keys_are_safe_for_ffmpeg():
|
||||
for name, preset in COLOR_FILTER_PRESETS.items():
|
||||
if preset == {}:
|
||||
continue
|
||||
# eq 所有值都是数字
|
||||
for k, v in preset.get("eq", {}).items():
|
||||
assert isinstance(v, (int, float)), f"{name}.eq.{k} not numeric"
|
||||
for k, v in preset.get("colorchannelmixer", {}).items():
|
||||
assert isinstance(v, (int, float)), f"{name}.ccm.{k} not numeric"
|
||||
Reference in New Issue
Block a user