Skill 详情
comfyui-video-production
在 ComfyUI 中规划和编排端到端视频制作流水线,涵盖 img2vid、txt2vid、vid2vid 和多镜头,并设有验证关卡。
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SKILL.md
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--- name: comfyui-video-production description: Plan and orchestrate end-to-end video production pipelines in ComfyUI with validation gates and error recovery. Handles img2vid, txt2vid, vid2vid, and multi-shot video production. Produces pipeline plans with correct step ordering (generate, validate, animate, validate, concat), model selection, retry strategies (seed randomization, parameter adjustment, model fallback), and VRAM-aware resource management. Use when asked to make a video, animate images, create a multi-shot video, set up a video pipeline, or orchestrate video production in ComfyUI. Does NOT cover still image generation, prompt writing, workflow building for non-video tasks, video editing in external tools, model training, installation, or hardware recommendations. --- # ComfyUI Video Production Pipeline End-to-end video production orchestration for ComfyUI with automatic error recovery, quality validation, and instance management. ## Quick Start: Which Pipeline? **Creating a multi-shot narrative video?** → **Keyframe Pipeline** - Generate keyframes → Animate → Stitch with transitions **Animating existing images?** → **I2V Batch Pipeline** - Load images → Queue I2V jobs → Auto-validate → Combine **Need smooth transitions between scenes?** → **Transition Pipeline** - Crossfades, motion blur, zoom effects via FFmpeg **ComfyUI stuck or crashed?** → **Instance Manager** - Auto-restart, health checks, queue monitoring **Debugging video issues?** → **Validation Suite** - Check resolution, FPS, codec, face consistency, color grading --- ## Core Pipelines ### Pipeline 1: Keyframe-to-Video (Complete Narrative) **Use when:** Creating story-driven videos with multiple distinct shots ``` 1. Keyframe Generation Phase - Generate consistent keyframes with IP-Adapter/LoRA - Validate face consistency, lighting, pose progression - Save to organized directory structure - Auto-retry failed generations 2. I2V Animation Phase - Queue each keyframe to I2V model (Wan 2.2, LTX-2, AnimateDiff) - Monitor progress via ComfyUI API - Validate each clip (resolution, fps, duration) - Auto-retry with different seeds if failed 3. Concatenation Phase - Pre-flight validation (ensure all clips match) - Apply transition effects (crossfade, motion blur) - FFmpeg encoding with proper codec - Export final video with metadata 4. Quality Assurance - Face consistency check across clips - Color grading consistency - Audio sync validation (if applicable) - Generate QA report ``` **Expected output:** Single cohesive video with smooth transitions --- ### Pipeline 2: Batch I2V Processing **Use when:** You have multiple images to animate independently ``` 1. Image Discovery - Scan directory for source images - Validate image specs (resolution, format) - Generate processing manifest 2. Parallel I2V Queue - Queue all images to ComfyUI with appropriate prompts - Stagger submissions to avoid overload - Monitor queue depth and ETA 3. Progressive Validation - Check each completed video immediately - Flag issues (wrong resolution, fps, corruption) - Auto-retry flagged videos 4. Export & Organize - Move validated videos to output directory - Generate index with metadata - Create contact sheet (thumbnail preview grid) ``` **Expected output:** Directory of validated animated clips --- ### Pipeline 3: Video Concatenation with Transitions **Use when:** Combining existing video clips with professional transitions ``` 1. Clip Validation - Verify all clips exist and are readable - Check resolution, fps, codec consistency - Report mismatches with fix suggestions 2. Transition Planning - Detect scene changes (cut detection) - Recommend transition types (crossfade, zoom, pan) - Calculate transition timing 3. FFmpeg Pipeline - Apply transitions between clips - Re-encode with consistent settings - Preserve quality (high bitrate, proper codec)在 GitHub 阅读完整来源 (打开外部页面)