Video Processing & Editing
Expert in FFmpeg-based video editing, processing automation, and export optimization for modern content creation workflows.
When to Use
✅ Use for:
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Automated video editing pipelines (script-to-video)
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Cutting, trimming, concatenating clips
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Adding transitions, effects, overlays
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Audio mixing and normalization
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Subtitle/caption handling
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Export optimization for platforms
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Batch video processing
-
Color grading and correction
❌ NOT for:
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Real-time video editing UI (use DaVinci Resolve/Premiere)
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3D compositing (use After Effects/Blender)
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Motion graphics animation (use After Effects)
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Basic screen recording (use OBS)
Technology Selection
Video Editing Tools
Tool Speed Features Use Case
FFmpeg Very Fast CLI automation Production pipelines
MoviePy Medium Python API Programmatic editing
PyAV Fast Low-level control Custom processing
DaVinci Resolve Slow Full NLE Manual editing
Decision tree:
Need automation? → FFmpeg Need Python API? → MoviePy Need frame-level control? → PyAV Need manual editing? → DaVinci Resolve
Common Anti-Patterns
Anti-Pattern 1: Not Using Keyframe-Aligned Cuts
Novice thinking: "Just cut the video at any timestamp"
Problem: Causes artifacts, black frames, and playback issues.
Wrong approach:
❌ Cut at arbitrary timestamp (not keyframe-aligned)
ffmpeg -i input.mp4 -ss 00:01:23.456 -to 00:02:45.678 -c copy output.mp4
Result: Black frames, artifacts, sync issues
Why wrong:
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Video codecs use keyframes (I-frames) every 2-10 seconds
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Non-keyframe cuts require re-encoding
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Using -c copy (stream copy) without keyframe alignment breaks playback
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GOP (Group of Pictures) structure depends on keyframes
Correct approach 1: Re-encode for precise cuts
✅ Re-encode for frame-accurate cutting
ffmpeg -i input.mp4 -ss 00:01:23.456 -to 00:02:45.678
-c:v libx264 -crf 18 -preset medium
-c:a aac -b:a 192k
output.mp4
Frame-accurate, but slower (re-encoding)
Correct approach 2: Keyframe-aligned stream copy
✅ Fast cutting with keyframe alignment
Step 1: Find keyframes near cut points
ffprobe -select_streams v -show_frames -show_entries frame=pkt_pts_time,key_frame
-of csv input.mp4 | grep ",1$" | awk -F',' '{print $2}'
Step 2: Cut at nearest keyframes (fast, no re-encoding)
ffmpeg -i input.mp4 -ss 00:01:22.000 -to 00:02:46.000 -c copy output.mp4
Blazing fast, no quality loss, but not frame-accurate
Correct approach 3: Two-pass for best of both worlds
✅ Fast seek + precise cut
ffmpeg -ss 00:01:20.000 -i input.mp4
-ss 00:00:03.456 -to 00:01:25.678
-c:v libx264 -crf 18 -preset medium
-c:a aac -b:a 192k
output.mp4
-ss BEFORE -i: Fast seek to keyframe (no decode)
-ss AFTER -i: Precise trim (only decode needed portion)
Performance comparison:
Method Time (1-hour video) Accuracy Quality
Stream copy (arbitrary) 2s ❌ Broken ❌ Artifacts
Stream copy (keyframe) 2s ±2s ✅ Perfect
Re-encode (simple) 15min ✅ Frame ⚠️ Quality loss
Two-pass (optimal) 3min ✅ Frame ✅ Perfect
Timeline context:
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2010: FFmpeg required full re-encoding for cuts
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2015: -c copy added for stream copying
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2020: Two-pass cutting became best practice
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2024: Hardware acceleration (NVENC) makes re-encoding viable
Anti-Pattern 2: Re-encoding Unnecessarily
Novice thinking: "Apply all edits in one FFmpeg command"
Problem: Multiple re-encodings cause cumulative quality loss.
Wrong approach:
❌ Re-encode for each operation (quality degradation)
Operation 1: Trim
ffmpeg -i input.mp4 -ss 00:01:00 -to 00:05:00
-c:v libx264 -crf 23 temp1.mp4
Operation 2: Add audio
ffmpeg -i temp1.mp4 -i audio.mp3 -c:v libx264 -crf 23
-map 0:v -map 1:a temp2.mp4
Operation 3: Add subtitles
ffmpeg -i temp2.mp4 -vf subtitles=subs.srt
-c:v libx264 -crf 23 output.mp4
Result: 3x re-encoding = significant quality loss
Why wrong:
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Each re-encode is lossy (even with high CRF)
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Cumulative quality loss (generation loss)
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3x encoding time
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Wasted disk I/O
Correct approach 1: Chain operations in single command
✅ Single-pass encoding with all operations
ffmpeg -ss 00:01:00 -i input.mp4 -i audio.mp3
-to 00:04:00
-vf "subtitles=subs.srt"
-map 0:v -map 1:a
-c:v libx264 -crf 18 -preset medium
-c:a aac -b:a 192k
output.mp4
Single re-encode, all operations applied at once
Correct approach 2: Use stream copy when possible
✅ Lossless operations with stream copy
Trim (stream copy)
ffmpeg -i input.mp4 -ss 00:01:00 -to 00:05:00 -c copy temp.mp4
Add audio (stream copy video, encode audio)
ffmpeg -i temp.mp4 -i audio.mp3
-map 0:v -map 1:a
-c:v copy -c:a aac -b:a 192k
temp2.mp4
Burn subtitles (must re-encode video)
ffmpeg -i temp2.mp4 -vf subtitles=subs.srt
-c:v libx264 -crf 18 -preset medium
-c:a copy
output.mp4
Only 1 video re-encode (for subtitles)
Quality comparison:
Method Encoding Passes Quality (VMAF) Time
3x re-encode (CRF 23) 3 82/100 45min
Single pass (CRF 23) 1 91/100 15min
Stream copy + 1 encode 1 95/100 18min
All stream copy 0 100/100 30s
Anti-Pattern 3: Ignoring Color Space Conversions
Novice thinking: "Just concatenate videos together"
Problem: Color shifts, mismatched brightness, broken playback.
Wrong approach:
❌ Concatenate videos with different color spaces
clip1.mp4: BT.709 (HD), yuv420p
clip2.mp4: BT.601 (SD), yuvj420p (full range)
clip3.mp4: BT.2020 (HDR), yuv420p10le
Create concat list
echo "file 'clip1.mp4'" > list.txt echo "file 'clip2.mp4'" >> list.txt echo "file 'clip3.mp4'" >> list.txt
Concatenate without color normalization
ffmpeg -f concat -safe 0 -i list.txt -c copy output.mp4
Result: Color shifts between clips, broken HDR metadata
Why wrong:
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Different color spaces (BT.601 vs BT.709 vs BT.2020)
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Different pixel formats (yuv420p vs yuvj420p)
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Different color ranges (limited vs full)
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Metadata conflicts
Correct approach:
✅ Normalize color space before concatenation
Step 1: Analyze color space of each clip
ffprobe -v error -select_streams v:0
-show_entries stream=color_space,color_transfer,color_primaries,pix_fmt
-of default=noprint_wrappers=1 clip1.mp4
Step 2: Normalize all clips to common color space
Target: BT.709 (HD), yuv420p, limited range
Normalize clip1 (already BT.709)
ffmpeg -i clip1.mp4 -c copy clip1_normalized.mp4
Normalize clip2 (BT.601 SD → BT.709 HD)
ffmpeg -i clip2.mp4
-vf "scale=in_range=full:out_range=limited,colorspace=bt709:iall=bt601:fast=1"
-color_primaries bt709
-color_trc bt709
-colorspace bt709
-c:v libx264 -crf 18 -preset medium
-c:a copy
clip2_normalized.mp4
Normalize clip3 (BT.2020 HDR → BT.709 SDR)
ffmpeg -i clip3.mp4
-vf "zscale=t=linear:npl=100,format=gbrpf32le,zscale=p=bt709,tonemap=hable:desat=0,zscale=t=bt709:m=bt709:r=limited,format=yuv420p"
-color_primaries bt709
-color_trc bt709
-colorspace bt709
-c:v libx264 -crf 18 -preset medium
-c:a copy
clip3_normalized.mp4
Step 3: Concatenate normalized clips
echo "file 'clip1_normalized.mp4'" > list.txt echo "file 'clip2_normalized.mp4'" >> list.txt echo "file 'clip3_normalized.mp4'" >> list.txt
ffmpeg -f concat -safe 0 -i list.txt -c copy output.mp4
Color space guide:
Standard Color Space Transfer Primaries Use Case
BT.601 SD bt470bg bt470bg Old SD content
BT.709 HD bt709 bt709 Modern HD/FHD
BT.2020 UHD/HDR smpte2084 bt2020 4K HDR
sRGB Web iec61966-2-1 bt709 Web delivery
Anti-Pattern 4: Poor Audio Sync
Novice thinking: "Video and audio are separate, just overlay them"
Problem: Lip sync issues, audio drift, broken playback.
Wrong approach:
❌ Replace audio without sync consideration
ffmpeg -i video.mp4 -i audio.mp3
-map 0:v -map 1:a
-c:v copy -c:a copy
output.mp4
Problems:
- Audio duration ≠ video duration
- No audio stretching/compression
- Drift over time
Why wrong:
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Audio and video have different durations
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No timebase synchronization
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No drift correction
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Ignores original audio sync
Correct approach 1: Stretch/compress audio to match video
✅ Adjust audio speed to match video duration
Get durations
VIDEO_DUR=$(ffprobe -v error -show_entries format=duration
-of default=noprint_wrappers=1:nokey=1 video.mp4)
AUDIO_DUR=$(ffprobe -v error -show_entries format=duration
-of default=noprint_wrappers=1:nokey=1 audio.mp3)
Calculate speed ratio
RATIO=$(echo "$VIDEO_DUR / $AUDIO_DUR" | bc -l)
Stretch audio to match video (with pitch correction)
ffmpeg -i video.mp4 -i audio.mp3
-filter_complex "[1:a]atempo=${RATIO}[a]"
-map 0:v -map "[a]"
-c:v copy -c:a aac -b:a 192k
output.mp4
Correct approach 2: Precise offset and trim
✅ Sync audio with offset and trim
Audio starts 0.5s late, trim to match video
ffmpeg -i video.mp4 -itsoffset 0.5 -i audio.mp3
-map 0:v -map 1:a
-shortest
-c:v copy -c:a aac -b:a 192k
output.mp4
-itsoffset: Delay audio by 0.5s
-shortest: Trim to shortest stream
Correct approach 3: Mix multiple audio tracks with sync
✅ Mix dialogue, music, effects with precise timing
ffmpeg -i video.mp4 -i dialogue.wav -i music.mp3 -i sfx.wav
-filter_complex "
[1:a]adelay=0|0[dlg];
[2:a]volume=0.3,adelay=500|500[mus];
[3:a]adelay=1200|1200[sfx];
[dlg][mus][sfx]amix=inputs=3:duration=first[a]
"
-map 0:v -map "[a]"
-c:v copy -c:a aac -b:a 256k
output.mp4
adelay: Precise millisecond timing
amix: Mix multiple audio streams
volume: Normalize levels
Audio sync checklist:
□ Verify video and audio durations match □ Use -shortest to prevent excess audio □ Apply adelay for precise timing offsets □ Use atempo for speed adjustment (maintains pitch) □ Set audio bitrate appropriately (128k-256k) □ Test lip sync at beginning, middle, end
Anti-Pattern 5: Wrong Codec/Bitrate for Platform
Novice thinking: "One export settings for everything"
Problem: Wasted bandwidth, poor quality, rejected uploads, compatibility issues.
Wrong approach:
❌ Export everything at 4K 50 Mbps
ffmpeg -i input.mp4
-c:v libx264 -b:v 50M -s 3840x2160
-c:a aac -b:a 320k
output.mp4
For Instagram story: 2 GB file, rejected (max 100 MB)
For YouTube: Could use 10 Mbps and look identical
For Twitter: Exceeds bitrate limits
Why wrong:
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Platform-specific size/bitrate limits
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Over-encoding wastes bandwidth
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Wrong resolution for platform
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Incompatible codecs
Correct approach: Platform-optimized exports
YouTube (recommended settings):
✅ YouTube 1080p upload
ffmpeg -i input.mp4
-c:v libx264 -preset slow -crf 18
-s 1920x1080 -r 30
-pix_fmt yuv420p
-color_primaries bt709 -color_trc bt709 -colorspace bt709
-movflags +faststart
-c:a aac -b:a 192k -ar 48000
youtube_1080p.mp4
YouTube 4K upload
ffmpeg -i input.mp4
-c:v libx264 -preset slow -crf 18
-s 3840x2160 -r 60
-pix_fmt yuv420p
-movflags +faststart
-c:a aac -b:a 256k -ar 48000
youtube_4k.mp4
Instagram (Stories, Reels, Feed):
✅ Instagram Story (9:16, max 100 MB, 15s)
ffmpeg -i input.mp4
-c:v libx264 -preset medium -crf 23
-s 1080x1920 -r 30 -t 15
-pix_fmt yuv420p
-movflags +faststart
-c:a aac -b:a 128k
instagram_story.mp4
✅ Instagram Reel (9:16, max 90s)
ffmpeg -i input.mp4
-c:v libx264 -preset medium -crf 23
-s 1080x1920 -r 30 -t 90
-pix_fmt yuv420p
-movflags +faststart
-c:a aac -b:a 128k
instagram_reel.mp4
✅ Instagram Feed (1:1 or 4:5)
ffmpeg -i input.mp4
-c:v libx264 -preset medium -crf 23
-s 1080x1080 -r 30
-pix_fmt yuv420p
-movflags +faststart
-c:a aac -b:a 128k
instagram_feed.mp4
Twitter/X:
✅ Twitter video (max 512 MB, 2:20)
ffmpeg -i input.mp4
-c:v libx264 -preset medium -crf 23
-s 1280x720 -r 30 -t 140
-maxrate 5000k -bufsize 10000k
-pix_fmt yuv420p
-movflags +faststart
-c:a aac -b:a 128k
twitter.mp4
TikTok:
✅ TikTok (9:16, max 287 MB, 10 min)
ffmpeg -i input.mp4
-c:v libx264 -preset medium -crf 23
-s 1080x1920 -r 30 -t 600
-pix_fmt yuv420p
-movflags +faststart
-c:a aac -b:a 128k
tiktok.mp4
Web (HTML5 video):
✅ Web optimized (fast load, broad compatibility)
ffmpeg -i input.mp4
-c:v libx264 -preset medium -crf 23
-s 1920x1080 -r 30
-pix_fmt yuv420p
-profile:v baseline -level 3.0
-movflags +faststart
-c:a aac -b:a 128k -ar 48000
web.mp4
Platform specs table:
Platform Max Size Max Duration Resolution FPS Bitrate Codec
YouTube Unlimited Unlimited 8K 60 Auto H.264/VP9
Instagram Story 100 MB 15s 1080x1920 30 ~5 Mbps H.264
Instagram Reel 1 GB 90s 1080x1920 30 ~8 Mbps H.264
Twitter 512 MB 2:20 1920x1080 60 5 Mbps H.264
TikTok 287 MB 10min 1080x1920 30 ~4 Mbps H.264
LinkedIn 5 GB 10min 1920x1080 30 5 Mbps H.264
Web Varies Varies 1920x1080 30 2-5 Mbps H.264
Export optimization checklist:
□ Use -movflags +faststart for web (progressive download) □ Use -pix_fmt yuv420p for broad compatibility □ Set -r 30 for most platforms (avoid variable framerate) □ Use -preset slow for final exports (better quality) □ Use -preset ultrafast for drafts □ Apply -maxrate and -bufsize for streaming □ Test playback on target platform before bulk export
Production Checklist
□ Align cuts to keyframes (or two-pass seek) □ Chain operations in single FFmpeg command □ Normalize color spaces before concatenating □ Verify audio/video sync (test at multiple points) □ Use platform-specific export presets □ Apply -movflags +faststart for web delivery □ Set proper color metadata (bt709 for HD) □ Test output file on target platform □ Keep lossless intermediate files (ProRes, FFV1) □ Use hardware acceleration for batch jobs (NVENC, VideoToolbox)
When to Use vs Avoid
Scenario Appropriate?
Automated video pipeline (script → video) ✅ Yes - FFmpeg automation
Batch process 100 videos ✅ Yes - parallel FFmpeg jobs
Trim/cut clips programmatically ✅ Yes - precise cutting
Add subtitles to videos ✅ Yes - burn or soft subs
Color grade footage ⚠️ Limited - basic only
Multi-cam editing ❌ No - use DaVinci Resolve
Motion graphics ❌ No - use After Effects
Real-time preview editing ❌ No - use Premiere/Resolve
References
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/references/ffmpeg-guide.md
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Complete FFmpeg command reference
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/references/timeline-editing.md
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Timeline concepts, multi-track editing
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/references/export-optimization.md
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Platform-specific export settings
Scripts
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scripts/video_editor.py
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Cut, trim, concatenate, transitions, effects
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scripts/batch_processor.py
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Parallel batch video processing
This skill guides: Video editing | FFmpeg | Timeline editing | Transitions | Export optimization | Audio mixing | Color grading | Automated video production