🎬 The Free Media Post-Production Guide (2026)

Generating media is solved. This is the finishing half — upscale to 4K, smooth to 60fps, split stems, master to loudness spec, subtitle, and dub — all for $0 and, because you monetize, all filtered hard on commercial licensing.

Verified June 2026. Claims are ✅ verified (read from a primary source — GitHub LICENSE, model card, or pricing page) or ⚠️ verify (page was JS/login -gated). Researched with a multi-model sweep (GPT-5.5, Gemini 3.1 Pro, Claude Opus 4.8) and reconciled against official sources. Companion to the Awesome Free Compute list, the Token-Maxxing Guide (image/video generation), and the Audio Generation Guide. This file is the post / finishing layer that takes generated media to publish-ready.

Contents

• TL;DR
• The licensing landmines
• 1. Video finishing
• 2. Audio finishing
• 3. Translation, subtitles, dubbing
• 4. Visual assets and compositing
• 5. The $0 finishing pipelines
• Sources

TL;DR

One-liner: Audio → Demucs → Matchering → ffmpeg loudnorm −14 LUFS. Video → Upscayl (Real-ESRGAN 4×) → chaiNNer (FILM/RIFE → 60fps) → DaVinci Resolve. Reach → Whisper → IndicTrans2/Azure → Subtitle Edit → OpenVoice dub. All $0, all clean.

License = output, not just tool. With MIT / BSD / Apache / GPL tools, the media you output (your masters, videos, subtitles) is 100% yours to monetize. GPL copyleft only governs redistributing the software, never your render.

The licensing landmines

The whole reason this guide leads with licensing: most "free" restoration and translation models are research/non-commercial, and several are silently bundled into the free GUIs everyone uses.

⚠️ Non-commercial — do NOT use on monetized output

✅ Green-light — free and commercial

Real-ESRGAN (BSD-3), SwinIR / BSRGAN (Apache), APISR (GPL-3), GFPGAN / RestoreFormer / DDColor (Apache), Google FILM / FLAVR / IFRNet (Apache/MIT), Upscayl (AGPL), chaiNNer (GPL), DaVinci Resolve Free · Demucs (MIT), DeepFilterNet (MIT/Apache), Resemble Enhance / VoiceFixer (MIT), RNNoise (BSD), Matchering (GPL), ffmpeg / Audacity · IndicTrans2 (MIT), Opus-MT / MADLAD-400 (Apache), Azure Translator F0 / DeepL Free / Google Translation free tiers, Whisper (MIT), Subtitle Edit / Aegisub, OpenVoice (MIT). Compositing / 3D (§4): SAM 2 (Apache), BiRefNet / InSPyReNet / MODNet / rembg (MIT/Apache), RVM (GPL-3), TRELLIS / TripoSR / InstantMesh (MIT/Apache), Hunyuan3D (Tencent Community), Stable Fast 3D (Stability, <$1M rev).

1. Video finishing

Goal: take a 1080p/30fps AI render to a 4K / 60fps master, commercial-clean, on an Apple Silicon Mac (or free Colab/Kaggle).

1.1 Upscaling / super-resolution

1.2 Frame interpolation → 60fps

1.3 Face & video restoration

1.4 Free Mac apps / GUIs (no code)

• Upscayl (AGPL) — native Apple-Silicon upscaler app; bundles Real-ESRGAN + Remacri; Vulkan/NCNN GPU. The easy button for 4K.
• chaiNNer (GPL) — node-based editor; drag .pth models (SwinIR, RIFE, GFPGAN) into a flowchart. The most powerful Mac-native option; runs RIFE via PyTorch/MPS.
• DaVinci Resolve (Free) — commercial use allowed; final color + encode to H.265/ProRes. Free timeline caps at 4K UHD — exactly your target.
• Flowframes (open) — great RIFE/FILM GUI but Windows-only (Parallels kills GPU accel on Mac); prefer chaiNNer on macOS.

Apple Silicon advantage: unified memory means a 32 GB Mac effectively has 32 GB of "VRAM" — beating a 24 GB RTX 4090 for big 4K frames. Rough local time for a 3-min clip: ~1–2 h to 4K (Real-ESRGAN) + ~15 min to 60fps (RIFE), all background, $0. On an 8 GB M1, offload to Kaggle (30 GPU-h/wk) instead.

2. Audio finishing

Since you generate full mixes (Suno/ACE-Step), separation is optional — used for instrumental/karaoke versions or to fix a single stem. Mastering + loudness is the part you should always do.

2.1 Stem separation / karaoke

2.2 Denoise / cleanup (apply to an isolated vocal stem)

2.3 Mastering & loudness

• Matchering 2.0 (GPL-3.0) 🥇 — reference mastering: feed your TARGET track + a commercial REFERENCE song; it matches RMS, EQ, peak, and stereo width with a true-peak limiter. Your master is unrestricted (GPL governs only redistributing the software). pip install matchering, native on macOS; also in the UVR5 app.
• ffmpeg loudnorm — hit platform loudness (EBU R128) for free. Two-pass (recommended for files):

sh # 1) measure ffmpeg -i in.wav -af loudnorm=I=-14:TP=-1:LRA=11:print_format=json -f null - # 2) apply the printed measured_* values ffmpeg -i in.wav -af loudnorm=I=-14:TP=-1:LRA=11:\ measured_I=…:measured_TP=…:measured_LRA=…:measured_thresh=…:offset=…:linear=true \ -ar 48k out.wav

⚠️ −14 LUFS is the widely-cited YouTube target but is not officially published by YouTube (the AES streaming recommendation is −16 LUFS / −1.5 dBTP). Treat −14 LUFS / −1 dBTP as a sensible default, not gospel. - LANDR / eMastered / BandLab free tiers — preview-only; you must pay to download a usable/commercial master. Matchering + ffmpeg beats them at $0.

2.4 Edit / convert

Audacity (GPLv3) for manual multitrack edits; ffmpeg for format/codec, sample-rate, trim, normalize; SoundTouch / Rubber Band for pitch/tempo. Output is yours.

3. Translation, subtitles, dubbing

To take Hindi/Hinglish content global — commercial-clean.

3.1 Translation — hosted free tiers

3.2 Translation — open weights

3.3 Subtitles

Pipeline: Whisper / faster-whisper (transcribe — MIT) → IndicTrans2 / Azure (translate) → Subtitle Edit (MIT) or Aegisub for timing/styling/SRT → ffmpeg to burn or mux. All commercial-clean. (For karaoke word-timing, see AUDIO.md §3.4 — WhisperX.)

3.4 Dubbing (the genuinely hard one)

Fully voice-preserving, commercial-clean, $0 dubbing is still hard — the best speech-to-speech models (SeamlessM4T v2, NLLB) are CC-BY-NC. The clean path is to assemble it:

1. Transcribe → Whisper / faster-whisper
2. Translate → IndicTrans2 or Azure F0
3. Speak → OpenVoice (MIT, commercial voice cloning/conversion) or a commercial-clean TTS (Azure F0; see AUDIO.md §2)
4. Align / mux → ffmpeg + manual timing in Subtitle Edit

Hosted free dubbing apps (HeyGen ~3 videos/mo, Rask, Vozo, KapWing) are easy but their free-tier commercial rights/watermarks are ⚠️ unverified — check before release.

4. Visual assets and compositing

Two creative finishing powers: pull your subject off its background (matting) to composite over an AI-generated scene, and spin up 3D props/visualizers — all $0 and commercial-clean. Run everything in ComfyUI on Apple Silicon (MPS) or free Colab/Kaggle.

4.1 Background removal & video matting

⚠️ The popular BRIA RMBG (1.4 & 2.0) is CC-BY-NC — non-commercial, and it's the silent default in many "remove background" tools. Commercial-clean alternatives:

Pick: RVM for a person dancing in a music video (temporally stable soft alpha), BiRefNet for poster/thumbnail cutouts, SAM 2 to track a specific prop.

4.2 Image / text → 3D (props, visualizers, motion graphics)

Generate a mesh (GLB/OBJ) from one image or a prompt, then drop it into Blender / After Effects for spinning logos, props, or abstract visualizers. ~8–12 GB VRAM; a 16 GB+ Mac runs these locally.

Pick: TRELLIS for geometry, Hunyuan3D for textured props (mind the region clause). Avoid the free web apps — their free-tier outputs are non-commercial.

5. The $0 finishing pipelines

Three end-to-end recipes, every step commercial-clean:

A. Music master (audio): Demucs (optional stems/karaoke) → DeepFilterNet (optional vocal cleanup) → Matchering (reference master) → ffmpeg loudnorm → −14 LUFS / −1 dBTP WAV.

B. 4K / 60fps video master: Upscayl (Real-ESRGAN 4×) → chaiNNer (FILM, or RIFE if your weights verify → 60fps) → DaVinci Resolve Free (grade + encode H.265/ProRes). Offload to Kaggle if on an 8 GB Mac.

C. Global reach (subtitles + dub): Whisper → IndicTrans2 / Azure F0 → Subtitle Edit (SRT) → (optional) OpenVoice dub → ffmpeg mux.

Total cost: $0. Commercial exposure: none, as long as you stay on the green-light tools in the licensing landmines.

Sources

Primary sources fetched/verified June 2026 (representative):

• Video — upscaling/interp/restore: github.com/xinntao/Real-ESRGAN (BSD-3); github.com/JingyunLiang/SwinIR; github.com/Fanghua-Yu/SUPIR (non-commercial); github.com/hzwer/Practical-RIFE; github.com/google-research/frame-interpolation (FILM, Apache); github.com/TencentARC/GFPGAN (Apache); github.com/sczhou/CodeFormer/blob/master/LICENSE (NTU S-Lab, non-commercial).
• Video — apps: github.com/upscayl/upscayl (AGPL); github.com/chaiNNer-org/chaiNNer (GPL); blackmagicdesign.com/products/davinciresolve.
• Audio — separation/cleanup: github.com/facebookresearch/demucs + adefossez/demucs (MIT); github.com/Anjok07/ultimatevocalremovergui (MIT GUI); github.com/sigsep/open-unmix-pytorch (umxl = CC-BY-NC-SA); github.com/Rikorose/DeepFilterNet (MIT/Apache); github.com/resemble-ai/resemble-enhance (MIT).
• Audio — mastering/loudness: github.com/sergree/matchering (GPL-3.0); k.ylo.ph/2016/04/04/loudnorm.html (ffmpeg loudnorm two-pass); audacityteam.org.
• Translation/dubbing: github.com/AI4Bharat/IndicTrans2 (MIT); huggingface.co/google/madlad400-3b-mt (Apache); huggingface.co/Helsinki-NLP (Opus-MT); huggingface.co/facebook/seamless-m4t-v2-large + /nllb-200-distilled-600M (CC-BY-NC); github.com/myshell-ai/OpenVoice (MIT); azure.microsoft.com/pricing/details/translator (F0 2M chars/mo); developers.deepl.com/docs/resources/usage-limits (500k/mo); github.com/SubtitleEdit/subtitleedit (MIT).

Quotas/licenses are point-in-time (June 2026) and change — re-verify any non-commercial flag and any "weights unstated" model before a commercial release. Corrections via PR welcome.

📝 Spotted a stale quota or a license that changed? This guide is open source — edit it on GitHub.