🎬 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
| Need | Use (commercial-safe) | Notes |
|---|---|---|
| 🔍 4K upscale | Real-ESRGAN (BSD-3) via Upscayl (Mac app) | Native Apple Silicon, no setup. |
| 🎞️ Smooth 60fps | Google FILM (Apache-2.0) | RIFE is faster but its weights license is disputed — see landmines. |
| 🙂 Face restore | GFPGAN / RestoreFormer (Apache-2.0) | Not CodeFormer (non-commercial). |
| 🎚️ Stems / karaoke | Demucs (MIT) via UVR5 GUI (MPS on Mac) | SOTA open separation, clean license. |
| 🧹 Vocal cleanup | DeepFilterNet (MIT/Apache) / Resemble Enhance (MIT) | 48 kHz denoise, real-time on CPU. |
| 🎛️ Mastering + loudness | Matchering (GPL) + ffmpeg loudnorm → −14 LUFS |
Output is 100% yours to monetize. |
| 🌐 Translate (Indian langs) | IndicTrans2 (MIT) or Azure Translator F0 (2M chars/mo) | The two best commercial-clean routes. |
| 📝 Subtitles | Whisper → translate → Subtitle Edit (MIT) | Burn with ffmpeg. |
| 🗣️ Dub (voice-preserving) | OpenVoice (MIT) + commercial TTS | SeamlessM4T/NLLB are non-commercial. |
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
| Tool | Restriction | Domain |
|---|---|---|
| SUPIR | academic / non-commercial license | Upscaling |
| CodeFormer | NTU S-Lab License 1.0 (research only) — bundled in most WebUIs; untick it | Face restore |
| Practical-RIFE weights | code is MIT but the weights' commercial status is disputed/version-dependent | 60fps interpolation |
Open-Unmix umxl (default model) |
CC BY-NC-SA 4.0 | Stem separation |
| SeamlessM4T v2 · NLLB-200 · Aya Expanse · TowerInstruct | CC-BY-NC | Translation / dubbing |
| Coqui XTTS-v2 | CPML (non-commercial, incl. outputs) | Dubbing voice |
| ElevenLabs free tier | commercial license only from Starter ($5/mo) | Dubbing voice |
| ❔ Mel-Band Roformer / many MDX-Net checkpoints | code MIT but weights often have no stated license — treat as unverified | Stem separation |
| BRIA RMBG 1.4 / 2.0 | CC-BY-NC — the silent default in many "remove background" tools | Background removal |
| Stable Zero123 | Stability non-commercial research license | Image→3D |
| Meshy · Tripo · Rodin (free tiers) | free web outputs are CC-BY-NC (commercial needs a paid plan) | Image→3D |
✅ 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
| Model | License | Commercial? | Notes |
|---|---|---|---|
| Real-ESRGAN 🥇 | BSD-3-Clause | ✅ | Fast, low VRAM (runs on 8 GB Macs); the default. Image + video variants. |
| SwinIR / BSRGAN | Apache-2.0 | ✅ | Heavier, more natural textures (less "plastic"); MPS on Mac. |
| APISR | GPL-3.0 | ✅ (output yours) | Best for anime / line-art renders; wants 32 GB+ unified memory. |
| SUPIR | ⚠️ custom non-commercial | ❌ | Stunning detail, but legally radioactive for monetized work + 24 GB VRAM. Skip. |
1.2 Frame interpolation → 60fps
| Model | License | Commercial? | Notes |
|---|---|---|---|
| Google FILM 🥇 | Apache-2.0 | ✅ | Unambiguously safe; great on large motion (can wobble backgrounds). The pick for monetized 60fps. |
| Practical-RIFE | code MIT; weights disputed | ⚠️ verify | Fastest + smoothest (NCNN on Apple Silicon). Some sources say v4.x weights are MIT, others "research only" — verify your exact version, or use FILM. |
| FLAVR / IFRNet | Apache-2.0 / MIT | ✅ | Solid, but lack the polished Mac/NCNN GUIs RIFE has. |
1.3 Face & video restoration
| Model | License | Commercial? | Notes |
|---|---|---|---|
| GFPGAN 🥇 | Apache-2.0 | ✅ | Fixes mangled AI faces; can over-smooth skin. Legally bulletproof. |
| RestoreFormer | Apache-2.0 | ✅ | Slightly more natural texture than GFPGAN. |
| DDColor | Apache-2.0 | ✅ | Colorize B&W/archival-style footage. |
| CodeFormer | ⚠️ NTU S-Lab (non-commercial) | ❌ | Best quality — but bundled into nearly every WebUI/node graph. Actively untick it on a monetized channel. |
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
.pthmodels (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
| Tool | License (code / weights) | Commercial? | Notes |
|---|---|---|---|
| Demucs / HT-Demucs v4 🥇 | MIT / MIT | ✅ | SOTA open separation (SDR 9.0). --two-stems=vocals → instrumental/karaoke. CPU-native on Mac (~1.5× track length). Active fork: adefossez/demucs. |
| UVR5 (Ultimate Vocal Remover) | MIT GUI / models vary | ✅ GUI; ⚠️ per-model | Mac arm64 .dmg with MPS GPU; the friendliest way to run Demucs/MDX on M-series. Also bundles Matchering. |
| Mel-Band Roformer | MIT code / unstated weights | ⚠️ | Best vocal isolation, but the popular checkpoints have no license — avoid for monetized output unless you confirm terms. |
| Spleeter | MIT | ✅ | Older, and ⚠️ TensorFlow has M1 issues — use on Colab if at all. |
Open-Unmix umxl |
MIT code / CC BY-NC-SA | ❌ | Default model is non-commercial. Don't. |
2.2 Denoise / cleanup (apply to an isolated vocal stem)
| Tool | License | Commercial? | Notes |
|---|---|---|---|
| DeepFilterNet (2/3) 🥇 | MIT or Apache-2.0 | ✅ | 48 kHz, real-time on CPU; ships a standalone deep-filter binary. |
| Resemble Enhance | MIT | ✅ | Denoise + restoration (44.1 kHz); free HF Space. |
| VoiceFixer | MIT | ✅ | Restores clipped/reverberant/noisy speech. |
| RNNoise | BSD-3 | ✅ | Lightweight real-time voice denoise (Audacity plugin). |
| Adobe Podcast — Enhance Speech | proprietary free web | ⚠️ verify | Excellent quality; commercial terms not verifiable from their SPA. |
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
| Service | Free quota | Hindi/Indic | Commercial on free? |
|---|---|---|---|
| Azure Translator F0 🥇 | 2M chars/mo | strong, many Indic langs | ✅ (you already use Azure) |
| DeepL API Free | 500k chars/mo | now lists Hindi + Indic | ✅ (no NC clause found) |
| Google Cloud Translation | 500k chars/mo + $300/90d | strong hi + Indic |
✅ |
3.2 Translation — open weights
| Model | License | Commercial? | Notes |
|---|---|---|---|
| IndicTrans2 (AI4Bharat) 🥇 | MIT | ✅ | Best commercial-clean open MT for Indian languages (all 22). 200M distilled runs on Mac/Colab. |
| Opus-MT / Helsinki-NLP | MIT / Apache | ✅ | Light CPU baseline; modest hi→en quality. |
| MADLAD-400 | Apache-2.0 | ✅ | Broad multilingual incl. Hindi; not Indic-specialized. |
| NLLB-200 · Aya Expanse · TowerInstruct | ⚠️ CC-BY-NC | ❌ | Strong, but non-commercial — avoid for monetized work. |
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:
- Transcribe → Whisper / faster-whisper
- Translate → IndicTrans2 or Azure F0
- Speak → OpenVoice (MIT, commercial voice cloning/conversion) or a commercial-clean TTS (Azure F0; see AUDIO.md §2)
- 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:
| Tool | License | Commercial? | Video | Best at |
|---|---|---|---|---|
| Robust Video Matting (RVM) | GPL-3.0 | ✅ (your render is yours) | ✅ real-time | soft, flicker-free alpha for a moving person |
| BiRefNet | MIT | ✅ | stills (per-frame) | highest-quality stills/hair — the RMBG replacement |
| Meta SAM 2 | Apache-2.0 | ✅ | ✅ (tracking) | tracking a prop across frames (hard mask → blur edge) |
| MODNet | Apache-2.0 | ✅ | ✅ | fast portrait matting |
| rembg (U²-Net / IS-Net) | MIT | ✅ | stills/video | one-command CLI / app |
| InSPyReNet | MIT | ✅ | stills | very high-res salient cutouts |
| ~~BRIA RMBG 1.4 / 2.0~~ | CC-BY-NC | ❌ | stills | (avoid on monetized work) |
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.
| Tool | License | Commercial? | Notes |
|---|---|---|---|
| Microsoft TRELLIS | MIT | ✅ | cleanest geometry; current open SOTA |
| Hunyuan3D 2.0 / 2.1 | Tencent Community | ✅ (you own the mesh) | best auto-texturing; ⚠️ license void in EU/UK/South Korea, <1M MAU |
| TripoSR | MIT | ✅ | fastest single-image → mesh |
| InstantMesh | Apache-2.0 | ✅ | multi-view → clean mesh |
| Stable Fast 3D | Stability Community | ✅ (<$1M rev) | quick textured mesh |
| ~~Stable Zero123~~ | NC research | ❌ | non-commercial |
| ~~Meshy / Tripo / Rodin~~ (free tiers) | CC-BY-NC TOS | ❌ | free web outputs are non-commercial |
Pick: TRELLIS for geometry, Hunyuan3D for textured props (mind the region clause). Avoid the free web apps — their free-tier outputs are non-commercial.
🍎 Apple Silicon: run all of the above in ComfyUI via Metal/MPS; a 16 GB+ Mac handles TRELLIS / BiRefNet / RVM locally. Offload heavier 3D to Kaggle's free T4 on an 8 GB machine.
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(ffmpegloudnormtwo-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.