AIFENG DCS · POD AI Reality Lab

Reality lab for POD AI · RTX 5080 16GB · open-source models + self-built pipeline route · Language: zh-CN | id-ID | en-US

Technology Selection Table

ComponentOpen-source licenseVRAM requirementFit conclusion for this machineAlternative comparison
ComfyUIGPL-3.0Lightweight itself; VRAM depends on the loaded modelPerfect fit: portable build, no install, ASCII-only pathvs hand-written inference framework: no wheel-reinvention, ready node ecosystem
SDXL 1.0OpenRAIL-Mfp8 ≈7 GB16 GB VRAM is ample; ~10–20 s per imagevs FLUX.1-dev: faster, looser license, slightly weaker quality
FLUX.1-dev fp8Non-commercial licensefp8 ≈12 GBRuns in 16 GB; commercial use needs license review — prefer SDXL or FLUX.1-schnell in productionvs SDXL: higher quality but slower, restricted license
ControlNet (SDXL)Apache-2.0≈2–3 GB, shares VRAM with the base modelFits: line-art control is a core need in the print industryvs uncontrolled generation: composition control is night and day
IPAdapterApache-2.0≈1–2 GBFits: reference-style transfer = the key to print-pattern extractionvs training a LoRA: train-free plug-and-play, slightly less precise
rembg (U²-Net)MITRuns on CPU, GPU optionalPerfect: background removal is the first prepress stepvs paid remove.bg API: local, free, unlimited
Real-ESRGANBSD-3-Clause≈2 GBPerfect: upscales small art to print resolutionvs paid Topaz / waifu2x: same-tier quality, free
vtracerMIT / Apache-2.0Pure CPUPerfect: bitmap-to-vector for DTF/UV cutlinesvs Adobe Illustrator subscription: free CLI, batch-friendly
OpenCVApache-2.0Pure CPUPerfect: DPI check + bleed + safe area fully automaticvs commercial preflight software: free and embeddable in our own pipeline
PillowHPND (PIL)Pure CPUPerfect: text layout / color pick / recolor fully scriptedvs manual Photoshop: batch orders are orders of magnitude faster
Ideogram APIPaid closed-sourceCloud, no local loadFallback only: complex ID/EN text posters (local models render text poorly)vs local SDXL text: far higher text accuracy, pay-per-image, ≤5% share
⚠ FLUX License Notice
FLUX.1-dev carries a non-commercial license, so commercial use needs separate review; for production we recommend SDXL as the primary choice, or FLUX.1-schnell (Apache-2.0, commercial-friendly). This table states it as it is — nothing hidden.

🔍 Honesty Statement

Once again: Lingtu's internal implementation cannot be verified, but the industry-standard practice = open-source models + self-built workflow. Every component above is a public open-source project — licenses, VRAM, and alternatives are all transparent.

PENDING · awaiting boss approval
⚠ The boss is asked again before every single step starts