50 training photos

AI dataset generator for one identity

A single hero still is a fragile lock. Generate an auto dataset of training photos so later generations have coverage across angles and outfits. Stills are 4 credits; a ten-photo dataset pack is 40.

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Why datasets beat one reference

  1. 01

    Cover angles

    Front, 3/4, smile, serious, different crops. LoRA and Genome downstream both fail if every still is the same selfie.

  2. 02

    Cover wardrobe and light

    If the dataset is only golden hour bikini, the gym set will invent a sister.

  3. 03

    Then generate production

    Daily content should ride on the dataset distribution, not fight it.

Credit math (from the product FAQ)

Stills

A photo is 4 credits. A ten-photo dataset is 40 credits.

Auto dataset

Home positions auto dataset as 50 training photos — use it as the identity backbone, not as the public feed dump.

Fizzly’s LoRA advice, translated

Public LoRA guides say 10–30 curated stills, 20–30 as a sweet spot. Our auto dataset exists so you are not hand-picking from 400 messy gens.

Questions

Is this an ML dataset for researchers?+

No. It is a character lookbook/training pack for your influencer model inside fanv.ai — not ImageNet.

Related

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Generate a dataset