Why consistency matters
**No pet photos required for video** — you can create any pet scenario from text alone. Optional **Pet Profile** (premium, with photo upload) is for when you want the strongest match to a real companion across scenes.
If you ask Midjourney or Stable Diffusion for ten images of your cat, each cat looks different — coat, pattern, eyes, build. The model keeps “inventing” a new animal.
Pet owners do not want “an orange tabby.” They want *their* Niancao.
Limits of older approaches
Prompt-only
Describe the pet in text: “orange tabby, amber eyes, white chest, medium build…”
Problems:
LoRA fine-tuning
Train a small LoRA on your pet’s photos so the model “knows” that face.
Problems:
How CopyDog approaches it
We blend several techniques:
1. Feature extraction (Pet Profile)
With optional **Pet Profile**, after 3–5 photo uploads the AI pulls structured traits:
Those fields live in the Pet Profile when you use it.
2. Prompt augmentation
On every image pass, we inject optimized descriptions — not naive string concat — so the base model reads them reliably.
3. Reference conditioning
When you’ve uploaded references, we use image-to-image and character-reference flows so scenes can lean on photos as well as prose.
4. Style lock
One project shares art-style parameters across shots so the look stays unified.
Results
With this stack, CopyDog keeps identity aligned across:
It is not pixel-perfect (today’s models have limits), but viewers should still recognize “that’s the same pet.”
What’s next
As models improve, we are exploring:
The goal: every pet gets a faithful “digital twin.”