catvton-train-reconstruction
Specialized pipeline for training and reviewing CatVTON models with support for local dataset annotations and mask generation.
Install
mkdir -p .claude/skills/catvton-train-reconstruction && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/14776" && unzip -o skill.zip -d .claude/skills/catvton-train-reconstruction && rm skill.zipInstalls to .claude/skills/catvton-train-reconstruction
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Use when implementing, reviewing, or extending CatVTON-style training in this repository. Focus on DressCode-based training, agnostic mask generation from local dataset annotations, and attention checkpoint export compatible with CatVTON inference layouts.Key capabilities
- →Generate agnostic masks for training
- →Validate training pair datasets
- →Export attention checkpoints
- →Review CatVTON model implementation
- →Manage CatVTON-style training in this repository
- →Validate dataset logic against DressCode files
How it works
This skill manages CatVTON-style training within a specific repository, focusing on generating agnostic masks and ensuring checkpoint compatibility.
Inputs & outputs
When to use catvton-train-reconstruction
- →Generate agnostic masks for training
- →Validate training pair datasets
- →Export attention checkpoints
- →Review CatVTON model implementation
About this skill
CatVTON Train Reconstruction
Use this skill for work inside CatVTON_practice.
What this repo is for
This project is a practice implementation of CatVTON-style training centered on the local DressCode dataset under data/DressCode.
The important local constraint is that DressCode here does not already contain agnostic_masks, so training must either generate them on the fly or cache them before use.
Workflow
- Read
references/repo-notes.md. - Keep the implementation scoped to this repo before reaching back into the original CatVTON repo.
- Preserve CatVTON-compatible checkpoint layout:
<output>/<dataset_tag>/attention
- Prefer self-attention-only training unless the user explicitly asks for a different fine-tuning target.
- When changing dataset logic, validate against the actual files under
data/DressCode.
Validation rules
- Confirm
train_pairs.txtand test pair files still parse. - Confirm masks are generated or loaded consistently.
- Confirm the saved checkpoint contains attention weights that can be reloaded later.
References
references/repo-notes.md
When not to use it
- →When the task is outside the CatVTON_practice repository
- →When the dataset is not local DressCode
- →When not focused on CatVTON-style training
Limitations
- →Training is centered on the local DressCode dataset under data/DressCode
- →Implementation is scoped to this repo before reaching back into the original CatVTON repo
- →Training must either generate agnostic_masks on the fly or cache them before use
How it compares
This skill provides a structured workflow for CatVTON training with specific dataset and checkpoint constraints, unlike a generic training setup.
Compared to similar skills
catvton-train-reconstruction side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| catvton-train-reconstruction (this skill) | 0 | — | No flags | Intermediate |
| robotics-code-generator | 14 | 8mo | No flags | Advanced |
| modal | 5 | 7mo | Review | Intermediate |
| hugging-face-cli | 3 | 6mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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