{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "mirros-lab-agentgarten--speed-up-rgb-preview-with-taehv-decoder",
 "repo": "MirroS-Lab/AgentGarten",
 "repo_url": "https://github.com/MirroS-Lab/AgentGarten",
 "repo_slug": "mirros-lab-agentgarten",
 "title": "Decode renderer RGB preview faster with TAEHV",
 "page_title": "How to decode renderer RGB preview faster with TAEHV with Agent Garten",
 "summary": "Attach the TAEHV decoder to speed up RGB output while encoding stays on the Wan encoder.",
 "who": "A researcher who reviews many renderer previews and finds RGB decoding slows each review cycle.",
 "problem": "Full Wan decoding makes it slow to check many rendered clips during a review session.",
 "outcome": "Faster RGB decoding for previews, with encoding unchanged on the Wan encoder.",
 "steps": [
  "Complete the install and weight download steps from the Get started section.",
  "Download `taew2_2_super.pth` from the TAEHV project at https://github.com/madebyollin/taehv to a local path. (inferred, check the README)",
  "Add `model.conditioner.codec.decoder={_target_:wm.codecs.TAEW22SuperDecoder,pretrained_path:/path/to/taew2_2_super.pth}` as an extra override to the run command, replacing the path with yours.",
  "Run the validation render from the first use case, for example `bash scripts/run.sh experiment=cosmos3/bidirectional train.max_iterations=0 train.validate_at_start=true trainer.callbacks.samples.every_n=1` with the override added. (inferred, check the README)"
 ],
 "agent_prompt": "Using the AgentGarten repo at <repo path>, add the TAEHV decoder override for the file at <taew2_2_super.pth path> and render the validation clips. Expected output: the same comparison videos under samples/, with RGB decoded through the TAEHV decoder. Verify that the decoder path in the override exists on disk before reporting success.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "2 hours",
 "basis": "readme",
 "caveat": "The TAEHV decoder only changes RGB decoding, and the README states that encoding stays on the Wan encoder.",
 "category": "Research",
 "tags": [
  "Research"
 ],
 "lang": "python",
 "requirements": [
  "A CUDA host with Python 3.11+ and PyTorch 2.9+",
  "Access to the Hugging Face weights for Cosmos3-Nano and Wan2.2-TI2V-5B, plus disk space for them",
  "Git and the hf command-line tool",
  "For training: a JSONL manifest of your own clips with depth and normal data"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.7,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/mirros-lab-agentgarten/speed-up-rgb-preview-with-taehv-decoder/",
 "md": "https://dedupedai.com/use-cases/mirros-lab-agentgarten/speed-up-rgb-preview-with-taehv-decoder/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/mirros-lab-agentgarten--speed-up-rgb-preview-with-taehv-decoder.json",
 "api_version": "v1"
}