Nv Generate Mr

NV-Generate-MR

Purpose

• Used for generating synthetic body MRI volumes with NV-Generate-CTMR rflow-mr. Not for paired masks or production training data.
• Use the wrapper exactly as documented; do not replace the upstream entrypoint with a handwritten implementation.
• Do not write custom inference code for normal runs. The wrapper owns config staging, output paths, and validation.
• Manifest I/O: inputs are model_config_override; outputs are synthetic_mr_volumes and result_json.

Instructions

• Read skill_manifest.yaml before changing arguments, side effects, or validation gates.
• Run scripts/run_mr.py through the documented command below; keep outputs under a caller-provided run directory.
• If a host agent exposes run_script, use run_script("scripts/run_mr.py", args=[...]); otherwise run the Bash/Python command shown below.
• Emit a single bash code block, and keep the python -m pip install -r "$NV_GENERATE_ROOT/requirements.txt" step in that same command — the runtime may be a fresh environment without nibabel/MONAI, so dropping the install fails with ModuleNotFoundError.
• Do not add rm, mkdir, or any cleanup of --output-dir; the wrapper creates it. Use a fresh --output-dir instead of deleting one.
• Check the emitted JSON and paired verifier guidance before treating the run as evidence.

Available Scripts

Prerequisites

• Runtime requirements: GPU/CUDA when declared by the manifest; Python packages listed in runtime.side_effects.pip_packages.
• Side effects: writes generated outputs under the caller's --output-dir, may cache model assets under ~/.cache/huggingface/, and may contact https://huggingface.co or https://github.com during setup.
• Run commands from the repository root unless an existing section below says otherwise.

Limitations

• This is a thin wrapper. Inference, sampling, and decoding are delegated entirely to NVIDIA-Medtech/NV-Generate-CTMR's scripts.diff_model_infer. Do not modify code under $NV_GENERATE_ROOT or the repo-local fallback at .workbench_data/upstreams/NV-Generate-CTMR.
• rflow-mr generates image-only synthetic MRI volumes. It does not emit paired segmentation masks.
• The upstream README recommends rflow-mr-brain instead for brain MRI synthesis; use skills/nv-generate-mr-brain for that path.
• NV-Generate-MR weights are listed by upstream as NVIDIA Non-Commercial. Do not use outputs as production training data without legal and quality review.
• Not for clinical deployment, clinical interpretation, autonomous diagnosis, regulatory submission.

Troubleshooting

Wraps the upstream NVIDIA-Medtech/NV-Generate-CTMR MR image-only generation workflow. The wrapper does not reimplement diffusion sampling or autoencoder decoding. It stages config overrides, runs the documented python -m scripts.diff_model_infer command for rflow-mr, then summarizes the generated NIfTI volume.

Exact Runnable Surface

For user run commands in a fresh benchmark environment, use this setup plus repo-root wrapper command exactly:

export NV_GENERATE_ROOT="${NV_GENERATE_ROOT:-$HOME/.cache/nvidia-skills/upstreams/NV-Generate-CTMR-61c4ec7}" && \
python -m pip install -r "$NV_GENERATE_ROOT/requirements.txt" && \
python skills/nv-generate-mr/scripts/run_mr.py PATH_TO_MR_CONFIG.json --output-dir OUT_DIR --modality mri_t1 --random-seed 0

Do not invent generate.sh, infer.py, Medical AI Skills run, or python -m nv_generate_mr commands. PATH_TO_MR_CONFIG.json must be the user's supplied request path.