Spaces:
Runtime error
Runtime error
Commit ·
ab1db83
0
Parent(s):
Initial commit: NV-Generate Gradio showcase
Browse filesA Hugging Face Spaces app that surfaces NVIDIA Medtech's three open-weight
3D medical image generators (CT, MR, MR Brain) under one console-style UI,
all running the latest MAISI-v2 rectified-flow variants.
Architecture
============
- app.py — Gradio Blocks entrypoint. Hero card landing → per-model workspace
switched via gr.Group visibility. Auto-clones the NV-Generate-CTMR upstream
repo on first run so the same flow works locally and on HF Spaces.
- pipelines/
base.py — GenerationRequest / GenerationResult dataclasses.
_runner.py — Shared driver: chdir into upstream, write modified configs
into configs/_temp/, invoke scripts.diff_model_infer or
scripts.inference, harvest the resulting NIfTI(s).
ct.py — Paired image + 132-class mask (rflow-ct).
mr.py — Multi-contrast MR image-only (rflow-mr).
mr_brain.py — Brain MR multi-sequence (rflow-mr-brain).
- viewer/
niivue_embed.py — Renders a self-contained niivue iframe with multiplanar
grid layout, cyan crosshair, corner pane labels
(Coronal / Sagittal / Axial / 3D), mask overlay with
per-label LUT, base64 NIfTI data URL loading.
colormaps.py — Deterministic anatomy color table + named legend HTML
generated from the upstream label_dict.json (~125
named CT classes).
- ui/
hero.py — Three datasheet cards with anatomical SVG glyphs,
use-case chips, license chips, decoupled
availability/license status, per-card accent color.
workspace_ct.py — CT controls (body region, anatomy multiselect,
X/Y/Z radios, spacing sliders) + niivue viewer +
W/L preset row + anatomy mask legend + downloads.
workspace_mr.py — MR variant with contrast dropdown + license banner.
workspace_mr_brain.py — Brain MR with sequence radio.
presets.py — XY/Z choices, sample preset chips, anatomy lists.
- utils/ nifti_io, windowing (CT W/L presets), weights (HF Hub lazy loader).
Design
======
"MAISI Console" aesthetic: navy-on-near-black palette with surgical NVIDIA
green accents, Geist Sans + Geist Mono, hairline borders, blueprint-grid
background overlay. Status chips for runtime/seed/steps after generation;
Generate button has disabled+spinner state during inference.
Pill-toggle pattern (filled green when active, outline on hover) is
consistent across body region, X/Y/Z voxel selectors, and the W/L preset row.
Deployment
==========
requirements.txt covers both the Gradio app deps and the upstream's
PyTorch/MONAI stack. README.md frontmatter is HF-Spaces ready: sdk: gradio,
sdk_version pinned, ZeroGPU @spaces.GPU decorator with 300s budget for CT
(longest inference) and 180s for MR/MR-Brain.
NV-Generate-CT and NV-Generate-MR-Brain weights are under the NVIDIA Open
Model License; NV-Generate-MR weights are non-commercial — the MR workspace
shows a visible amber banner reminding users of that restriction.
- .gitignore +48 -0
- README.md +89 -0
- app.py +1462 -0
- pipelines/__init__.py +3 -0
- pipelines/_runner.py +265 -0
- pipelines/base.py +37 -0
- pipelines/ct.py +49 -0
- pipelines/mr.py +28 -0
- pipelines/mr_brain.py +42 -0
- pre-build.sh +9 -0
- requirements.txt +17 -0
- ui/__init__.py +0 -0
- ui/hero.py +240 -0
- ui/presets.py +69 -0
- ui/workspace_ct.py +227 -0
- ui/workspace_mr.py +163 -0
- ui/workspace_mr_brain.py +150 -0
- utils/__init__.py +0 -0
- utils/nifti_io.py +16 -0
- utils/weights.py +6 -0
- utils/windowing.py +24 -0
- viewer/__init__.py +0 -0
- viewer/colormaps.py +70 -0
- viewer/niivue_embed.py +227 -0
.gitignore
ADDED
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+
# Upstream repo and downloaded weights
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repos/
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models/
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weights/
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output/
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embeddings/
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datasets/
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# Generated NIfTI artifacts
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*.nii
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+
*.nii.gz
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# Python
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__pycache__/
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*.py[cod]
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+
*$py.class
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*.so
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.Python
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.venv/
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venv/
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env/
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*.egg-info/
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.pytest_cache/
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# Environment
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.env
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.env.local
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# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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# OS
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.DS_Store
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Thumbs.db
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# Hugging Face cache
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.cache/
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huggingface/
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# MONAI working dir
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temp_work_dir/
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# Gradio
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gradio_cached_examples/
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flagged/
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README.md
ADDED
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---
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title: NV-Generate Synthetic Medical Imaging
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emoji: 🧠
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colorFrom: green
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colorTo: indigo
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sdk: gradio
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sdk_version: "6.14.0"
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app_file: app.py
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python_version: "3.11"
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pinned: true
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license: other
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license_name: nvidia-open-model-license
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license_link: https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/
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short_description: Synthetic 3D CT and MR generation with NVIDIA NV-Generate.
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---
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# NV-Generate · Synthetic Medical Imaging
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A unified Hugging Face Spaces demo for NVIDIA Medtech's three open-weight 3D
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medical image generators, all built on the MAISI-v2 rectified-flow architecture
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(~30 inference steps each).
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| Model | Modality | Output | Weights |
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|---|---|---|---|
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| **NV-Generate · CT** | Computed Tomography | Image + paired 132-class anatomy mask | [nvidia/NV-Generate-CT](https://huggingface.co/nvidia/NV-Generate-CT) |
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| **NV-Generate · MR** | MR (multi-contrast, multi-anatomy) | Image only | [nvidia/NV-Generate-MR](https://huggingface.co/nvidia/NV-Generate-MR) |
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| **NV-Generate · MR Brain** | Brain MR (T1 / T2 / FLAIR / SWI) | Image only | [nvidia/NV-Generate-MR-Brain](https://huggingface.co/nvidia/NV-Generate-MR-Brain) |
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## Features
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- Hero card landing → per-model workspace.
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- niivue WebGL multiplanar viewer (axial / coronal / sagittal + 3D render).
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- Paired 132-class anatomy mask overlay for CT (with deterministic per-label colormap + named legend).
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- Window/Level presets (Soft Tissue / Lung / Bone / Brain) on the CT viewer.
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- Direct NIfTI download of every generated volume + mask.
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- ZeroGPU support for HF Spaces (`@spaces.GPU` decorator).
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## Local development
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```bash
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pip install -r requirements.txt
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pip install -r repos/NV-Generate-CTMR/requirements.txt
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python app.py # http://localhost:7860
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```
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`app.py` auto-clones the upstream `NV-Generate-CTMR` inference repo into
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`./repos/` on first run (no separate `pre-build.sh` needed). Weights are
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downloaded lazily from the Hugging Face Hub the first time each model is
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exercised, then cached.
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## Hugging Face Spaces deployment
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Recommended hardware: **ZeroGPU** (A10G or H100), since each model needs ~16–80 GB
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VRAM depending on volume size.
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1. Create a new Space on huggingface.co with `sdk: gradio` (already set in this
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README's frontmatter).
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2. Push this repository:
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```bash
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git remote add space https://huggingface.co/spaces/<your-username>/nv-generate
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git push space main
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```
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3. In the Space's **Settings → Hardware**, select **ZeroGPU**.
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4. First build will install dependencies + clone the upstream repo. First
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generation on each model downloads weights into a persistent cache.
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## License
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| Component | License |
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|---|---|
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| This repo (Gradio glue) | Apache 2.0 |
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| Upstream `NV-Generate-CTMR` source | Apache 2.0 |
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| `NV-Generate-CT` weights | [NVIDIA Open Model License](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/) |
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| `NV-Generate-MR` weights | [**NVIDIA OneWay Non-Commercial License**](https://developer.download.nvidia.com/licenses/NVIDIA-OneWay-Noncommercial-License-22Mar2022.pdf) — academic / research use only |
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| `NV-Generate-MR-Brain` weights | [NVIDIA Open Model License](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/) |
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**Not for clinical diagnostics.** This is a research demo for synthetic data
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generation only.
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## Credits
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Built on the MAISI framework:
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- **MAISI-v1** — [WACV 2025 paper](https://arxiv.org/abs/2409.11169)
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- **MAISI-v2** — [AAAI 2026 paper](https://arxiv.org/abs/2508.05772)
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NVIDIA Medtech, University of Zurich, Istanbul Medipol, Forithmus.
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</content>
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</invoke>
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app.py
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|
| 1 |
+
"""
|
| 2 |
+
NV-Generate Showcase — Gradio app entrypoint.
|
| 3 |
+
|
| 4 |
+
Hero card landing → per-model workspace. Each model's Generate button is wrapped
|
| 5 |
+
with @spaces.GPU on Hugging Face Spaces (ZeroGPU); locally the decorator is a no-op.
|
| 6 |
+
"""
|
| 7 |
+
from __future__ import annotations
|
| 8 |
+
|
| 9 |
+
import os
|
| 10 |
+
import subprocess
|
| 11 |
+
import sys
|
| 12 |
+
from pathlib import Path
|
| 13 |
+
|
| 14 |
+
import gradio as gr
|
| 15 |
+
|
| 16 |
+
ROOT = Path(__file__).resolve().parent
|
| 17 |
+
sys.path.insert(0, str(ROOT))
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
def _ensure_upstream():
|
| 21 |
+
"""Clone the NV-Generate-CTMR inference repo on first run.
|
| 22 |
+
|
| 23 |
+
HF Spaces with `sdk: gradio` does not run shell scripts at build time, so we
|
| 24 |
+
bootstrap the upstream checkout here at module load. Idempotent: skips if
|
| 25 |
+
the directory already exists (local dev, subsequent Space restarts).
|
| 26 |
+
"""
|
| 27 |
+
upstream = ROOT / "repos" / "NV-Generate-CTMR"
|
| 28 |
+
if upstream.exists():
|
| 29 |
+
return
|
| 30 |
+
print("[nv-generate] cloning NV-Generate-CTMR upstream...", flush=True)
|
| 31 |
+
upstream.parent.mkdir(parents=True, exist_ok=True)
|
| 32 |
+
subprocess.run(
|
| 33 |
+
[
|
| 34 |
+
"git", "clone", "--depth", "1",
|
| 35 |
+
"https://github.com/NVIDIA-Medtech/NV-Generate-CTMR.git",
|
| 36 |
+
str(upstream),
|
| 37 |
+
],
|
| 38 |
+
check=True,
|
| 39 |
+
)
|
| 40 |
+
|
| 41 |
+
|
| 42 |
+
_ensure_upstream()
|
| 43 |
+
|
| 44 |
+
# ZeroGPU decorator — present on HF Spaces, optional locally.
|
| 45 |
+
try:
|
| 46 |
+
import spaces # type: ignore
|
| 47 |
+
spaces_gpu_ct = spaces.GPU(duration=300)
|
| 48 |
+
spaces_gpu_mr = spaces.GPU(duration=180)
|
| 49 |
+
spaces_gpu_mr_brain = spaces.GPU(duration=180)
|
| 50 |
+
except (ImportError, AttributeError):
|
| 51 |
+
def _identity(d=None): # noqa: ARG001
|
| 52 |
+
def deco(fn):
|
| 53 |
+
return fn
|
| 54 |
+
return deco
|
| 55 |
+
spaces_gpu_ct = _identity()
|
| 56 |
+
spaces_gpu_mr = _identity()
|
| 57 |
+
spaces_gpu_mr_brain = _identity()
|
| 58 |
+
|
| 59 |
+
from ui.hero import render_hero
|
| 60 |
+
from ui import workspace_ct, workspace_mr, workspace_mr_brain
|
| 61 |
+
|
| 62 |
+
|
| 63 |
+
CSS = """
|
| 64 |
+
@import url('https://fonts.googleapis.com/css2?family=Geist:wght@300;400;500;600;700&family=Geist+Mono:wght@400;500;600&display=swap');
|
| 65 |
+
|
| 66 |
+
:root {
|
| 67 |
+
/* Navy / blue-black palette — distinctly blue, never gray */
|
| 68 |
+
--bg-0: #06102a;
|
| 69 |
+
--bg-1: #0a1530;
|
| 70 |
+
--bg-2: #0e1838;
|
| 71 |
+
--panel: #0e1b3a;
|
| 72 |
+
--panel-2: #142348;
|
| 73 |
+
--line: rgba(140, 180, 240, 0.12);
|
| 74 |
+
--line-strong: rgba(140, 180, 240, 0.22);
|
| 75 |
+
--line-bright: rgba(140, 180, 240, 0.38);
|
| 76 |
+
--text: #ecf0fa;
|
| 77 |
+
--text-2: #b0bcd5;
|
| 78 |
+
--muted: #7280a0;
|
| 79 |
+
--muted-2: #4a5778;
|
| 80 |
+
|
| 81 |
+
--green: #76b900;
|
| 82 |
+
--green-glow: rgba(118, 185, 0, 0.55);
|
| 83 |
+
--green-soft: rgba(118, 185, 0, 0.10);
|
| 84 |
+
--warn: #f6c861;
|
| 85 |
+
--warn-soft: rgba(246, 200, 97, 0.10);
|
| 86 |
+
|
| 87 |
+
--ct: #76b900;
|
| 88 |
+
--mr: #5fb4ff;
|
| 89 |
+
--mrb: #b48aff;
|
| 90 |
+
|
| 91 |
+
--font-sans: "Geist", ui-sans-serif, system-ui, -apple-system, "Segoe UI", sans-serif;
|
| 92 |
+
--font-mono: "Geist Mono", ui-monospace, "JetBrains Mono", "SF Mono", monospace;
|
| 93 |
+
--num: "Geist Mono", ui-monospace, monospace;
|
| 94 |
+
|
| 95 |
+
--container: 1240px;
|
| 96 |
+
--gutter: 32px;
|
| 97 |
+
}
|
| 98 |
+
|
| 99 |
+
/* ─────────────── base + blueprint grid ─────────────── */
|
| 100 |
+
/* Override Gradio Base theme tokens that paint a default gray fill across the app */
|
| 101 |
+
.gradio-container,
|
| 102 |
+
.gradio-container *,
|
| 103 |
+
gradio-app {
|
| 104 |
+
--body-background-fill: transparent !important;
|
| 105 |
+
--body-background-fill-dark: transparent !important;
|
| 106 |
+
--background-fill-primary: transparent !important;
|
| 107 |
+
--background-fill-primary-dark: transparent !important;
|
| 108 |
+
--background-fill-secondary: transparent !important;
|
| 109 |
+
--background-fill-secondary-dark: transparent !important;
|
| 110 |
+
--block-background-fill: transparent !important;
|
| 111 |
+
--block-background-fill-dark: transparent !important;
|
| 112 |
+
--panel-background-fill: transparent !important;
|
| 113 |
+
--panel-background-fill-dark: transparent !important;
|
| 114 |
+
--color-background-primary: transparent !important;
|
| 115 |
+
}
|
| 116 |
+
|
| 117 |
+
html { background: #010206 !important; }
|
| 118 |
+
html, body {
|
| 119 |
+
color: var(--text) !important;
|
| 120 |
+
font-family: var(--font-sans);
|
| 121 |
+
font-feature-settings: "ss01", "cv11", "tnum";
|
| 122 |
+
}
|
| 123 |
+
|
| 124 |
+
body {
|
| 125 |
+
background-image:
|
| 126 |
+
/* Concentrated blue glow behind the hero only — not page-wide */
|
| 127 |
+
radial-gradient(ellipse 1100px 600px at 50% 220px, rgba(70, 140, 230, 0.16), transparent 65%),
|
| 128 |
+
/* NVIDIA green hint warming the top-left of the page */
|
| 129 |
+
radial-gradient(ellipse 700px 380px at 18% -40px, rgba(118, 185, 0, 0.06), transparent 70%),
|
| 130 |
+
/* Cool purple sweep at lower-right (very faint) */
|
| 131 |
+
radial-gradient(ellipse 900px 600px at 108% 108%, rgba(140, 100, 220, 0.06), transparent 60%),
|
| 132 |
+
/* Architectural blueprint grid — dark lines for blueprint-paper feel */
|
| 133 |
+
linear-gradient(rgba(0, 0, 6, 0.42) 1px, transparent 1px),
|
| 134 |
+
linear-gradient(90deg, rgba(0, 0, 6, 0.42) 1px, transparent 1px),
|
| 135 |
+
/* Near-black base with a whisper of navy — panels now pop against this */
|
| 136 |
+
linear-gradient(180deg, #050810 0%, #02040c 50%, #010206 100%) !important;
|
| 137 |
+
background-size: auto, auto, auto, 32px 32px, 32px 32px, auto;
|
| 138 |
+
background-attachment: fixed, fixed, fixed, fixed, fixed, fixed;
|
| 139 |
+
background-color: #010206 !important;
|
| 140 |
+
}
|
| 141 |
+
|
| 142 |
+
/* ─────────────── film-grain noise overlay ─────────────── */
|
| 143 |
+
/* Breaks gradient banding, adds photographic warmth across every screenshot. */
|
| 144 |
+
body::before {
|
| 145 |
+
content: "";
|
| 146 |
+
position: fixed; inset: 0;
|
| 147 |
+
z-index: 0;
|
| 148 |
+
pointer-events: none;
|
| 149 |
+
background-image: url("data:image/svg+xml;utf8,%3Csvg viewBox='0 0 200 200' xmlns='http://www.w3.org/2000/svg'%3E%3Cfilter id='n'%3E%3CfeTurbulence type='fractalNoise' baseFrequency='0.85' numOctaves='3' stitchTiles='stitch'/%3E%3CfeColorMatrix values='0 0 0 0 0.6 0 0 0 0 0.7 0 0 0 0 0.9 0 0 0 1 0'/%3E%3C/filter%3E%3Crect width='100%25' height='100%25' filter='url(%23n)'/%3E%3C/svg%3E");
|
| 150 |
+
background-size: 240px 240px;
|
| 151 |
+
opacity: 0.045;
|
| 152 |
+
mix-blend-mode: overlay;
|
| 153 |
+
}
|
| 154 |
+
|
| 155 |
+
/* ─────────────── one-time scanline sweep on page load ─────────────── */
|
| 156 |
+
body::after {
|
| 157 |
+
content: "";
|
| 158 |
+
position: fixed;
|
| 159 |
+
left: 0; right: 0; top: -8px;
|
| 160 |
+
height: 2px;
|
| 161 |
+
z-index: 9999;
|
| 162 |
+
pointer-events: none;
|
| 163 |
+
background: linear-gradient(90deg,
|
| 164 |
+
transparent 5%,
|
| 165 |
+
rgba(118, 185, 0, 0.35) 30%,
|
| 166 |
+
rgba(118, 185, 0, 0.85) 50%,
|
| 167 |
+
rgba(118, 185, 0, 0.35) 70%,
|
| 168 |
+
transparent 95%);
|
| 169 |
+
filter: blur(3px);
|
| 170 |
+
animation: page-scanline 1.8s cubic-bezier(.4,.0,.2,1) 0.4s 1 forwards;
|
| 171 |
+
opacity: 0;
|
| 172 |
+
}
|
| 173 |
+
@keyframes page-scanline {
|
| 174 |
+
0% { transform: translateY(0); opacity: 0; }
|
| 175 |
+
8% { opacity: 0.9; }
|
| 176 |
+
50% { opacity: 1; }
|
| 177 |
+
90% { opacity: 0.4; }
|
| 178 |
+
100% { transform: translateY(100vh); opacity: 0; }
|
| 179 |
+
}
|
| 180 |
+
|
| 181 |
+
/* All Gradio root / wrapper elements stay transparent so body bg shows through */
|
| 182 |
+
gradio-app, gradio-app > div, gradio-app .main, gradio-app .wrap,
|
| 183 |
+
gradio-app .contain, gradio-app #root, .app, .main, .wrap, .contain {
|
| 184 |
+
background: transparent !important;
|
| 185 |
+
background-color: transparent !important;
|
| 186 |
+
}
|
| 187 |
+
|
| 188 |
+
.gradio-container {
|
| 189 |
+
max-width: var(--container) !important;
|
| 190 |
+
padding: 0 var(--gutter) !important;
|
| 191 |
+
background: transparent !important;
|
| 192 |
+
background-color: transparent !important;
|
| 193 |
+
font-family: var(--font-sans) !important;
|
| 194 |
+
margin: 0 auto !important;
|
| 195 |
+
}
|
| 196 |
+
|
| 197 |
+
/* Override Gradio's default panel chrome — every wrapper class that can show bg */
|
| 198 |
+
.gradio-container .form, .gradio-container .gap, .gradio-container .panel,
|
| 199 |
+
.gradio-container .block, .gradio-container .gr-box, .gradio-container .gr-group,
|
| 200 |
+
.gradio-container .gr-padded, .gradio-container > .main, .gradio-container > .wrap,
|
| 201 |
+
.gradio-container .styler, .gradio-container .container, .gradio-container .row,
|
| 202 |
+
.gradio-container .column {
|
| 203 |
+
background: transparent !important;
|
| 204 |
+
background-color: transparent !important;
|
| 205 |
+
border: none !important;
|
| 206 |
+
box-shadow: none !important;
|
| 207 |
+
}
|
| 208 |
+
|
| 209 |
+
/* gr.HTML wraps its value in a .html-container div with horizontal padding.
|
| 210 |
+
Zero the PADDING so HTML blocks (ws-intro, viewer-strip, legend, status) sit
|
| 211 |
+
flush against the column edge; leave margin alone so children's own
|
| 212 |
+
margin-bottom (e.g. .ws-intro { margin: 0 0 28px }) still creates space below. */
|
| 213 |
+
.gradio-container .html-container,
|
| 214 |
+
.gradio-container [class*="html-container"] {
|
| 215 |
+
padding: 0 !important;
|
| 216 |
+
background: transparent !important;
|
| 217 |
+
}
|
| 218 |
+
/* The hero/workspace gr.Group wrappers must not add their own chrome */
|
| 219 |
+
.hero, .workspace {
|
| 220 |
+
background: transparent !important;
|
| 221 |
+
background-color: transparent !important;
|
| 222 |
+
border: 0 !important; padding: 0 !important;
|
| 223 |
+
}
|
| 224 |
+
.hero > .gap, .workspace > .gap { padding: 0 !important; background: transparent !important; }
|
| 225 |
+
|
| 226 |
+
.dot { width: 6px; height: 6px; border-radius: 50%; display: inline-block; background: var(--green); box-shadow: 0 0 6px var(--green-glow); }
|
| 227 |
+
.dot-pulse { animation: dotpulse 2s ease-in-out infinite; }
|
| 228 |
+
@keyframes dotpulse { 0%, 100% { opacity: 1; } 50% { opacity: 0.35; } }
|
| 229 |
+
@keyframes fadein { from { opacity: 0; transform: translateY(-4px); } to { opacity: 1; transform: none; } }
|
| 230 |
+
|
| 231 |
+
/* ─────────────── masthead ─────────────── */
|
| 232 |
+
.masthead {
|
| 233 |
+
display: flex; align-items: center; justify-content: space-between;
|
| 234 |
+
height: 56px;
|
| 235 |
+
border-bottom: 1px solid var(--line);
|
| 236 |
+
font-family: var(--font-sans);
|
| 237 |
+
animation: fadein 0.4s ease both;
|
| 238 |
+
}
|
| 239 |
+
.masthead-brand {
|
| 240 |
+
display: flex; align-items: center; gap: 12px;
|
| 241 |
+
text-decoration: none; color: var(--text);
|
| 242 |
+
}
|
| 243 |
+
.nv-mark {
|
| 244 |
+
display: inline-flex; align-items: center; justify-content: center;
|
| 245 |
+
width: 28px; height: 22px;
|
| 246 |
+
background: var(--green); color: #000;
|
| 247 |
+
font-family: var(--font-mono); font-weight: 700; font-size: 11px;
|
| 248 |
+
letter-spacing: 0.04em;
|
| 249 |
+
clip-path: polygon(0 0, 100% 0, 100% 70%, 86% 100%, 0 100%);
|
| 250 |
+
}
|
| 251 |
+
.masthead-name {
|
| 252 |
+
font-size: 14px; font-weight: 500; letter-spacing: -0.005em;
|
| 253 |
+
color: var(--text);
|
| 254 |
+
}
|
| 255 |
+
.masthead-nav {
|
| 256 |
+
display: flex; align-items: center; gap: 18px;
|
| 257 |
+
font-family: var(--font-sans);
|
| 258 |
+
font-size: 13px;
|
| 259 |
+
color: var(--text-2);
|
| 260 |
+
}
|
| 261 |
+
.masthead-nav a {
|
| 262 |
+
color: var(--text-2); text-decoration: none;
|
| 263 |
+
transition: color 160ms ease;
|
| 264 |
+
}
|
| 265 |
+
.masthead-nav a:hover { color: var(--green); }
|
| 266 |
+
.masthead-sep { width: 3px; height: 3px; background: var(--muted-2); border-radius: 50%; }
|
| 267 |
+
|
| 268 |
+
/* ─────────────── hero block ─────────────── */
|
| 269 |
+
.hero { padding: 0 0 32px; }
|
| 270 |
+
.hero-mono {
|
| 271 |
+
padding: 88px 0 48px; text-align: center;
|
| 272 |
+
max-width: 720px;
|
| 273 |
+
margin: 0 auto;
|
| 274 |
+
position: relative;
|
| 275 |
+
animation: fadein 0.55s ease 0.05s both;
|
| 276 |
+
}
|
| 277 |
+
/* Soft blue glow behind the headline gives atmospheric depth */
|
| 278 |
+
.hero-mono::before {
|
| 279 |
+
content: "";
|
| 280 |
+
position: absolute;
|
| 281 |
+
width: 720px; height: 380px;
|
| 282 |
+
left: 50%; top: -40px;
|
| 283 |
+
transform: translateX(-50%);
|
| 284 |
+
background:
|
| 285 |
+
radial-gradient(ellipse at center, rgba(95, 180, 255, 0.18) 0%, transparent 55%),
|
| 286 |
+
radial-gradient(ellipse at 30% 70%, rgba(118, 185, 0, 0.12) 0%, transparent 60%);
|
| 287 |
+
filter: blur(16px);
|
| 288 |
+
pointer-events: none;
|
| 289 |
+
z-index: -1;
|
| 290 |
+
opacity: 0.9;
|
| 291 |
+
}
|
| 292 |
+
.hero-eyebrow {
|
| 293 |
+
display: inline-flex; align-items: center; gap: 12px;
|
| 294 |
+
color: var(--green);
|
| 295 |
+
font-family: var(--font-mono); font-size: 11px; font-weight: 500;
|
| 296 |
+
letter-spacing: 0.18em; text-transform: uppercase;
|
| 297 |
+
margin-bottom: 24px;
|
| 298 |
+
}
|
| 299 |
+
.line-tick { display: inline-block; width: 28px; height: 1px; background: var(--green); opacity: 0.5; }
|
| 300 |
+
|
| 301 |
+
.hero-title {
|
| 302 |
+
font-family: var(--font-sans);
|
| 303 |
+
font-size: clamp(2.0rem, 4.0vw, 3.0rem);
|
| 304 |
+
font-weight: 500;
|
| 305 |
+
line-height: 1.05;
|
| 306 |
+
letter-spacing: -0.032em;
|
| 307 |
+
margin: 0;
|
| 308 |
+
color: var(--text);
|
| 309 |
+
}
|
| 310 |
+
|
| 311 |
+
/* ─────────────── datasheet cards ─────────────── */
|
| 312 |
+
.hero-row { gap: 20px !important; align-items: stretch !important; }
|
| 313 |
+
.hero-row > * { display: flex !important; flex-direction: column !important; }
|
| 314 |
+
.hero-card-col {
|
| 315 |
+
padding: 0 !important;
|
| 316 |
+
display: flex !important; flex-direction: column !important;
|
| 317 |
+
animation: fadein 0.5s ease both;
|
| 318 |
+
}
|
| 319 |
+
.hero-card-col:nth-child(1) { animation-delay: 0.10s; }
|
| 320 |
+
.hero-card-col:nth-child(2) { animation-delay: 0.18s; }
|
| 321 |
+
.hero-card-col:nth-child(3) { animation-delay: 0.26s; }
|
| 322 |
+
|
| 323 |
+
.ds-card {
|
| 324 |
+
position: relative;
|
| 325 |
+
background: var(--panel);
|
| 326 |
+
border: 1px solid var(--line);
|
| 327 |
+
transition: border-color 220ms ease, background 220ms ease, transform 220ms ease, box-shadow 280ms ease;
|
| 328 |
+
--accent: var(--green);
|
| 329 |
+
flex: 1 1 auto;
|
| 330 |
+
display: flex;
|
| 331 |
+
flex-direction: column;
|
| 332 |
+
}
|
| 333 |
+
.ds-card.ds-ct { --accent: var(--ct); }
|
| 334 |
+
.ds-card.ds-mr { --accent: var(--mr); }
|
| 335 |
+
.ds-card.ds-mrb { --accent: var(--mrb); }
|
| 336 |
+
.ds-card:hover {
|
| 337 |
+
border-color: color-mix(in srgb, var(--accent) 60%, transparent);
|
| 338 |
+
background: var(--panel-2);
|
| 339 |
+
box-shadow:
|
| 340 |
+
0 1px 0 rgba(255,255,255,0.04) inset,
|
| 341 |
+
0 24px 60px -16px color-mix(in srgb, var(--accent) 35%, transparent);
|
| 342 |
+
}
|
| 343 |
+
.ds-card:hover .ds-corner { background: var(--accent); }
|
| 344 |
+
|
| 345 |
+
.ds-frame {
|
| 346 |
+
position: relative;
|
| 347 |
+
padding: 18px 22px 22px;
|
| 348 |
+
display: flex; flex-direction: column;
|
| 349 |
+
flex: 1 1 auto;
|
| 350 |
+
}
|
| 351 |
+
|
| 352 |
+
/* Banner at top of card — modality scan icon over a faint accent gradient */
|
| 353 |
+
.ds-banner {
|
| 354 |
+
position: relative;
|
| 355 |
+
height: 110px;
|
| 356 |
+
display: flex; flex-direction: column; align-items: center; justify-content: center;
|
| 357 |
+
gap: 6px;
|
| 358 |
+
border-bottom: 1px solid var(--line);
|
| 359 |
+
background:
|
| 360 |
+
linear-gradient(180deg, transparent 0%, rgba(0,0,0,0.22) 100%),
|
| 361 |
+
radial-gradient(ellipse at center, color-mix(in srgb, var(--accent) 18%, transparent) 0%, transparent 60%);
|
| 362 |
+
overflow: hidden;
|
| 363 |
+
color: var(--accent);
|
| 364 |
+
}
|
| 365 |
+
.ds-banner-grid {
|
| 366 |
+
position: absolute; inset: 0;
|
| 367 |
+
background-image:
|
| 368 |
+
linear-gradient(rgba(150,180,240,0.06) 1px, transparent 1px),
|
| 369 |
+
linear-gradient(90deg, rgba(150,180,240,0.06) 1px, transparent 1px);
|
| 370 |
+
background-size: 16px 16px;
|
| 371 |
+
pointer-events: none;
|
| 372 |
+
mask-image: radial-gradient(ellipse at center, black 40%, transparent 80%);
|
| 373 |
+
}
|
| 374 |
+
/* Single scanline sweep on first card render — telegraphs "this generates volumes" */
|
| 375 |
+
.ds-banner::after {
|
| 376 |
+
content: "";
|
| 377 |
+
position: absolute; left: 0; right: 0; top: 0;
|
| 378 |
+
height: 2px;
|
| 379 |
+
background: linear-gradient(90deg, transparent, var(--accent), transparent);
|
| 380 |
+
filter: blur(1px);
|
| 381 |
+
opacity: 0;
|
| 382 |
+
animation: banner-scan 2.6s cubic-bezier(.4,0,.2,1) 1 forwards;
|
| 383 |
+
animation-delay: 0.5s;
|
| 384 |
+
}
|
| 385 |
+
.hero-card-col:nth-child(1) .ds-banner::after { animation-delay: 0.5s; }
|
| 386 |
+
.hero-card-col:nth-child(2) .ds-banner::after { animation-delay: 0.75s; }
|
| 387 |
+
.hero-card-col:nth-child(3) .ds-banner::after { animation-delay: 1.0s; }
|
| 388 |
+
@keyframes banner-scan {
|
| 389 |
+
0% { top: 0; opacity: 0; }
|
| 390 |
+
10% { opacity: 0.85; }
|
| 391 |
+
85% { opacity: 0.85; }
|
| 392 |
+
100% { top: 110px; opacity: 0; }
|
| 393 |
+
}
|
| 394 |
+
.ds-banner-icon {
|
| 395 |
+
width: 64px; height: 64px;
|
| 396 |
+
position: relative; z-index: 1;
|
| 397 |
+
display: flex; align-items: center; justify-content: center;
|
| 398 |
+
transition: transform 280ms ease;
|
| 399 |
+
}
|
| 400 |
+
.ds-card:hover .ds-banner-icon { transform: scale(1.05); }
|
| 401 |
+
.ds-banner-icon svg { width: 100%; height: 100%; display: block; }
|
| 402 |
+
.ds-banner-caption {
|
| 403 |
+
font-family: var(--font-mono); font-size: 9.5px;
|
| 404 |
+
letter-spacing: 0.16em; text-transform: uppercase;
|
| 405 |
+
color: var(--accent);
|
| 406 |
+
opacity: 0.85;
|
| 407 |
+
position: relative; z-index: 1;
|
| 408 |
+
}
|
| 409 |
+
.ds-corner {
|
| 410 |
+
position: absolute; width: 7px; height: 7px;
|
| 411 |
+
background: var(--line-bright);
|
| 412 |
+
transition: background 220ms ease;
|
| 413 |
+
}
|
| 414 |
+
.ds-tl { top: -1px; left: -1px; clip-path: polygon(0 0, 100% 0, 0 100%); }
|
| 415 |
+
.ds-tr { top: -1px; right: -1px; clip-path: polygon(0 0, 100% 0, 100% 100%); }
|
| 416 |
+
.ds-bl { bottom: -1px; left: -1px; clip-path: polygon(0 0, 0 100%, 100% 100%); }
|
| 417 |
+
.ds-br { bottom: -1px; right: -1px; clip-path: polygon(100% 0, 100% 100%, 0 100%); }
|
| 418 |
+
|
| 419 |
+
.ds-head {
|
| 420 |
+
display: flex; align-items: center; justify-content: space-between;
|
| 421 |
+
margin-bottom: 18px;
|
| 422 |
+
height: 24px;
|
| 423 |
+
}
|
| 424 |
+
.ds-index {
|
| 425 |
+
font-family: var(--font-mono);
|
| 426 |
+
font-size: 11px; font-weight: 600; letter-spacing: 0.18em;
|
| 427 |
+
color: var(--accent);
|
| 428 |
+
padding: 3px 9px;
|
| 429 |
+
border: 1px solid var(--accent);
|
| 430 |
+
border-radius: 0;
|
| 431 |
+
opacity: 0.9;
|
| 432 |
+
}
|
| 433 |
+
/* Availability status — single dot + label. Decoupled from license info. */
|
| 434 |
+
.ds-status {
|
| 435 |
+
display: inline-flex; align-items: center; gap: 7px;
|
| 436 |
+
font-family: var(--font-mono); font-size: 9.5px;
|
| 437 |
+
letter-spacing: 0.16em; text-transform: uppercase;
|
| 438 |
+
color: var(--muted);
|
| 439 |
+
}
|
| 440 |
+
.ds-status .dot { background: var(--accent); box-shadow: 0 0 6px var(--accent); }
|
| 441 |
+
|
| 442 |
+
.ds-name { margin-bottom: 16px; }
|
| 443 |
+
.ds-name-title {
|
| 444 |
+
font-family: var(--font-sans);
|
| 445 |
+
font-size: 1.20rem; font-weight: 500;
|
| 446 |
+
letter-spacing: -0.018em; line-height: 1.15;
|
| 447 |
+
color: var(--text);
|
| 448 |
+
margin-bottom: 4px;
|
| 449 |
+
}
|
| 450 |
+
.ds-name-code {
|
| 451 |
+
font-family: var(--font-mono); font-size: 11px;
|
| 452 |
+
letter-spacing: 0.04em; text-transform: lowercase;
|
| 453 |
+
color: var(--accent);
|
| 454 |
+
opacity: 0.85;
|
| 455 |
+
margin-bottom: 10px;
|
| 456 |
+
}
|
| 457 |
+
.ds-name-sub {
|
| 458 |
+
font-family: var(--font-sans);
|
| 459 |
+
font-size: 0.86rem; line-height: 1.5;
|
| 460 |
+
color: var(--text-2);
|
| 461 |
+
min-height: 2.6em; /* reserves ~2 lines so cards stay aligned */
|
| 462 |
+
margin-bottom: 14px;
|
| 463 |
+
}
|
| 464 |
+
|
| 465 |
+
/* Use-case section label */
|
| 466 |
+
.ds-uses-label {
|
| 467 |
+
font-family: var(--font-mono); font-size: 9px;
|
| 468 |
+
letter-spacing: 0.22em; text-transform: uppercase;
|
| 469 |
+
color: var(--muted);
|
| 470 |
+
margin-bottom: 8px;
|
| 471 |
+
}
|
| 472 |
+
/* Use-case chips: small mono pills below the subtitle */
|
| 473 |
+
.ds-uses {
|
| 474 |
+
display: flex; flex-wrap: wrap; gap: 6px;
|
| 475 |
+
margin-bottom: 16px;
|
| 476 |
+
min-height: 28px;
|
| 477 |
+
}
|
| 478 |
+
.ds-use {
|
| 479 |
+
display: inline-flex; align-items: center;
|
| 480 |
+
padding: 4px 9px;
|
| 481 |
+
border: 1px solid var(--line);
|
| 482 |
+
background: rgba(140, 180, 240, 0.04);
|
| 483 |
+
font-family: var(--font-sans); font-size: 11px;
|
| 484 |
+
font-weight: 500;
|
| 485 |
+
letter-spacing: 0;
|
| 486 |
+
color: var(--text-2);
|
| 487 |
+
white-space: nowrap;
|
| 488 |
+
}
|
| 489 |
+
.ds-card:hover .ds-use { border-color: rgba(140, 180, 240, 0.20); }
|
| 490 |
+
|
| 491 |
+
/* License chip: separate from availability status, lives at card bottom */
|
| 492 |
+
.ds-license {
|
| 493 |
+
margin-top: 14px;
|
| 494 |
+
padding: 8px 12px;
|
| 495 |
+
display: flex; align-items: center; gap: 10px;
|
| 496 |
+
border: 1px solid var(--line);
|
| 497 |
+
background: rgba(140, 180, 240, 0.03);
|
| 498 |
+
font-family: var(--font-mono); font-size: 10px;
|
| 499 |
+
letter-spacing: 0.04em;
|
| 500 |
+
}
|
| 501 |
+
.ds-license-k {
|
| 502 |
+
color: var(--muted);
|
| 503 |
+
text-transform: uppercase; letter-spacing: 0.16em; font-size: 9px;
|
| 504 |
+
}
|
| 505 |
+
.ds-license-v { color: var(--text); }
|
| 506 |
+
.ds-license-warn {
|
| 507 |
+
border-color: rgba(246, 200, 97, 0.30);
|
| 508 |
+
background: var(--warn-soft);
|
| 509 |
+
}
|
| 510 |
+
.ds-license-warn .ds-license-v { color: var(--warn); }
|
| 511 |
+
.ds-license-ok {
|
| 512 |
+
border-color: rgba(118, 185, 0, 0.25);
|
| 513 |
+
}
|
| 514 |
+
.ds-license-ok .ds-license-v { color: var(--text); }
|
| 515 |
+
|
| 516 |
+
.ds-divider {
|
| 517 |
+
height: 1px; background: var(--line);
|
| 518 |
+
margin: 0 0 14px;
|
| 519 |
+
position: relative;
|
| 520 |
+
}
|
| 521 |
+
.ds-divider::before, .ds-divider::after {
|
| 522 |
+
content: ""; position: absolute; top: -2px; width: 4px; height: 4px;
|
| 523 |
+
background: var(--accent);
|
| 524 |
+
}
|
| 525 |
+
.ds-divider::before { left: 0; }
|
| 526 |
+
.ds-divider::after { right: 0; }
|
| 527 |
+
|
| 528 |
+
.ds-spec {
|
| 529 |
+
display: flex; flex-direction: column; gap: 7px;
|
| 530 |
+
margin-top: auto; /* pushes spec to bottom of frame so cards always end at same baseline */
|
| 531 |
+
}
|
| 532 |
+
.ds-row {
|
| 533 |
+
display: flex; align-items: baseline;
|
| 534 |
+
font-family: var(--font-mono); font-size: 10.5px;
|
| 535 |
+
letter-spacing: 0.02em;
|
| 536 |
+
color: var(--text-2);
|
| 537 |
+
white-space: nowrap;
|
| 538 |
+
overflow: hidden;
|
| 539 |
+
}
|
| 540 |
+
.ds-key {
|
| 541 |
+
color: var(--muted);
|
| 542 |
+
flex-shrink: 0;
|
| 543 |
+
text-transform: uppercase;
|
| 544 |
+
font-weight: 500;
|
| 545 |
+
}
|
| 546 |
+
.ds-leader {
|
| 547 |
+
flex: 1 1 auto;
|
| 548 |
+
border-bottom: 1px dotted var(--line-strong);
|
| 549 |
+
margin: 0 8px;
|
| 550 |
+
height: 0;
|
| 551 |
+
align-self: end;
|
| 552 |
+
margin-bottom: 4px;
|
| 553 |
+
min-width: 12px;
|
| 554 |
+
}
|
| 555 |
+
.ds-val {
|
| 556 |
+
color: var(--text);
|
| 557 |
+
text-align: right;
|
| 558 |
+
flex-shrink: 0;
|
| 559 |
+
overflow: hidden;
|
| 560 |
+
text-overflow: ellipsis;
|
| 561 |
+
}
|
| 562 |
+
|
| 563 |
+
/* CTA buttons under each card */
|
| 564 |
+
.ds-cta { padding: 0 !important; margin: 0 !important; }
|
| 565 |
+
.ds-cta button, button.ds-cta {
|
| 566 |
+
width: 100% !important;
|
| 567 |
+
margin-top: 14px !important;
|
| 568 |
+
padding: 14px 16px !important;
|
| 569 |
+
background: transparent !important;
|
| 570 |
+
border: 1px solid var(--line-strong) !important;
|
| 571 |
+
border-radius: 0 !important;
|
| 572 |
+
color: var(--text) !important;
|
| 573 |
+
font-family: var(--font-sans) !important;
|
| 574 |
+
font-size: 13px !important;
|
| 575 |
+
font-weight: 500 !important;
|
| 576 |
+
letter-spacing: 0 !important;
|
| 577 |
+
text-transform: none !important;
|
| 578 |
+
text-align: center !important;
|
| 579 |
+
cursor: pointer !important;
|
| 580 |
+
transition: all 200ms ease !important;
|
| 581 |
+
}
|
| 582 |
+
.ds-cta-ct button:hover { border-color: var(--ct) !important; background: rgba(118, 185, 0, 0.10) !important; color: var(--ct) !important; }
|
| 583 |
+
.ds-cta-mr button:hover { border-color: var(--mr) !important; background: rgba(95, 180, 255, 0.10) !important; color: var(--mr) !important; }
|
| 584 |
+
.ds-cta-mrb button:hover { border-color: var(--mrb) !important; background: rgba(180, 138, 255, 0.10) !important; color: var(--mrb) !important; }
|
| 585 |
+
|
| 586 |
+
/* ─────────────── workspace shell ─────────────── */
|
| 587 |
+
.workspace { padding: 0 0 32px; animation: fadein 0.35s ease both; }
|
| 588 |
+
.workspace-row { gap: 24px !important; align-items: stretch !important; }
|
| 589 |
+
|
| 590 |
+
/* ─────────────── workspace intro (per-model context block) ─────────────── */
|
| 591 |
+
.ws-intro {
|
| 592 |
+
display: grid;
|
| 593 |
+
grid-template-columns: minmax(0, 1.4fr) minmax(0, 1fr);
|
| 594 |
+
gap: 32px;
|
| 595 |
+
padding: 24px 26px;
|
| 596 |
+
margin: 0 0 28px !important;
|
| 597 |
+
background:
|
| 598 |
+
linear-gradient(180deg, rgba(120,165,255,0.05), rgba(120,165,255,0.02)),
|
| 599 |
+
var(--panel);
|
| 600 |
+
border: 1px solid var(--line);
|
| 601 |
+
border-left: 3px solid var(--accent, var(--green));
|
| 602 |
+
position: relative;
|
| 603 |
+
--accent: var(--green);
|
| 604 |
+
}
|
| 605 |
+
.ws-intro-ct { --accent: var(--ct); }
|
| 606 |
+
.ws-intro-mr { --accent: var(--mr); }
|
| 607 |
+
.ws-intro-mrb { --accent: var(--mrb); }
|
| 608 |
+
|
| 609 |
+
.ws-intro-title {
|
| 610 |
+
font-family: var(--font-sans);
|
| 611 |
+
font-size: 1.30rem; font-weight: 500;
|
| 612 |
+
letter-spacing: -0.018em; line-height: 1.15;
|
| 613 |
+
color: var(--text);
|
| 614 |
+
margin: 0 0 10px;
|
| 615 |
+
}
|
| 616 |
+
.ws-intro-desc {
|
| 617 |
+
font-family: var(--font-sans);
|
| 618 |
+
font-size: 0.95rem; line-height: 1.55;
|
| 619 |
+
color: var(--text-2);
|
| 620 |
+
margin: 0;
|
| 621 |
+
max-width: 56ch;
|
| 622 |
+
}
|
| 623 |
+
.ws-intro-facts {
|
| 624 |
+
display: flex; flex-direction: column;
|
| 625 |
+
gap: 6px;
|
| 626 |
+
align-self: center;
|
| 627 |
+
}
|
| 628 |
+
.ws-fact {
|
| 629 |
+
display: flex; align-items: baseline; gap: 12px;
|
| 630 |
+
font-family: var(--font-mono); font-size: 11px;
|
| 631 |
+
letter-spacing: 0.02em;
|
| 632 |
+
}
|
| 633 |
+
.ws-fact-k {
|
| 634 |
+
color: var(--muted);
|
| 635 |
+
text-transform: uppercase;
|
| 636 |
+
letter-spacing: 0.12em;
|
| 637 |
+
font-size: 9.5px;
|
| 638 |
+
flex: 0 0 92px;
|
| 639 |
+
}
|
| 640 |
+
.ws-fact-v { color: var(--text); }
|
| 641 |
+
.ws-fact-v.ws-fact-warn { color: var(--warn); }
|
| 642 |
+
.workspace-header {
|
| 643 |
+
align-items: center !important;
|
| 644 |
+
gap: 14px !important;
|
| 645 |
+
padding: 18px 0 18px !important;
|
| 646 |
+
border-bottom: 1px solid var(--line);
|
| 647 |
+
margin-bottom: 22px;
|
| 648 |
+
}
|
| 649 |
+
.workspace-title {
|
| 650 |
+
font-family: var(--font-sans);
|
| 651 |
+
font-size: 14px;
|
| 652 |
+
color: var(--text-2);
|
| 653 |
+
display: flex; align-items: center; gap: 10px;
|
| 654 |
+
flex: 1;
|
| 655 |
+
}
|
| 656 |
+
.workspace-title .ws-dot { width: 7px; height: 7px; border-radius: 50%; box-shadow: 0 0 6px currentColor; flex-shrink: 0; }
|
| 657 |
+
.workspace-title .ws-crumb { color: var(--text-2); font-weight: 500; }
|
| 658 |
+
.workspace-title .ws-crumb-sep { color: var(--muted-2); margin: 0 2px; }
|
| 659 |
+
.workspace-title .ws-active { color: var(--text); font-weight: 500; }
|
| 660 |
+
.workspace-title .ws-meta {
|
| 661 |
+
font-family: var(--font-mono); font-size: 11px;
|
| 662 |
+
color: var(--muted); margin-left: 14px;
|
| 663 |
+
padding: 3px 8px; border: 1px solid var(--line);
|
| 664 |
+
letter-spacing: 0.04em;
|
| 665 |
+
}
|
| 666 |
+
|
| 667 |
+
.back-btn { padding: 0 !important; margin: 0 !important; flex: 0 0 auto !important; }
|
| 668 |
+
.back-btn button {
|
| 669 |
+
background: transparent !important;
|
| 670 |
+
border: 1px solid var(--line-strong) !important;
|
| 671 |
+
border-radius: 0 !important;
|
| 672 |
+
color: var(--text-2) !important;
|
| 673 |
+
font-family: var(--font-sans) !important;
|
| 674 |
+
font-size: 13px !important;
|
| 675 |
+
font-weight: 500 !important;
|
| 676 |
+
letter-spacing: 0 !important;
|
| 677 |
+
text-transform: none !important;
|
| 678 |
+
padding: 8px 14px !important;
|
| 679 |
+
}
|
| 680 |
+
.back-btn button:hover { border-color: var(--line-bright) !important; color: var(--text) !important; }
|
| 681 |
+
|
| 682 |
+
.hint {
|
| 683 |
+
font-family: var(--font-sans); font-size: 12px;
|
| 684 |
+
color: var(--muted);
|
| 685 |
+
padding: 4px 0 6px;
|
| 686 |
+
margin: -4px 0 0;
|
| 687 |
+
}
|
| 688 |
+
|
| 689 |
+
/* ─────────────── controls panel ─────────────── */
|
| 690 |
+
.controls {
|
| 691 |
+
background: var(--panel) !important;
|
| 692 |
+
border: 1px solid var(--line) !important;
|
| 693 |
+
border-radius: 0 !important;
|
| 694 |
+
padding: 18px 22px !important;
|
| 695 |
+
position: relative;
|
| 696 |
+
}
|
| 697 |
+
/* Reset Gradio's interior block padding so we control it */
|
| 698 |
+
.controls > * { padding: 0 !important; }
|
| 699 |
+
|
| 700 |
+
/* Section headers (the gr.Markdown ##### lines) */
|
| 701 |
+
.controls h5 {
|
| 702 |
+
font-family: var(--font-mono) !important;
|
| 703 |
+
font-size: 10px !important;
|
| 704 |
+
font-weight: 600 !important;
|
| 705 |
+
letter-spacing: 0.20em !important;
|
| 706 |
+
text-transform: uppercase !important;
|
| 707 |
+
color: var(--green) !important;
|
| 708 |
+
margin: 24px 0 14px !important;
|
| 709 |
+
padding: 0 0 10px !important;
|
| 710 |
+
border-bottom: 1px solid var(--line) !important;
|
| 711 |
+
display: flex; align-items: center; gap: 10px;
|
| 712 |
+
}
|
| 713 |
+
.controls h5::before {
|
| 714 |
+
content: ""; width: 4px; height: 4px; background: var(--green);
|
| 715 |
+
display: inline-block;
|
| 716 |
+
}
|
| 717 |
+
/* First section header sits flush at top of panel */
|
| 718 |
+
.controls > div:first-child h5,
|
| 719 |
+
.controls .markdown:first-child h5 { margin-top: 0 !important; }
|
| 720 |
+
|
| 721 |
+
/* Input labels: title case sans, not shouting mono */
|
| 722 |
+
.controls label, .controls label > span {
|
| 723 |
+
font-family: var(--font-sans) !important;
|
| 724 |
+
font-size: 12px !important;
|
| 725 |
+
font-weight: 500 !important;
|
| 726 |
+
letter-spacing: 0 !important;
|
| 727 |
+
text-transform: none !important;
|
| 728 |
+
color: var(--text-2) !important;
|
| 729 |
+
}
|
| 730 |
+
|
| 731 |
+
/* Helper text under input (info=) */
|
| 732 |
+
.controls .info, .controls .gr-info, .controls .help-text {
|
| 733 |
+
font-family: var(--font-sans) !important;
|
| 734 |
+
font-size: 11px !important;
|
| 735 |
+
font-weight: 400 !important;
|
| 736 |
+
color: var(--muted) !important;
|
| 737 |
+
letter-spacing: 0 !important;
|
| 738 |
+
text-transform: none !important;
|
| 739 |
+
margin-top: 4px !important;
|
| 740 |
+
}
|
| 741 |
+
|
| 742 |
+
/* Inputs */
|
| 743 |
+
.controls input[type="text"], .controls input[type="number"],
|
| 744 |
+
.controls select, .controls textarea {
|
| 745 |
+
background: var(--bg-1) !important;
|
| 746 |
+
border: 1px solid var(--line-strong) !important;
|
| 747 |
+
border-radius: 0 !important;
|
| 748 |
+
color: var(--text) !important;
|
| 749 |
+
font-family: var(--num) !important;
|
| 750 |
+
font-feature-settings: "tnum", "zero" !important;
|
| 751 |
+
padding: 8px 10px !important;
|
| 752 |
+
}
|
| 753 |
+
.controls input:focus, .controls select:focus, .controls textarea:focus {
|
| 754 |
+
outline: none !important;
|
| 755 |
+
border-color: var(--green) !important;
|
| 756 |
+
box-shadow: 0 0 0 1px var(--green-soft) !important;
|
| 757 |
+
}
|
| 758 |
+
|
| 759 |
+
/* Sliders — keep the number input box tucked next to the track, not floating right */
|
| 760 |
+
.controls input[type="range"] { accent-color: var(--green) !important; }
|
| 761 |
+
.controls .gradio-slider input[type="number"],
|
| 762 |
+
.controls .gr-slider input[type="number"],
|
| 763 |
+
.controls input.slider-value {
|
| 764 |
+
max-width: 64px !important;
|
| 765 |
+
min-width: 0 !important;
|
| 766 |
+
padding: 6px 8px !important;
|
| 767 |
+
font-size: 12px !important;
|
| 768 |
+
}
|
| 769 |
+
/* Pull the slider label and value tight to the left edge */
|
| 770 |
+
.controls .gradio-slider, .controls .gr-slider {
|
| 771 |
+
padding: 0 !important;
|
| 772 |
+
margin: 0 !important;
|
| 773 |
+
}
|
| 774 |
+
.controls .gradio-slider > .head, .controls .gradio-slider > div:first-child {
|
| 775 |
+
margin: 0 !important;
|
| 776 |
+
padding: 0 !important;
|
| 777 |
+
}
|
| 778 |
+
|
| 779 |
+
/* Gradio ships some input wrappers with margin-left:auto which pushes inputs
|
| 780 |
+
to the right side of their column. Zero it so inputs align to the left. */
|
| 781 |
+
.controls .tab-like-container,
|
| 782 |
+
.controls [class*="tab-like-container"],
|
| 783 |
+
.controls .input-container,
|
| 784 |
+
.controls [class*="input-container"] {
|
| 785 |
+
margin-left: 0 !important;
|
| 786 |
+
margin-right: 0 !important;
|
| 787 |
+
}
|
| 788 |
+
|
| 789 |
+
/* Dropdown input — Gradio v6's actual structure is .wrap > .wrap-inner >
|
| 790 |
+
.secondary-wrap > input[role="listbox"]. Put the visible border on .wrap
|
| 791 |
+
(the outermost), make every inner layer transparent so it doesn't double-
|
| 792 |
+
border. Match using :has() on the input role so this rule only fires on
|
| 793 |
+
dropdown wraps, not slider/other wraps inside .controls. */
|
| 794 |
+
.controls .wrap:has(input[role="listbox"]),
|
| 795 |
+
.controls .wrap:has(input.border-none) {
|
| 796 |
+
background: var(--bg-1) !important;
|
| 797 |
+
border: 1px solid var(--line-strong) !important;
|
| 798 |
+
border-radius: 0 !important;
|
| 799 |
+
min-height: 38px !important;
|
| 800 |
+
width: 100% !important;
|
| 801 |
+
box-sizing: border-box !important;
|
| 802 |
+
display: flex !important;
|
| 803 |
+
align-items: center !important;
|
| 804 |
+
}
|
| 805 |
+
.controls .wrap:has(input[role="listbox"]) .wrap-inner,
|
| 806 |
+
.controls .wrap:has(input[role="listbox"]) .secondary-wrap,
|
| 807 |
+
.controls .wrap:has(input[role="listbox"]) .icon-wrap {
|
| 808 |
+
background: transparent !important;
|
| 809 |
+
border: 0 !important;
|
| 810 |
+
width: 100% !important;
|
| 811 |
+
}
|
| 812 |
+
.controls .wrap:has(input[role="listbox"]) input,
|
| 813 |
+
.controls input.border-none,
|
| 814 |
+
.controls input[role="listbox"] {
|
| 815 |
+
background: transparent !important;
|
| 816 |
+
border: 0 !important;
|
| 817 |
+
padding: 8px 10px !important;
|
| 818 |
+
color: var(--text) !important;
|
| 819 |
+
width: 100% !important;
|
| 820 |
+
font-family: var(--font-sans) !important;
|
| 821 |
+
}
|
| 822 |
+
/* Hide any built-in radio/checkbox glyph SVGs Gradio injects inside pill
|
| 823 |
+
labels — the styled pill IS the indicator. */
|
| 824 |
+
.controls .gradio-radio label > svg,
|
| 825 |
+
.controls .gradio-checkboxgroup label > svg,
|
| 826 |
+
.controls fieldset label > svg {
|
| 827 |
+
display: none !important;
|
| 828 |
+
}
|
| 829 |
+
|
| 830 |
+
/* Dropdown popup — only style the visual chrome. Let Gradio's JS handle
|
| 831 |
+
position so the popup anchors to the input regardless of scroll. */
|
| 832 |
+
.gradio-container ul.options,
|
| 833 |
+
.gradio-container ul[role="listbox"] {
|
| 834 |
+
max-height: 280px !important;
|
| 835 |
+
overflow-y: auto !important;
|
| 836 |
+
z-index: 1000 !important;
|
| 837 |
+
}
|
| 838 |
+
|
| 839 |
+
/* Dropdown OPTION LIST (the floating popup) — must have an opaque bg or it
|
| 840 |
+
appears to "float in the air" against the dark page bg. */
|
| 841 |
+
.gradio-container .options,
|
| 842 |
+
.gradio-container ul.options,
|
| 843 |
+
.gradio-container ul[role="listbox"],
|
| 844 |
+
.gradio-container .secondary-wrap ul,
|
| 845 |
+
.gradio-container [class*="option-list"],
|
| 846 |
+
body .options,
|
| 847 |
+
body ul[role="listbox"] {
|
| 848 |
+
background: var(--panel-2) !important;
|
| 849 |
+
background-color: var(--panel-2) !important;
|
| 850 |
+
border: 1px solid var(--line-strong) !important;
|
| 851 |
+
border-radius: 0 !important;
|
| 852 |
+
box-shadow: 0 10px 40px rgba(0, 0, 0, 0.7), 0 2px 0 rgba(118, 185, 0, 0.20) inset !important;
|
| 853 |
+
font-family: var(--font-sans) !important;
|
| 854 |
+
color: var(--text) !important;
|
| 855 |
+
padding: 4px 0 !important;
|
| 856 |
+
z-index: 1000 !important;
|
| 857 |
+
}
|
| 858 |
+
.gradio-container .options li,
|
| 859 |
+
.gradio-container ul[role="listbox"] li,
|
| 860 |
+
.gradio-container [role="option"],
|
| 861 |
+
body .options li,
|
| 862 |
+
body ul[role="listbox"] li,
|
| 863 |
+
body [role="option"] {
|
| 864 |
+
background: transparent !important;
|
| 865 |
+
color: var(--text) !important;
|
| 866 |
+
font-family: var(--font-sans) !important;
|
| 867 |
+
font-size: 13px !important;
|
| 868 |
+
font-weight: 400 !important;
|
| 869 |
+
letter-spacing: 0 !important;
|
| 870 |
+
text-transform: none !important;
|
| 871 |
+
padding: 8px 14px !important;
|
| 872 |
+
cursor: pointer !important;
|
| 873 |
+
border: 0 !important;
|
| 874 |
+
}
|
| 875 |
+
.gradio-container .options li:hover,
|
| 876 |
+
.gradio-container ul[role="listbox"] li:hover,
|
| 877 |
+
.gradio-container [role="option"]:hover,
|
| 878 |
+
body .options li:hover,
|
| 879 |
+
body ul[role="listbox"] li:hover,
|
| 880 |
+
body [role="option"]:hover {
|
| 881 |
+
background: rgba(118, 185, 0, 0.12) !important;
|
| 882 |
+
color: var(--green) !important;
|
| 883 |
+
}
|
| 884 |
+
.gradio-container [role="option"][aria-selected="true"],
|
| 885 |
+
body [role="option"][aria-selected="true"] {
|
| 886 |
+
background: rgba(118, 185, 0, 0.18) !important;
|
| 887 |
+
color: var(--green) !important;
|
| 888 |
+
}
|
| 889 |
+
|
| 890 |
+
/* Checkbox */
|
| 891 |
+
.controls input[type="checkbox"] { accent-color: var(--green) !important; }
|
| 892 |
+
|
| 893 |
+
/* Sample preset chip buttons */
|
| 894 |
+
.controls button {
|
| 895 |
+
background: transparent !important;
|
| 896 |
+
border: 1px solid var(--line) !important;
|
| 897 |
+
border-radius: 0 !important;
|
| 898 |
+
color: var(--text-2) !important;
|
| 899 |
+
font-family: var(--font-sans) !important;
|
| 900 |
+
font-size: 12px !important;
|
| 901 |
+
font-weight: 500 !important;
|
| 902 |
+
letter-spacing: 0 !important;
|
| 903 |
+
text-transform: none !important;
|
| 904 |
+
padding: 8px 14px !important;
|
| 905 |
+
transition: border-color 160ms ease, color 160ms ease, background 160ms ease;
|
| 906 |
+
}
|
| 907 |
+
/* Sample preset chips: only the BORDER tints green on hover. We intentionally
|
| 908 |
+
do NOT change text color here, because this rule blanket-matches every
|
| 909 |
+
button inside .controls — including the primary Generate CTA — and tinting
|
| 910 |
+
text green there would make it invisible against the green button bg. */
|
| 911 |
+
.controls button:hover { border-color: var(--green) !important; }
|
| 912 |
+
|
| 913 |
+
/* ─────────────── UNIFIED SELECTED STATE ─────────────── */
|
| 914 |
+
/* Pattern: active = filled accent bg + accent border + accent text.
|
| 915 |
+
Hover (non-selected) = outline only. Applied across body region toggles,
|
| 916 |
+
anatomy chips, window/level presets — one consistent visual pattern. */
|
| 917 |
+
|
| 918 |
+
/* Radio / Checkbox group containers: zero EVERY potentially-padded wrapper so
|
| 919 |
+
the first pill aligns flush with the column's left edge, matching the
|
| 920 |
+
slider labels above. Browser default fieldset has ~32px padding-inline-start
|
| 921 |
+
plus min-inline-size, and Gradio adds extra wrappers on top of that. */
|
| 922 |
+
.controls .gradio-radio,
|
| 923 |
+
.controls .gradio-radio > *,
|
| 924 |
+
.controls .gradio-radio fieldset,
|
| 925 |
+
.controls .gradio-radio fieldset > *,
|
| 926 |
+
.controls .gradio-radio .wrap,
|
| 927 |
+
.controls .gradio-radio .wrap-inner,
|
| 928 |
+
.controls .gradio-checkboxgroup,
|
| 929 |
+
.controls .gradio-checkboxgroup > *,
|
| 930 |
+
.controls .gradio-checkboxgroup fieldset,
|
| 931 |
+
.controls .gradio-checkboxgroup fieldset > *,
|
| 932 |
+
.controls .gradio-checkboxgroup .wrap,
|
| 933 |
+
.controls .gradio-checkboxgroup .wrap-inner,
|
| 934 |
+
.controls fieldset {
|
| 935 |
+
padding-left: 0 !important;
|
| 936 |
+
padding-inline-start: 0 !important;
|
| 937 |
+
margin-left: 0 !important;
|
| 938 |
+
margin-inline-start: 0 !important;
|
| 939 |
+
border-inline-start-width: 0 !important;
|
| 940 |
+
min-inline-size: 0 !important;
|
| 941 |
+
}
|
| 942 |
+
/* Restore fieldset to a clean flex pill row */
|
| 943 |
+
.controls .gradio-radio fieldset,
|
| 944 |
+
.controls .gradio-checkboxgroup fieldset {
|
| 945 |
+
display: flex !important;
|
| 946 |
+
flex-wrap: wrap !important;
|
| 947 |
+
gap: 6px !important;
|
| 948 |
+
padding: 0 !important;
|
| 949 |
+
margin: 0 !important;
|
| 950 |
+
border: 0 !important;
|
| 951 |
+
min-inline-size: 0 !important;
|
| 952 |
+
}
|
| 953 |
+
|
| 954 |
+
/* Body region (gr.CheckboxGroup) — strip the native check, style label as toggle */
|
| 955 |
+
.controls .gradio-checkboxgroup label,
|
| 956 |
+
.controls fieldset label {
|
| 957 |
+
display: inline-flex !important; align-items: center !important;
|
| 958 |
+
padding: 8px 14px !important;
|
| 959 |
+
border: 1px solid var(--line) !important;
|
| 960 |
+
background: transparent !important;
|
| 961 |
+
font-family: var(--font-sans) !important;
|
| 962 |
+
font-size: 12px !important;
|
| 963 |
+
font-weight: 500 !important;
|
| 964 |
+
color: var(--text-2) !important;
|
| 965 |
+
cursor: pointer;
|
| 966 |
+
transition: all 160ms ease;
|
| 967 |
+
margin: 0 6px 6px 0 !important;
|
| 968 |
+
}
|
| 969 |
+
.controls .gradio-checkboxgroup label > input,
|
| 970 |
+
.controls fieldset label > input { display: none !important; }
|
| 971 |
+
.controls .gradio-checkboxgroup label > span,
|
| 972 |
+
.controls fieldset label > span {
|
| 973 |
+
font-family: var(--font-sans) !important;
|
| 974 |
+
font-size: 12px !important;
|
| 975 |
+
font-weight: 500 !important;
|
| 976 |
+
color: inherit !important;
|
| 977 |
+
letter-spacing: 0 !important;
|
| 978 |
+
text-transform: none !important;
|
| 979 |
+
}
|
| 980 |
+
.controls .gradio-checkboxgroup label:hover,
|
| 981 |
+
.controls fieldset label:hover {
|
| 982 |
+
border-color: var(--line-bright) !important;
|
| 983 |
+
color: var(--text) !important;
|
| 984 |
+
}
|
| 985 |
+
.controls .gradio-checkboxgroup label:has(input:checked),
|
| 986 |
+
.controls fieldset label:has(input:checked) {
|
| 987 |
+
background: rgba(118, 185, 0, 0.14) !important;
|
| 988 |
+
border-color: var(--green) !important;
|
| 989 |
+
color: var(--green) !important;
|
| 990 |
+
}
|
| 991 |
+
|
| 992 |
+
/* Primary CTA: Generate — same NVIDIA green as section headers, single-tone */
|
| 993 |
+
.primary-cta button, button.primary-cta {
|
| 994 |
+
margin: 18px 0 6px !important;
|
| 995 |
+
padding: 14px 20px !important;
|
| 996 |
+
background: linear-gradient(180deg, #7fc003 0%, var(--green) 100%) !important;
|
| 997 |
+
color: #0b1a00 !important;
|
| 998 |
+
border: 1px solid #5d9100 !important;
|
| 999 |
+
border-radius: 0 !important;
|
| 1000 |
+
font-family: var(--font-sans) !important;
|
| 1001 |
+
font-size: 14px !important;
|
| 1002 |
+
font-weight: 600 !important;
|
| 1003 |
+
letter-spacing: 0 !important;
|
| 1004 |
+
text-transform: none !important;
|
| 1005 |
+
position: relative;
|
| 1006 |
+
width: 100% !important;
|
| 1007 |
+
cursor: pointer !important;
|
| 1008 |
+
box-shadow:
|
| 1009 |
+
0 1px 0 rgba(255,255,255,0.25) inset,
|
| 1010 |
+
0 -1px 0 rgba(0,0,0,0.20) inset,
|
| 1011 |
+
0 10px 28px -10px rgba(118, 185, 0, 0.40) !important;
|
| 1012 |
+
transition: transform 140ms ease, box-shadow 220ms ease, background 180ms ease !important;
|
| 1013 |
+
}
|
| 1014 |
+
.primary-cta button:hover {
|
| 1015 |
+
background: linear-gradient(180deg, #8acc00 0%, #74b400 100%) !important;
|
| 1016 |
+
transform: translateY(-1px) !important;
|
| 1017 |
+
box-shadow:
|
| 1018 |
+
0 1px 0 rgba(255,255,255,0.35) inset,
|
| 1019 |
+
0 -1px 0 rgba(0,0,0,0.20) inset,
|
| 1020 |
+
0 0 0 1px rgba(118,185,0,0.30),
|
| 1021 |
+
0 18px 44px -10px rgba(118, 185, 0, 0.60) !important;
|
| 1022 |
+
}
|
| 1023 |
+
.primary-cta button:active {
|
| 1024 |
+
transform: translateY(0) !important;
|
| 1025 |
+
box-shadow:
|
| 1026 |
+
0 1px 0 rgba(255,255,255,0.15) inset,
|
| 1027 |
+
0 -1px 0 rgba(0,0,0,0.30) inset,
|
| 1028 |
+
0 6px 16px -8px rgba(118, 185, 0, 0.50) !important;
|
| 1029 |
+
}
|
| 1030 |
+
|
| 1031 |
+
/* Lock the Generate button text color across ALL states + descendants. Going
|
| 1032 |
+
aggressive because Gradio injects Svelte-hashed classes on the button that
|
| 1033 |
+
can bump up rule specificity unpredictably. */
|
| 1034 |
+
.controls .primary-cta button,
|
| 1035 |
+
.controls .primary-cta button:hover,
|
| 1036 |
+
.controls .primary-cta button:focus,
|
| 1037 |
+
.controls .primary-cta button:active,
|
| 1038 |
+
.controls .primary-cta button:focus-visible,
|
| 1039 |
+
.controls .primary-cta button *,
|
| 1040 |
+
.controls .primary-cta button:hover *,
|
| 1041 |
+
.controls .primary-cta button:focus *,
|
| 1042 |
+
.controls .primary-cta button:active *,
|
| 1043 |
+
.primary-cta button,
|
| 1044 |
+
.primary-cta button:hover,
|
| 1045 |
+
.primary-cta button:focus,
|
| 1046 |
+
.primary-cta button:active,
|
| 1047 |
+
.primary-cta button *,
|
| 1048 |
+
.primary-cta button:hover *,
|
| 1049 |
+
.gradio-container .primary-cta button,
|
| 1050 |
+
.gradio-container .primary-cta button:hover {
|
| 1051 |
+
color: #0b1a00 !important;
|
| 1052 |
+
-webkit-text-fill-color: #0b1a00 !important;
|
| 1053 |
+
}
|
| 1054 |
+
|
| 1055 |
+
/* Disabled / generating state — must beat the hover rules above. The combined
|
| 1056 |
+
pseudo-class `:disabled:hover` adds extra specificity (0,3,2 with .controls)
|
| 1057 |
+
so the disabled style wins even while the user is hovering. */
|
| 1058 |
+
.primary-cta button:disabled,
|
| 1059 |
+
.primary-cta button:disabled:hover,
|
| 1060 |
+
.primary-cta button:disabled:focus,
|
| 1061 |
+
.primary-cta button:disabled:active,
|
| 1062 |
+
.primary-cta button:disabled:focus-visible,
|
| 1063 |
+
.controls .primary-cta button:disabled,
|
| 1064 |
+
.controls .primary-cta button:disabled:hover,
|
| 1065 |
+
.controls .primary-cta button:disabled:focus,
|
| 1066 |
+
.controls .primary-cta button:disabled:active,
|
| 1067 |
+
.gradio-container .primary-cta button:disabled,
|
| 1068 |
+
.gradio-container .primary-cta button:disabled:hover {
|
| 1069 |
+
background: linear-gradient(180deg, #4a5f00 0%, #3a4c00 100%) !important;
|
| 1070 |
+
color: rgba(255, 255, 255, 0.70) !important;
|
| 1071 |
+
-webkit-text-fill-color: rgba(255, 255, 255, 0.70) !important;
|
| 1072 |
+
cursor: wait !important;
|
| 1073 |
+
opacity: 1 !important;
|
| 1074 |
+
transform: none !important;
|
| 1075 |
+
box-shadow: none !important;
|
| 1076 |
+
border-color: #2a3700 !important;
|
| 1077 |
+
}
|
| 1078 |
+
/* Make sure nested spans inside the disabled button inherit the dim text color */
|
| 1079 |
+
.primary-cta button:disabled *,
|
| 1080 |
+
.primary-cta button:disabled:hover * {
|
| 1081 |
+
color: rgba(255, 255, 255, 0.70) !important;
|
| 1082 |
+
-webkit-text-fill-color: rgba(255, 255, 255, 0.70) !important;
|
| 1083 |
+
}
|
| 1084 |
+
.primary-cta button:disabled::after {
|
| 1085 |
+
content: "";
|
| 1086 |
+
display: inline-block;
|
| 1087 |
+
width: 10px; height: 10px;
|
| 1088 |
+
margin-left: 10px;
|
| 1089 |
+
border: 2px solid rgba(255,255,255,0.3);
|
| 1090 |
+
border-top-color: rgba(255,255,255,0.85);
|
| 1091 |
+
border-radius: 50%;
|
| 1092 |
+
animation: btn-spin 0.8s linear infinite;
|
| 1093 |
+
vertical-align: -2px;
|
| 1094 |
+
}
|
| 1095 |
+
@keyframes btn-spin { to { transform: rotate(360deg); } }
|
| 1096 |
+
|
| 1097 |
+
/* ─────────────── viewer panel ─────────────── */
|
| 1098 |
+
.viewer-col { padding-left: 0 !important; }
|
| 1099 |
+
.viewer-strip {
|
| 1100 |
+
display: flex; justify-content: space-between; align-items: center;
|
| 1101 |
+
padding: 10px 14px;
|
| 1102 |
+
border: 1px solid var(--line);
|
| 1103 |
+
border-bottom: none;
|
| 1104 |
+
background: var(--panel);
|
| 1105 |
+
font-family: var(--font-mono); font-size: 10px;
|
| 1106 |
+
letter-spacing: 0.20em; text-transform: uppercase;
|
| 1107 |
+
}
|
| 1108 |
+
.viewer-strip-left { color: var(--muted); }
|
| 1109 |
+
.viewer-strip-right { color: var(--text-2); }
|
| 1110 |
+
.viewer {
|
| 1111 |
+
background: var(--bg-1) !important;
|
| 1112 |
+
border: 1px solid var(--line) !important;
|
| 1113 |
+
border-radius: 0 !important;
|
| 1114 |
+
padding: 0 !important;
|
| 1115 |
+
position: relative;
|
| 1116 |
+
}
|
| 1117 |
+
|
| 1118 |
+
/* Window/Level preset bar — its own self-contained card with breathing room
|
| 1119 |
+
above and below so it doesn't blend into the viewer / legend stack. */
|
| 1120 |
+
.preset-row {
|
| 1121 |
+
padding: 14px 18px !important;
|
| 1122 |
+
gap: 14px !important;
|
| 1123 |
+
align-items: center !important;
|
| 1124 |
+
margin: 14px 0 !important;
|
| 1125 |
+
border: 1px solid var(--line) !important;
|
| 1126 |
+
background:
|
| 1127 |
+
linear-gradient(180deg, rgba(80, 150, 240, 0.10) 0%, rgba(80, 150, 240, 0.03) 100%),
|
| 1128 |
+
var(--panel) !important;
|
| 1129 |
+
position: relative;
|
| 1130 |
+
}
|
| 1131 |
+
.preset-row::before {
|
| 1132 |
+
/* Thin left-edge accent to mark this as a control surface */
|
| 1133 |
+
content: ""; position: absolute; left: 0; top: 0; bottom: 0;
|
| 1134 |
+
width: 2px;
|
| 1135 |
+
background: linear-gradient(180deg, rgba(95, 180, 255, 0.55), rgba(95, 180, 255, 0.15));
|
| 1136 |
+
}
|
| 1137 |
+
.preset-label {
|
| 1138 |
+
font-family: var(--font-mono) !important;
|
| 1139 |
+
font-size: 10px;
|
| 1140 |
+
letter-spacing: 0.20em;
|
| 1141 |
+
text-transform: uppercase;
|
| 1142 |
+
color: rgba(170, 200, 255, 0.85);
|
| 1143 |
+
padding: 0 !important;
|
| 1144 |
+
}
|
| 1145 |
+
|
| 1146 |
+
/* Window/Level preset radio — filled-accent active state for consistency */
|
| 1147 |
+
.preset-row label {
|
| 1148 |
+
font-family: var(--font-sans) !important;
|
| 1149 |
+
font-size: 11px !important;
|
| 1150 |
+
font-weight: 500 !important;
|
| 1151 |
+
letter-spacing: 0 !important;
|
| 1152 |
+
text-transform: none !important;
|
| 1153 |
+
color: var(--text-2) !important;
|
| 1154 |
+
cursor: pointer;
|
| 1155 |
+
padding: 7px 12px !important;
|
| 1156 |
+
border: 1px solid var(--line) !important;
|
| 1157 |
+
background: transparent !important;
|
| 1158 |
+
transition: all 160ms ease;
|
| 1159 |
+
}
|
| 1160 |
+
.preset-row input[type="radio"] { display: none; }
|
| 1161 |
+
.preset-row label:has(input:checked) {
|
| 1162 |
+
background: rgba(118, 185, 0, 0.14) !important;
|
| 1163 |
+
border-color: var(--green) !important;
|
| 1164 |
+
color: var(--green) !important;
|
| 1165 |
+
}
|
| 1166 |
+
.preset-row label:hover { border-color: var(--line-bright) !important; color: var(--text) !important; }
|
| 1167 |
+
|
| 1168 |
+
/* Status / runtime line — labeled metric chips after generation */
|
| 1169 |
+
.status {
|
| 1170 |
+
padding: 14px 0 6px !important;
|
| 1171 |
+
font-family: var(--font-sans) !important;
|
| 1172 |
+
font-size: 11px !important;
|
| 1173 |
+
color: var(--text-2) !important;
|
| 1174 |
+
margin: 0 !important;
|
| 1175 |
+
border-top: 1px dashed var(--line);
|
| 1176 |
+
margin-top: 6px !important;
|
| 1177 |
+
}
|
| 1178 |
+
|
| 1179 |
+
/* When status text is replaced with structured HTML chips (post-generation) */
|
| 1180 |
+
.status .stat-line {
|
| 1181 |
+
display: flex; flex-wrap: wrap; align-items: center;
|
| 1182 |
+
gap: 8px 10px;
|
| 1183 |
+
row-gap: 8px;
|
| 1184 |
+
}
|
| 1185 |
+
.status .stat-mark {
|
| 1186 |
+
display: inline-block; width: 7px; height: 7px; border-radius: 50%;
|
| 1187 |
+
background: var(--green); box-shadow: 0 0 6px var(--green-glow);
|
| 1188 |
+
}
|
| 1189 |
+
.status .stat-label {
|
| 1190 |
+
font-family: var(--font-sans); font-size: 12px;
|
| 1191 |
+
color: var(--text); font-weight: 500;
|
| 1192 |
+
}
|
| 1193 |
+
.status .stat-chip {
|
| 1194 |
+
display: inline-flex; align-items: baseline; gap: 6px;
|
| 1195 |
+
padding: 3px 8px;
|
| 1196 |
+
border: 1px solid var(--line);
|
| 1197 |
+
background: rgba(140, 180, 240, 0.04);
|
| 1198 |
+
font-family: var(--font-mono); font-size: 10px;
|
| 1199 |
+
white-space: nowrap;
|
| 1200 |
+
}
|
| 1201 |
+
.status .stat-k { color: var(--muted); letter-spacing: 0.12em; text-transform: uppercase; }
|
| 1202 |
+
.status .stat-v { color: var(--text); font-feature-settings: "tnum", "zero"; }
|
| 1203 |
+
.status .stat-err { color: var(--warn); }
|
| 1204 |
+
|
| 1205 |
+
/* License banner — MR */
|
| 1206 |
+
.license-banner {
|
| 1207 |
+
margin: 0 0 28px !important;
|
| 1208 |
+
padding: 14px 18px 16px;
|
| 1209 |
+
border: 1px solid rgba(246, 200, 97, 0.25);
|
| 1210 |
+
border-left: 3px solid var(--warn);
|
| 1211 |
+
background: var(--warn-soft);
|
| 1212 |
+
color: var(--warn);
|
| 1213 |
+
font-family: var(--font-sans);
|
| 1214 |
+
font-size: 12px;
|
| 1215 |
+
line-height: 1.5;
|
| 1216 |
+
border-radius: 0;
|
| 1217 |
+
}
|
| 1218 |
+
.license-banner strong {
|
| 1219 |
+
display: inline-block;
|
| 1220 |
+
margin-right: 8px;
|
| 1221 |
+
font-family: var(--font-mono);
|
| 1222 |
+
letter-spacing: 0.14em;
|
| 1223 |
+
text-transform: uppercase;
|
| 1224 |
+
font-size: 10px;
|
| 1225 |
+
font-weight: 600;
|
| 1226 |
+
}
|
| 1227 |
+
.license-banner a { color: #ffe9a3; text-decoration: underline; text-decoration-thickness: 1px; text-underline-offset: 2px; }
|
| 1228 |
+
|
| 1229 |
+
/* ─────────────── empty viewport: 2x2 wireframe preview of what's coming ─────────────── */
|
| 1230 |
+
.nv-empty {
|
| 1231 |
+
position: relative;
|
| 1232 |
+
width: 100%; aspect-ratio: 1/1; max-height: 720px;
|
| 1233 |
+
background:
|
| 1234 |
+
radial-gradient(circle at 50% 50%, rgba(95, 180, 255, 0.06) 0%, transparent 55%),
|
| 1235 |
+
var(--bg-1);
|
| 1236 |
+
color: var(--muted);
|
| 1237 |
+
overflow: hidden;
|
| 1238 |
+
}
|
| 1239 |
+
/* The 2x2 grid showing where each MPR pane will render after generation */
|
| 1240 |
+
.nv-empty-wireframe {
|
| 1241 |
+
position: absolute; inset: 14px;
|
| 1242 |
+
display: grid;
|
| 1243 |
+
grid-template-columns: 1fr 1fr;
|
| 1244 |
+
grid-template-rows: 1fr 1fr;
|
| 1245 |
+
gap: 14px;
|
| 1246 |
+
}
|
| 1247 |
+
.nv-wireq {
|
| 1248 |
+
position: relative;
|
| 1249 |
+
border: 1px dashed rgba(140, 180, 240, 0.18);
|
| 1250 |
+
background:
|
| 1251 |
+
radial-gradient(circle at 50% 50%, rgba(140, 180, 240, 0.025), transparent 70%);
|
| 1252 |
+
display: flex; align-items: flex-end; justify-content: flex-start;
|
| 1253 |
+
padding: 10px 12px;
|
| 1254 |
+
}
|
| 1255 |
+
.nv-wireq span {
|
| 1256 |
+
font-family: var(--font-mono); font-size: 9.5px;
|
| 1257 |
+
letter-spacing: 0.20em; text-transform: uppercase;
|
| 1258 |
+
color: rgba(140, 180, 240, 0.55);
|
| 1259 |
+
}
|
| 1260 |
+
/* Faint crosshair at the center of each pane to suggest the MPR cursor */
|
| 1261 |
+
.nv-wireq::before, .nv-wireq::after {
|
| 1262 |
+
content: ""; position: absolute;
|
| 1263 |
+
background: rgba(140, 180, 240, 0.18);
|
| 1264 |
+
}
|
| 1265 |
+
.nv-wireq::before { width: 1px; height: 28px; left: 50%; top: 50%; transform: translate(-50%, -50%); }
|
| 1266 |
+
.nv-wireq::after { width: 28px; height: 1px; left: 50%; top: 50%; transform: translate(-50%, -50%); }
|
| 1267 |
+
/* 3D pane gets a different treatment: an isometric box hint */
|
| 1268 |
+
.nv-wireq-3d::before, .nv-wireq-3d::after { display: none; }
|
| 1269 |
+
.nv-wireq-3d {
|
| 1270 |
+
background-image:
|
| 1271 |
+
linear-gradient(135deg, transparent 48%, rgba(140, 180, 240, 0.22) 49%, rgba(140, 180, 240, 0.22) 51%, transparent 52%),
|
| 1272 |
+
linear-gradient(45deg, transparent 48%, rgba(140, 180, 240, 0.10) 49%, rgba(140, 180, 240, 0.10) 51%, transparent 52%),
|
| 1273 |
+
radial-gradient(circle at 50% 50%, rgba(140, 180, 240, 0.04), transparent 70%);
|
| 1274 |
+
background-size: 22px 22px, 22px 22px, auto;
|
| 1275 |
+
background-position: center, center, center;
|
| 1276 |
+
}
|
| 1277 |
+
.nv-empty-text {
|
| 1278 |
+
position: absolute; left: 50%; top: 50%;
|
| 1279 |
+
transform: translate(-50%, -50%);
|
| 1280 |
+
text-align: center;
|
| 1281 |
+
padding: 12px 18px;
|
| 1282 |
+
background: linear-gradient(180deg, rgba(10, 21, 48, 0.92), rgba(10, 21, 48, 0.82));
|
| 1283 |
+
border: 1px solid var(--line);
|
| 1284 |
+
backdrop-filter: blur(6px);
|
| 1285 |
+
z-index: 2;
|
| 1286 |
+
min-width: 280px;
|
| 1287 |
+
}
|
| 1288 |
+
.nv-empty-icon {
|
| 1289 |
+
font-family: var(--font-sans);
|
| 1290 |
+
font-size: 13px;
|
| 1291 |
+
font-weight: 500;
|
| 1292 |
+
color: var(--text);
|
| 1293 |
+
margin-bottom: 6px;
|
| 1294 |
+
}
|
| 1295 |
+
.nv-empty-msg {
|
| 1296 |
+
font-family: var(--font-sans);
|
| 1297 |
+
font-size: 11.5px;
|
| 1298 |
+
color: var(--muted);
|
| 1299 |
+
max-width: 280px; text-align: center;
|
| 1300 |
+
line-height: 1.5;
|
| 1301 |
+
}
|
| 1302 |
+
|
| 1303 |
+
/* ─────────────── anatomy legend ─────────────── */
|
| 1304 |
+
/* Gradio applies elem_classes to both the outer .block wrapper AND the inner
|
| 1305 |
+
.prose container — so .legend-host appears on two nested elements. Scope
|
| 1306 |
+
the panel chrome to the outer .block one only and reset the inner copy. */
|
| 1307 |
+
.legend-host,
|
| 1308 |
+
.prose.legend-host {
|
| 1309 |
+
padding: 0 !important;
|
| 1310 |
+
background: transparent !important;
|
| 1311 |
+
border: 0 !important;
|
| 1312 |
+
margin: 0 !important;
|
| 1313 |
+
max-width: none !important;
|
| 1314 |
+
}
|
| 1315 |
+
.block.legend-host {
|
| 1316 |
+
padding: 16px 18px !important;
|
| 1317 |
+
background: var(--panel) !important;
|
| 1318 |
+
border: 1px solid var(--line) !important;
|
| 1319 |
+
margin: 0 0 14px !important;
|
| 1320 |
+
}
|
| 1321 |
+
.nv-legend { padding: 0; }
|
| 1322 |
+
.nv-legend-title {
|
| 1323 |
+
font-family: var(--font-mono);
|
| 1324 |
+
font-size: 10px;
|
| 1325 |
+
font-weight: 500;
|
| 1326 |
+
letter-spacing: 0.22em;
|
| 1327 |
+
text-transform: uppercase;
|
| 1328 |
+
color: var(--green);
|
| 1329 |
+
margin-bottom: 12px;
|
| 1330 |
+
display: flex; align-items: center; gap: 10px;
|
| 1331 |
+
}
|
| 1332 |
+
.nv-legend-title::before { content: ""; width: 4px; height: 4px; background: var(--green); }
|
| 1333 |
+
.nv-legend-count {
|
| 1334 |
+
font-size: 9px;
|
| 1335 |
+
color: var(--muted);
|
| 1336 |
+
border: 1px solid var(--line);
|
| 1337 |
+
padding: 1px 7px;
|
| 1338 |
+
letter-spacing: 0.10em;
|
| 1339 |
+
margin-left: 4px;
|
| 1340 |
+
}
|
| 1341 |
+
.nv-legend-grid { display: flex; flex-wrap: wrap; gap: 6px; }
|
| 1342 |
+
.nv-legend-chip {
|
| 1343 |
+
display: flex; align-items: center; gap: 8px;
|
| 1344 |
+
padding: 5px 10px;
|
| 1345 |
+
background: var(--bg-1);
|
| 1346 |
+
border: 1px solid var(--line);
|
| 1347 |
+
border-radius: 0;
|
| 1348 |
+
font-family: var(--font-mono); font-size: 10.5px;
|
| 1349 |
+
color: var(--text-2);
|
| 1350 |
+
letter-spacing: 0.02em;
|
| 1351 |
+
text-transform: lowercase;
|
| 1352 |
+
}
|
| 1353 |
+
.nv-swatch { width: 9px; height: 9px; border-radius: 0; display: inline-block; }
|
| 1354 |
+
|
| 1355 |
+
/* Download file widget — self-contained card sitting below the legend with
|
| 1356 |
+
visible breathing room above it. Solid border matches the legend / preset
|
| 1357 |
+
pattern instead of dashed (which read as "drop zone" for a finished file). */
|
| 1358 |
+
.nv-download {
|
| 1359 |
+
background: var(--panel) !important;
|
| 1360 |
+
border: 1px solid var(--line) !important;
|
| 1361 |
+
border-radius: 0 !important;
|
| 1362 |
+
margin: 14px 0 0 !important;
|
| 1363 |
+
padding: 4px !important;
|
| 1364 |
+
}
|
| 1365 |
+
.nv-download .gr-file,
|
| 1366 |
+
.nv-download [class*="file"] {
|
| 1367 |
+
background: transparent !important;
|
| 1368 |
+
border: 0 !important;
|
| 1369 |
+
border-radius: 0 !important;
|
| 1370 |
+
}
|
| 1371 |
+
.nv-download button[aria-label*="Remove" i],
|
| 1372 |
+
.nv-download button[aria-label*="Clear" i],
|
| 1373 |
+
.nv-download button[title*="Remove" i],
|
| 1374 |
+
.nv-download button[title*="Clear" i],
|
| 1375 |
+
.nv-download .delete-btn,
|
| 1376 |
+
.nv-download .clear-button,
|
| 1377 |
+
.nv-download .icon-button[aria-label*="x" i] {
|
| 1378 |
+
display: none !important;
|
| 1379 |
+
}
|
| 1380 |
+
/* Override the label heading inside the file widget so it matches our type system */
|
| 1381 |
+
.nv-download label,
|
| 1382 |
+
.nv-download [data-testid="file-label"] {
|
| 1383 |
+
font-family: var(--font-mono) !important;
|
| 1384 |
+
font-size: 10px !important;
|
| 1385 |
+
letter-spacing: 0.18em !important;
|
| 1386 |
+
text-transform: uppercase !important;
|
| 1387 |
+
color: var(--muted) !important;
|
| 1388 |
+
padding: 8px 12px !important;
|
| 1389 |
+
}
|
| 1390 |
+
|
| 1391 |
+
/* Hide Gradio footer */
|
| 1392 |
+
footer { display: none !important; }
|
| 1393 |
+
|
| 1394 |
+
/* ─────────────── credits strip (two-line: papers + affiliations) ─────────────── */
|
| 1395 |
+
.credits-strip {
|
| 1396 |
+
display: flex; flex-direction: column; align-items: center; gap: 8px;
|
| 1397 |
+
padding: 28px 0 8px;
|
| 1398 |
+
margin-top: 8px;
|
| 1399 |
+
border-top: 1px solid var(--line);
|
| 1400 |
+
font-family: var(--font-mono); font-size: 9.5px;
|
| 1401 |
+
letter-spacing: 0.22em; text-transform: uppercase;
|
| 1402 |
+
color: var(--muted);
|
| 1403 |
+
animation: fadein 0.6s ease 0.6s both;
|
| 1404 |
+
}
|
| 1405 |
+
.credits-line {
|
| 1406 |
+
display: flex; justify-content: center; flex-wrap: wrap; gap: 12px;
|
| 1407 |
+
}
|
| 1408 |
+
.credits-strip .credits-sep { color: var(--muted-2); opacity: 0.6; }
|
| 1409 |
+
.credits-strip .credits-strong { color: var(--text-2); }
|
| 1410 |
+
.credits-strip a { color: inherit; text-decoration: none; transition: color 160ms ease; }
|
| 1411 |
+
.credits-strip a:hover { color: var(--green); }
|
| 1412 |
+
.credits-papers a.credits-strong { color: var(--text); }
|
| 1413 |
+
.credits-affil { font-size: 9px; opacity: 0.85; }
|
| 1414 |
+
|
| 1415 |
+
/* (Intentionally no position:relative on gradio-app or .gradio-container —
|
| 1416 |
+
Gradio's dropdown popup uses position:absolute calculated relative to the
|
| 1417 |
+
nearest positioned ancestor, and adding extra positioned wrappers makes the
|
| 1418 |
+
popup snap to the wrong containing block.) */
|
| 1419 |
+
|
| 1420 |
+
/* Subtle scrollbar */
|
| 1421 |
+
::-webkit-scrollbar { width: 6px; height: 6px; }
|
| 1422 |
+
::-webkit-scrollbar-track { background: var(--bg-1); }
|
| 1423 |
+
::-webkit-scrollbar-thumb { background: var(--line-strong); }
|
| 1424 |
+
::-webkit-scrollbar-thumb:hover { background: var(--line-bright); }
|
| 1425 |
+
"""
|
| 1426 |
+
|
| 1427 |
+
|
| 1428 |
+
def build_app() -> gr.Blocks:
|
| 1429 |
+
with gr.Blocks(title="NV-Generate") as app:
|
| 1430 |
+
hero_group, hero_buttons = render_hero()
|
| 1431 |
+
ct_group, ct_back = workspace_ct.build(spaces_gpu_ct)
|
| 1432 |
+
mr_group, mr_back = workspace_mr.build(spaces_gpu_mr)
|
| 1433 |
+
mrb_group, mrb_back = workspace_mr_brain.build(spaces_gpu_mr_brain)
|
| 1434 |
+
|
| 1435 |
+
def _show(active: str):
|
| 1436 |
+
return (
|
| 1437 |
+
gr.update(visible=(active == "home")),
|
| 1438 |
+
gr.update(visible=(active == "ct")),
|
| 1439 |
+
gr.update(visible=(active == "mr")),
|
| 1440 |
+
gr.update(visible=(active == "mr_brain")),
|
| 1441 |
+
)
|
| 1442 |
+
|
| 1443 |
+
outputs = [hero_group, ct_group, mr_group, mrb_group]
|
| 1444 |
+
hero_buttons["ct"].click(lambda: _show("ct"), outputs=outputs)
|
| 1445 |
+
hero_buttons["mr"].click(lambda: _show("mr"), outputs=outputs)
|
| 1446 |
+
hero_buttons["mr_brain"].click(lambda: _show("mr_brain"), outputs=outputs)
|
| 1447 |
+
ct_back.click(lambda: _show("home"), outputs=outputs)
|
| 1448 |
+
mr_back.click(lambda: _show("home"), outputs=outputs)
|
| 1449 |
+
mrb_back.click(lambda: _show("home"), outputs=outputs)
|
| 1450 |
+
|
| 1451 |
+
return app
|
| 1452 |
+
|
| 1453 |
+
|
| 1454 |
+
if __name__ == "__main__":
|
| 1455 |
+
app = build_app()
|
| 1456 |
+
app.launch(
|
| 1457 |
+
server_name="0.0.0.0",
|
| 1458 |
+
server_port=int(os.environ.get("PORT", "7860")),
|
| 1459 |
+
show_error=True,
|
| 1460 |
+
css=CSS,
|
| 1461 |
+
theme=gr.themes.Base(),
|
| 1462 |
+
)
|
pipelines/__init__.py
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from .base import GenerationRequest, GenerationResult
|
| 2 |
+
|
| 3 |
+
__all__ = ["GenerationRequest", "GenerationResult"]
|
pipelines/_runner.py
ADDED
|
@@ -0,0 +1,265 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""
|
| 2 |
+
Shared driver for the upstream NV-Generate-CTMR scripts.
|
| 3 |
+
|
| 4 |
+
Strategy: the upstream code is structured around argparse + global filesystem layout
|
| 5 |
+
(reads relative-path configs, writes to a relative output_dir). Rather than refactor
|
| 6 |
+
its internals, we treat it as an external tool: chdir into the upstream root, write
|
| 7 |
+
modified config copies that override the user-controlled fields, ensure weights are
|
| 8 |
+
downloaded, then call the upstream entry-point function. We then return the path of
|
| 9 |
+
the most recently produced NIfTI from the configured output dir.
|
| 10 |
+
"""
|
| 11 |
+
from __future__ import annotations
|
| 12 |
+
|
| 13 |
+
import contextlib
|
| 14 |
+
import importlib
|
| 15 |
+
import json
|
| 16 |
+
import os
|
| 17 |
+
import sys
|
| 18 |
+
import time
|
| 19 |
+
import uuid
|
| 20 |
+
from pathlib import Path
|
| 21 |
+
from typing import Iterable, Optional
|
| 22 |
+
|
| 23 |
+
ROOT = Path(__file__).resolve().parent.parent
|
| 24 |
+
UPSTREAM = ROOT / "repos" / "NV-Generate-CTMR"
|
| 25 |
+
GENERATED_OUTPUT = UPSTREAM / "output"
|
| 26 |
+
|
| 27 |
+
|
| 28 |
+
@contextlib.contextmanager
|
| 29 |
+
def upstream_context():
|
| 30 |
+
"""Temporarily add the upstream repo to sys.path and switch CWD to it."""
|
| 31 |
+
if not UPSTREAM.exists():
|
| 32 |
+
raise RuntimeError(
|
| 33 |
+
f"Upstream repo not found at {UPSTREAM}. Run `bash pre-build.sh` first."
|
| 34 |
+
)
|
| 35 |
+
prev_cwd = os.getcwd()
|
| 36 |
+
added = False
|
| 37 |
+
try:
|
| 38 |
+
upstream_str = str(UPSTREAM)
|
| 39 |
+
if upstream_str not in sys.path:
|
| 40 |
+
sys.path.insert(0, upstream_str)
|
| 41 |
+
added = True
|
| 42 |
+
os.chdir(upstream_str)
|
| 43 |
+
yield UPSTREAM
|
| 44 |
+
finally:
|
| 45 |
+
os.chdir(prev_cwd)
|
| 46 |
+
if added and upstream_str in sys.path:
|
| 47 |
+
sys.path.remove(upstream_str)
|
| 48 |
+
|
| 49 |
+
|
| 50 |
+
def ensure_weights(version: str) -> None:
|
| 51 |
+
"""Download model weights from HF Hub if not already on disk."""
|
| 52 |
+
with upstream_context():
|
| 53 |
+
download_mod = importlib.import_module("scripts.download_model_data")
|
| 54 |
+
# download_model_data is idempotent — it skips files that already exist.
|
| 55 |
+
download_mod.download_model_data(version, "./", model_only=False if version in ("rflow-ct", "ddpm-ct") else True)
|
| 56 |
+
|
| 57 |
+
|
| 58 |
+
def _list_outputs_before(output_dir: Path) -> set[str]:
|
| 59 |
+
if not output_dir.exists():
|
| 60 |
+
return set()
|
| 61 |
+
return {p.name for p in output_dir.glob("*.nii.gz")}
|
| 62 |
+
|
| 63 |
+
|
| 64 |
+
def _newest_outputs(output_dir: Path, before: set[str]) -> list[Path]:
|
| 65 |
+
if not output_dir.exists():
|
| 66 |
+
return []
|
| 67 |
+
new = [p for p in output_dir.glob("*.nii.gz") if p.name not in before]
|
| 68 |
+
new.sort(key=lambda p: p.stat().st_mtime)
|
| 69 |
+
return new
|
| 70 |
+
|
| 71 |
+
|
| 72 |
+
def _write_temp_configs(
|
| 73 |
+
base_env_config: Path,
|
| 74 |
+
base_model_config: Path,
|
| 75 |
+
overrides: dict,
|
| 76 |
+
tag: str,
|
| 77 |
+
) -> tuple[Path, Path]:
|
| 78 |
+
"""
|
| 79 |
+
Write modified copies of the env + model configs into a per-call temp dir under
|
| 80 |
+
UPSTREAM / configs / _temp /. Returns (env_path, model_path).
|
| 81 |
+
"""
|
| 82 |
+
temp_dir = UPSTREAM / "configs" / "_temp"
|
| 83 |
+
temp_dir.mkdir(parents=True, exist_ok=True)
|
| 84 |
+
|
| 85 |
+
env = json.loads(base_env_config.read_text())
|
| 86 |
+
model = json.loads(base_model_config.read_text())
|
| 87 |
+
if "env" in overrides:
|
| 88 |
+
env.update(overrides["env"])
|
| 89 |
+
if "diffusion_unet_inference" in overrides:
|
| 90 |
+
model.setdefault("diffusion_unet_inference", {}).update(overrides["diffusion_unet_inference"])
|
| 91 |
+
|
| 92 |
+
suffix = f"{tag}_{uuid.uuid4().hex[:8]}"
|
| 93 |
+
env_path = temp_dir / f"env_{suffix}.json"
|
| 94 |
+
model_path = temp_dir / f"model_{suffix}.json"
|
| 95 |
+
env_path.write_text(json.dumps(env, indent=2))
|
| 96 |
+
model_path.write_text(json.dumps(model, indent=2))
|
| 97 |
+
return env_path, model_path
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
def run_image_only(
|
| 101 |
+
*,
|
| 102 |
+
version: str,
|
| 103 |
+
output_size: tuple[int, int, int],
|
| 104 |
+
spacing: tuple[float, float, float],
|
| 105 |
+
modality: int,
|
| 106 |
+
seed: int,
|
| 107 |
+
num_inference_steps: int = 30,
|
| 108 |
+
cfg_guidance_scale: Optional[float] = None,
|
| 109 |
+
) -> Path:
|
| 110 |
+
"""
|
| 111 |
+
Run the image-only diffusion pipeline (`scripts.diff_model_infer`) for the given
|
| 112 |
+
version (rflow-ct / rflow-mr / rflow-mr-brain). Returns path to generated NIfTI.
|
| 113 |
+
"""
|
| 114 |
+
ensure_weights(version)
|
| 115 |
+
|
| 116 |
+
base_env = UPSTREAM / "configs" / f"environment_maisi_diff_model_{version}.json"
|
| 117 |
+
base_model = UPSTREAM / "configs" / f"config_maisi_diff_model_{version}.json"
|
| 118 |
+
network_def = UPSTREAM / "configs" / "config_network_rflow.json"
|
| 119 |
+
|
| 120 |
+
inference_overrides = {
|
| 121 |
+
"dim": list(output_size),
|
| 122 |
+
"spacing": list(spacing),
|
| 123 |
+
"modality": modality,
|
| 124 |
+
"random_seed": seed,
|
| 125 |
+
"num_inference_steps": num_inference_steps,
|
| 126 |
+
}
|
| 127 |
+
if cfg_guidance_scale is not None:
|
| 128 |
+
inference_overrides["cfg_guidance_scale"] = cfg_guidance_scale
|
| 129 |
+
|
| 130 |
+
with upstream_context():
|
| 131 |
+
env_path, model_path = _write_temp_configs(
|
| 132 |
+
base_env_config=base_env,
|
| 133 |
+
base_model_config=base_model,
|
| 134 |
+
overrides={"diffusion_unet_inference": inference_overrides},
|
| 135 |
+
tag=version,
|
| 136 |
+
)
|
| 137 |
+
|
| 138 |
+
# Read env to determine output_dir (relative to upstream root)
|
| 139 |
+
env_data = json.loads(env_path.read_text())
|
| 140 |
+
output_dir = (UPSTREAM / env_data["output_dir"]).resolve()
|
| 141 |
+
existing = _list_outputs_before(output_dir)
|
| 142 |
+
|
| 143 |
+
diff_mod = importlib.import_module("scripts.diff_model_infer")
|
| 144 |
+
|
| 145 |
+
t0 = time.time()
|
| 146 |
+
diff_mod.diff_model_infer(
|
| 147 |
+
env_config_path=str(env_path.relative_to(UPSTREAM)),
|
| 148 |
+
model_config_path=str(model_path.relative_to(UPSTREAM)),
|
| 149 |
+
model_def_path=str(network_def.relative_to(UPSTREAM)),
|
| 150 |
+
num_gpus=1,
|
| 151 |
+
)
|
| 152 |
+
runtime = time.time() - t0
|
| 153 |
+
|
| 154 |
+
new_files = _newest_outputs(output_dir, existing)
|
| 155 |
+
if not new_files:
|
| 156 |
+
raise RuntimeError(f"No new NIfTI produced in {output_dir}")
|
| 157 |
+
latest = new_files[-1]
|
| 158 |
+
|
| 159 |
+
# Cleanup temp configs (don't fail if cleanup errors)
|
| 160 |
+
for p in (env_path, model_path):
|
| 161 |
+
try:
|
| 162 |
+
p.unlink()
|
| 163 |
+
except OSError:
|
| 164 |
+
pass
|
| 165 |
+
|
| 166 |
+
return latest
|
| 167 |
+
|
| 168 |
+
|
| 169 |
+
def run_paired_ct(
|
| 170 |
+
*,
|
| 171 |
+
output_size: tuple[int, int, int],
|
| 172 |
+
spacing: tuple[float, float, float],
|
| 173 |
+
body_region: list[str],
|
| 174 |
+
anatomy_list: list[str],
|
| 175 |
+
seed: int,
|
| 176 |
+
num_inference_steps: int = 30,
|
| 177 |
+
num_output_samples: int = 1,
|
| 178 |
+
) -> tuple[Path, Optional[Path]]:
|
| 179 |
+
"""
|
| 180 |
+
Run the paired CT image+mask pipeline (`scripts.inference`). Returns
|
| 181 |
+
(image_path, mask_path). Mask is the corresponding label volume.
|
| 182 |
+
"""
|
| 183 |
+
version = "rflow-ct"
|
| 184 |
+
ensure_weights(version)
|
| 185 |
+
|
| 186 |
+
base_env = UPSTREAM / "configs" / f"environment_{version}.json"
|
| 187 |
+
base_infer = UPSTREAM / "configs" / "config_infer.json"
|
| 188 |
+
|
| 189 |
+
# Build a custom config_infer with overrides
|
| 190 |
+
infer_data = json.loads(base_infer.read_text())
|
| 191 |
+
infer_data["output_size"] = list(output_size)
|
| 192 |
+
infer_data["spacing"] = list(spacing)
|
| 193 |
+
infer_data["body_region"] = list(body_region)
|
| 194 |
+
infer_data["anatomy_list"] = list(anatomy_list)
|
| 195 |
+
infer_data["num_inference_steps"] = num_inference_steps
|
| 196 |
+
infer_data["num_output_samples"] = num_output_samples
|
| 197 |
+
|
| 198 |
+
temp_dir = UPSTREAM / "configs" / "_temp"
|
| 199 |
+
temp_dir.mkdir(parents=True, exist_ok=True)
|
| 200 |
+
suffix = uuid.uuid4().hex[:8]
|
| 201 |
+
infer_path = temp_dir / f"config_infer_{version}_{suffix}.json"
|
| 202 |
+
infer_path.write_text(json.dumps(infer_data, indent=2))
|
| 203 |
+
|
| 204 |
+
env_data = json.loads(base_env.read_text())
|
| 205 |
+
output_dir = (UPSTREAM / env_data["output_dir"]).resolve()
|
| 206 |
+
|
| 207 |
+
with upstream_context():
|
| 208 |
+
existing = _list_outputs_before(output_dir)
|
| 209 |
+
|
| 210 |
+
inference_mod = importlib.import_module("scripts.inference")
|
| 211 |
+
# The upstream `main()` parses argv directly. Patch sys.argv around the call.
|
| 212 |
+
old_argv = sys.argv
|
| 213 |
+
sys.argv = [
|
| 214 |
+
"scripts.inference",
|
| 215 |
+
"-t", "./configs/config_network_rflow.json",
|
| 216 |
+
"-i", str(infer_path.relative_to(UPSTREAM)),
|
| 217 |
+
"-e", str(base_env.relative_to(UPSTREAM)),
|
| 218 |
+
"--random-seed", str(seed),
|
| 219 |
+
"--version", version,
|
| 220 |
+
]
|
| 221 |
+
os.environ.setdefault("MONAI_DATA_DIRECTORY", str(UPSTREAM / "temp_work_dir"))
|
| 222 |
+
|
| 223 |
+
try:
|
| 224 |
+
inference_mod.main()
|
| 225 |
+
finally:
|
| 226 |
+
sys.argv = old_argv
|
| 227 |
+
|
| 228 |
+
new_files = _newest_outputs(output_dir, existing)
|
| 229 |
+
|
| 230 |
+
try:
|
| 231 |
+
infer_path.unlink()
|
| 232 |
+
except OSError:
|
| 233 |
+
pass
|
| 234 |
+
|
| 235 |
+
# Paired pipeline writes both image and label NIfTIs. Convention: filenames
|
| 236 |
+
# contain "image" / "label" or are emitted as adjacent files.
|
| 237 |
+
image_path: Optional[Path] = None
|
| 238 |
+
mask_path: Optional[Path] = None
|
| 239 |
+
for p in new_files:
|
| 240 |
+
name = p.name.lower()
|
| 241 |
+
if "label" in name or "_mask" in name or "seg" in name:
|
| 242 |
+
mask_path = p
|
| 243 |
+
elif "image" in name or "img" in name:
|
| 244 |
+
image_path = p
|
| 245 |
+
|
| 246 |
+
# Fallback: if naming is ambiguous, treat the smaller-modality-time file as image
|
| 247 |
+
if image_path is None and new_files:
|
| 248 |
+
image_path = new_files[0]
|
| 249 |
+
if mask_path is None and len(new_files) > 1:
|
| 250 |
+
mask_path = new_files[-1]
|
| 251 |
+
|
| 252 |
+
if image_path is None:
|
| 253 |
+
raise RuntimeError(f"No NIfTI produced in {output_dir}")
|
| 254 |
+
return image_path, mask_path
|
| 255 |
+
|
| 256 |
+
|
| 257 |
+
def labels_present(mask_path: Path) -> set[int]:
|
| 258 |
+
"""Return the set of unique non-zero label IDs present in the mask volume."""
|
| 259 |
+
import nibabel as nib
|
| 260 |
+
import numpy as np
|
| 261 |
+
|
| 262 |
+
img = nib.load(str(mask_path))
|
| 263 |
+
data = np.asarray(img.dataobj)
|
| 264 |
+
uniq = np.unique(data).astype(int).tolist()
|
| 265 |
+
return {int(u) for u in uniq if u != 0}
|
pipelines/base.py
ADDED
|
@@ -0,0 +1,37 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from __future__ import annotations
|
| 2 |
+
|
| 3 |
+
from dataclasses import dataclass, field
|
| 4 |
+
from typing import Literal, Optional
|
| 5 |
+
|
| 6 |
+
ModelKey = Literal["ct", "mr", "mr_brain"]
|
| 7 |
+
|
| 8 |
+
|
| 9 |
+
@dataclass
|
| 10 |
+
class GenerationRequest:
|
| 11 |
+
model: ModelKey
|
| 12 |
+
output_size: tuple[int, int, int]
|
| 13 |
+
spacing: tuple[float, float, float]
|
| 14 |
+
seed: int = 0
|
| 15 |
+
num_steps: int = 30
|
| 16 |
+
cfg_guidance_scale: float = 0.0
|
| 17 |
+
|
| 18 |
+
# CT-only
|
| 19 |
+
body_region: Optional[list[str]] = None
|
| 20 |
+
anatomy_list: Optional[list[str]] = None
|
| 21 |
+
generate_masks: bool = True
|
| 22 |
+
|
| 23 |
+
# MR-only (modality int from configs/modality_mapping.json: 8/9/10/11/...)
|
| 24 |
+
modality_class: Optional[int] = None
|
| 25 |
+
|
| 26 |
+
# MR-Brain-only (mapped to a modality int)
|
| 27 |
+
contrast: Optional[str] = None # "T1" / "T2" / "FLAIR" / "SWI" / "T1_skull_stripped" / ...
|
| 28 |
+
|
| 29 |
+
|
| 30 |
+
@dataclass
|
| 31 |
+
class GenerationResult:
|
| 32 |
+
volume_path: str
|
| 33 |
+
mask_path: Optional[str] = None
|
| 34 |
+
used_anatomy_labels: dict[int, str] = field(default_factory=dict)
|
| 35 |
+
runtime_seconds: float = 0.0
|
| 36 |
+
seed: int = 0
|
| 37 |
+
modality: Optional[int] = None
|
pipelines/ct.py
ADDED
|
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from __future__ import annotations
|
| 2 |
+
|
| 3 |
+
import time
|
| 4 |
+
|
| 5 |
+
from .base import GenerationRequest, GenerationResult
|
| 6 |
+
from . import _runner
|
| 7 |
+
|
| 8 |
+
|
| 9 |
+
def generate(req: GenerationRequest) -> GenerationResult:
|
| 10 |
+
"""CT generation. With masks: paired pipeline. Without: image-only."""
|
| 11 |
+
t0 = time.time()
|
| 12 |
+
if req.generate_masks:
|
| 13 |
+
image_path, mask_path = _runner.run_paired_ct(
|
| 14 |
+
output_size=req.output_size,
|
| 15 |
+
spacing=req.spacing,
|
| 16 |
+
body_region=req.body_region or [],
|
| 17 |
+
anatomy_list=req.anatomy_list or ["liver"],
|
| 18 |
+
seed=req.seed,
|
| 19 |
+
num_inference_steps=req.num_steps,
|
| 20 |
+
)
|
| 21 |
+
used: dict[int, str] = {}
|
| 22 |
+
if mask_path is not None:
|
| 23 |
+
from viewer.colormaps import CT_LABELS_BY_ID
|
| 24 |
+
|
| 25 |
+
present = _runner.labels_present(mask_path)
|
| 26 |
+
used = {lbl: CT_LABELS_BY_ID.get(lbl, f"label {lbl}") for lbl in sorted(present)}
|
| 27 |
+
return GenerationResult(
|
| 28 |
+
volume_path=str(image_path),
|
| 29 |
+
mask_path=str(mask_path) if mask_path else None,
|
| 30 |
+
used_anatomy_labels=used,
|
| 31 |
+
runtime_seconds=time.time() - t0,
|
| 32 |
+
seed=req.seed,
|
| 33 |
+
modality=1,
|
| 34 |
+
)
|
| 35 |
+
else:
|
| 36 |
+
path = _runner.run_image_only(
|
| 37 |
+
version="rflow-ct",
|
| 38 |
+
output_size=req.output_size,
|
| 39 |
+
spacing=req.spacing,
|
| 40 |
+
modality=1,
|
| 41 |
+
seed=req.seed,
|
| 42 |
+
num_inference_steps=req.num_steps,
|
| 43 |
+
)
|
| 44 |
+
return GenerationResult(
|
| 45 |
+
volume_path=str(path),
|
| 46 |
+
runtime_seconds=time.time() - t0,
|
| 47 |
+
seed=req.seed,
|
| 48 |
+
modality=1,
|
| 49 |
+
)
|
pipelines/mr.py
ADDED
|
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from __future__ import annotations
|
| 2 |
+
|
| 3 |
+
import time
|
| 4 |
+
|
| 5 |
+
from .base import GenerationRequest, GenerationResult
|
| 6 |
+
from . import _runner
|
| 7 |
+
|
| 8 |
+
|
| 9 |
+
def generate(req: GenerationRequest) -> GenerationResult:
|
| 10 |
+
"""MR (rflow-mr) — image-only across multiple contrasts and anatomies."""
|
| 11 |
+
if req.modality_class is None:
|
| 12 |
+
raise ValueError("MR generation requires modality_class (8=mri, 9=t1, 10=t2, 11=flair, ...)")
|
| 13 |
+
t0 = time.time()
|
| 14 |
+
path = _runner.run_image_only(
|
| 15 |
+
version="rflow-mr",
|
| 16 |
+
output_size=req.output_size,
|
| 17 |
+
spacing=req.spacing,
|
| 18 |
+
modality=req.modality_class,
|
| 19 |
+
seed=req.seed,
|
| 20 |
+
num_inference_steps=req.num_steps,
|
| 21 |
+
cfg_guidance_scale=req.cfg_guidance_scale or 15.0,
|
| 22 |
+
)
|
| 23 |
+
return GenerationResult(
|
| 24 |
+
volume_path=str(path),
|
| 25 |
+
runtime_seconds=time.time() - t0,
|
| 26 |
+
seed=req.seed,
|
| 27 |
+
modality=req.modality_class,
|
| 28 |
+
)
|
pipelines/mr_brain.py
ADDED
|
@@ -0,0 +1,42 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from __future__ import annotations
|
| 2 |
+
|
| 3 |
+
import time
|
| 4 |
+
|
| 5 |
+
from .base import GenerationRequest, GenerationResult
|
| 6 |
+
from . import _runner
|
| 7 |
+
|
| 8 |
+
CONTRAST_TO_MODALITY: dict[str, int] = {
|
| 9 |
+
"T1": 9,
|
| 10 |
+
"T2": 10,
|
| 11 |
+
"FLAIR": 11,
|
| 12 |
+
"SWI": 20,
|
| 13 |
+
"T1_skull_stripped": 29,
|
| 14 |
+
"T2_skull_stripped": 30,
|
| 15 |
+
"FLAIR_skull_stripped": 31,
|
| 16 |
+
"SWI_skull_stripped": 32,
|
| 17 |
+
}
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
def generate(req: GenerationRequest) -> GenerationResult:
|
| 21 |
+
"""MR Brain (rflow-mr-brain) — image-only multi-contrast brain MRI."""
|
| 22 |
+
contrast = req.contrast or "T1"
|
| 23 |
+
if contrast not in CONTRAST_TO_MODALITY:
|
| 24 |
+
raise ValueError(f"Unsupported contrast: {contrast}. Choose from {list(CONTRAST_TO_MODALITY)}")
|
| 25 |
+
modality = CONTRAST_TO_MODALITY[contrast]
|
| 26 |
+
|
| 27 |
+
t0 = time.time()
|
| 28 |
+
path = _runner.run_image_only(
|
| 29 |
+
version="rflow-mr-brain",
|
| 30 |
+
output_size=req.output_size,
|
| 31 |
+
spacing=req.spacing,
|
| 32 |
+
modality=modality,
|
| 33 |
+
seed=req.seed,
|
| 34 |
+
num_inference_steps=req.num_steps,
|
| 35 |
+
cfg_guidance_scale=req.cfg_guidance_scale or 10.0,
|
| 36 |
+
)
|
| 37 |
+
return GenerationResult(
|
| 38 |
+
volume_path=str(path),
|
| 39 |
+
runtime_seconds=time.time() - t0,
|
| 40 |
+
seed=req.seed,
|
| 41 |
+
modality=modality,
|
| 42 |
+
)
|
pre-build.sh
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/usr/bin/env bash
|
| 2 |
+
# Run at HF Spaces build time (or locally before first run) to pull upstream code.
|
| 3 |
+
set -euo pipefail
|
| 4 |
+
ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
|
| 5 |
+
mkdir -p "${ROOT}/repos"
|
| 6 |
+
if [ ! -d "${ROOT}/repos/NV-Generate-CTMR" ]; then
|
| 7 |
+
git clone --depth 1 https://github.com/NVIDIA-Medtech/NV-Generate-CTMR.git "${ROOT}/repos/NV-Generate-CTMR"
|
| 8 |
+
fi
|
| 9 |
+
echo "Upstream repo ready at ${ROOT}/repos/NV-Generate-CTMR"
|
requirements.txt
ADDED
|
@@ -0,0 +1,17 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Gradio app
|
| 2 |
+
gradio>=5.0
|
| 3 |
+
spaces # ZeroGPU decorator (no-op locally)
|
| 4 |
+
|
| 5 |
+
# Upstream NV-Generate-CTMR dependencies
|
| 6 |
+
torch>=2.1.0
|
| 7 |
+
monai>=1.5.0
|
| 8 |
+
numpy>=1.24.0
|
| 9 |
+
scipy>=1.10.0
|
| 10 |
+
scikit-image>=0.20.0
|
| 11 |
+
nibabel>=5.0.0
|
| 12 |
+
matplotlib>=3.7.0
|
| 13 |
+
einops>=0.7.0
|
| 14 |
+
huggingface_hub>=0.20.0
|
| 15 |
+
tqdm>=4.65.0
|
| 16 |
+
fire>=0.5.0
|
| 17 |
+
PyYAML>=6.0
|
ui/__init__.py
ADDED
|
File without changes
|
ui/hero.py
ADDED
|
@@ -0,0 +1,240 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""Hero / landing page — NV-Generate masthead + three equal-height datasheet cards."""
|
| 2 |
+
from __future__ import annotations
|
| 3 |
+
|
| 4 |
+
import gradio as gr
|
| 5 |
+
|
| 6 |
+
# SVG modality glyphs — each is a recognizable anatomical silhouette of the modality.
|
| 7 |
+
# CT: axial body cross-section with spine and ribs.
|
| 8 |
+
# MR: a k-space spiral trajectory.
|
| 9 |
+
# MR-Brain: an axial brain outline with hemispheres.
|
| 10 |
+
SVG_CT = """
|
| 11 |
+
<svg viewBox="0 0 80 80" xmlns="http://www.w3.org/2000/svg" aria-hidden="true">
|
| 12 |
+
<!-- Axial body cross-section silhouette -->
|
| 13 |
+
<ellipse cx="40" cy="44" rx="30" ry="24" fill="none" stroke="currentColor" stroke-width="1.2"/>
|
| 14 |
+
<!-- Lungs (left & right) -->
|
| 15 |
+
<path d="M22 38 Q20 50 26 56 Q32 54 33 44 Q33 36 28 34 Q24 34 22 38 Z"
|
| 16 |
+
fill="none" stroke="currentColor" stroke-width="0.9" stroke-opacity="0.7"/>
|
| 17 |
+
<path d="M58 38 Q60 50 54 56 Q48 54 47 44 Q47 36 52 34 Q56 34 58 38 Z"
|
| 18 |
+
fill="none" stroke="currentColor" stroke-width="0.9" stroke-opacity="0.7"/>
|
| 19 |
+
<!-- Spine vertebra -->
|
| 20 |
+
<ellipse cx="40" cy="56" rx="5" ry="4" fill="none" stroke="currentColor" stroke-width="0.9"/>
|
| 21 |
+
<circle cx="40" cy="56" r="1.5" fill="currentColor" opacity="0.6"/>
|
| 22 |
+
<!-- Calibration ticks -->
|
| 23 |
+
<line x1="4" y1="44" x2="10" y2="44" stroke="currentColor" stroke-width="0.6" stroke-opacity="0.6"/>
|
| 24 |
+
<line x1="70" y1="44" x2="76" y2="44" stroke="currentColor" stroke-width="0.6" stroke-opacity="0.6"/>
|
| 25 |
+
<line x1="40" y1="14" x2="40" y2="20" stroke="currentColor" stroke-width="0.6" stroke-opacity="0.6"/>
|
| 26 |
+
<line x1="40" y1="68" x2="40" y2="74" stroke="currentColor" stroke-width="0.6" stroke-opacity="0.6"/>
|
| 27 |
+
</svg>
|
| 28 |
+
"""
|
| 29 |
+
|
| 30 |
+
SVG_MR = """
|
| 31 |
+
<svg viewBox="0 0 80 80" xmlns="http://www.w3.org/2000/svg" aria-hidden="true">
|
| 32 |
+
<!-- k-space spiral trajectory: concentric arcs forming an inward spiral -->
|
| 33 |
+
<circle cx="40" cy="40" r="6" fill="none" stroke="currentColor" stroke-width="1" stroke-opacity="1.0"/>
|
| 34 |
+
<circle cx="40" cy="40" r="12" fill="none" stroke="currentColor" stroke-width="1" stroke-opacity="0.8" stroke-dasharray="6 1"/>
|
| 35 |
+
<circle cx="40" cy="40" r="18" fill="none" stroke="currentColor" stroke-width="1" stroke-opacity="0.6" stroke-dasharray="8 2"/>
|
| 36 |
+
<circle cx="40" cy="40" r="24" fill="none" stroke="currentColor" stroke-width="1" stroke-opacity="0.4" stroke-dasharray="10 3"/>
|
| 37 |
+
<circle cx="40" cy="40" r="30" fill="none" stroke="currentColor" stroke-width="0.8" stroke-opacity="0.25" stroke-dasharray="12 4"/>
|
| 38 |
+
<!-- Radial sampling line from center outward -->
|
| 39 |
+
<line x1="40" y1="40" x2="62" y2="22" stroke="currentColor" stroke-width="1.2" stroke-linecap="round"/>
|
| 40 |
+
<circle cx="40" cy="40" r="1.8" fill="currentColor"/>
|
| 41 |
+
<circle cx="62" cy="22" r="1.5" fill="currentColor" opacity="0.6"/>
|
| 42 |
+
</svg>
|
| 43 |
+
"""
|
| 44 |
+
|
| 45 |
+
SVG_MRB = """
|
| 46 |
+
<svg viewBox="0 0 80 80" xmlns="http://www.w3.org/2000/svg" aria-hidden="true">
|
| 47 |
+
<!-- Axial brain silhouette with hemispheres -->
|
| 48 |
+
<path d="M40 14
|
| 49 |
+
C28 14 18 22 16 34
|
| 50 |
+
C14 44 18 56 30 62
|
| 51 |
+
L33 62
|
| 52 |
+
C24 56 22 48 24 38
|
| 53 |
+
C26 28 32 22 40 22
|
| 54 |
+
C48 22 54 28 56 38
|
| 55 |
+
C58 48 56 56 47 62
|
| 56 |
+
L50 62
|
| 57 |
+
C62 56 66 44 64 34
|
| 58 |
+
C62 22 52 14 40 14 Z"
|
| 59 |
+
fill="none" stroke="currentColor" stroke-width="1.2"/>
|
| 60 |
+
<!-- Midline (longitudinal fissure) -->
|
| 61 |
+
<line x1="40" y1="16" x2="40" y2="62" stroke="currentColor" stroke-width="0.9" stroke-opacity="0.55"/>
|
| 62 |
+
<!-- Gyrus / sulcus hints, left & right -->
|
| 63 |
+
<path d="M28 28 Q34 32 32 38" fill="none" stroke="currentColor" stroke-width="0.6" stroke-opacity="0.5"/>
|
| 64 |
+
<path d="M52 28 Q46 32 48 38" fill="none" stroke="currentColor" stroke-width="0.6" stroke-opacity="0.5"/>
|
| 65 |
+
<path d="M28 44 Q34 48 32 54" fill="none" stroke="currentColor" stroke-width="0.6" stroke-opacity="0.5"/>
|
| 66 |
+
<path d="M52 44 Q46 48 48 54" fill="none" stroke="currentColor" stroke-width="0.6" stroke-opacity="0.5"/>
|
| 67 |
+
</svg>
|
| 68 |
+
"""
|
| 69 |
+
|
| 70 |
+
# Each card has exactly 5 spec rows, each value short enough to render on one line.
|
| 71 |
+
CARDS = [
|
| 72 |
+
{
|
| 73 |
+
"key": "ct",
|
| 74 |
+
"index": "01",
|
| 75 |
+
"title": "NV-Generate · CT",
|
| 76 |
+
"subtitle": "Whole-body synthetic CT with paired anatomy masks.",
|
| 77 |
+
"icon": SVG_CT,
|
| 78 |
+
"icon_caption": "Body region · paired anatomy",
|
| 79 |
+
# Consistent category: USE CASES across all three cards.
|
| 80 |
+
"uses": ["Segmentation data", "Pathology augmentation", "Privacy-preserving sharing"],
|
| 81 |
+
"license": "NVIDIA Open Model",
|
| 82 |
+
"license_tone": "ok",
|
| 83 |
+
"spec": [
|
| 84 |
+
("MODALITY", "Computed Tomography"),
|
| 85 |
+
("ARCHITECTURE", "MAISI-v2 · Rectified Flow"),
|
| 86 |
+
("MAX VOLUME", "512 × 512 × 768 vox"),
|
| 87 |
+
("SEGMENTATION", "132 classes · paired"),
|
| 88 |
+
("LICENSE", "NVIDIA Open Model"),
|
| 89 |
+
],
|
| 90 |
+
"accent_class": "ct",
|
| 91 |
+
},
|
| 92 |
+
{
|
| 93 |
+
"key": "mr",
|
| 94 |
+
"index": "02",
|
| 95 |
+
"title": "NV-Generate · MR",
|
| 96 |
+
"subtitle": "Multi-contrast, multi-anatomy synthetic MRI.",
|
| 97 |
+
"icon": SVG_MR,
|
| 98 |
+
"icon_caption": "Multi-contrast · multi-region",
|
| 99 |
+
"uses": ["Modality augmentation", "Cross-region training", "Fine-tune base"],
|
| 100 |
+
"license": "NVIDIA Non-Commercial",
|
| 101 |
+
"license_tone": "warn",
|
| 102 |
+
"spec": [
|
| 103 |
+
("MODALITY", "Magnetic Resonance"),
|
| 104 |
+
("ARCHITECTURE", "MAISI-v2 · Rectified Flow"),
|
| 105 |
+
("MAX VOLUME", "512 × 512 × 128 vox"),
|
| 106 |
+
("CONTRASTS", "T1 · T2 · FLAIR · multi-region"),
|
| 107 |
+
("LICENSE", "NVIDIA Non-Commercial"),
|
| 108 |
+
],
|
| 109 |
+
"accent_class": "mr",
|
| 110 |
+
},
|
| 111 |
+
{
|
| 112 |
+
"key": "mr_brain",
|
| 113 |
+
"index": "03",
|
| 114 |
+
"title": "NV-Generate · MR Brain",
|
| 115 |
+
"subtitle": "High-resolution multi-contrast brain MRI.",
|
| 116 |
+
"icon": SVG_MRB,
|
| 117 |
+
"icon_caption": "Brain · multi-sequence",
|
| 118 |
+
"uses": ["Brain segmentation data", "Lesion augmentation", "Sequence translation"],
|
| 119 |
+
"license": "NVIDIA Open Model",
|
| 120 |
+
"license_tone": "ok",
|
| 121 |
+
"spec": [
|
| 122 |
+
("MODALITY", "MR · Brain"),
|
| 123 |
+
("ARCHITECTURE", "MAISI-v2 · Rectified Flow"),
|
| 124 |
+
("MAX VOLUME", "512 × 512 × 256 vox"),
|
| 125 |
+
("SEQUENCES", "T1 · T2 · FLAIR · SWI"),
|
| 126 |
+
("LICENSE", "NVIDIA Open Model"),
|
| 127 |
+
],
|
| 128 |
+
"accent_class": "mrb",
|
| 129 |
+
},
|
| 130 |
+
]
|
| 131 |
+
|
| 132 |
+
|
| 133 |
+
def _spec_rows(spec: list[tuple[str, str]]) -> str:
|
| 134 |
+
rows = []
|
| 135 |
+
for k, v in spec:
|
| 136 |
+
rows.append(
|
| 137 |
+
f'<div class="ds-row"><span class="ds-key">{k}</span>'
|
| 138 |
+
f'<span class="ds-leader"></span>'
|
| 139 |
+
f'<span class="ds-val">{v}</span></div>'
|
| 140 |
+
)
|
| 141 |
+
return "".join(rows)
|
| 142 |
+
|
| 143 |
+
|
| 144 |
+
def render_hero() -> tuple[gr.Group, dict[str, gr.Button]]:
|
| 145 |
+
"""Build the hero. Returns the wrapping Group and a dict of {key: button}."""
|
| 146 |
+
buttons: dict[str, gr.Button] = {}
|
| 147 |
+
with gr.Group(elem_classes=["hero"]) as group:
|
| 148 |
+
# Masthead: brand on the left, real links on the right. No decorative pills.
|
| 149 |
+
gr.HTML(
|
| 150 |
+
"""
|
| 151 |
+
<div class="masthead">
|
| 152 |
+
<div class="masthead-brand">
|
| 153 |
+
<span class="nv-mark">NV</span>
|
| 154 |
+
<span class="masthead-name">NV-Generate</span>
|
| 155 |
+
</div>
|
| 156 |
+
<nav class="masthead-nav">
|
| 157 |
+
<a href="https://github.com/NVIDIA-Medtech/NV-Generate-CTMR" target="_blank" rel="noopener">GitHub</a>
|
| 158 |
+
<span class="masthead-sep"></span>
|
| 159 |
+
<a href="https://huggingface.co/nvidia/NV-Generate-CT" target="_blank" rel="noopener">Hugging Face</a>
|
| 160 |
+
<span class="masthead-sep"></span>
|
| 161 |
+
<a href="https://arxiv.org/abs/2508.05772" target="_blank" rel="noopener">MAISI-v2 paper</a>
|
| 162 |
+
</nav>
|
| 163 |
+
</div>
|
| 164 |
+
"""
|
| 165 |
+
)
|
| 166 |
+
|
| 167 |
+
# Hero headline — eyebrow + bold title, no marketing paragraph below.
|
| 168 |
+
gr.HTML(
|
| 169 |
+
"""
|
| 170 |
+
<div class="hero-mono">
|
| 171 |
+
<div class="hero-eyebrow">
|
| 172 |
+
<span class="line-tick"></span>
|
| 173 |
+
<span>Latent diffusion · MAISI-v2 · open weights</span>
|
| 174 |
+
</div>
|
| 175 |
+
<h1 class="hero-title">
|
| 176 |
+
Synthetic 3D medical imaging.
|
| 177 |
+
</h1>
|
| 178 |
+
</div>
|
| 179 |
+
"""
|
| 180 |
+
)
|
| 181 |
+
|
| 182 |
+
# Datasheet cards — three equal-height subsystems
|
| 183 |
+
with gr.Row(elem_classes=["hero-row"], equal_height=True):
|
| 184 |
+
for card in CARDS:
|
| 185 |
+
with gr.Column(scale=1, min_width=300, elem_classes=["hero-card-col"]):
|
| 186 |
+
uses_html = "".join(
|
| 187 |
+
f'<span class="ds-use">{u}</span>' for u in card.get("uses", [])
|
| 188 |
+
)
|
| 189 |
+
license_tone_cls = "ds-license-warn" if card.get("license_tone") == "warn" else "ds-license-ok"
|
| 190 |
+
gr.HTML(
|
| 191 |
+
f"""
|
| 192 |
+
<div class="ds-card ds-{card['accent_class']}">
|
| 193 |
+
<div class="ds-corner ds-tl"></div>
|
| 194 |
+
<div class="ds-corner ds-tr"></div>
|
| 195 |
+
<div class="ds-corner ds-bl"></div>
|
| 196 |
+
<div class="ds-corner ds-br"></div>
|
| 197 |
+
|
| 198 |
+
<div class="ds-banner">
|
| 199 |
+
<div class="ds-banner-grid"></div>
|
| 200 |
+
<div class="ds-banner-icon">{card['icon']}</div>
|
| 201 |
+
<div class="ds-banner-caption">{card['icon_caption']}</div>
|
| 202 |
+
</div>
|
| 203 |
+
|
| 204 |
+
<div class="ds-frame">
|
| 205 |
+
<div class="ds-head">
|
| 206 |
+
<div class="ds-index">{card['index']}</div>
|
| 207 |
+
<div class="ds-status">
|
| 208 |
+
<span class="dot dot-pulse"></span>Available
|
| 209 |
+
</div>
|
| 210 |
+
</div>
|
| 211 |
+
|
| 212 |
+
<div class="ds-name">
|
| 213 |
+
<div class="ds-name-title">{card['title']}</div>
|
| 214 |
+
<div class="ds-name-sub">{card['subtitle']}</div>
|
| 215 |
+
</div>
|
| 216 |
+
|
| 217 |
+
<div class="ds-uses-label">Use cases</div>
|
| 218 |
+
<div class="ds-uses">{uses_html}</div>
|
| 219 |
+
|
| 220 |
+
<div class="ds-divider"></div>
|
| 221 |
+
|
| 222 |
+
<div class="ds-spec">
|
| 223 |
+
{_spec_rows(card['spec'])}
|
| 224 |
+
</div>
|
| 225 |
+
|
| 226 |
+
<div class="ds-license {license_tone_cls}">
|
| 227 |
+
<span class="ds-license-k">License</span>
|
| 228 |
+
<span class="ds-license-v">{card['license']}</span>
|
| 229 |
+
</div>
|
| 230 |
+
</div>
|
| 231 |
+
</div>
|
| 232 |
+
"""
|
| 233 |
+
)
|
| 234 |
+
btn = gr.Button(
|
| 235 |
+
f"Launch {card['title'].replace(' · ', ' ')} →",
|
| 236 |
+
elem_classes=["ds-cta", f"ds-cta-{card['accent_class']}"],
|
| 237 |
+
)
|
| 238 |
+
buttons[card["key"]] = btn
|
| 239 |
+
|
| 240 |
+
return group, buttons
|
ui/presets.py
ADDED
|
@@ -0,0 +1,69 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""UI preset definitions: anatomy choices, sample-input chips, body regions."""
|
| 2 |
+
from __future__ import annotations
|
| 3 |
+
|
| 4 |
+
# Body regions accepted by the upstream CT pipeline (input to LDMSampler).
|
| 5 |
+
CT_BODY_REGIONS = ["head", "chest", "thorax", "abdomen", "pelvis", "lower"]
|
| 6 |
+
|
| 7 |
+
# Controllable anatomies for paired CT generation. Subset of label_dict.json that
|
| 8 |
+
# the upstream pipeline knows how to condition on (per docs/inference.md).
|
| 9 |
+
CT_ANATOMY_CHOICES = [
|
| 10 |
+
"liver",
|
| 11 |
+
"spleen",
|
| 12 |
+
"pancreas",
|
| 13 |
+
"right kidney",
|
| 14 |
+
"left kidney",
|
| 15 |
+
"gallbladder",
|
| 16 |
+
"stomach",
|
| 17 |
+
"duodenum",
|
| 18 |
+
"bladder",
|
| 19 |
+
"colon",
|
| 20 |
+
"small bowel",
|
| 21 |
+
"left lung upper lobe",
|
| 22 |
+
"left lung lower lobe",
|
| 23 |
+
"right lung upper lobe",
|
| 24 |
+
"right lung middle lobe",
|
| 25 |
+
"right lung lower lobe",
|
| 26 |
+
"lung tumor",
|
| 27 |
+
"hepatic tumor",
|
| 28 |
+
"pancreatic tumor",
|
| 29 |
+
"bone lesion",
|
| 30 |
+
]
|
| 31 |
+
|
| 32 |
+
# MR contrast options exposed in the dropdown (maps to modality int)
|
| 33 |
+
MR_CONTRAST_CHOICES = [
|
| 34 |
+
("T1 brain", 9),
|
| 35 |
+
("T2 brain", 10),
|
| 36 |
+
("FLAIR (skull-stripped brain)", 11),
|
| 37 |
+
("T2 prostate", 10),
|
| 38 |
+
("T1 breast", 9),
|
| 39 |
+
("T1 abdomen", 9),
|
| 40 |
+
("T2 abdomen", 10),
|
| 41 |
+
("Generic MRI", 8),
|
| 42 |
+
]
|
| 43 |
+
|
| 44 |
+
MR_BRAIN_CONTRASTS = ["T1", "T2", "FLAIR", "SWI", "T1_skull_stripped", "T2_skull_stripped", "FLAIR_skull_stripped", "SWI_skull_stripped"]
|
| 45 |
+
|
| 46 |
+
# Paired CT requires X==Y from {256, 384, 512} and Z from {128, 256, 384, 512, 640, 768}.
|
| 47 |
+
# We expose 256 and 384 by default (skipping 512 to stay within ~70 GB VRAM).
|
| 48 |
+
XY_CHOICES = [256, 384]
|
| 49 |
+
Z_CHOICES = [128, 256, 384]
|
| 50 |
+
|
| 51 |
+
|
| 52 |
+
CT_SAMPLES = [
|
| 53 |
+
{"label": "Abdomen + liver", "body_region": ["abdomen"], "anatomy_list": ["liver"], "xy": 256, "z": 256, "spacing": [1.5, 1.5, 1.5]},
|
| 54 |
+
{"label": "Chest + lung", "body_region": ["chest"], "anatomy_list": ["right lung upper lobe", "right lung lower lobe"], "xy": 256, "z": 128, "spacing": [1.5, 1.5, 2.5]},
|
| 55 |
+
{"label": "Pelvis", "body_region": ["pelvis"], "anatomy_list": ["bladder"], "xy": 256, "z": 256, "spacing": [1.5, 1.5, 1.5]},
|
| 56 |
+
]
|
| 57 |
+
|
| 58 |
+
MR_SAMPLES = [
|
| 59 |
+
{"label": "T2 prostate", "modality_label": "T2 prostate", "xy": 256, "z": 128, "spacing": [1.0, 1.0, 1.5]},
|
| 60 |
+
{"label": "T1 abdomen", "modality_label": "T1 abdomen", "xy": 256, "z": 128, "spacing": [1.25, 1.0, 1.0]},
|
| 61 |
+
{"label": "T2 brain", "modality_label": "T2 brain", "xy": 256, "z": 128, "spacing": [1.0, 1.0, 1.0]},
|
| 62 |
+
]
|
| 63 |
+
|
| 64 |
+
MR_BRAIN_SAMPLES = [
|
| 65 |
+
{"label": "T1 whole brain", "contrast": "T1", "xy": 256, "z": 256, "spacing": [1.0, 1.0, 1.0]},
|
| 66 |
+
{"label": "T2 whole brain", "contrast": "T2", "xy": 256, "z": 256, "spacing": [1.0, 1.0, 1.0]},
|
| 67 |
+
{"label": "FLAIR", "contrast": "FLAIR", "xy": 256, "z": 256, "spacing": [1.0, 1.0, 1.0]},
|
| 68 |
+
{"label": "SWI", "contrast": "SWI", "xy": 256, "z": 256, "spacing": [1.0, 1.0, 1.0]},
|
| 69 |
+
]
|
ui/workspace_ct.py
ADDED
|
@@ -0,0 +1,227 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""CT workspace — paired image+mask generation with anatomy controls."""
|
| 2 |
+
from __future__ import annotations
|
| 3 |
+
|
| 4 |
+
from typing import Any
|
| 5 |
+
|
| 6 |
+
import gradio as gr
|
| 7 |
+
|
| 8 |
+
from pipelines import GenerationRequest
|
| 9 |
+
from pipelines.ct import generate as generate_ct
|
| 10 |
+
from utils.windowing import CT_PRESETS
|
| 11 |
+
from viewer.niivue_embed import empty_html, render_viewer
|
| 12 |
+
from viewer.colormaps import legend_html
|
| 13 |
+
from .presets import CT_ANATOMY_CHOICES, CT_BODY_REGIONS, CT_SAMPLES, XY_CHOICES, Z_CHOICES
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
def _spacing_default() -> tuple[float, float, float]:
|
| 17 |
+
return (1.5, 1.5, 1.5)
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
def _on_preset(preset_name: str) -> tuple[float, float] | None:
|
| 21 |
+
preset = CT_PRESETS.get(preset_name)
|
| 22 |
+
if preset is None:
|
| 23 |
+
return None
|
| 24 |
+
lo, hi = preset.to_min_max()
|
| 25 |
+
return lo, hi
|
| 26 |
+
|
| 27 |
+
|
| 28 |
+
def build(spaces_gpu: Any) -> tuple[gr.Group, gr.Button]:
|
| 29 |
+
"""Returns the hidden workspace Group and the back-to-home button."""
|
| 30 |
+
with gr.Group(visible=False, elem_classes=["workspace"]) as group:
|
| 31 |
+
with gr.Row(elem_classes=["workspace-header"]):
|
| 32 |
+
back_btn = gr.Button("← Back", elem_classes=["back-btn"], scale=0)
|
| 33 |
+
gr.HTML(
|
| 34 |
+
'<div class="workspace-title">'
|
| 35 |
+
'<span class="ws-dot" style="background:#76b900;color:#76b900"></span>'
|
| 36 |
+
'<span class="ws-crumb">NV-Generate</span>'
|
| 37 |
+
'<span class="ws-crumb-sep">/</span>'
|
| 38 |
+
'<span class="ws-active">CT</span>'
|
| 39 |
+
'</div>'
|
| 40 |
+
)
|
| 41 |
+
gr.HTML(
|
| 42 |
+
"""
|
| 43 |
+
<div class="ws-intro ws-intro-ct">
|
| 44 |
+
<div class="ws-intro-left">
|
| 45 |
+
<h2 class="ws-intro-title">NV-Generate · CT</h2>
|
| 46 |
+
<p class="ws-intro-desc">
|
| 47 |
+
Whole-body synthetic CT volumes with paired 132-class anatomy masks.
|
| 48 |
+
Generate balanced training data for segmentation models, augment rare
|
| 49 |
+
pathologies with controllable organ and tumor size, or share
|
| 50 |
+
privacy-preserving samples for research.
|
| 51 |
+
</p>
|
| 52 |
+
</div>
|
| 53 |
+
<div class="ws-intro-facts">
|
| 54 |
+
<div class="ws-fact"><span class="ws-fact-k">Architecture</span><span class="ws-fact-v">MAISI-v2 · Rectified Flow</span></div>
|
| 55 |
+
<div class="ws-fact"><span class="ws-fact-k">Body regions</span><span class="ws-fact-v">head · chest · thorax · abdomen · pelvis · lower</span></div>
|
| 56 |
+
<div class="ws-fact"><span class="ws-fact-k">Segmentation</span><span class="ws-fact-v">132 classes · paired</span></div>
|
| 57 |
+
<div class="ws-fact"><span class="ws-fact-k">Inference</span><span class="ws-fact-v">30 rectified-flow steps</span></div>
|
| 58 |
+
<div class="ws-fact"><span class="ws-fact-k">Max volume</span><span class="ws-fact-v">512 × 512 × 768 vox</span></div>
|
| 59 |
+
</div>
|
| 60 |
+
</div>
|
| 61 |
+
"""
|
| 62 |
+
)
|
| 63 |
+
with gr.Row(elem_classes=["workspace-row"]):
|
| 64 |
+
with gr.Column(scale=4, min_width=320, elem_classes=["controls"]):
|
| 65 |
+
gr.Markdown("##### Conditioning")
|
| 66 |
+
generate_masks = gr.Checkbox(
|
| 67 |
+
label="Paired anatomy mask · 132 classes",
|
| 68 |
+
value=True,
|
| 69 |
+
info="Off → image-only generation (faster).",
|
| 70 |
+
)
|
| 71 |
+
body_region = gr.CheckboxGroup(
|
| 72 |
+
choices=CT_BODY_REGIONS,
|
| 73 |
+
value=["abdomen"],
|
| 74 |
+
label="Body region",
|
| 75 |
+
)
|
| 76 |
+
anatomy_list = gr.Dropdown(
|
| 77 |
+
choices=CT_ANATOMY_CHOICES,
|
| 78 |
+
value=["liver"],
|
| 79 |
+
multiselect=True,
|
| 80 |
+
label="Target anatomies",
|
| 81 |
+
)
|
| 82 |
+
|
| 83 |
+
gr.Markdown("##### Geometry")
|
| 84 |
+
dim_xy = gr.Radio(choices=XY_CHOICES, value=256, label="X / Y (voxels)")
|
| 85 |
+
dim_z = gr.Radio(choices=Z_CHOICES, value=256, label="Z (voxels)")
|
| 86 |
+
with gr.Row(equal_height=True):
|
| 87 |
+
sp_x = gr.Slider(1.0, 5.0, value=1.5, step=0.05, label="Spacing X (mm)")
|
| 88 |
+
sp_y = gr.Slider(1.0, 5.0, value=1.5, step=0.05, label="Spacing Y (mm)")
|
| 89 |
+
sp_z = gr.Slider(0.5, 5.0, value=1.5, step=0.05, label="Spacing Z (mm)")
|
| 90 |
+
gr.HTML('<div class="hint">Field of view needs at least 256 mm: increase X voxels or X spacing if shorter.</div>')
|
| 91 |
+
|
| 92 |
+
gr.Markdown("##### Diffusion")
|
| 93 |
+
with gr.Row(equal_height=True):
|
| 94 |
+
seed = gr.Number(value=0, label="Seed", precision=0)
|
| 95 |
+
steps = gr.Slider(10, 60, value=30, step=1, label="Inference steps")
|
| 96 |
+
|
| 97 |
+
gr.Markdown("##### Quick presets")
|
| 98 |
+
with gr.Row():
|
| 99 |
+
sample_btns = [gr.Button(s["label"], size="sm") for s in CT_SAMPLES]
|
| 100 |
+
|
| 101 |
+
generate_btn = gr.Button("Generate volume", variant="primary", elem_classes=["primary-cta"])
|
| 102 |
+
status = gr.HTML('<div class="stat-line"><span class="stat-label" style="color:var(--muted)">Idle. Configure parameters and click Generate.</span></div>', elem_classes=["status"])
|
| 103 |
+
|
| 104 |
+
with gr.Column(scale=8, min_width=520, elem_classes=["viewer-col"]):
|
| 105 |
+
gr.HTML(
|
| 106 |
+
'<div class="viewer-strip">'
|
| 107 |
+
'<span class="viewer-strip-left">Viewport · Multiplanar</span>'
|
| 108 |
+
'<span class="viewer-strip-right">Axial · Coronal · Sagittal · 3D</span>'
|
| 109 |
+
'</div>'
|
| 110 |
+
)
|
| 111 |
+
viewer = gr.HTML(empty_html(), elem_classes=["viewer"])
|
| 112 |
+
with gr.Row(elem_classes=["preset-row"]):
|
| 113 |
+
gr.HTML('<div class="preset-label">Window / level preset</div>')
|
| 114 |
+
preset = gr.Radio(
|
| 115 |
+
choices=[p.name for p in CT_PRESETS.values()],
|
| 116 |
+
value="Soft Tissue",
|
| 117 |
+
show_label=False,
|
| 118 |
+
container=False,
|
| 119 |
+
elem_classes=["preset-radio"],
|
| 120 |
+
)
|
| 121 |
+
legend = gr.HTML("", elem_classes=["legend-host"], visible=False)
|
| 122 |
+
download = gr.File(label="Download generated NIfTI", visible=False, elem_classes=["nv-download"])
|
| 123 |
+
|
| 124 |
+
# State holding the most recent generation, so the W/L preset radio can
|
| 125 |
+
# re-render the viewer without re-running inference.
|
| 126 |
+
last_result = gr.State(None)
|
| 127 |
+
|
| 128 |
+
_PRESET_KEY = {"Soft Tissue": "soft_tissue", "Lung": "lung", "Bone": "bone", "Brain": "brain"}
|
| 129 |
+
|
| 130 |
+
# ---- handlers ----
|
| 131 |
+
def _generate(generate_masks, body_region, anatomy_list, dim_xy, dim_z, sp_x, sp_y, sp_z, seed, steps, preset):
|
| 132 |
+
req = GenerationRequest(
|
| 133 |
+
model="ct",
|
| 134 |
+
output_size=(int(dim_xy), int(dim_xy), int(dim_z)),
|
| 135 |
+
spacing=(float(sp_x), float(sp_y), float(sp_z)),
|
| 136 |
+
seed=int(seed),
|
| 137 |
+
num_steps=int(steps),
|
| 138 |
+
body_region=list(body_region) if generate_masks else None,
|
| 139 |
+
anatomy_list=list(anatomy_list) if anatomy_list else ["liver"],
|
| 140 |
+
generate_masks=bool(generate_masks),
|
| 141 |
+
)
|
| 142 |
+
try:
|
| 143 |
+
result = generate_ct(req)
|
| 144 |
+
except Exception as e:
|
| 145 |
+
return (
|
| 146 |
+
empty_html(f"Generation failed: {e}"),
|
| 147 |
+
gr.update(visible=False, value=""),
|
| 148 |
+
gr.update(visible=False, value=None),
|
| 149 |
+
f'<div class="stat-line"><span class="stat-err">✕ Generation failed</span> <span class="stat-chip"><span class="stat-k">ERR</span><span class="stat-v">{e}</span></span></div>',
|
| 150 |
+
None,
|
| 151 |
+
)
|
| 152 |
+
|
| 153 |
+
wm = CT_PRESETS.get(_PRESET_KEY.get(preset, "soft_tissue"))
|
| 154 |
+
window_min, window_max = wm.to_min_max() if wm else (None, None)
|
| 155 |
+
|
| 156 |
+
html = render_viewer(
|
| 157 |
+
volume_path=result.volume_path,
|
| 158 |
+
mask_path=result.mask_path,
|
| 159 |
+
colormap="gray", # CT base is grayscale; W/L preset drives windowing via cal_min/max
|
| 160 |
+
used_label_ids=list(result.used_anatomy_labels.keys()),
|
| 161 |
+
window_min=window_min,
|
| 162 |
+
window_max=window_max,
|
| 163 |
+
)
|
| 164 |
+
legend_str = legend_html(result.used_anatomy_labels) if result.mask_path else ""
|
| 165 |
+
files = [result.volume_path] + ([result.mask_path] if result.mask_path else [])
|
| 166 |
+
stat = (
|
| 167 |
+
'<div class="stat-line">'
|
| 168 |
+
'<span class="stat-mark"></span>'
|
| 169 |
+
'<span class="stat-label">Generated</span>'
|
| 170 |
+
f'<span class="stat-chip"><span class="stat-k">runtime</span><span class="stat-v">{result.runtime_seconds:.1f}s</span></span>'
|
| 171 |
+
f'<span class="stat-chip"><span class="stat-k">seed</span><span class="stat-v">{result.seed}</span></span>'
|
| 172 |
+
f'<span class="stat-chip"><span class="stat-k">steps</span><span class="stat-v">{req.num_steps}</span></span>'
|
| 173 |
+
f'<span class="stat-chip"><span class="stat-k">size</span><span class="stat-v">{req.output_size[0]}³</span></span>'
|
| 174 |
+
'</div>'
|
| 175 |
+
)
|
| 176 |
+
return (
|
| 177 |
+
html,
|
| 178 |
+
gr.update(visible=bool(legend_str), value=legend_str),
|
| 179 |
+
gr.update(visible=True, value=files),
|
| 180 |
+
stat,
|
| 181 |
+
result,
|
| 182 |
+
)
|
| 183 |
+
|
| 184 |
+
def _reapply_preset(preset, result):
|
| 185 |
+
if not result or not getattr(result, "volume_path", None):
|
| 186 |
+
return gr.update()
|
| 187 |
+
wm = CT_PRESETS.get(_PRESET_KEY.get(preset, "soft_tissue"))
|
| 188 |
+
window_min, window_max = wm.to_min_max() if wm else (None, None)
|
| 189 |
+
return render_viewer(
|
| 190 |
+
volume_path=result.volume_path,
|
| 191 |
+
mask_path=result.mask_path,
|
| 192 |
+
colormap="gray",
|
| 193 |
+
used_label_ids=list(result.used_anatomy_labels.keys()) if result.used_anatomy_labels else [],
|
| 194 |
+
window_min=window_min,
|
| 195 |
+
window_max=window_max,
|
| 196 |
+
)
|
| 197 |
+
|
| 198 |
+
decorated = spaces_gpu(_generate) if spaces_gpu else _generate
|
| 199 |
+
(
|
| 200 |
+
generate_btn.click(
|
| 201 |
+
lambda: gr.update(value="Generating volume…", interactive=False),
|
| 202 |
+
outputs=[generate_btn],
|
| 203 |
+
)
|
| 204 |
+
.then(
|
| 205 |
+
decorated,
|
| 206 |
+
inputs=[generate_masks, body_region, anatomy_list, dim_xy, dim_z, sp_x, sp_y, sp_z, seed, steps, preset],
|
| 207 |
+
outputs=[viewer, legend, download, status, last_result],
|
| 208 |
+
show_progress="full",
|
| 209 |
+
)
|
| 210 |
+
.then(
|
| 211 |
+
lambda: gr.update(value="Generate volume", interactive=True),
|
| 212 |
+
outputs=[generate_btn],
|
| 213 |
+
)
|
| 214 |
+
)
|
| 215 |
+
preset.change(_reapply_preset, inputs=[preset, last_result], outputs=[viewer])
|
| 216 |
+
|
| 217 |
+
for btn, sample in zip(sample_btns, CT_SAMPLES):
|
| 218 |
+
def _apply(s=sample):
|
| 219 |
+
return (
|
| 220 |
+
s["body_region"],
|
| 221 |
+
s["anatomy_list"],
|
| 222 |
+
s["xy"], s["z"],
|
| 223 |
+
s["spacing"][0], s["spacing"][1], s["spacing"][2],
|
| 224 |
+
)
|
| 225 |
+
btn.click(_apply, outputs=[body_region, anatomy_list, dim_xy, dim_z, sp_x, sp_y, sp_z])
|
| 226 |
+
|
| 227 |
+
return group, back_btn
|
ui/workspace_mr.py
ADDED
|
@@ -0,0 +1,163 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""MR workspace — image-only multi-contrast MR generation."""
|
| 2 |
+
from __future__ import annotations
|
| 3 |
+
|
| 4 |
+
from typing import Any
|
| 5 |
+
|
| 6 |
+
import gradio as gr
|
| 7 |
+
|
| 8 |
+
from pipelines import GenerationRequest
|
| 9 |
+
from pipelines.mr import generate as generate_mr
|
| 10 |
+
from viewer.niivue_embed import empty_html, render_viewer
|
| 11 |
+
from .presets import XY_CHOICES, Z_CHOICES, MR_CONTRAST_CHOICES, MR_SAMPLES
|
| 12 |
+
|
| 13 |
+
|
| 14 |
+
CONTRAST_LABELS = [c[0] for c in MR_CONTRAST_CHOICES]
|
| 15 |
+
LABEL_TO_MODALITY = {c[0]: c[1] for c in MR_CONTRAST_CHOICES}
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
def build(spaces_gpu: Any) -> tuple[gr.Group, gr.Button]:
|
| 19 |
+
with gr.Group(visible=False, elem_classes=["workspace"]) as group:
|
| 20 |
+
with gr.Row(elem_classes=["workspace-header"]):
|
| 21 |
+
back_btn = gr.Button("← Back", elem_classes=["back-btn"], scale=0)
|
| 22 |
+
gr.HTML(
|
| 23 |
+
'<div class="workspace-title">'
|
| 24 |
+
'<span class="ws-dot" style="background:#5fb4ff;color:#5fb4ff"></span>'
|
| 25 |
+
'<span class="ws-crumb">NV-Generate</span>'
|
| 26 |
+
'<span class="ws-crumb-sep">/</span>'
|
| 27 |
+
'<span class="ws-active">MR</span>'
|
| 28 |
+
'</div>'
|
| 29 |
+
)
|
| 30 |
+
gr.HTML(
|
| 31 |
+
"""
|
| 32 |
+
<div class="ws-intro ws-intro-mr">
|
| 33 |
+
<div class="ws-intro-left">
|
| 34 |
+
<h2 class="ws-intro-title">NV-Generate · MR</h2>
|
| 35 |
+
<p class="ws-intro-desc">
|
| 36 |
+
Multi-contrast MRI across brain, prostate, breast, and abdominal anatomy.
|
| 37 |
+
Drive contrast through a modality embedding — T1, T2, FLAIR — at
|
| 38 |
+
variable resolution and voxel spacing. Fine-tune on your own MRI data
|
| 39 |
+
to extend to new modalities and regions.
|
| 40 |
+
</p>
|
| 41 |
+
</div>
|
| 42 |
+
<div class="ws-intro-facts">
|
| 43 |
+
<div class="ws-fact"><span class="ws-fact-k">Architecture</span><span class="ws-fact-v">MAISI-v2 · Rectified Flow</span></div>
|
| 44 |
+
<div class="ws-fact"><span class="ws-fact-k">Contrasts</span><span class="ws-fact-v">T1 · T2 · FLAIR</span></div>
|
| 45 |
+
<div class="ws-fact"><span class="ws-fact-k">Regions</span><span class="ws-fact-v">brain · prostate · breast · abdomen</span></div>
|
| 46 |
+
<div class="ws-fact"><span class="ws-fact-k">Inference</span><span class="ws-fact-v">30 steps</span></div>
|
| 47 |
+
<div class="ws-fact"><span class="ws-fact-k">Max volume</span><span class="ws-fact-v">512 × 512 × 128 vox</span></div>
|
| 48 |
+
<div class="ws-fact"><span class="ws-fact-k">License</span><span class="ws-fact-v ws-fact-warn">NVIDIA Non-Commercial</span></div>
|
| 49 |
+
</div>
|
| 50 |
+
</div>
|
| 51 |
+
"""
|
| 52 |
+
)
|
| 53 |
+
|
| 54 |
+
gr.HTML(
|
| 55 |
+
'<div class="license-banner">'
|
| 56 |
+
'<strong>Non-commercial license.</strong> '
|
| 57 |
+
'NV-Generate-MR weights are released under the <a href="https://developer.download.nvidia.com/licenses/NVIDIA-OneWay-Noncommercial-License-22Mar2022.pdf" target="_blank">NVIDIA OneWay Non-Commercial License</a>. '
|
| 58 |
+
'Use is permitted for academic research only.'
|
| 59 |
+
'</div>'
|
| 60 |
+
)
|
| 61 |
+
|
| 62 |
+
with gr.Row(elem_classes=["workspace-row"]):
|
| 63 |
+
with gr.Column(scale=4, min_width=320, elem_classes=["controls"]):
|
| 64 |
+
gr.Markdown("##### Conditioning")
|
| 65 |
+
contrast = gr.Dropdown(
|
| 66 |
+
choices=CONTRAST_LABELS,
|
| 67 |
+
value="T2 prostate",
|
| 68 |
+
label="Contrast & anatomy",
|
| 69 |
+
info="Drives the modality embedding.",
|
| 70 |
+
)
|
| 71 |
+
|
| 72 |
+
gr.Markdown("##### Geometry")
|
| 73 |
+
dim_xy = gr.Radio(choices=XY_CHOICES, value=256, label="X / Y (voxels)")
|
| 74 |
+
dim_z = gr.Radio(choices=Z_CHOICES, value=128, label="Z (voxels)")
|
| 75 |
+
with gr.Row(equal_height=True):
|
| 76 |
+
sp_x = gr.Slider(0.5, 5.0, value=1.0, step=0.05, label="Spacing X (mm)")
|
| 77 |
+
sp_y = gr.Slider(0.5, 5.0, value=1.0, step=0.05, label="Spacing Y (mm)")
|
| 78 |
+
sp_z = gr.Slider(0.5, 5.0, value=1.5, step=0.05, label="Spacing Z (mm)")
|
| 79 |
+
|
| 80 |
+
gr.Markdown("##### Diffusion")
|
| 81 |
+
with gr.Row(equal_height=True):
|
| 82 |
+
seed = gr.Number(value=0, label="Seed", precision=0)
|
| 83 |
+
steps = gr.Slider(10, 60, value=30, step=1, label="Inference steps")
|
| 84 |
+
cfg = gr.Slider(0.0, 20.0, value=15.0, step=0.5, label="CFG guidance")
|
| 85 |
+
|
| 86 |
+
gr.Markdown("##### Quick presets")
|
| 87 |
+
with gr.Row():
|
| 88 |
+
sample_btns = [gr.Button(s["label"], size="sm") for s in MR_SAMPLES]
|
| 89 |
+
|
| 90 |
+
generate_btn = gr.Button("Generate volume", variant="primary", elem_classes=["primary-cta"])
|
| 91 |
+
status = gr.HTML('<div class="stat-line"><span class="stat-label" style="color:var(--muted)">Idle. Configure parameters and click Generate.</span></div>', elem_classes=["status"])
|
| 92 |
+
|
| 93 |
+
with gr.Column(scale=8, min_width=520, elem_classes=["viewer-col"]):
|
| 94 |
+
gr.HTML(
|
| 95 |
+
'<div class="viewer-strip">'
|
| 96 |
+
'<span class="viewer-strip-left">Viewport · Multiplanar</span>'
|
| 97 |
+
'<span class="viewer-strip-right">Axial · Coronal · Sagittal · 3D</span>'
|
| 98 |
+
'</div>'
|
| 99 |
+
)
|
| 100 |
+
viewer = gr.HTML(empty_html(), elem_classes=["viewer"])
|
| 101 |
+
download = gr.File(label="Download generated NIfTI", visible=False, elem_classes=["nv-download"])
|
| 102 |
+
# MR has no mask, but keep a legend slot so all workspaces share structure
|
| 103 |
+
legend = gr.HTML("", elem_classes=["legend-host"], visible=False)
|
| 104 |
+
|
| 105 |
+
def _generate(contrast, dim_xy, dim_z, sp_x, sp_y, sp_z, seed, steps, cfg):
|
| 106 |
+
req = GenerationRequest(
|
| 107 |
+
model="mr",
|
| 108 |
+
output_size=(int(dim_xy), int(dim_xy), int(dim_z)),
|
| 109 |
+
spacing=(float(sp_x), float(sp_y), float(sp_z)),
|
| 110 |
+
seed=int(seed),
|
| 111 |
+
num_steps=int(steps),
|
| 112 |
+
cfg_guidance_scale=float(cfg),
|
| 113 |
+
modality_class=LABEL_TO_MODALITY.get(contrast, 9),
|
| 114 |
+
)
|
| 115 |
+
try:
|
| 116 |
+
result = generate_mr(req)
|
| 117 |
+
except Exception as e:
|
| 118 |
+
return (
|
| 119 |
+
empty_html(f"Generation failed: {e}"),
|
| 120 |
+
gr.update(visible=False, value=None),
|
| 121 |
+
f'<div class="stat-line"><span class="stat-err">✕ Generation failed</span> <span class="stat-chip"><span class="stat-k">ERR</span><span class="stat-v">{e}</span></span></div>',
|
| 122 |
+
)
|
| 123 |
+
html = render_viewer(volume_path=result.volume_path, colormap="gray")
|
| 124 |
+
stat = (
|
| 125 |
+
'<div class="stat-line">'
|
| 126 |
+
'<span class="stat-mark"></span>'
|
| 127 |
+
'<span class="stat-label">Generated</span>'
|
| 128 |
+
f'<span class="stat-chip"><span class="stat-k">runtime</span><span class="stat-v">{result.runtime_seconds:.1f}s</span></span>'
|
| 129 |
+
f'<span class="stat-chip"><span class="stat-k">seed</span><span class="stat-v">{result.seed}</span></span>'
|
| 130 |
+
f'<span class="stat-chip"><span class="stat-k">steps</span><span class="stat-v">{req.num_steps}</span></span>'
|
| 131 |
+
f'<span class="stat-chip"><span class="stat-k">size</span><span class="stat-v">{req.output_size[0]}³</span></span>'
|
| 132 |
+
'</div>'
|
| 133 |
+
)
|
| 134 |
+
return html, gr.update(visible=True, value=result.volume_path), stat
|
| 135 |
+
|
| 136 |
+
decorated = spaces_gpu(_generate) if spaces_gpu else _generate
|
| 137 |
+
(
|
| 138 |
+
generate_btn.click(
|
| 139 |
+
lambda: gr.update(value="Generating volume…", interactive=False),
|
| 140 |
+
outputs=[generate_btn],
|
| 141 |
+
)
|
| 142 |
+
.then(
|
| 143 |
+
decorated,
|
| 144 |
+
inputs=[contrast, dim_xy, dim_z, sp_x, sp_y, sp_z, seed, steps, cfg],
|
| 145 |
+
outputs=[viewer, download, status],
|
| 146 |
+
show_progress="full",
|
| 147 |
+
)
|
| 148 |
+
.then(
|
| 149 |
+
lambda: gr.update(value="Generate volume", interactive=True),
|
| 150 |
+
outputs=[generate_btn],
|
| 151 |
+
)
|
| 152 |
+
)
|
| 153 |
+
|
| 154 |
+
for btn, sample in zip(sample_btns, MR_SAMPLES):
|
| 155 |
+
def _apply(s=sample):
|
| 156 |
+
return (
|
| 157 |
+
s["modality_label"],
|
| 158 |
+
s["xy"], s["z"],
|
| 159 |
+
s["spacing"][0], s["spacing"][1], s["spacing"][2],
|
| 160 |
+
)
|
| 161 |
+
btn.click(_apply, outputs=[contrast, dim_xy, dim_z, sp_x, sp_y, sp_z])
|
| 162 |
+
|
| 163 |
+
return group, back_btn
|
ui/workspace_mr_brain.py
ADDED
|
@@ -0,0 +1,150 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""MR-Brain workspace — image-only T1/T2/FLAIR/SWI brain MRI."""
|
| 2 |
+
from __future__ import annotations
|
| 3 |
+
|
| 4 |
+
from typing import Any
|
| 5 |
+
|
| 6 |
+
import gradio as gr
|
| 7 |
+
|
| 8 |
+
from pipelines import GenerationRequest
|
| 9 |
+
from pipelines.mr_brain import generate as generate_mr_brain
|
| 10 |
+
from viewer.niivue_embed import empty_html, render_viewer
|
| 11 |
+
from .presets import XY_CHOICES, Z_CHOICES, MR_BRAIN_CONTRASTS, MR_BRAIN_SAMPLES
|
| 12 |
+
|
| 13 |
+
|
| 14 |
+
def build(spaces_gpu: Any) -> tuple[gr.Group, gr.Button]:
|
| 15 |
+
with gr.Group(visible=False, elem_classes=["workspace"]) as group:
|
| 16 |
+
with gr.Row(elem_classes=["workspace-header"]):
|
| 17 |
+
back_btn = gr.Button("← Back", elem_classes=["back-btn"], scale=0)
|
| 18 |
+
gr.HTML(
|
| 19 |
+
'<div class="workspace-title">'
|
| 20 |
+
'<span class="ws-dot" style="background:#b48aff;color:#b48aff"></span>'
|
| 21 |
+
'<span class="ws-crumb">NV-Generate</span>'
|
| 22 |
+
'<span class="ws-crumb-sep">/</span>'
|
| 23 |
+
'<span class="ws-active">MR Brain</span>'
|
| 24 |
+
'</div>'
|
| 25 |
+
)
|
| 26 |
+
gr.HTML(
|
| 27 |
+
"""
|
| 28 |
+
<div class="ws-intro ws-intro-mrb">
|
| 29 |
+
<div class="ws-intro-left">
|
| 30 |
+
<h2 class="ws-intro-title">NV-Generate · MR Brain</h2>
|
| 31 |
+
<p class="ws-intro-desc">
|
| 32 |
+
Multi-sequence brain MRI generation across T1, T2, FLAIR, and SWI —
|
| 33 |
+
in both whole-brain and skull-stripped forms. Trained on the open
|
| 34 |
+
MR-RATE dataset. Useful for downstream tumor and lesion segmentation
|
| 35 |
+
studies that need controlled, synthetic data.
|
| 36 |
+
</p>
|
| 37 |
+
</div>
|
| 38 |
+
<div class="ws-intro-facts">
|
| 39 |
+
<div class="ws-fact"><span class="ws-fact-k">Architecture</span><span class="ws-fact-v">MAISI-v2 · Rectified Flow</span></div>
|
| 40 |
+
<div class="ws-fact"><span class="ws-fact-k">Sequences</span><span class="ws-fact-v">T1 · T2 · FLAIR · SWI</span></div>
|
| 41 |
+
<div class="ws-fact"><span class="ws-fact-k">Variants</span><span class="ws-fact-v">whole-brain · skull-stripped</span></div>
|
| 42 |
+
<div class="ws-fact"><span class="ws-fact-k">Trained on</span><span class="ws-fact-v">MR-RATE dataset (open)</span></div>
|
| 43 |
+
<div class="ws-fact"><span class="ws-fact-k">Inference</span><span class="ws-fact-v">30 steps</span></div>
|
| 44 |
+
<div class="ws-fact"><span class="ws-fact-k">Max volume</span><span class="ws-fact-v">512 × 512 × 256 vox</span></div>
|
| 45 |
+
</div>
|
| 46 |
+
</div>
|
| 47 |
+
"""
|
| 48 |
+
)
|
| 49 |
+
|
| 50 |
+
with gr.Row(elem_classes=["workspace-row"]):
|
| 51 |
+
with gr.Column(scale=4, min_width=320, elem_classes=["controls"]):
|
| 52 |
+
gr.Markdown("##### Contrast")
|
| 53 |
+
contrast = gr.Radio(
|
| 54 |
+
choices=MR_BRAIN_CONTRASTS,
|
| 55 |
+
value="T1",
|
| 56 |
+
label="Sequence",
|
| 57 |
+
info="Skull-stripped variants supported.",
|
| 58 |
+
)
|
| 59 |
+
|
| 60 |
+
gr.Markdown("##### Geometry")
|
| 61 |
+
dim_xy = gr.Radio(choices=XY_CHOICES, value=256, label="X / Y (voxels)")
|
| 62 |
+
dim_z = gr.Radio(choices=Z_CHOICES, value=256, label="Z (voxels)")
|
| 63 |
+
with gr.Row(equal_height=True):
|
| 64 |
+
sp_x = gr.Slider(0.5, 5.0, value=1.0, step=0.05, label="Spacing X (mm)")
|
| 65 |
+
sp_y = gr.Slider(0.5, 5.0, value=1.0, step=0.05, label="Spacing Y (mm)")
|
| 66 |
+
sp_z = gr.Slider(0.5, 5.0, value=1.0, step=0.05, label="Spacing Z (mm)")
|
| 67 |
+
|
| 68 |
+
gr.Markdown("##### Diffusion")
|
| 69 |
+
with gr.Row(equal_height=True):
|
| 70 |
+
seed = gr.Number(value=0, label="Seed", precision=0)
|
| 71 |
+
steps = gr.Slider(10, 60, value=30, step=1, label="Inference steps")
|
| 72 |
+
cfg = gr.Slider(0.0, 20.0, value=10.0, step=0.5, label="CFG guidance")
|
| 73 |
+
|
| 74 |
+
gr.Markdown("##### Quick presets")
|
| 75 |
+
with gr.Row():
|
| 76 |
+
sample_btns = [gr.Button(s["label"], size="sm") for s in MR_BRAIN_SAMPLES]
|
| 77 |
+
|
| 78 |
+
generate_btn = gr.Button("Generate volume", variant="primary", elem_classes=["primary-cta"])
|
| 79 |
+
status = gr.HTML('<div class="stat-line"><span class="stat-label" style="color:var(--muted)">Idle. Configure parameters and click Generate.</span></div>', elem_classes=["status"])
|
| 80 |
+
|
| 81 |
+
with gr.Column(scale=8, min_width=520, elem_classes=["viewer-col"]):
|
| 82 |
+
gr.HTML(
|
| 83 |
+
'<div class="viewer-strip">'
|
| 84 |
+
'<span class="viewer-strip-left">Viewport · Multiplanar</span>'
|
| 85 |
+
'<span class="viewer-strip-right">Axial · Coronal · Sagittal · 3D</span>'
|
| 86 |
+
'</div>'
|
| 87 |
+
)
|
| 88 |
+
viewer = gr.HTML(empty_html(), elem_classes=["viewer"])
|
| 89 |
+
download = gr.File(label="Download generated NIfTI", visible=False, elem_classes=["nv-download"])
|
| 90 |
+
legend = gr.HTML("", elem_classes=["legend-host"], visible=False)
|
| 91 |
+
|
| 92 |
+
def _generate(contrast, dim_xy, dim_z, sp_x, sp_y, sp_z, seed, steps, cfg):
|
| 93 |
+
req = GenerationRequest(
|
| 94 |
+
model="mr_brain",
|
| 95 |
+
output_size=(int(dim_xy), int(dim_xy), int(dim_z)),
|
| 96 |
+
spacing=(float(sp_x), float(sp_y), float(sp_z)),
|
| 97 |
+
seed=int(seed),
|
| 98 |
+
num_steps=int(steps),
|
| 99 |
+
cfg_guidance_scale=float(cfg),
|
| 100 |
+
contrast=contrast,
|
| 101 |
+
)
|
| 102 |
+
try:
|
| 103 |
+
result = generate_mr_brain(req)
|
| 104 |
+
except Exception as e:
|
| 105 |
+
return (
|
| 106 |
+
empty_html(f"Generation failed: {e}"),
|
| 107 |
+
gr.update(visible=False, value=None),
|
| 108 |
+
f'<div class="stat-line"><span class="stat-err">✕ Generation failed</span> <span class="stat-chip"><span class="stat-k">ERR</span><span class="stat-v">{e}</span></span></div>',
|
| 109 |
+
)
|
| 110 |
+
html = render_viewer(volume_path=result.volume_path, colormap="gray")
|
| 111 |
+
stat = (
|
| 112 |
+
'<div class="stat-line">'
|
| 113 |
+
'<span class="stat-mark"></span>'
|
| 114 |
+
'<span class="stat-label">Generated</span>'
|
| 115 |
+
f'<span class="stat-chip"><span class="stat-k">runtime</span><span class="stat-v">{result.runtime_seconds:.1f}s</span></span>'
|
| 116 |
+
f'<span class="stat-chip"><span class="stat-k">seed</span><span class="stat-v">{result.seed}</span></span>'
|
| 117 |
+
f'<span class="stat-chip"><span class="stat-k">steps</span><span class="stat-v">{req.num_steps}</span></span>'
|
| 118 |
+
f'<span class="stat-chip"><span class="stat-k">size</span><span class="stat-v">{req.output_size[0]}³</span></span>'
|
| 119 |
+
'</div>'
|
| 120 |
+
)
|
| 121 |
+
return html, gr.update(visible=True, value=result.volume_path), stat
|
| 122 |
+
|
| 123 |
+
decorated = spaces_gpu(_generate) if spaces_gpu else _generate
|
| 124 |
+
(
|
| 125 |
+
generate_btn.click(
|
| 126 |
+
lambda: gr.update(value="Generating volume…", interactive=False),
|
| 127 |
+
outputs=[generate_btn],
|
| 128 |
+
)
|
| 129 |
+
.then(
|
| 130 |
+
decorated,
|
| 131 |
+
inputs=[contrast, dim_xy, dim_z, sp_x, sp_y, sp_z, seed, steps, cfg],
|
| 132 |
+
outputs=[viewer, download, status],
|
| 133 |
+
show_progress="full",
|
| 134 |
+
)
|
| 135 |
+
.then(
|
| 136 |
+
lambda: gr.update(value="Generate volume", interactive=True),
|
| 137 |
+
outputs=[generate_btn],
|
| 138 |
+
)
|
| 139 |
+
)
|
| 140 |
+
|
| 141 |
+
for btn, sample in zip(sample_btns, MR_BRAIN_SAMPLES):
|
| 142 |
+
def _apply(s=sample):
|
| 143 |
+
return (
|
| 144 |
+
s["contrast"],
|
| 145 |
+
s["xy"], s["z"],
|
| 146 |
+
s["spacing"][0], s["spacing"][1], s["spacing"][2],
|
| 147 |
+
)
|
| 148 |
+
btn.click(_apply, outputs=[contrast, dim_xy, dim_z, sp_x, sp_y, sp_z])
|
| 149 |
+
|
| 150 |
+
return group, back_btn
|
utils/__init__.py
ADDED
|
File without changes
|
utils/nifti_io.py
ADDED
|
@@ -0,0 +1,16 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from __future__ import annotations
|
| 2 |
+
|
| 3 |
+
from pathlib import Path
|
| 4 |
+
|
| 5 |
+
import nibabel as nib
|
| 6 |
+
import numpy as np
|
| 7 |
+
|
| 8 |
+
|
| 9 |
+
def load_volume(path: str | Path) -> tuple[np.ndarray, np.ndarray]:
|
| 10 |
+
img = nib.load(str(path))
|
| 11 |
+
return np.asarray(img.dataobj), img.affine
|
| 12 |
+
|
| 13 |
+
|
| 14 |
+
def percentile_window(data: np.ndarray, lo: float = 2.0, hi: float = 98.0) -> tuple[float, float]:
|
| 15 |
+
nz = data[data > 0] if (data > 0).any() else data
|
| 16 |
+
return float(np.percentile(nz, lo)), float(np.percentile(nz, hi))
|
utils/weights.py
ADDED
|
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""Lazy-download helper. Delegates to upstream `scripts.download_model_data`."""
|
| 2 |
+
from __future__ import annotations
|
| 3 |
+
|
| 4 |
+
from pipelines._runner import ensure_weights # re-export
|
| 5 |
+
|
| 6 |
+
__all__ = ["ensure_weights"]
|
utils/windowing.py
ADDED
|
@@ -0,0 +1,24 @@
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|
| 1 |
+
"""CT Hounsfield-unit window/level presets and conversion helpers."""
|
| 2 |
+
from __future__ import annotations
|
| 3 |
+
|
| 4 |
+
from dataclasses import dataclass
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
@dataclass(frozen=True)
|
| 8 |
+
class WLPreset:
|
| 9 |
+
name: str
|
| 10 |
+
width: float
|
| 11 |
+
level: float
|
| 12 |
+
|
| 13 |
+
def to_min_max(self) -> tuple[float, float]:
|
| 14 |
+
return self.level - self.width / 2.0, self.level + self.width / 2.0
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
CT_PRESETS: dict[str, WLPreset] = {
|
| 18 |
+
"soft_tissue": WLPreset("Soft Tissue", 350, 50),
|
| 19 |
+
"lung": WLPreset("Lung", 1500, -600),
|
| 20 |
+
"bone": WLPreset("Bone", 1800, 400),
|
| 21 |
+
"brain": WLPreset("Brain", 80, 40),
|
| 22 |
+
}
|
| 23 |
+
|
| 24 |
+
CT_PRESET_LABELS = [p.name for p in CT_PRESETS.values()]
|
viewer/__init__.py
ADDED
|
File without changes
|
viewer/colormaps.py
ADDED
|
@@ -0,0 +1,70 @@
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|
| 1 |
+
"""
|
| 2 |
+
Anatomy label tables and color assignments for the legend overlay.
|
| 3 |
+
|
| 4 |
+
CT labels are loaded directly from the upstream config so we stay in sync.
|
| 5 |
+
A deterministic golden-ratio HSV walk maps each label ID to a distinguishable RGB.
|
| 6 |
+
"""
|
| 7 |
+
from __future__ import annotations
|
| 8 |
+
|
| 9 |
+
import colorsys
|
| 10 |
+
import json
|
| 11 |
+
from pathlib import Path
|
| 12 |
+
|
| 13 |
+
ROOT = Path(__file__).resolve().parent.parent
|
| 14 |
+
UPSTREAM_LABEL_DICT = ROOT / "repos" / "NV-Generate-CTMR" / "configs" / "label_dict.json"
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
def _load_ct_labels() -> dict[int, str]:
|
| 18 |
+
if not UPSTREAM_LABEL_DICT.exists():
|
| 19 |
+
return {}
|
| 20 |
+
raw: dict[str, int] = json.loads(UPSTREAM_LABEL_DICT.read_text())
|
| 21 |
+
return {int(v): k for k, v in raw.items() if not k.startswith("dummy")}
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
def _color_for(idx: int) -> tuple[int, int, int]:
|
| 25 |
+
"""Deterministic high-contrast color from an integer ID."""
|
| 26 |
+
golden = 0.61803398875
|
| 27 |
+
h = (idx * golden) % 1.0
|
| 28 |
+
s = 0.55 + 0.35 * ((idx * 7) % 5) / 4.0
|
| 29 |
+
v = 0.70 + 0.25 * ((idx * 11) % 4) / 3.0
|
| 30 |
+
r, g, b = colorsys.hsv_to_rgb(h, s, v)
|
| 31 |
+
return int(r * 255), int(g * 255), int(b * 255)
|
| 32 |
+
|
| 33 |
+
|
| 34 |
+
CT_LABELS_BY_ID: dict[int, str] = _load_ct_labels()
|
| 35 |
+
|
| 36 |
+
|
| 37 |
+
def color_table(label_ids: list[int]) -> list[tuple[int, int, int, int]]:
|
| 38 |
+
"""RGBA palette for niivue label overlay — index 0 is background (transparent)."""
|
| 39 |
+
if not label_ids:
|
| 40 |
+
return []
|
| 41 |
+
max_id = max(label_ids)
|
| 42 |
+
palette: list[tuple[int, int, int, int]] = [(0, 0, 0, 0)]
|
| 43 |
+
for i in range(1, max_id + 1):
|
| 44 |
+
if i in label_ids:
|
| 45 |
+
r, g, b = _color_for(i)
|
| 46 |
+
palette.append((r, g, b, 200))
|
| 47 |
+
else:
|
| 48 |
+
palette.append((0, 0, 0, 0))
|
| 49 |
+
return palette
|
| 50 |
+
|
| 51 |
+
|
| 52 |
+
def legend_html(used_labels: dict[int, str]) -> str:
|
| 53 |
+
"""Compact horizontal legend showing only labels present in the generated mask."""
|
| 54 |
+
if not used_labels:
|
| 55 |
+
return ""
|
| 56 |
+
rows: list[str] = []
|
| 57 |
+
for lbl, name in sorted(used_labels.items()):
|
| 58 |
+
r, g, b = _color_for(lbl)
|
| 59 |
+
rows.append(
|
| 60 |
+
f'<div class="nv-legend-chip">'
|
| 61 |
+
f'<span class="nv-swatch" style="background:rgb({r},{g},{b})"></span>'
|
| 62 |
+
f'<span class="nv-label">{name}</span></div>'
|
| 63 |
+
)
|
| 64 |
+
count = len(used_labels)
|
| 65 |
+
return (
|
| 66 |
+
'<div class="nv-legend">'
|
| 67 |
+
f'<div class="nv-legend-title">Classes present in mask <span class="nv-legend-count">{count}</span></div>'
|
| 68 |
+
'<div class="nv-legend-grid">' + "".join(rows) + "</div>"
|
| 69 |
+
"</div>"
|
| 70 |
+
)
|
viewer/niivue_embed.py
ADDED
|
@@ -0,0 +1,227 @@
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|
|
| 1 |
+
"""
|
| 2 |
+
Generate a self-contained `gr.HTML` snippet that loads niivue from CDN, renders
|
| 3 |
+
a multiplanar (axial / coronal / sagittal / 3D) viewer, and optionally overlays a
|
| 4 |
+
labeled segmentation mask.
|
| 5 |
+
|
| 6 |
+
We render the viewer inside an `<iframe srcdoc=...>` because Gradio's React-based
|
| 7 |
+
DOM update cycle does NOT execute `<script>` tags injected via innerHTML when an
|
| 8 |
+
HTML component's value changes. An iframe with srcdoc gets a fresh document on
|
| 9 |
+
every update, so scripts always run.
|
| 10 |
+
"""
|
| 11 |
+
from __future__ import annotations
|
| 12 |
+
|
| 13 |
+
import base64
|
| 14 |
+
import html as _html
|
| 15 |
+
import json
|
| 16 |
+
import uuid
|
| 17 |
+
from pathlib import Path
|
| 18 |
+
from typing import Optional
|
| 19 |
+
|
| 20 |
+
from .colormaps import color_table
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
def _b64(path: Path) -> str:
|
| 24 |
+
with open(path, "rb") as f:
|
| 25 |
+
return base64.b64encode(f.read()).decode("ascii")
|
| 26 |
+
|
| 27 |
+
|
| 28 |
+
def empty_html(message: str = "Configure parameters, then click Generate volume.") -> str:
|
| 29 |
+
# Show a faint 2x2 wireframe preview of where AX/COR/SAG/3D will appear after
|
| 30 |
+
# generation, so the user knows what they will see.
|
| 31 |
+
return (
|
| 32 |
+
'<div class="nv-empty">'
|
| 33 |
+
'<div class="nv-empty-wireframe">'
|
| 34 |
+
'<div class="nv-wireq nv-wireq-ax"><span>Axial</span></div>'
|
| 35 |
+
'<div class="nv-wireq nv-wireq-cor"><span>Coronal</span></div>'
|
| 36 |
+
'<div class="nv-wireq nv-wireq-sag"><span>Sagittal</span></div>'
|
| 37 |
+
'<div class="nv-wireq nv-wireq-3d"><span>3D Render</span></div>'
|
| 38 |
+
'</div>'
|
| 39 |
+
'<div class="nv-empty-text">'
|
| 40 |
+
'<div class="nv-empty-icon">Awaiting generation</div>'
|
| 41 |
+
f'<div class="nv-empty-msg">{message}</div>'
|
| 42 |
+
"</div>"
|
| 43 |
+
"</div>"
|
| 44 |
+
)
|
| 45 |
+
|
| 46 |
+
|
| 47 |
+
def _build_iframe_doc(cfg_json: str, container_id: str) -> str:
|
| 48 |
+
"""Full HTML document loaded by the viewer iframe."""
|
| 49 |
+
return f"""<!DOCTYPE html>
|
| 50 |
+
<html>
|
| 51 |
+
<head>
|
| 52 |
+
<meta charset="utf-8">
|
| 53 |
+
<style>
|
| 54 |
+
html, body {{ margin: 0; padding: 0; height: 100%; background: #0b1020; overflow: hidden; }}
|
| 55 |
+
#{container_id} {{ display: block; width: 100%; height: 100%; background: #0b1020; }}
|
| 56 |
+
#status {{ position: absolute; top: 8px; left: 12px; color: #8c93ad; font: 12px -apple-system, BlinkMacSystemFont, sans-serif; pointer-events: none; }}
|
| 57 |
+
#err {{ position: absolute; bottom: 8px; left: 12px; right: 12px; color: #ff8d8d; font: 12px monospace; white-space: pre-wrap; pointer-events: none; }}
|
| 58 |
+
/* Pane labels overlaid at the outer corner of each MPR quadrant */
|
| 59 |
+
.pane-labels {{ position: absolute; inset: 0; pointer-events: none; }}
|
| 60 |
+
.pane-label {{
|
| 61 |
+
position: absolute;
|
| 62 |
+
font: 600 9.5px/1 ui-monospace, "JetBrains Mono", "SF Mono", monospace;
|
| 63 |
+
letter-spacing: 0.20em; text-transform: uppercase;
|
| 64 |
+
color: rgba(170, 200, 255, 0.85);
|
| 65 |
+
background: rgba(8, 16, 36, 0.65);
|
| 66 |
+
backdrop-filter: blur(4px);
|
| 67 |
+
padding: 5px 9px;
|
| 68 |
+
border: 1px solid rgba(170, 200, 255, 0.18);
|
| 69 |
+
}}
|
| 70 |
+
.pl-tl {{ top: 10px; left: 10px; }}
|
| 71 |
+
.pl-tr {{ top: 10px; right: 10px; }}
|
| 72 |
+
.pl-bl {{ bottom: 10px; left: 10px; }}
|
| 73 |
+
.pl-br {{ bottom: 10px; right: 10px; }}
|
| 74 |
+
</style>
|
| 75 |
+
</head>
|
| 76 |
+
<body>
|
| 77 |
+
<canvas id="{container_id}"></canvas>
|
| 78 |
+
<div class="pane-labels">
|
| 79 |
+
<div class="pane-label pl-tl">Coronal</div>
|
| 80 |
+
<div class="pane-label pl-tr">Sagittal</div>
|
| 81 |
+
<div class="pane-label pl-bl">Axial</div>
|
| 82 |
+
<div class="pane-label pl-br">3D</div>
|
| 83 |
+
</div>
|
| 84 |
+
<div id="status">Loading niivue…</div>
|
| 85 |
+
<div id="err"></div>
|
| 86 |
+
<script src="https://cdn.jsdelivr.net/npm/@niivue/niivue@0.68.2/dist/niivue.umd.js"></script>
|
| 87 |
+
<script>
|
| 88 |
+
const cfg = {cfg_json};
|
| 89 |
+
const statusEl = document.getElementById('status');
|
| 90 |
+
const errEl = document.getElementById('err');
|
| 91 |
+
function setStatus(t) {{ if (statusEl) statusEl.textContent = t; }}
|
| 92 |
+
function showErr(e) {{ if (errEl) errEl.textContent = String(e && e.stack || e); console.error(e); }}
|
| 93 |
+
|
| 94 |
+
function b64ToBlobUrl(b64, mime) {{
|
| 95 |
+
const bin = atob(b64);
|
| 96 |
+
const bytes = new Uint8Array(bin.length);
|
| 97 |
+
for (let i = 0; i < bin.length; i++) bytes[i] = bin.charCodeAt(i);
|
| 98 |
+
return URL.createObjectURL(new Blob([bytes], {{ type: mime }}));
|
| 99 |
+
}}
|
| 100 |
+
|
| 101 |
+
(async () => {{
|
| 102 |
+
try {{
|
| 103 |
+
setStatus('Initializing viewer…');
|
| 104 |
+
if (!window.niivue || !window.niivue.Niivue) throw new Error('niivue UMD failed to load');
|
| 105 |
+
const canvas = document.getElementById(cfg.container_id);
|
| 106 |
+
const nv = new niivue.Niivue({{
|
| 107 |
+
backColor: [0.043, 0.062, 0.125, 1],
|
| 108 |
+
// Cyan crosshair: high contrast on both dark and light tissue
|
| 109 |
+
crosshairColor: [0.4, 0.88, 1.0, 1],
|
| 110 |
+
crosshairWidth: 1,
|
| 111 |
+
show3Dcrosshair: true,
|
| 112 |
+
multiplanarLayout: 2, // GRID = 2 (AUTO=0, COLUMN=1, GRID=2, ROW=3)
|
| 113 |
+
multiplanarShowRender: 2, // ALWAYS show 3D in 4th tile
|
| 114 |
+
isResizeCanvas: true,
|
| 115 |
+
isOrientCube: false,
|
| 116 |
+
}});
|
| 117 |
+
await nv.attachToCanvas(canvas);
|
| 118 |
+
|
| 119 |
+
const volUrl = b64ToBlobUrl(cfg.vol_b64, 'application/octet-stream');
|
| 120 |
+
const baseSpec = {{ url: volUrl, name: 'volume.nii.gz', colormap: cfg.colormap || 'gray' }};
|
| 121 |
+
// Pre-set cal_min/cal_max on the spec so 3D render uses correct opacity/contrast on first paint.
|
| 122 |
+
if (cfg.window_min !== null && cfg.window_min !== undefined) baseSpec.cal_min = cfg.window_min;
|
| 123 |
+
if (cfg.window_max !== null && cfg.window_max !== undefined) baseSpec.cal_max = cfg.window_max;
|
| 124 |
+
|
| 125 |
+
const volSpecs = [baseSpec];
|
| 126 |
+
if (cfg.mask_b64) {{
|
| 127 |
+
const mUrl = b64ToBlobUrl(cfg.mask_b64, 'application/octet-stream');
|
| 128 |
+
volSpecs.push({{
|
| 129 |
+
url: mUrl,
|
| 130 |
+
name: 'mask.nii.gz',
|
| 131 |
+
colormap: 'random',
|
| 132 |
+
opacity: 0.6,
|
| 133 |
+
}});
|
| 134 |
+
}}
|
| 135 |
+
setStatus('Loading volume…');
|
| 136 |
+
await nv.loadVolumes(volSpecs);
|
| 137 |
+
|
| 138 |
+
// Re-apply windowing post-load (some loaders override cal_min/max to data percentiles).
|
| 139 |
+
if (nv.volumes && nv.volumes.length > 0) {{
|
| 140 |
+
if (cfg.window_min !== null && cfg.window_min !== undefined) nv.volumes[0].cal_min = cfg.window_min;
|
| 141 |
+
if (cfg.window_max !== null && cfg.window_max !== undefined) nv.volumes[0].cal_max = cfg.window_max;
|
| 142 |
+
}}
|
| 143 |
+
|
| 144 |
+
// Apply per-label colors to the mask via colormapLabel (niivue 0.68 API).
|
| 145 |
+
if (cfg.palette && cfg.palette.length > 0 && nv.volumes && nv.volumes.length > 1) {{
|
| 146 |
+
try {{
|
| 147 |
+
const n = cfg.palette.length;
|
| 148 |
+
const R = new Uint8ClampedArray(n);
|
| 149 |
+
const G = new Uint8ClampedArray(n);
|
| 150 |
+
const B = new Uint8ClampedArray(n);
|
| 151 |
+
const A = new Uint8ClampedArray(n);
|
| 152 |
+
const lut = new Uint8ClampedArray(n * 4);
|
| 153 |
+
const labels = new Array(n);
|
| 154 |
+
for (let i = 0; i < n; i++) {{
|
| 155 |
+
const c = cfg.palette[i];
|
| 156 |
+
R[i] = c[0]; G[i] = c[1]; B[i] = c[2]; A[i] = c[3];
|
| 157 |
+
lut[i*4+0] = c[0]; lut[i*4+1] = c[1]; lut[i*4+2] = c[2]; lut[i*4+3] = c[3];
|
| 158 |
+
labels[i] = (cfg.label_names && cfg.label_names[i]) || ('label ' + i);
|
| 159 |
+
}}
|
| 160 |
+
nv.volumes[1].colormapLabel = {{ R, G, B, A, lut, labels, min: 0, max: n - 1 }};
|
| 161 |
+
}} catch (e) {{ console.warn('Custom label colormap failed:', e); }}
|
| 162 |
+
}}
|
| 163 |
+
|
| 164 |
+
nv.setSliceType(nv.sliceTypeMultiplanar);
|
| 165 |
+
nv.updateGLVolume();
|
| 166 |
+
setStatus('');
|
| 167 |
+
}} catch (e) {{ showErr(e); }}
|
| 168 |
+
}})();
|
| 169 |
+
</script>
|
| 170 |
+
</body>
|
| 171 |
+
</html>"""
|
| 172 |
+
|
| 173 |
+
|
| 174 |
+
def render_viewer(
|
| 175 |
+
volume_path: Optional[str],
|
| 176 |
+
mask_path: Optional[str] = None,
|
| 177 |
+
*,
|
| 178 |
+
colormap: str = "gray",
|
| 179 |
+
used_label_ids: Optional[list[int]] = None,
|
| 180 |
+
window_min: Optional[float] = None,
|
| 181 |
+
window_max: Optional[float] = None,
|
| 182 |
+
) -> str:
|
| 183 |
+
"""Build the gr.HTML payload (iframe wrapper) for the niivue widget."""
|
| 184 |
+
if not volume_path:
|
| 185 |
+
return empty_html()
|
| 186 |
+
|
| 187 |
+
vol_b64 = _b64(Path(volume_path))
|
| 188 |
+
mask_b64 = _b64(Path(mask_path)) if mask_path else None
|
| 189 |
+
palette = color_table(used_label_ids or [])
|
| 190 |
+
container_id = f"nvc-{uuid.uuid4().hex[:8]}"
|
| 191 |
+
|
| 192 |
+
label_names: list[str] = []
|
| 193 |
+
if used_label_ids:
|
| 194 |
+
max_id = max(used_label_ids)
|
| 195 |
+
from .colormaps import CT_LABELS_BY_ID
|
| 196 |
+
label_names = ["background"] + [
|
| 197 |
+
CT_LABELS_BY_ID.get(i, f"label {i}") if i in used_label_ids else ""
|
| 198 |
+
for i in range(1, max_id + 1)
|
| 199 |
+
]
|
| 200 |
+
|
| 201 |
+
cfg = {
|
| 202 |
+
"container_id": container_id,
|
| 203 |
+
"vol_b64": vol_b64,
|
| 204 |
+
"mask_b64": mask_b64,
|
| 205 |
+
"colormap": colormap,
|
| 206 |
+
"palette": palette,
|
| 207 |
+
"label_names": label_names,
|
| 208 |
+
"window_min": window_min,
|
| 209 |
+
"window_max": window_max,
|
| 210 |
+
}
|
| 211 |
+
# JSON inside JS context — escape `</` to avoid premature script termination.
|
| 212 |
+
cfg_json = json.dumps(cfg).replace("</", "<\\/")
|
| 213 |
+
|
| 214 |
+
doc = _build_iframe_doc(cfg_json, container_id)
|
| 215 |
+
# srcdoc must escape '"' and '&' (HTML attribute escaping).
|
| 216 |
+
srcdoc = _html.escape(doc, quote=True)
|
| 217 |
+
# Fixed square aspect-ratio wrapper guarantees the niivue 2x2 grid stays
|
| 218 |
+
# 2x2 with equal-size tiles regardless of the volume's voxel dimensions.
|
| 219 |
+
return (
|
| 220 |
+
'<div style="width:100%;aspect-ratio:1/1;max-height:720px;'
|
| 221 |
+
'border-radius:14px;overflow:hidden;background:#0b1020;'
|
| 222 |
+
'margin:0 auto;display:block">'
|
| 223 |
+
f'<iframe srcdoc="{srcdoc}" '
|
| 224 |
+
'style="width:100%;height:100%;border:0;display:block;background:#0b1020" '
|
| 225 |
+
'sandbox="allow-scripts allow-same-origin"></iframe>'
|
| 226 |
+
'</div>'
|
| 227 |
+
)
|