pixi.toml

[workspace]
authors = ["pablo vela <pablovela5620@gmail.com>"]
channels = ["https://prefix.dev/ai-demos", "https://prefix.dev/conda-forge"]
name = "examples-monorepo"
# Explicit local conda/PyPI name mapping keeps overrides deterministic.
conda-pypi-map = { conda-forge = "conda-pypi-map.json", "https://prefix.dev/ai-demos/" = "conda-pypi-map-ai-demos.json" }
# Plain subdirs are the CPU/mac lanes; the named entries carry the CUDA-13
# virtual packages. Features opt in by listing a name — see AGENTS.md
# "Platforms & lockfile".
platforms = [
    "linux-64",
    "linux-aarch64",
    "osx-arm64",
    # glibc 2.35 lets the manylinux_2_35 tensorrt-cu13 wheels resolve; every
    # CUDA-13 host has glibc >= 2.35.
    { name = "linux-64-cuda13", platform = "linux-64", cuda = "13.0", glibc = "2.35" },
    { name = "linux-aarch64-cuda13", platform = "linux-aarch64", cuda = "13.0", glibc = "2.35" },
]
version = "0.1.0"
# Named workspace platforms need pixi >= 0.71; the fleet runs 0.73.
requires-pixi = ">=0.73"
preview = ["pixi-build"]

# ─── pypi-options (workspace-level) ─────────────────────────────────────────
[pypi-options]

[pypi-options.dependency-overrides]
iopath = ">=0.1.10"
fsspec = ">=2025.3,<=2026.2.0"

# ─── common feature (shared loose base deps) ───────────────────────────────
# osx-arm64 lets mac-targeting packages compose `common`; an env solves for
# macOS only when EVERY feature lists osx-arm64, so linux envs are unaffected.
[feature.common]
platforms = ["linux-64", "linux-aarch64", "osx-arm64"]

[feature.common.dependencies]
av = "*"
py-opencv = "*"
numpy = "*"
pyserde = ">=0.31.2,<0.32"
jaxtyping = "<0.3"
typing_extensions = ">=4.1.0,<4.13.0"
hf-transfer = "*"
scipy = "*"
huggingface_hub = "*"
tqdm = "*"
transformers = ">=5.0.0"
jupyterlab = "*"

[feature.common.target.linux-aarch64.dependencies]
xorg-libx11 = "*"
xorg-xorgproto = "*"

# simplecv imports torch at module load; a common-only macOS env has no other
# torch provider, so scope CPU torch to osx-arm64 (Linux keeps pytorch-gpu).
[feature.common.target.osx-arm64.dependencies]
pytorch-cpu = "*"
# rerun-sdk's dataloader extra needs torchvision; conda provides the matching build.
torchvision = "*"

[feature.common.pypi-dependencies]
# datafusion only — the dataloader extra would drag torch into common envs.
rerun-sdk = { version = "==0.35.0", extras = ["datafusion"] }
gradio = "==6.13.0"
gradio-rerun = "==0.35.0"
simplecv = { path = "packages/simplecv", editable = true }

# ─── catalog common feature (Rerun catalog prerelease lane) ────────────────
# Explicit platforms required — see AGENTS.md "Platforms & lockfile".
[feature.catalog-common]
platforms = ["linux-64", "linux-aarch64"]

[feature.catalog-common.dependencies]
av = "*"
py-opencv = "*"
numpy = "*"
pyserde = ">=0.31.2,<0.32"
jaxtyping = "<0.3"
typing_extensions = ">=4.1.0,<4.13.0"
hf-transfer = "*"
scipy = "*"
huggingface_hub = "*"
tqdm = "*"
transformers = ">=5.0.0"

[feature.catalog-common.target.linux-aarch64.dependencies]
xorg-libx11 = "*"
xorg-xorgproto = "*"

[feature.catalog-common.pypi-dependencies]
simplecv = { path = "packages/simplecv", editable = true }

# Catalog lane: common's rerun-sdk + the dataloader extra; for unreleased
# builds see AGENTS.md "Testing Rerun builds".
# Explicit platforms required — see AGENTS.md "Platforms & lockfile".
[feature.rerun-prerelease]
platforms = ["linux-64", "linux-aarch64"]

[feature.rerun-prerelease.pypi-dependencies]
rerun-sdk = { version = "==0.36.0a1+dev", extras = [
    "datafusion",
    "dataloader",
] }

[feature.rerun-prerelease.pypi-options]
index-url = "https://pypi.org/simple"
find-links = [{ url = "https://build.rerun.io/commit/4265652/wheels/" }]
prerelease-mode = "allow"


# ─── CUDA 13.0 feature (shared across all GPU envs) ─────────────────────────
# linux-64 + linux-aarch64 (DGX Spark). An env gains aarch64 only if its other
# features also allow it; x86-only features pin platforms = ["linux-64"].
[feature.cuda]
# CUDA virtual packages come from the named workspace platforms above.
platforms = ["linux-64-cuda13", "linux-aarch64-cuda13"]

[feature.cuda.dependencies]
# CUDA Build Tools
cuda-compiler = "*"
cuda-version = "13.0.*"
cuda-cudart-dev = "*"
cuda-crt = "*"
libcusparse-dev = "*"
cuda-driver-dev = "*"
cuda-nvcc = "*"
cuda-nvrtc-dev = "*"
cuda-nvtx = "*"
cuda-nvtx-dev = "*"
cuda-nvml-dev = "*"
cuda-profiler-api = "*"
# CUDA Libraries
cudnn = "*"
libcublas-dev = "*"
libcudss-dev = "*"
libcufile-dev = "*"
libcufft-dev = "*"
libcurand-dev = "*"
libcusolver-dev = "*"
cusparselt = "*"
libnvjitlink = "*"
# PyTorch — forces the cuda130/2.12.1 build (explicit beats relying on cuda-version alone)
pytorch-gpu = ">=2.12,<2.13"
torchvision = "*"
# onnxruntime — conda-forge *_cuda130 builds cover linux-64 AND linux-aarch64,
# replacing the old two-index pypi onnxruntime-gpu split. Build glob required:
# CPU builds carry no cuda-version constraint. No sm_121 SASS — the GB10 Spark
# JITs the bundled compute_120 PTX (validated on-device 2026-08-05).
# MIGRATION GOTCHA: envs installed before this switch keep stale files from the
# pypi wheel (its onnxruntime_pybind11_state.cpython-*.so shadows conda's plain
# .so → CUDA-EP segfault at session creation). Recreate such envs:
# rm -rf .pixi/envs/<env> && pixi install --frozen -e <env>.
onnxruntime = { version = ">=1.26.0,<2", build = "*cuda130*" }

# TensorRT — one shared source for every cuda env (pypi.nvidia.com ships both
# platforms, cp310–cp313). tensorrt-cu13-libs' stale metadata demands
# nvidia-cuda-runtime-cu13; NVIDIA's empty 0.0.0a0 placeholder satisfies it
# (conda supplies the real CUDA runtime).
[feature.cuda.pypi-dependencies]
tensorrt-cu13 = { version = "==11.2.1.2", index = "https://pypi.nvidia.com" }
nvidia-cuda-runtime-cu13 = "==0.0.0a0"
cuda-python = "*"
# The dynamo exporter — the only torch.onnx.export path now that TRT 11 made
# strongly-typed networks mandatory — imports onnxscript at export time.
onnxscript = "*"

# $CONDA_PREFIX/lib MUST come first (this key replaces pixi's default; ORT needs
# conda's cuDNN/cuBLAS), then the pip TRT wheels' libnvinfer. Both python dirs
# are listed because cuda envs span 3.11 and 3.12; missing paths are skipped.
[feature.cuda.activation.env]
LD_LIBRARY_PATH = "$CONDA_PREFIX/lib:$CONDA_PREFIX/lib/python3.12/site-packages/tensorrt_libs:$CONDA_PREFIX/lib/python3.11/site-packages/tensorrt_libs${LD_LIBRARY_PATH:+:$LD_LIBRARY_PATH}"

# ─── ide feature (standalone dev env for Zed/IDE tooling) ────────────────────
# Explicit platforms required — see AGENTS.md "Platforms & lockfile".
[feature.ide]
platforms = ["linux-64", "linux-aarch64"]

[feature.ide.dependencies]
python = "3.12.*"

# ─── dev feature (shared across all *-dev envs) ─────────────────────────────
# osx-arm64 so mac-targeting *-dev envs get the tooling; linux-only envs stay
# linux-only via platform intersection.
[feature.dev]
platforms = ["linux-64", "linux-aarch64", "osx-arm64"]

[feature.dev.dependencies]
ruff = "*"
pytest = ">=8.0.0,<9"
beartype = ">=0.22.9"
pyrefly = ">=1.1.0"
hypothesis = "*"
vulture = "*"

[feature.dev.pypi-dependencies]
types-tqdm = "*"

[feature.dev.activation.env]
PIXI_DEV_MODE = "1"
PYREFLY_TARGET = "."
PYREFLY_EXTRA_ARGS = ""

[feature.dev.tasks.lint]
cmd = "cd $PACKAGE_DIR && ruff check ."
description = "Lint the package"

[feature.dev.tasks.typecheck]
cmd = "cd $PACKAGE_DIR && pyrefly check -c ../../pyrefly.toml $PYREFLY_TARGET $PYREFLY_EXTRA_ARGS"
description = "Typecheck the package"

[feature.dev.tasks.deadcode]
cmd = "cd $PACKAGE_DIR && vulture --config pyproject.toml"
description = "Find dead code in the package"

[feature.dev.tasks.tests]
cmd = "cd $PACKAGE_DIR && pytest -q"
description = "Run package tests"

# ═══════════════════════════════════════════════════════════════════════════
# simplecv
# ═══════════════════════════════════════════════════════════════════════════
[feature.simplecv]
platforms = ["linux-64"]

[feature.simplecv.dependencies]
python = "3.12.*"
einops = ">=0.8.0,<0.9"
icecream = ">=2.1.3,<3"
pandas = ">=2.3.3,<2.4"
tyro = ">=0.9.1,<0.10"
open3d = ">=0.19.0,<0.20"
natsort = ">=8.4.0,<9"
libjpeg-turbo = "*"
requests = "*"
torchcodec = "*"
hdf5 = "*"
h5py = ">=3.12.1,<4"
dill = ">=0.3.8,<0.4.1"
datasets = ">=4.0.0"

[feature.simplecv.pypi-dependencies]
jax = ">=0.6.0,<0.7"
jaxopt = ">=0.8.5,<0.9"
lovely-jax = "*"
smplx = ">=0.1.28"
rtmlib = { git = "https://github.com/pablovela5620/rtmlib.git", rev = "98bca2193c39b349034b280803b54c9ee58f7c68" }
wilor-nano = { path = "packages/wilor-nano", editable = true }
trtkit = { path = "packages/trtkit", editable = true }
timm = "<1.0"
vrs = ">=1.1.0"
PyTurboJPEG = ">=1.7.0"

[feature.simplecv.activation.env]
PACKAGE_DIR = "packages/simplecv"
PYREFLY_TARGET = "simplecv"
PYREFLY_EXTRA_ARGS = "--baseline pyrefly-baseline.json"

[feature.simplecv.tasks.simplecv-view-polycam-data]
cmd = "python tools/view_polycam.py --polycam-zip-path data/example-room-scan-poly.zip"
depends-on = ["_download-simplecv-example-polycam-data"]
cwd = "packages/simplecv"
description = "View example Polycam data"

[feature.simplecv.tasks.simplecv-view-exoego-data]
cmd = "python tools/view_exoego.py"
depends-on = ["_download-simplecv-hocap-sample"]
cwd = "packages/simplecv"
description = "View example HoCap exo/ego data"

[feature.simplecv.tasks.simplecv-view-torchcodec-multiview]
cmd = "python tools/view_torchcodec_multiview.py"
cwd = "packages/simplecv"
description = "View videos with TorchCodec CUDA multiview decoding"

[feature.simplecv.tasks.simplecv-download-hot3d]
cmd = "python tools/download_hot3d.py"
cwd = "packages/simplecv"
description = "Download HOT3D Aria sequences from CDN URLs"

[feature.simplecv.tasks.simplecv-preprocess-hot3d]
cmd = "python tools/preprocess_hot3d.py"
cwd = "packages/simplecv"
description = "Convert HOT3D VRS files to AV1 MP4 for SimpleCV"

[feature.simplecv.tasks.simplecv-download-aria-gen2-pilot]
cmd = "python tools/download_aria_gen2_pilot.py"
cwd = "packages/simplecv"
description = "Download Aria Gen2 Pilot sequences from CDN URLs"

[feature.simplecv.tasks.simplecv-preprocess-aria-gen2-pilot]
cmd = "python tools/preprocess_aria_gen2_pilot.py"
cwd = "packages/simplecv"
description = "Convert Aria Gen2 Pilot VRS files to AV1 MP4 for SimpleCV"

[feature.simplecv.tasks.simplecv-preprocess-epfl-smart-kitchen]
cmd = "python tools/preprocess_epfl_smart_kitchen.py"
cwd = "packages/simplecv"
description = "Build an AV1-transcoded EPFL-Smart-Kitchen mirror for SimpleCV"

[feature.simplecv.tasks.simplecv-download-mamma]
cmd = "python tools/download_mamma.py"
cwd = "packages/simplecv"
description = "Download one MAMMA sequence per subset (register at mamma.is.tue.mpg.de; set MAMMA_USERNAME/MAMMA_PASSWORD)"

[feature.simplecv.tasks.simplecv-preprocess-mamma]
cmd = "python tools/preprocess_mamma.py"
cwd = "packages/simplecv"
description = "Re-encode downloaded MAMMA yuv444 videos to AV1 yuv420 (videos_av1 mirror)"

[feature.simplecv.tasks.simplecv-catalog-serve]
# Tier 1: empty in-memory catalog. High ulimit: the server holds one open fd
# per registered recording (6332 files overflow the default).
cmd = "bash -c 'ulimit -n 524288 && rerun server --port 9988'"
description = "Serve an empty ExoEgo Forge catalog on :9988 (2-tier; leave running)"

[feature.simplecv.tasks.simplecv-catalog-register]
# Tier 2: register the v1 root (flat /world/{exo,ego}/<name> layout → --layout flat).
cmd = "python tools/catalog_register.py --rrd-root /mnt/8tb/data/exoego-forge-catalog --layout flat"
cwd = "packages/simplecv"
description = "Register the v1 (flat) root into the running catalog"

[feature.simplecv.tasks.simplecv-catalog-register-rig]
# `--suffix=-rig` (equals form — a bare `-rig` parses as a flag) avoids
# recording_id collisions with the v1 entries.
cmd = "python tools/catalog_register.py --rrd-root /mnt/8tb/data/exoego-forge-catalog-rig --suffix=-rig"
cwd = "packages/simplecv"
description = "Register the rig (exoego:v2) root as -rig entries into the running catalog"

[feature.simplecv.tasks._download-simplecv-example-polycam-data]
cmd = "test -e data/example-room-scan-poly.zip || hf download pablovela5620/polycam-example-data example-room-scan-poly.zip --repo-type dataset --local-dir data/"
cwd = "packages/simplecv"
outputs = ["packages/simplecv/data/example-room-scan-poly.zip"]
description = "Download an example Polycam dataset from Hugging Face"

[feature.simplecv.tasks._download-simplecv-example-easymocap-data]
cmd = "test -e data/412-hand.zip || hf download pablovela5620/easymocap-example-data 412-hand.zip --repo-type dataset --local-dir data/"
cwd = "packages/simplecv"
outputs = ["packages/simplecv/data/412-hand.zip"]
description = "Download an example EasyMocap dataset from Hugging Face"

[feature.simplecv.tasks._download-simplecv-hocap-sample]
cmd = "test -e data/hocap/sample.zip && test -e data/hocap/sample || (mkdir -p data/hocap/ && hf download pablovela5620/hocap-sample sample.zip --repo-type dataset --local-dir data/hocap/ && python -m zipfile -e data/hocap/sample.zip data/hocap/)"
cwd = "packages/simplecv"
outputs = [
    "packages/simplecv/data/hocap/sample.zip",
    "packages/simplecv/data/hocap/sample",
]
description = "Download and extract an example HoCap dataset from Hugging Face"

[feature.simplecv.tasks._download-simplecv-epfl-smart-kitchen-sample]
cmd = "test -e data/epfl-smart-kitchen/sample.zip && test -e data/epfl-smart-kitchen/sample || (mkdir -p data/epfl-smart-kitchen/ && hf download pablovela5620/epfl-smart-kitchen-sample sample.zip --repo-type dataset --local-dir data/epfl-smart-kitchen/ && python -m zipfile -e data/epfl-smart-kitchen/sample.zip data/epfl-smart-kitchen/)"
cwd = "packages/simplecv"
outputs = [
    "packages/simplecv/data/epfl-smart-kitchen/sample.zip",
    "packages/simplecv/data/epfl-smart-kitchen/sample",
]
description = "Download and extract an example EPFL-Smart-Kitchen dataset from Hugging Face"

[feature.simplecv.tasks._download-simplecv-assembly101-sample]
cmd = "test -e data/assembly101-sample || hf download pablovela5620/Assembly101-Sample --repo-type dataset --include 'assembly101-sample/**' --local-dir data/"
cwd = "packages/simplecv"
outputs = ["packages/simplecv/data/assembly101-sample"]
description = "Download an example Assembly101 dataset from Hugging Face"

[feature.simplecv.tasks._download-simplecv-assembly101-720-sample]
cmd = "test -e data/assembly101-720-sample || hf download pablovela5620/Assembly101-Sample --repo-type dataset --include 'assembly101-720-sample/**' --local-dir data/"
cwd = "packages/simplecv"
outputs = ["packages/simplecv/data/assembly101-720-sample"]
description = "Download an example Assembly101 720p dataset from Hugging Face"

# ═══════════════════════════════════════════════════════════════════════════
# monoprior
# ═══════════════════════════════════════════════════════════════════════════
[feature.monoprior]
platforms = ["linux-64"]

[feature.monoprior.dependencies]
python = "3.12.*"
icecream = ">=2.1.3,<2.2"
einops = ">=0.8.0,<0.9"
matplotlib = ">=3.8.3,<3.9"
wandb = ">=0.19.10,<0.20"
pandas = ">=2.3.3,<2.4"
jupyterlab = ">=4.2.0,<4.3"
tyro = ">=0.9.1,<0.10"
open3d = ">=0.19.0,<0.20"
easydict = ">=1.13,<2"
imageio = ">=2.37.0,<3"
imageio-ffmpeg = ">=0.6.0,<0.7"
natsort = ">=8.4.0,<9"

[feature.monoprior.pypi-dependencies]
monopriors = { path = "packages/monoprior", editable = true }
sam3 = { path = "packages/sam3", editable = true }
trtkit = { path = "packages/trtkit", editable = true }
vggt = { git = "https://github.com/pablovela5620/vggt.git", rev = "5ed6ec88a951f27959f73bc72eb4b6dc7a028b0c" }

[feature.monoprior.activation.env]
PACKAGE_DIR = "packages/monoprior"
PYREFLY_TARGET = "monopriors/apis monopriors/data monopriors/gradio_ui monopriors/models monopriors/dc_utils.py monopriors/depth_utils.py monopriors/rr_logging_utils.py monopriors/scale_utils.py monopriors/__init__.py"

# ── Download tasks (hidden, used as depends-on) ─────────────────────────
[feature.monoprior.tasks._monoprior-download-single-image]
cmd = "test -d data/examples/single-image || hf download pablovela5620/monoprior-example --include 'single-image/*' --repo-type dataset --local-dir data/examples/"
cwd = "packages/monoprior"

[feature.monoprior.tasks._monoprior-download-multiview]
cmd = "test -f data/examples/multiview/car_landscape_12/IMG_2944.jpg || hf download pablovela5620/monoprior-example --include 'multiview/*' --repo-type dataset --local-dir data/examples/"
cwd = "packages/monoprior"

[feature.monoprior.tasks._monoprior-download-g3t-examples]
cmd = "test -f data/examples/multiview/bench/005.png && test -f data/examples/multiview/stairs/004.png && test -f data/examples/multiview/tree/006.png || (mkdir -p data/examples/multiview && curl -fsSL --retry 3 https://codeload.github.com/g3t-paper/g3t/tar.gz/193ce19574b73f0778a475ee54aadeb848e86b88 -o data/examples/g3t-examples.tar.gz && tar -xzf data/examples/g3t-examples.tar.gz --strip-components=3 -C data/examples/multiview g3t-193ce19574b73f0778a475ee54aadeb848e86b88/examples/g3t && rm -f data/examples/g3t-examples.tar.gz)"
cwd = "packages/monoprior"

[feature.monoprior.tasks.monoprior-download-multiview-examples]
depends-on = [
    "_monoprior-download-multiview",
    "_monoprior-download-g3t-examples",
]
description = "Download the Monopriors and official G3T multiview examples"

[feature.monoprior.tasks._monoprior-download-video]
cmd = "test -d data/examples/video || hf download pablovela5620/monoprior-example --include 'video/*' --repo-type dataset --local-dir data/examples/"
cwd = "packages/monoprior"

[feature.monoprior.tasks._monoprior-download-polycam]
cmd = "test -d data/examples/polycam || hf download pablovela5620/monoprior-example --include 'polycam/*' --repo-type dataset --local-dir data/examples/"
cwd = "packages/monoprior"

# ── Demo tasks ───────────────────────────────────────────────────────────
[feature.monoprior.tasks.monoprior-relative-depth]
cmd = "python tools/demos/relative_depth.py --image-path data/examples/single-image/room.jpg"
depends-on = ["_monoprior-download-single-image"]
cwd = "packages/monoprior"
description = "Run relative depth estimation on example image"

[feature.monoprior.tasks.monoprior-multiview-depth]
cmd = "python tools/demos/multiview_depth.py --image-dir data/examples/multiview/car_landscape_12"
depends-on = ["_monoprior-download-multiview"]
cwd = "packages/monoprior"
description = "Run VGGT or G3T multiview depth on example images"

[feature.monoprior.tasks.monoprior-multiview-calibration]
cmd = "python tools/demos/multiview_calibration.py --image-dir data/examples/multiview/car_landscape_12"
depends-on = ["_monoprior-download-multiview"]
cwd = "packages/monoprior"
description = "Run multiview calibration on example images"

[feature.monoprior.tasks.monoprior-video-depth]
cmd = "python tools/demos/video_depth.py --video-path data/examples/video/davis_rollercoaster.mp4"
depends-on = ["_monoprior-download-video"]
cwd = "packages/monoprior"
description = "Run video depth estimation on example video"

[feature.monoprior.tasks.monoprior-polycam-inference]
cmd = "python tools/demos/polycam_inference.py --polycam-zip-path data/examples/polycam/example-room-scan-poly.zip"
depends-on = ["_monoprior-download-polycam"]
cwd = "packages/monoprior"
description = "Run monoprior inference on Polycam dataset"

[feature.monoprior.tasks.monoprior-promptda-polycam]
cmd = "python tools/demos/promptda_polycam.py --polycam-zip-path data/examples/polycam/example-room-scan-poly.zip"
depends-on = ["_monoprior-download-polycam"]
cwd = "packages/monoprior"
description = "Run PromptDA depth completion on Polycam dataset"

[feature.monoprior.tasks.monoprior-metric-depth]
cmd = "python tools/demos/metric_depth.py --image-path data/examples/single-image/room.jpg"
depends-on = ["_monoprior-download-single-image"]
cwd = "packages/monoprior"
description = "Run metric depth estimation on example image"

[feature.monoprior.tasks.monoprior-surface-normals]
cmd = "python tools/demos/surface_normals.py --image-path data/examples/single-image/room.jpg"
depends-on = ["_monoprior-download-single-image"]
cwd = "packages/monoprior"
description = "Run surface normal estimation on example image"

[feature.monoprior.tasks.monoprior]
cmd = "python tools/demos/monoprior.py --image-path data/examples/single-image/room.jpg"
depends-on = ["_monoprior-download-single-image"]
cwd = "packages/monoprior"
description = "Run monoprior (metric depth + normals) on example image"

# ── App tasks (Gradio UIs) ──────────────────────────────────────────────
[feature.monoprior.tasks.monoprior-depth-compare-app]
cmd = "python tools/apps/depth_compare_app.py"
cwd = "packages/monoprior"
description = "Launch Gradio depth comparison UI"

[feature.monoprior.tasks.monoprior-calibration-app]
cmd = "python tools/apps/calibration_app.py"
depends-on = ["monoprior-download-multiview-examples"]
cwd = "packages/monoprior"
description = "Launch Gradio multiview calibration UI"

[feature.monoprior.tasks.monoprior-multiview-geometry-app]
cmd = "python tools/apps/multiview_geometry_app.py"
depends-on = ["monoprior-download-multiview-examples"]
cwd = "packages/monoprior"
description = "Launch Gradio multiview geometry UI"

[feature.monoprior.tasks.monoprior-metric-depth-app]
cmd = "python tools/apps/metric_depth_app.py"
cwd = "packages/monoprior"
description = "Launch Gradio metric depth UI"

[feature.monoprior.tasks.monoprior-depth-alignment-app]
cmd = "python tools/apps/depth_alignment_app.py"
cwd = "packages/monoprior"
description = "Launch Gradio depth alignment UI"

# ── Utility tasks ────────────────────────────────────────────────────────
[feature.monoprior.tasks.monoprior-build-wheel]
cmd = "python -m pip install build && python -m build"
cwd = "packages/monoprior"

[feature.monoprior.tasks.monoprior-upload-pypi]
cmd = "python -m pip install twine && twine check dist/*"
cwd = "packages/monoprior"

[feature.monoprior.tasks.monoprior-upload-hf]
cmd = "python tools/utils/upload_to_hf.py"
depends-on = ["monoprior-build-wheel"]
cwd = "packages/monoprior"

# ═══════════════════════════════════════════════════════════════════════════
# prompt-da
# ═══════════════════════════════════════════════════════════════════════════
[feature.prompt-da]
platforms = ["linux-64"]

[feature.prompt-da.dependencies]
python = "3.12.*"
open3d = ">=0.19.0,<0.20"

[feature.prompt-da.pypi-dependencies]
rerun-prompt-da = { path = "packages/prompt-da", editable = true }
monopriors = { path = "packages/monoprior", editable = true }
sam3 = { path = "packages/sam3", editable = true }
trtkit = { path = "packages/trtkit", editable = true }
# onnx: needed by torch's legacy ONNX exporter (TRT comes from the cuda feature).
onnx = "*"

[feature.prompt-da.activation.env]
PACKAGE_DIR = "packages/prompt-da"

# Explicit platforms required — see AGENTS.md "Platforms & lockfile".
[feature.prompt-da-demo]
platforms = ["linux-64", "linux-aarch64"]

[feature.prompt-da-demo.tasks._prompt-da-download-polycam-example]
cmd = """
test -e data/6G-room-example.zip || hf download pablovela5620/polycam-example-data 6G-room-example.zip --repo-type dataset --local-dir data/
"""
cwd = "packages/prompt-da"
outputs = ["packages/prompt-da/data/6G-room-example.zip"]
description = "Download the example Polycam zip from HuggingFace"

[feature.prompt-da-demo.tasks.prompt-da-polycam]
cmd = "python tools/prompt_da_polycam.py --polycam-zip-path data/6G-room-example.zip"
depends-on = ["_prompt-da-download-polycam-example"]
cwd = "packages/prompt-da"
description = "Run PromptDA on the example Polycam dataset"

[feature.prompt-da-demo.tasks.prompt-da-trt-polycam]
cmd = "python tools/prompt_da_trt_polycam.py --polycam-zip-path data/6G-room-example.zip"
depends-on = ["_prompt-da-download-polycam-example"]
cwd = "packages/prompt-da"
description = "Run batched TensorRT PromptDA on the example Polycam dataset"

[feature.prompt-da-demo.tasks.prompt-da-app]
cmd = "python tools/gradio_app.py"
depends-on = ["_prompt-da-download-polycam-example"]
cwd = "packages/prompt-da"
description = "Run the gradio app"

[feature.prompt-da-demo.tasks.prompt-da-dev-app]
cmd = "gradio tools/gradio_app.py"
depends-on = ["_prompt-da-download-polycam-example"]
cwd = "packages/prompt-da"
description = "Run the gradio app in dev mode"

# prompt-da-stream: streaming inference straight from the Rerun dataloader.
# Its own lane because it needs the 0.36 prerelease dataloader (ColumnDecoder,
# fetch_size); `common`'s 0.35 pin and a prerelease pin cannot share an env.
# Explicit platforms required — see AGENTS.md "Platforms & lockfile".
[feature.prompt-da-stream]
platforms = ["linux-64"]

[feature.prompt-da-stream.dependencies]
imagecodecs = ">=2024.9.22"
# arkitscenes_download.ingest imports these at package load.
trimesh = "*"
pillow = "*"
av = ">=18"
# simplecv's SegmentNvdecDecoder decodes the segment's AV1 packets on NVDEC.
torchcodec = "*"
# ffmpeg <902 links libjxl 0.11 and dlopen-fails beside the env's 0.12.
ffmpeg = { version = ">=8.1", build-number = ">=902" }

[feature.prompt-da-stream.pypi-dependencies]
arkitscenes-download = { path = "packages/arkitscenes-download", editable = true }

[feature.prompt-da-stream.tasks.prompt-da-arkitscenes]
cmd = "python tools/catalog_promptda.py"
cwd = "packages/prompt-da"
env = { RERUN_INSECURE_SKIP_HOST_CHECK = "1" }
description = "Run PromptDA over ARKitScenes catalog segments and stream the result to the viewer (cloud catalog by default, writes no layer)"

[feature.prompt-da-stream.tasks.prompt-da-arkitscenes-register]
cmd = "python tools/prompt_da_arkitscenes.py"
cwd = "packages/prompt-da"
env = { RERUN_INSECURE_SKIP_HOST_CHECK = "1", OMP_WAIT_POLICY = "PASSIVE", KMP_BLOCKTIME = "0" }
description = "Ingest: run PromptDA over local ARKitScenes segments with NVDEC and register the promptda layer — writes an RRD, shows nothing (needs arkitscenes-download-serve running)"

[feature.prompt-da-stream.tasks.prompt-da-arkitscenes-register-raw]
cmd = "python tools/prompt_da_arkitscenes_raw.py"
cwd = "packages/prompt-da"
env = { RERUN_INSECURE_SKIP_HOST_CHECK = "1" }
description = "Ingest: same as prompt-da-arkitscenes-register but decodes the raw .mov with torchcodec, registering the promptda_raw layer (needs arkitscenes-download-serve running)"

# ═══════════════════════════════════════════════════════════════════════════
# wilor-nano
# ═══════════════════════════════════════════════════════════════════════════
# Explicit platforms required — see AGENTS.md "Platforms & lockfile".
[feature.wilor-nano]
platforms = ["linux-64", "linux-aarch64"]

[feature.wilor-nano.dependencies]
python = "3.12.*"
dill = ">=0.4.0,<0.5"
trimesh = "*"
pyrender = "*"
torchcodec = "*"

[feature.wilor-nano.pypi-dependencies]
wilor_nano = { path = "packages/wilor-nano", editable = true }
trtkit = { path = "packages/trtkit", editable = true }
# daggr (a personal absolute-path editable dep) was removed for reproducibility;
# the optional tools/daggr_*.py demos need it installed manually.
rtmlib = { git = "https://github.com/pablovela5620/rtmlib.git", rev = "98bca2193c39b349034b280803b54c9ee58f7c68" }
onnx = ">=1.12.0,<1.18.0"
onnxscript = "*"

[feature.wilor-nano.activation.env]
PACKAGE_DIR = "packages/wilor-nano"

[feature.wilor-nano.tasks.wilor-nano-image-example]
cmd = "python tools/wilor_inference.py --image-path assets/img.png"
cwd = "packages/wilor-nano"
description = "Run WiLoR inference on example image"

[feature.wilor-nano.tasks.wilor-nano-video-example]
cmd = "python tools/wilor_inference.py --video-path assets/video.mp4"
cwd = "packages/wilor-nano"
description = "Run WiLoR inference on example video using the original PyTorch path"

[feature.wilor-nano.tasks.wilor-nano-video-trt]
cmd = "python tools/wilor_inference_trt.py"
cwd = "packages/wilor-nano"
description = "Run WiLoR video inference with the accepted batched TensorRT detector and full-WiLor backend"

[feature.wilor-nano.tasks.wilor-nano-export-onnx]
cmd = "python tools/conversion/export_wilor_onnx.py"
cwd = "packages/wilor-nano"
description = "Export WiLoR ONNX graphs used to rebuild TensorRT engines"

[feature.wilor-nano.tasks.wilor-nano-build-trt]
cmd = "python tools/conversion/build_wilor_tensorrt.py"
cwd = "packages/wilor-nano"
description = "Build machine-local WiLoR TensorRT engines from exported ONNX graphs"

[feature.wilor-nano.tasks.wilor-nano-compare-reference]
cmd = "python tools/compare_rrd_reference.py --reference-rrd tests/reference_data/wilor_video_30.rrd --candidate-rrd /tmp/wilor_candidate.rrd --index video_time --rtol 0.01 --atol 0.25"
cwd = "packages/wilor-nano"
description = "Compare a candidate WiLoR RRD against the checked-in reference RRD"

# ═══════════════════════════════════════════════════════════════════════════
# egoexo-forge
# ═══════════════════════════════════════════════════════════════════════════
# Explicit platforms required — see AGENTS.md "Platforms & lockfile".
[feature.egoexo-forge]
platforms = ["linux-64", "linux-aarch64"]

[feature.egoexo-forge.dependencies]
python = "3.12.*"
icecream = ">=2.1.3,<3"
tyro = ">=0.9.1,<0.10"
open3d = ">=0.19.0,<0.20"
h5py = ">=3.13.0,<4"
natsort = ">=8.4.0,<9"

[feature.egoexo-forge.target.linux-64.dependencies]
datasets = ">=4.0.0"

[feature.egoexo-forge.pypi-dependencies]
egoexo-forge = { path = "packages/egoexo-forge", editable = true }
timm = "<1.0"
rtmlib = { git = "https://github.com/pablovela5620/rtmlib.git", rev = "98bca2193c39b349034b280803b54c9ee58f7c68" }

[feature.egoexo-forge.activation.env]
PACKAGE_DIR = "packages/egoexo-forge"
PYREFLY_TARGET = "src/egoexo_forge tools"

# Explicit platforms required — see AGENTS.md "Platforms & lockfile".
[feature.egoexo-forge-demo]
platforms = ["linux-64", "linux-aarch64"]

[feature.egoexo-forge-demo.tasks.egoexo-forge-app]
cmd = "python tools/app.py"
cwd = "packages/egoexo-forge"
description = "Launch the EgoExo Forge Gradio viewer"

[feature.egoexo-forge-demo.tasks.egoexo-forge-batch-convert]
cmd = "python tools/batch_convert.py"
cwd = "packages/egoexo-forge"
description = "Deprecated no-op: ego/exo → .rrd conversion moved to simplecv (simplecv.apis.batch_raw_to_rrd)"

[feature.egoexo-forge-demo.tasks.egoexo-forge-catalog]
cmd = "python tools/catalog.py"
cwd = "packages/egoexo-forge"
description = "Mount HF-hosted egoexo-forge RRDs (5 per source) as a Rerun catalog server"

# ═══════════════════════════════════════════════════════════════════════════
# mv-api
# ═══════════════════════════════════════════════════════════════════════════
[feature.mv-api]
platforms = ["linux-64"]

[feature.mv-api.dependencies]
python = "3.12.*"
h5py = ">=3.13.0,<4"
natsort = ">=8.4.0,<9"
open3d = ">=0.19.0,<0.20"
scikit-image = ">=0.24.0,<0.25"
torchcodec = "*"
tyro = ">=0.9.1,<0.10"

[feature.mv-api.target.linux-64.dependencies]
datasets = ">=4.0.0"

[feature.mv-api.pypi-dependencies]
mv-api = { path = "packages/mv-api", editable = true }
monopriors = { path = "packages/monoprior", editable = true }
posekit = { path = "packages/posekit", editable = true }
trtkit = { path = "packages/trtkit", editable = true }
onnx = "*"
sam3 = { path = "packages/sam3", editable = true }
wilor_nano = { path = "packages/wilor-nano", editable = true }
rtmlib = { git = "https://github.com/pablovela5620/rtmlib.git", rev = "98bca2193c39b349034b280803b54c9ee58f7c68" }
vggt = { git = "https://github.com/pablovela5620/vggt.git", rev = "5ed6ec88a951f27959f73bc72eb4b6dc7a028b0c" }

[feature.mv-api.activation.env]
PACKAGE_DIR = "packages/mv-api"

[feature.mv-api.tasks.mv-api-full-app]
cmd = "python tools/apps/full_exoego_app.py"
cwd = "packages/mv-api"
description = "Run the mv-api full exo/ego node app"

[feature.mv-api.tasks.mv-api-hocap-download]
cmd = "test -e data/hocap/sample || (rm -rf data/hocap/.sample-tmp data/hocap/sample && mkdir -p data/hocap/.sample-tmp && hf download pablovela5620/hocap-sample sample.zip --repo-type dataset --local-dir data/hocap/.sample-tmp && python -m zipfile -e data/hocap/.sample-tmp/sample.zip data/hocap/.sample-tmp && mv data/hocap/.sample-tmp/sample data/hocap/sample && rm -rf data/hocap/.sample-tmp)"
cwd = "packages/mv-api"
outputs = ["packages/mv-api/data/hocap/sample"]
description = "Download and extract the raw HoCap sample"

[feature.mv-api-catalog]
platforms = ["linux-64"]

[feature.mv-api-catalog.activation.env]
PACKAGE_DIR = "packages/mv-api"

[feature.mv-api-catalog.tasks.mv-api-catalog-prediction-layer]
cmd = "python tools/apps/catalog_prediction_layer.py"
cwd = "packages/mv-api"
description = "Generate and register the catalog-native MVAPI COCO133 prediction layer (needs a running catalog: simplecv-catalog-serve + simplecv-catalog-register)"

[feature.mv-api-catalog.tasks.mv-api-catalog-tests]
cmd = "python -m pytest -q tests/test_catalog_prediction_layer.py"
cwd = "packages/mv-api"
description = "Run focused catalog-native MVAPI prediction-layer tests"

[feature.mv-api-catalog-register-mac]
platforms = ["osx-arm64"]

[feature.mv-api-catalog-register-mac.dependencies]
av = "*"
datasets = ">=4.0.0"
h5py = ">=3.13.0,<4"
natsort = ">=8.4.0,<9"
python = "3.12.*"
scipy = "*"

[feature.mv-api-catalog-register-mac.pypi-dependencies]
tyro = ">=0.9.1,<0.10"
simplecv = { path = "packages/simplecv", editable = true }
rerun-sdk = { version = "==0.35.0", extras = ["datafusion"] }

[feature.mv-api-catalog-register-mac.pypi-options]
index-url = "https://pypi.org/simple"
prerelease-mode = "allow"

[feature.mv-api-catalog-register-mac.activation.env]
PACKAGE_DIR = "packages/mv-api"

[feature.mv-api-catalog-register-mac.tasks.mv-api-catalog-register]
cmd = "python tools/apps/register_catalog_with_predictions.py"
cwd = "packages/mv-api"
description = "Register existing prediction RRD layers into a running catalog on macOS (needs a running catalog: simplecv-catalog-serve + simplecv-catalog-register)"

# ═══════════════════════════════════════════════════════════════════════════
# sam3d-body-rerun
# ═══════════════════════════════════════════════════════════════════════════
[feature.sam3d-body]
platforms = ["linux-64"]

[feature.sam3d-body.dependencies]
python = "3.12.*"
tomlkit = "==0.12.0"
audioop-lts = "*"
pydub = "*"
open3d = ">=0.19.0,<0.20"
h5py = ">=3.11"
torchcodec = "*"
fsspec = ">=2025.3,<=2026.2.0"

[feature.sam3d-body.pypi-dependencies]
sam3d_body = { path = "packages/sam3d-body", editable = true }
monopriors = { path = "packages/monoprior", editable = true }
sam3 = { path = "packages/sam3", editable = true }
timm = ">=0.9"
natsort = ">=8.4"
datasets = ">=2.20"
kernels = ">=0.11.3"

[feature.sam3d-body.activation.env]
PACKAGE_DIR = "packages/sam3d-body"
PYREFLY_TARGET = "src/sam3d_body/api src/sam3d_body/gradio_ui src/sam3d_body/ops src/sam3d_body/build_models.py src/sam3d_body/sam_3d_body_estimator.py src/sam3d_body/metadata src/sam3d_body/__init__.py"

[feature.sam3d-body.tasks.sam3d-body-app]
cmd = "python tool/gradio_sam3d_body.py"
cwd = "packages/sam3d-body"
description = "Launch SAM3D Gradio app"

[feature.sam3d-body.tasks.sam3d-body-cli]
cmd = "python tool/demo.py --image-folder data/example-data"
cwd = "packages/sam3d-body"
description = "Run SAM3D CLI demo"

[feature.sam3d-body.tasks.sam3d-body-download-hocap-sample]
cmd = """
test -d data/sample || \
(hf download pablovela5620/hocap-sample sample.zip --repo-type dataset --local-dir data && \
unzip -o data/sample.zip -d data && \
rm data/sample.zip)
"""
cwd = "packages/sam3d-body"
outputs = ["packages/sam3d-body/data/sample/"]
description = "Download HoCap sample data from HuggingFace"

[feature.sam3d-body.tasks.sam3d-body-mv-video-demo]
cmd = """
python tool/demo_mv_video.py \
    --max-frames 100 \
    hocap \
    --root-directory data/sample \
    --subject-id 8 \
    --sequence-name 20231024_180733
"""
cwd = "packages/sam3d-body"
depends-on = ["sam3d-body-download-hocap-sample"]
description = "Run multiview video SAM3 segmentation demo with TSDF fusion"

[feature.sam3d-body.tasks.sam3d-body-mv-body-demo]
cmd = """
python tool/demo_mv_body.py \
    --max-frames 50 \
    hocap \
    --root-directory data/sample \
    --subject-id 8 \
    --sequence-name 20231024_180733
"""
cwd = "packages/sam3d-body"
depends-on = ["sam3d-body-download-hocap-sample"]
description = "Multiview 3D body mesh fitting with per-camera estimation"

# ═══════════════════════════════════════════════════════════════════════════
# sam3-rerun
# ═══════════════════════════════════════════════════════════════════════════
[feature.sam3]
platforms = ["linux-64"]

[feature.sam3.dependencies]
python = "3.12.*"

[feature.sam3.pypi-dependencies]
sam3 = { path = "packages/sam3", editable = true }
spaces = ">=0.43.0"

[feature.sam3.activation.env]
PACKAGE_DIR = "packages/sam3"

[feature.sam3.tasks.sam3-video-batch]
cmd = "python tools/demos/video_batch.py"
cwd = "packages/sam3"
description = "Batch video segmentation with SAM3"

[feature.sam3.tasks.sam3-video-chunk]
cmd = "python tools/demos/video_chunk.py"
cwd = "packages/sam3"
description = "Chunk-based video segmentation with SAM3 (memory-efficient)"

[feature.sam3.tasks.sam3-video-stream]
cmd = "python tools/demos/video_stream.py"
cwd = "packages/sam3"
description = "Streaming video segmentation with SAM3 (constant memory)"

[feature.sam3.tasks.sam3-app]
cmd = "python tools/apps/sam3_rerun_app.py"
cwd = "packages/sam3"
description = "Launch SAM3 segmentation Gradio app with Rerun viewer"

[feature.sam3.tasks.sam3-annotated-app]
cmd = "python tools/apps/sam3_annotated_app.py"
cwd = "packages/sam3"
description = "Launch SAM3 segmentation Gradio app with annotated image"

# ═══════════════════════════════════════════════════════════════════════════
# sapiens2-pose
# ═══════════════════════════════════════════════════════════════════════════
[feature.sapiens2-pose]
platforms = ["linux-64"]

[feature.sapiens2-pose.dependencies]
python = "3.12.*"

[feature.sapiens2-pose.pypi-dependencies]
sapiens2-pose = { path = "packages/sapiens2-pose", editable = true }
trtkit = { path = "packages/trtkit", editable = true }
onnx = "*"
onnxscript = "*"

[feature.sapiens2-pose.activation.env]
PACKAGE_DIR = "packages/sapiens2-pose"
PYREFLY_TARGET = "src/sapiens2_pose/api src/sapiens2_pose/gradio_ui.py src/sapiens2_pose/video_gradio_ui.py src/sapiens2_pose/__init__.py tools"
SAPIENS_PRELOAD_MODELS = "0"

[feature.sapiens2-pose.tasks.sapiens2-pose-app]
cmd = "python tools/gradio_app.py"
cwd = "packages/sapiens2-pose"
description = "Launch the Sapiens2 pose Gradio app"

[feature.sapiens2-pose.tasks.sapiens2-pose-video-app]
cmd = "python tools/video_gradio_app.py"
cwd = "packages/sapiens2-pose"
description = "Launch the Sapiens2 video pose Gradio app"

[feature.sapiens2-pose.tasks.sapiens2-pose-image]
cmd = "python tools/demos/image_pose.py"
cwd = "packages/sapiens2-pose"
description = "Run Sapiens2 image pose inference and write Rerun/numeric artifacts"

[feature.sapiens2-pose.tasks.sapiens2-pose-video]
cmd = "python tools/demos/video_pose.py"
cwd = "packages/sapiens2-pose"
description = "Run Sapiens2 video pose inference and write a Rerun RRD"

[feature.sapiens2-pose.tasks.sapiens2-pose-export-onnx]
cmd = "python tools/conversion/export_onnx.py"
cwd = "packages/sapiens2-pose"
description = "Export a Sapiens2 pose checkpoint to ONNX"

[feature.sapiens2-pose.tasks.sapiens2-pose-build-trt]
cmd = "python tools/conversion/build_tensorrt.py"
cwd = "packages/sapiens2-pose"
description = "Build a machine-local TensorRT engine from a Sapiens2 pose ONNX graph"

[feature.sapiens2-pose.tasks.sapiens2-pose-trt-image]
cmd = "python tools/demos/tensorrt_image_pose.py"
cwd = "packages/sapiens2-pose"
description = "Run Sapiens2 pose inference with a TensorRT heatmap backend"

[feature.sapiens2-pose.tasks.sapiens2-pose-compare-artifacts]
cmd = "python tools/eval/compare_pose_artifacts.py"
cwd = "packages/sapiens2-pose"
description = "Compare two Sapiens2 pose numeric artifacts"

[feature.sapiens2-pose.tasks.sapiens2-pose-compare-rrds]
cmd = "python tools/eval/compare_pose_rrds.py"
cwd = "packages/sapiens2-pose"
description = "Compare Sapiens2 pose values queried from two Rerun recordings"

[feature.sapiens2-pose.tasks.sapiens2-pose-benchmark-trt]
cmd = "python tools/eval/benchmark_tensorrt_pose.py"
cwd = "packages/sapiens2-pose"
description = "Benchmark PyTorch vs TensorRT Sapiens2 pose heatmap inference"

[feature.sapiens2-pose.tasks.sapiens2-pose-dev-app]
cmd = "gradio tools/gradio_app.py"
cwd = "packages/sapiens2-pose"
description = "Launch the Sapiens2 pose Gradio app in dev mode"

[feature.sapiens2-pose.tasks.sapiens2-pose-dev-video-app]
cmd = "GRADIO_SERVER_PORT=7861 gradio tools/video_gradio_app.py"
cwd = "packages/sapiens2-pose"
description = "Launch the Sapiens2 video pose Gradio app in dev mode"

# ═══════════════════════════════════════════════════════════════════════════
# sapiens-coco133-pose
# ═══════════════════════════════════════════════════════════════════════════
[feature.sapiens-coco133-pose]
platforms = ["linux-64"]

[feature.sapiens-coco133-pose.dependencies]
python = "3.12.*"
torchcodec = "*"
tyro = ">=0.9.1,<0.10"

[feature.sapiens-coco133-pose.pypi-dependencies]
sapiens-coco133-pose = { path = "packages/sapiens-coco133-pose", editable = true }
trtkit = { path = "packages/trtkit", editable = true }
sapiens2-pose = { path = "packages/sapiens2-pose", editable = true }
mv-api = { path = "packages/mv-api", editable = true }
wilor_nano = { path = "packages/wilor-nano", editable = true }
rtmlib = { git = "https://github.com/pablovela5620/rtmlib.git", rev = "98bca2193c39b349034b280803b54c9ee58f7c68" }
onnx = "*"
onnxscript = "*"

[feature.sapiens-coco133-pose.activation.env]
PACKAGE_DIR = "packages/sapiens-coco133-pose"
SAPIENS_PRELOAD_MODELS = "0"

[feature.sapiens-coco133-pose.tasks.sapiens-coco133-pose-iterable-video]
cmd = "python tools/demos/iterable_video_pose.py"
cwd = "packages/sapiens-coco133-pose"
description = "Run non-batched RTMLib YOLOX + Sapiens COCO-133 video pose and write the golden RRD/artifact"

[feature.sapiens-coco133-pose.tasks.sapiens-coco133-pose-video-trt]
cmd = "python tools/demos/batched_tensorrt_video_pose.py"
cwd = "packages/sapiens-coco133-pose"
description = "Run batched CUDA/TensorRT COCO-133 video pose"

[feature.sapiens-coco133-pose.tasks.sapiens-coco133-pose-export-pose-onnx]
cmd = "python tools/conversion/export_sapiens_pose_onnx.py"
cwd = "packages/sapiens-coco133-pose"
description = "Export static-batch FP16 Sapiens2 pose ONNX"

[feature.sapiens-coco133-pose.tasks.sapiens-coco133-pose-build-trt]
cmd = "python tools/conversion/build_tensorrt_engine.py"
cwd = "packages/sapiens-coco133-pose"
description = "Build a static-batch FP16 TensorRT engine from ONNX"

[feature.sapiens-coco133-pose.tasks.sapiens-coco133-pose-benchmark]
cmd = "python tools/eval/benchmark.py"
cwd = "packages/sapiens-coco133-pose"
description = "Benchmark iterable golden path against batched TensorRT path"

# ═══════════════════════════════════════════════════════════════════════════
# trtkit — shared PyTorch → ONNX → TensorRT runtimes + engine hub
# ═══════════════════════════════════════════════════════════════════════════
[feature.trtkit]
platforms = ["linux-64", "linux-aarch64"]

[feature.trtkit.dependencies]
python = "3.12.*"
tyro = ">=0.9.1,<0.10"
rich = "*"

[feature.trtkit.pypi-dependencies]
trtkit = { path = "packages/trtkit", editable = true }
onnx = "*"

[feature.trtkit.activation.env]
PACKAGE_DIR = "packages/trtkit"

# ═══════════════════════════════════════════════════════════════════════════
# posekit
# ═══════════════════════════════════════════════════════════════════════════
[feature.posekit]
platforms = ["linux-64"]

[feature.posekit.dependencies]
python = "3.12.*"
torchcodec = "*"
tyro = ">=0.9.1,<0.10"

[feature.posekit.pypi-dependencies]
posekit = { path = "packages/posekit", editable = true }
trtkit = { path = "packages/trtkit", editable = true }
sapiens2-pose = { path = "packages/sapiens2-pose", editable = true }
sam2 = { path = "packages/sam2-streaming", editable = true }
onnx = "*"
onnxscript = "*"

[feature.posekit.activation.env]
PACKAGE_DIR = "packages/posekit"

[feature.posekit.tasks.posekit-video-pose]
cmd = "python tools/demos/video_pose.py"
cwd = "packages/posekit"
description = "Run the GPU video 2D pose demo (detector + top-down pose over torch/onnx/tensorrt backends)"

[feature.posekit.tasks.posekit-video-track]
cmd = "python tools/demos/video_track.py"
cwd = "packages/posekit"
description = "Run the streaming detect/track/pose/re-ID demo (YOLOX + SAM2-streaming + RTMPose + CLIP)"

# ═══════════════════════════════════════════════════════════════════════════
# robocap-slam
# ═══════════════════════════════════════════════════════════════════════════
# Explicit platforms: libcublas can never solve on osx-arm64; omitting the list
# would abort every workspace lock write (see AGENTS.md "Platforms & lockfile").
[feature.robocap-slam]
platforms = ["linux-64", "linux-aarch64"]

[feature.robocap-slam.dependencies]
python = "3.12.*"
pyyaml = "*"
cuda-version = "13.*"
libcublas = "*"
libcusolver = "*"
libstdcxx-ng = ">=14.2"
pyarrow = ">=20.0.0,<21"
# CPU torch only satisfies simplecv's module-load import; cuVSLAM brings its
# own cu13 wheel and never executes torch.
pytorch-cpu = ">=2.8.0"

[feature.robocap-slam.pypi-dependencies]
robocap-slam = { path = "packages/robocap-slam", editable = true }
tyro = ">=0.9,<1"

[feature.robocap-slam.target.linux-64.pypi-dependencies]
cuvslam = { url = "https://github.com/nvidia-isaac/cuVSLAM/releases/download/v15.0.0/cuvslam-15.0.0%2Bcu13-cp312-abi3-manylinux_2_39_x86_64.whl" }

[feature.robocap-slam.target.linux-aarch64.pypi-dependencies]
cuvslam = { url = "https://github.com/nvidia-isaac/cuVSLAM/releases/download/v15.0.0/cuvslam-15.0.0%2Bcu13-cp312-abi3-manylinux_2_39_aarch64.whl" }

[feature.robocap-slam.activation.env]
PACKAGE_DIR = "packages/robocap-slam"
LD_LIBRARY_PATH = "${CONDA_PREFIX}/lib:${LD_LIBRARY_PATH}"

[feature.robocap-slam.tasks.robocap-slam-download-example]
cmd = """test -d data/robocap/f408193e6447b3b0_session_14 || hf download pablovela5620/robocap-example --repo-type dataset --local-dir data/robocap"""
cwd = "packages/robocap-slam"
outputs = ["packages/robocap-slam/data/robocap/f408193e6447b3b0_session_14"]
description = "Download example Robocap dataset from HuggingFace"

[feature.robocap-slam.tasks.robocap-slam-track]
cmd = "python tools/track_odometry.py"
cwd = "packages/robocap-slam"
depends-on = ["robocap-slam-download-example"]
description = "Run multicamera visual odometry on Robocap data"

[feature.robocap-slam.tasks.robocap-slam-track-slam]
cmd = "python tools/track_slam.py"
cwd = "packages/robocap-slam"
depends-on = ["robocap-slam-download-example"]
description = "Run multicamera visual SLAM on Robocap data"

[feature.robocap-slam.tasks.robocap-slam-track-candidate]
cmd = "python tools/track_odometry.py --rr-config.save /tmp/robocap_cuvslam_15_candidate.rrd --rr-config.headless --no-auto-orient --max-frames 30 --no-log-videos"
cwd = "packages/robocap-slam"
depends-on = ["robocap-slam-download-example"]
description = "Run a bounded Robocap odometry smoke and save the migrated cuVSLAM candidate RRD"

[feature.robocap-slam.tasks.robocap-slam-compare-reference]
cmd = "python tools/compare_rrd_reference.py --reference-rrd /tmp/robocap_cuvslam_0_2_0_baseline.rrd --candidate-rrd /tmp/robocap_cuvslam_15_candidate.rrd --index video_time --max-rows 30 --rtol 0.01 --atol 0.25"
cwd = "packages/robocap-slam"
description = "Compare migrated Robocap pose output against the saved cuVSLAM 0.2.0 baseline"

# ═══════════════════════════════════════════════════════════════════════════
# pysfm
# ═══════════════════════════════════════════════════════════════════════════
[feature.pysfm]
platforms = ["linux-64"]

[feature.pysfm.dependencies]
python = "3.12.*"
tyro = ">=0.9.1,<0.10"
# No CUDA-13 pycolmap on conda-forge yet: its cuda* builds pin cuda-version <13
# (hard conflict), and the PyPI wheel core-dumps in feature extraction. The
# conda cpu_* build links the env's own libs and passes all tests — the only
# cost is GPU SIFT. Switch back to build = "cuda*" once the conda-forge cuda130
# migration reaches colmap/pycolmap (or build them in ai-demos if GPU SIFT is
# needed sooner).
pycolmap = { version = "4.0.*", build = "cpu*" }

[feature.pysfm.pypi-dependencies]
pysfm = { path = "packages/pysfm", editable = true }

[feature.pysfm.activation.env]
PACKAGE_DIR = "packages/pysfm"

# ── Download tasks ───────────────────────────────────────────────────────
[feature.pysfm.tasks._pysfm-download-sfm-example]
cmd = """
test -d data/examples/sfm_reconstruction/Fountain || \
(mkdir -p data/examples/sfm_reconstruction && \
python -c "
import urllib.request, zipfile
urllib.request.urlretrieve('https://cvg-data.inf.ethz.ch/local-feature-evaluation-schoenberger2017/Strecha-Fountain.zip', '/tmp/fountain.zip')
zipfile.ZipFile('/tmp/fountain.zip').extractall('data/examples/sfm_reconstruction')
")
"""
cwd = "packages/pysfm"
description = "Download Fountain example dataset for SfM"

[feature.pysfm.tasks._pysfm-download-unknown-rig]
cmd = "test -e data/examples/unknown-rig/cam1.mp4 || hf download pablovela5620/pycolmap-glomap-example --include 'unknown-rig/*.mp4' --repo-type dataset --local-dir data/examples/"
cwd = "packages/pysfm"
description = "Download unknown-rig example videos"

[feature.pysfm.tasks._pysfm-download-calibrated-rig]
cmd = "test -e data/examples/calibrated-rig/video_dev1_session15_segment1_left-front.mp4 || hf download pablovela5620/pycolmap-glomap-example --include 'calibrated-rig/*.mp4' --repo-type dataset --local-dir data/examples/"
cwd = "packages/pysfm"
description = "Download calibrated-rig example videos"

# ── Demo tasks ───────────────────────────────────────────────────────────
[feature.pysfm.tasks.pysfm-sfm-reconstruction-demo]
cmd = "python tools/demos/sfm_reconstruction.py --image-dir data/examples/sfm_reconstruction/Fountain/images --rr-config.save data/examples/sfm_reconstruction/fountain.rrd"
depends-on = ["_pysfm-download-sfm-example"]
cwd = "packages/pysfm"
description = "Run COLMAP SfM reconstruction on Fountain dataset with Rerun viewer"

# ── App tasks ────────────────────────────────────────────────────────────
[feature.pysfm.tasks.pysfm-sfm-reconstruction-app]
cmd = "python tools/nodes/sfm_reconstruction_app.py"
depends-on = ["_pysfm-download-sfm-example"]
cwd = "packages/pysfm"
description = "Launch COLMAP SfM Gradio app with Rerun viewer"

[feature.pysfm.tasks.pysfm-vid-to-img-node]
cmd = "python tools/nodes/video_to_image_node.py"
depends-on = ["_pysfm-download-unknown-rig"]
cwd = "packages/pysfm"
description = "Launch Video-to-Image frame extraction Gradio app with Rerun viewer"

[feature.pysfm.tasks.pysfm-vid-to-img-node-dev]
cmd = "gradio tools/nodes/video_to_image_node.py --watch-dirs $PIXI_PROJECT_ROOT/packages/pysfm/pysfm"
depends-on = ["_pysfm-download-unknown-rig"]
cwd = "packages/pysfm"
description = "Video-to-Image Gradio app with hot reload"

[feature.pysfm.tasks.pysfm-vid-to-img-demo]
cmd = "python tools/demos/video_to_image.py --video-path data/examples/unknown-rig/cam1.mp4 --output-dir /tmp/video_to_image_output --rr-config.save /tmp/video_to_image_output/video_to_image.rrd"
depends-on = ["_pysfm-download-unknown-rig"]
cwd = "packages/pysfm"
description = "Run video-to-image frame extraction CLI demo (saves .rrd)"

[feature.pysfm.tasks.pysfm-vid-recon-demo]
cmd = "python tools/demos/pycolmap_vid_recon.py --config.video-path data/examples/unknown-rig/cam1.mp4"
depends-on = ["_pysfm-download-unknown-rig"]
cwd = "packages/pysfm"
description = "Monocular video reconstruction demo with Rerun viewer"

[feature.pysfm.tasks.pysfm-brush-train-kitchen-5k]
cmd = """
python tools/brush/train_colmap_brush.py \
  --images-dir /home/pablo/0Dev/data/colmap-data/multicam/images/6g-night-nov-29-2024/kitchen-nov-29-2024-train/0100 \
  --model-dir /home/pablo/0Dev/data/colmap-data/multicam/colmap/6g-night-nov-29-2024/kitchen-nov-29-2024-train/0100-aliked-lightglue-globalmapper-overlap10-timed-20260320/rig/sparse/0 \
  --work-root /home/pablo/0Dev/data/colmap-data/multicam/brush/6g-night-nov-29-2024/kitchen-nov-29-2024-train/0100-global-rig \
  --steps 5000 \
  --eval-split-every 10 \
  --eval-every 1000 \
  --export-every 5000 \
  --experiment-name 5k
"""
cwd = "packages/pysfm"
description = "Train a first 5k-step Brush splat from the kitchen train 0100 rig model"

[feature.pysfm.target.linux-64.dependencies]
brush = "==0.3.0"

# ═══════════════════════════════════════════════════════════════════════════
# vistadream
# ═══════════════════════════════════════════════════════════════════════════
[feature.vistadream]
platforms = ["linux-64"]

[feature.vistadream.dependencies]
python = "3.12.*"
cmake = ">=4.0.3,<5"
open3d = ">=0.19.0,<0.20"
scikit-learn = ">=1.7.1,<2"
nodejs = ">=25.7.0,<26"
torchmetrics = "*"
icecream = ">=2.1.3,<2.2"
einops = ">=0.8.0,<0.9"
imageio = ">=2.37.0,<3"
imageio-ffmpeg = ">=0.6.0,<0.7"
# ai-demos prebuilt for CUDA 13, Python 3.12, and Torch 2.12 (SM 8.6 + 12.0 + PTX); no runtime JIT.
gsplat = "==1.5.3"
[feature.vistadream.target.linux-64.dependencies]
splat-transform = "*"

[feature.vistadream.pypi-dependencies]
vistadream = { path = "packages/vistadream", editable = true }
monopriors = { path = "packages/monoprior", editable = true }
sam3 = { path = "packages/sam3", editable = true }
vggt = { git = "https://github.com/pablovela5620/vggt.git", rev = "5ed6ec88a951f27959f73bc72eb4b6dc7a028b0c" }
accelerate = "*"
plyfile = "*"
timm = "*"
diffusers = "*"
torchsde = "*"
roma = "*"
peft = "*"
omegaconf = "*"

[feature.vistadream.activation.env]
PACKAGE_DIR = "packages/vistadream"
PYREFLY_TARGET = "src/vistadream/api src/vistadream/gradio src/vistadream/resize_utils.py src/vistadream/__init__.py tools"
CUDA_HOME = "${CONDA_PREFIX}/targets/x86_64-linux"
CPATH = "${CONDA_PREFIX}/targets/x86_64-linux/include:${CPATH}"
PATH = "${CONDA_PREFIX}/nvvm/bin:${PATH}"

# ── Demo tasks ───────────────────────────────────────────────────────────
[feature.vistadream.tasks.vistadream-example]
cmd = "python tools/run_single_img.py --image-path data/office/IMG_4029.jpg"
cwd = "packages/vistadream"
description = "Run VistaDream single image 3D reconstruction"

[feature.vistadream.tasks.vistadream-gradio-app]
cmd = "python tools/gradio_app.py"
cwd = "packages/vistadream"
description = "Launch VistaDream Gradio web interface"

# ═══════════════════════════════════════════════════════════════════════════
# pyvrs-viewer
# ═══════════════════════════════════════════════════════════════════════════
# Explicit platforms required — see AGENTS.md "Platforms & lockfile".
[feature.pyvrs-viewer]
platforms = ["linux-64", "linux-aarch64"]

[feature.pyvrs-viewer.dependencies]
python = "3.12.*"
tyro = ">=0.9.1,<0.10"

[feature.pyvrs-viewer.pypi-dependencies]
pyvrs-viewer = { path = "packages/pyvrs-viewer", editable = true }
vrs = "*"
PyTurboJPEG = "*"

[feature.pyvrs-viewer.activation.env]
PACKAGE_DIR = "packages/pyvrs-viewer"

# ── Download tasks ───────────────────────────────────────────────────────
# Explicit platforms required — see AGENTS.md "Platforms & lockfile".
[feature.pyvrs-viewer-demo]
platforms = ["linux-64", "linux-aarch64"]

[feature.pyvrs-viewer-demo.tasks._pyvrs-viewer-download-hot3d-quest-vrs]
cmd = """
test -f data/hot3d_quest.vrs || \
curl -L -o data/hot3d_quest.vrs \
  'https://scontent.xx.fbcdn.net/m1/v/t6/An9GExjCnYwO02IsP_xnrencBwdUTHg2gxLtxbWcVVn05qEZ7MZ-TEyybVMIVS9tVckTd0anQCP058RBnetrmidiFc4kkKRCMwbZ9DPufV8VZ_CsSlmn9k-tJjAJCLjks31tl4mkR5k5EM_DIO69BeOPbcNzbaSxCr0.vrs/Hot3DQuest_v4.0.0_P0002_1464cbdc_main_recording.vrs?_nc_gid&ccb=10-5&oh=00_AfxEnSw-bXsG5fzYoCMC8z4yPRBu-dNnse9nztDGrOopEA&oe=69F370EC&_nc_sid=71efe3'
"""
cwd = "packages/pyvrs-viewer"
description = "Download Hot3D Quest VRS example (2 mono cameras)"

[feature.pyvrs-viewer-demo.tasks._pyvrs-viewer-download-hot3d-aria-vrs]
cmd = """
test -f data/hot3d_aria.vrs || \
curl -L -o data/hot3d_aria.vrs \
  'https://scontent.xx.fbcdn.net/m1/v/t6/An9jFWjgcg_1tMlA5V2DkwPV8hSjqqfw3fpaoe-Mz5PxqMZCzq5HZg_QJaX6Oq2jm0j8tAJ2I-H-c4FAOnDvqezuEho1RUFDWqe6d0AqrcOMK0LCjmnhXiNuihAr_-SDjNEPK1896cP9oVpHhp7bUEi0O795nufof00.vrs/Hot3DAria_v4.0.0_P0001_10a27bf7_main_recording.vrs?_nc_gid&ccb=10-6&oh=00_Afy-YiaePXBCaucxejkXfKbjTJG6dF2PvdJg0eLCPlxKyQ&oe=69F03AE5&_nc_sid=71efe3'
"""
cwd = "packages/pyvrs-viewer"
description = "Download Hot3D Aria VRS example (4 cameras + IMU + sensors)"

# ── Demo tasks ───────────────────────────────────────────────────────────
[feature.pyvrs-viewer-demo.tasks.pyvrs-viewer-vrs-to-rrd]
cmd = "python tools/demos/vrs_to_rrd.py"
cwd = "packages/pyvrs-viewer"
description = "Convert any VRS file (pass --vrs-path and other args after --)"

[feature.pyvrs-viewer-demo.tasks.pyvrs-viewer-vrs-to-rrd-quest]
cmd = "python tools/demos/vrs_to_rrd.py --vrs-path data/hot3d_quest.vrs --rr-config.save data/hot3d_quest.rrd"
depends-on = ["_pyvrs-viewer-download-hot3d-quest-vrs"]
cwd = "packages/pyvrs-viewer"
description = "Convert Hot3D Quest VRS to .rrd (2 mono cameras)"

[feature.pyvrs-viewer-demo.tasks.pyvrs-viewer-vrs-to-rrd-aria]
cmd = "python tools/demos/vrs_to_rrd.py --vrs-path data/hot3d_aria.vrs --rr-config.save data/hot3d_aria.rrd"
depends-on = ["_pyvrs-viewer-download-hot3d-aria-vrs"]
cwd = "packages/pyvrs-viewer"
description = "Convert Hot3D Aria VRS to .rrd (cameras + IMU + sensors)"

[feature.pyvrs-viewer-demo.tasks.pyvrs-viewer-benchmark]
cmd = "python tools/bench/run_benchmark.py"
cwd = "packages/pyvrs-viewer"
description = "Benchmark 5 Quest + 5 Aria VRS files (requires download URL JSONs)"

# ═══════════════════════════════════════════════════════════════════════════
# live-rerun — zero-transcode logging of hardware-encoded H.264/H.265 into
# Rerun VideoStream (backend #1: DepthAI/OAK)
# ═══════════════════════════════════════════════════════════════════════════
[feature.live-rerun]
platforms = ["linux-64", "linux-aarch64", "osx-arm64"]

[feature.live-rerun.dependencies]
python = "3.12.*"
tyro = ">=0.9.1,<0.10"

[feature.live-rerun.pypi-dependencies]
live-rerun = { path = "packages/live-rerun", editable = true }
# DepthAI 2.x required — 3.x fails to open this OAK unit. PyPI-only.
depthai = "==2.27.0.0"

[feature.live-rerun.activation.env]
PACKAGE_DIR = "packages/live-rerun"
PYREFLY_TARGET = "."
# depthai's incomplete compiled-module stubs are baselined.
PYREFLY_EXTRA_ARGS = "--baseline pyrefly-baseline.json"

[feature.live-rerun-demo]
platforms = ["linux-64", "linux-aarch64", "osx-arm64"]

[feature.live-rerun-demo.tasks.live-rerun-oak]
cmd = "python tools/apps/oak_live_rerun.py"
cwd = "packages/live-rerun"
description = "Stream an OAK camera's encoded H.265/H.264 to Rerun (pass --rr-config.save out.rrd for live+save)"

# ═══════════════════════════════════════════════════════════════════════════
# mast3r-slam
# ═══════════════════════════════════════════════════════════════════════════
[feature.mast3r-slam]
channels = [
    "https://prefix.dev/ai-demos",
    "https://conda.modular.com/max-nightly/",
    "conda-forge",
]
platforms = ["linux-64"]

[feature.mast3r-slam.dependencies]
python = "3.11.*"
torchcodec = "*"
eigen = ">=3.4.0,<4"
ffmpeg = ">=7.1.0"
open3d = ">=0.19.0,<0.20"
# mkl 2026 (forced by cuda13/torch-2.12) breaks faiss's mkl builds (.so.2 vs
# .so.3 soname clash). Routing BLAS through OpenBLAS drops mkl entirely; GPU
# kernels are identical, only the CPU BLAS backend differs.
libblas = { version = "*", build = "*openblas" }
faiss = { version = "*", build = "*openblas*" }
scikit-learn = "*"
matplotlib = "*"
trimesh = "*"
mojo = "*"

[feature.mast3r-slam.target.linux-64.dependencies]
lietorch = ">=0.3.0"
mast3r = { path = "packages/mast3r" }
asmk = { path = "packages/asmk" }

[feature.mast3r-slam.pypi-dependencies]
mast3r-slam = { path = "packages/mast3r-slam", editable = true }
einops = ">=0.8.0"
evo = "*"
natsort = ">=8.4"
pykdtree = "*"
roma = "*"
pyaml = "*"

[feature.mast3r-slam.activation.env]
PACKAGE_DIR = "packages/mast3r-slam"

# mojo comes directly from the max-nightly channel, not the modular
# metapackage (whose starlette pin conflicts with gradio).

# ── Build tasks (CUDA extensions compiled via setuptools, no pip) ────────
[feature.mast3r-slam.tasks._mast3r-slam-build-cuda-kernels]
cmd = "python setup.py build_ext --inplace"
cwd = "packages/mast3r-slam"
description = "Build mast3r-slam CUDA backend kernels"
inputs = [
    "packages/mast3r-slam/setup.py",
    "packages/mast3r-slam/mast3r_slam/backend/src/*.cpp",
    "packages/mast3r-slam/mast3r_slam/backend/src/*.cu",
    "packages/mast3r-slam/mast3r_slam/backend/include/*.h",
]
outputs = ["packages/mast3r-slam/mast3r_slam/_backends*.so"]

# ── Mojo kernel build ──────────────────────────────────────────────────
[feature.mast3r-slam.tasks._mast3r-slam-build-mojo-kernels]
cmd = "cd packages/mast3r-slam && mojo build --emit shared-lib -o mast3r_slam_mojo_backends.so mast3r_slam/backend/mojo/mast3r_slam_mojo_backends.mojo"
description = "Build mast3r-slam Mojo backend kernels"
inputs = ["packages/mast3r-slam/mast3r_slam/backend/mojo/*.mojo"]
outputs = ["packages/mast3r-slam/mast3r_slam_mojo_backends*.so"]

# ── Download tasks (hidden, used as depends-on) ─────────────────────────
[feature.mast3r-slam.tasks._mast3r-slam-download-checkpoints]
cmd = """
hf download pablovela5620/mast3r-slam \
    MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric.pth \
    MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric_retrieval_codebook.pkl \
    MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric_retrieval_trainingfree.pth \
    --repo-type model --local-dir checkpoints/
"""
cwd = "packages/mast3r-slam"
description = "Download MASt3R-SLAM model checkpoints"
outputs = [
    "packages/mast3r-slam/checkpoints/MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric.pth",
]

[feature.mast3r-slam.tasks._mast3r-slam-download-example-data]
cmd = "hf download pablovela5620/mast3r-slam-example-data normal-apt-tour.mp4 livingroom-tour.mp4 --repo-type dataset --local-dir data/"
cwd = "packages/mast3r-slam"
outputs = [
    "packages/mast3r-slam/data/normal-apt-tour.mp4",
    "packages/mast3r-slam/data/livingroom-tour.mp4",
]
description = "Download example video data"

# ── Test baseline task ──────────────────────────────────────────────────
[feature.mast3r-slam.tasks._mast3r-slam-generate-test-baseline]
cmd = """python tools/mast3r_slam_inference.py \
  --dataset data/normal-apt-tour.mp4 --img-size 224 \
  --config config/test.yaml --max-frames 30 --no-viz \
  --rr-config.save tests/fixtures/baseline_30frames.rrd"""
depends-on = [
    "_mast3r-slam-build-cuda-kernels",
    "_mast3r-slam-build-mojo-kernels",
    "_mast3r-slam-download-checkpoints",
    "_mast3r-slam-download-example-data",
]
cwd = "packages/mast3r-slam"
description = "Generate baseline .rrd for regression tests (30 frames, deterministic)"
outputs = ["packages/mast3r-slam/tests/fixtures/baseline_30frames.rrd"]

# ── Demo tasks ───────────────────────────────────────────────────────────
[feature.mast3r-slam.tasks.mast3r-slam-example-quick]
cmd = "python tools/mast3r_slam_inference.py --dataset data/normal-apt-tour.mp4 --img-size 224 --config config/fast.yaml --max-frames 100"
depends-on = [
    "_mast3r-slam-build-mojo-kernels",
    "_mast3r-slam-download-checkpoints",
    "_mast3r-slam-download-example-data",
]
cwd = "packages/mast3r-slam"
description = "Run MASt3R-SLAM on first 100 frames (fast config, ~2 min)"

[feature.mast3r-slam.tasks.mast3r-slam-example-fast]
cmd = "python tools/mast3r_slam_inference.py --dataset data/normal-apt-tour.mp4 --img-size 224 --config config/fast.yaml"
depends-on = [
    "_mast3r-slam-build-mojo-kernels",
    "_mast3r-slam-download-checkpoints",
    "_mast3r-slam-download-example-data",
]
cwd = "packages/mast3r-slam"
description = "Run MASt3R-SLAM inference (fast config, 224px, full video)"

[feature.mast3r-slam.tasks.mast3r-slam-example-base]
cmd = "python tools/mast3r_slam_inference.py --dataset data/normal-apt-tour.mp4 --img-size 512 --config config/base.yaml"
depends-on = [
    "_mast3r-slam-build-mojo-kernels",
    "_mast3r-slam-download-checkpoints",
    "_mast3r-slam-download-example-data",
]
cwd = "packages/mast3r-slam"
description = "Run MASt3R-SLAM inference (base config, 512px)"

[feature.mast3r-slam.tasks.mast3r-slam-app]
cmd = "python tools/gradio-app.py"
depends-on = [
    "_mast3r-slam-build-mojo-kernels",
    "_mast3r-slam-download-checkpoints",
    "_mast3r-slam-download-example-data",
]
cwd = "packages/mast3r-slam"
description = "Launch MASt3R-SLAM Gradio web UI"

# ═══════════════════════════════════════════════════════════════════════════
# gsplat-rust-renderer
# ═══════════════════════════════════════════════════════════════════════════
# osx-arm64 included for the viewer + PLY-loading flows; the `brush` conda
# package is linux-64-only.
[feature.gsplat-rust-renderer]
platforms = ["linux-64", "linux-aarch64", "osx-arm64"]

[feature.gsplat-rust-renderer.dependencies]
python = "3.12.*"
# rerun 0.35 crates require rustc >= 1.95
rust = "1.97.*"
clang = "*"
cmake = "*"
pkg-config = "*"
numpy = "*"
jaxtyping = "<0.3"
typing_extensions = ">=4.1.0,<4.13.0"
av = "*"
py-opencv = "*"
huggingface_hub = "*"
hf-transfer = "*"
tyro = ">=0.9.1,<0.10"
pyserde = ">=0.31.2,<0.32"
# CPU-only PyTorch for lpips metrics (no CUDA requirement).
pytorch-cpu = ">=2.8.0"
torchvision = "*"

[feature.gsplat-rust-renderer.target.linux-64.dependencies]
# gilrs (via re_viewer) links libudev through pkg-config at build time.
libudev = "257.*"
libxkbcommon = "*"
wayland = "*"
xorg-libx11 = "*"
xorg-libxcursor = "*"
xorg-libxi = "*"
xorg-libxinerama = "*"
xorg-libxrandr = "*"
brush = "==0.3.0"

# Same viewer build deps for aarch64; brush (linux-64-only) deliberately absent.
[feature.gsplat-rust-renderer.target.linux-aarch64.dependencies]
libudev = "257.*"
libxkbcommon = "*"
wayland = "*"
xorg-libx11 = "*"
xorg-libxcursor = "*"
xorg-libxi = "*"
xorg-libxinerama = "*"
xorg-libxrandr = "*"

[feature.gsplat-rust-renderer.pypi-dependencies]
gsplat-rust-renderer = { path = "packages/gsplat-rust-renderer", editable = true }
lpips = ">=0.1.4,<1"
plyfile = ">=1.1,<2"
rerun-sdk = "==0.35.0"
simplecv = { path = "packages/simplecv", editable = true }

[feature.gsplat-rust-renderer.activation.env]
PACKAGE_DIR = "packages/gsplat-rust-renderer"
# Make pixi's pkg-config files (libudev.pc) visible to cargo builds.
PKG_CONFIG_PATH = "${CONDA_PREFIX}/lib/pkgconfig"

# ── Download tasks ───────────────────────────────────────────────────────
# nerfbaselines HF data: datasets from nerfbaselines/nerfbaselines-data
# (blender/<scene>.zip), pretrained from nerfbaselines/nerfbaselines
# (3dgs-mcmc/blender/<scene>.zip, INRIA layout). Extraction is idempotent.
[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-data-lego]
cmd = "python -m gsplat_rust_renderer.nerfbaselines data lego"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines lego dataset (nerf-synthetic layout)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-data-hotdog]
cmd = "python -m gsplat_rust_renderer.nerfbaselines data hotdog"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines hotdog dataset (nerf-synthetic layout)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-data-chair]
cmd = "python -m gsplat_rust_renderer.nerfbaselines data chair"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines chair dataset (nerf-synthetic layout)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-data-drums]
cmd = "python -m gsplat_rust_renderer.nerfbaselines data drums"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines drums dataset (nerf-synthetic layout)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-data-ficus]
cmd = "python -m gsplat_rust_renderer.nerfbaselines data ficus"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines ficus dataset (nerf-synthetic layout)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-data-materials]
cmd = "python -m gsplat_rust_renderer.nerfbaselines data materials"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines materials dataset (nerf-synthetic layout)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-data-mic]
cmd = "python -m gsplat_rust_renderer.nerfbaselines data mic"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines mic dataset (nerf-synthetic layout)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-data-ship]
cmd = "python -m gsplat_rust_renderer.nerfbaselines data ship"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines ship dataset (nerf-synthetic layout)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-pretrained-lego]
cmd = "python -m gsplat_rust_renderer.nerfbaselines pretrained lego"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines pretrained lego 3dgs-mcmc model (INRIA-layout PLY)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-pretrained-hotdog]
cmd = "python -m gsplat_rust_renderer.nerfbaselines pretrained hotdog"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines pretrained hotdog 3dgs-mcmc model (INRIA-layout PLY)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-pretrained-chair]
cmd = "python -m gsplat_rust_renderer.nerfbaselines pretrained chair"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines pretrained chair 3dgs-mcmc model (INRIA-layout PLY)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-pretrained-drums]
cmd = "python -m gsplat_rust_renderer.nerfbaselines pretrained drums"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines pretrained drums 3dgs-mcmc model (INRIA-layout PLY)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-pretrained-ficus]
cmd = "python -m gsplat_rust_renderer.nerfbaselines pretrained ficus"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines pretrained ficus 3dgs-mcmc model (INRIA-layout PLY)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-pretrained-materials]
cmd = "python -m gsplat_rust_renderer.nerfbaselines pretrained materials"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines pretrained materials 3dgs-mcmc model (INRIA-layout PLY)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-pretrained-mic]
cmd = "python -m gsplat_rust_renderer.nerfbaselines pretrained mic"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines pretrained mic 3dgs-mcmc model (INRIA-layout PLY)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-pretrained-ship]
cmd = "python -m gsplat_rust_renderer.nerfbaselines pretrained ship"
cwd = "packages/gsplat-rust-renderer"
description = "Download + extract the nerfbaselines pretrained ship 3dgs-mcmc model (INRIA-layout PLY)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-nerfbaselines-all]
depends-on = [
    "_gsplat-rust-renderer-download-nerfbaselines-data-lego",
    "_gsplat-rust-renderer-download-nerfbaselines-data-hotdog",
    "_gsplat-rust-renderer-download-nerfbaselines-data-chair",
    "_gsplat-rust-renderer-download-nerfbaselines-data-drums",
    "_gsplat-rust-renderer-download-nerfbaselines-data-ficus",
    "_gsplat-rust-renderer-download-nerfbaselines-data-materials",
    "_gsplat-rust-renderer-download-nerfbaselines-data-mic",
    "_gsplat-rust-renderer-download-nerfbaselines-data-ship",
    "_gsplat-rust-renderer-download-nerfbaselines-pretrained-lego",
    "_gsplat-rust-renderer-download-nerfbaselines-pretrained-hotdog",
    "_gsplat-rust-renderer-download-nerfbaselines-pretrained-chair",
    "_gsplat-rust-renderer-download-nerfbaselines-pretrained-drums",
    "_gsplat-rust-renderer-download-nerfbaselines-pretrained-ficus",
    "_gsplat-rust-renderer-download-nerfbaselines-pretrained-materials",
    "_gsplat-rust-renderer-download-nerfbaselines-pretrained-mic",
    "_gsplat-rust-renderer-download-nerfbaselines-pretrained-ship",
]
description = "Download + extract all eight nerfbaselines Blender datasets and pretrained checkpoints"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-download-tandt]
cmd = """
test -d data/tandt || \
(mkdir -p data && \
wget -q --show-progress -O data/tandt_db.zip https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/datasets/input/tandt_db.zip && \
unzip -q data/tandt_db.zip -d data && \
rm data/tandt_db.zip)
"""
cwd = "packages/gsplat-rust-renderer"
outputs = ["packages/gsplat-rust-renderer/data/tandt/"]
description = "Download Tanks & Temples + Deep Blending datasets from INRIA"

# ── Brush training tasks ─────────────────────────────────────────────────
[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-install-brush-mac]
cmd = "test -x data/tools/brush-v0.3.0/brush_app || (mkdir -p data/tools/brush-v0.3.0 && curl -fL https://github.com/ArthurBrussee/brush/releases/download/v0.3.0/brush-app-aarch64-apple-darwin.tar.xz -o data/tools/brush-v0.3.0.tar.xz && echo '65b2631398c839be3c1d4d7160fe2326389dec87830aac0710985e6690a1048c  data/tools/brush-v0.3.0.tar.xz' | shasum -a 256 -c - && tar -xJf data/tools/brush-v0.3.0.tar.xz --strip-components=1 -C data/tools/brush-v0.3.0 && rm data/tools/brush-v0.3.0.tar.xz)"
cwd = "packages/gsplat-rust-renderer"
outputs = ["packages/gsplat-rust-renderer/data/tools/brush-v0.3.0/brush_app"]
description = "Install the checksummed official Brush v0.3.0 Apple Silicon binary project-locally"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-build-brush-metrics-mac]
cmd = "test -x data/tools/brush-v0.3.0-metrics/brush_app || (rm -rf data/tools/brush-v0.3.0-metrics-src data/tools/brush-v0.3.0-metrics-target && git clone --depth 1 --branch v0.3.0 https://github.com/ArthurBrussee/brush.git data/tools/brush-v0.3.0-metrics-src && git -C data/tools/brush-v0.3.0-metrics-src rev-parse HEAD | grep -qx 3edecbb2fe79d3e2c87eeab85b15e0b1dd10d486 && git -C data/tools/brush-v0.3.0-metrics-src apply ../../../patches/brush-v0.3.0-cli-loss.patch && CARGO_TARGET_DIR=data/tools/brush-v0.3.0-metrics-target cargo build --release --locked --manifest-path data/tools/brush-v0.3.0-metrics-src/Cargo.toml --package brush-app --bin brush_app && mkdir -p data/tools/brush-v0.3.0-metrics && cp data/tools/brush-v0.3.0-metrics-target/release/brush_app data/tools/brush-v0.3.0-metrics/brush_app && rm -rf data/tools/brush-v0.3.0-metrics-src data/tools/brush-v0.3.0-metrics-target)"
cwd = "packages/gsplat-rust-renderer"
outputs = [
    "packages/gsplat-rust-renderer/data/tools/brush-v0.3.0-metrics/brush_app",
]
description = "Build pinned Brush v0.3.0 locally with pure-CLI loss output (macOS Metal; embedded Rerun remains disabled)"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-brush-train-lego-mac]
cmd = "data/tools/brush-v0.3.0/brush_app data/nerfbaselines/data/lego --total-steps 7000 --export-every 50 --export-path data/brush-runs/lego"
depends-on = [
    "_gsplat-rust-renderer-install-brush-mac",
    "_gsplat-rust-renderer-download-nerfbaselines-data-lego",
]
cwd = "packages/gsplat-rust-renderer"
description = "Train Lego with Brush as a pure trainer and export PLY every 50 iterations (macOS Metal)"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-brush-replay-lego]
cmd = "zsh -c 'rm -rf data/brush-runs/lego && mkdir -p data/brush-runs/lego || exit 1; (RUST_LOG=brush_cli=info,brush_process::train_stream=info data/tools/brush-v0.3.0-metrics/brush_app data/nerfbaselines/data/lego --total-steps 7000 --export-every 50 --export-path data/brush-runs/lego --eval-every 500 --eval-save-to-disk > data/brush-runs/lego/brush.log 2>&1; trainer_status=$?; echo $trainer_status > data/brush-runs/lego/trainer.exit; exit $trainer_status) & trainer_pid=$!; trap \"kill $trainer_pid 2>/dev/null || true\" EXIT; python tools/visualize_brush_training.py --rr-config.application-id brush-training-replay --rr-config.save data/brush-runs/lego/training.rrd --rr-config.headless --scene-dir data/nerfbaselines/data/lego --export-dir data/brush-runs/lego --brush-log data/brush-runs/lego/brush.log --trainer-done-file data/brush-runs/lego/trainer.exit --total-iters 7000 --step-stride 50 --snapshot-stride 20 --sh-mode final --spin-speed 0.2 --eval-views-logged 4 --delete-processed-plys --delete-processed-eval-dirs; replay_status=$?; if test $replay_status -ne 0; then kill $trainer_pid 2>/dev/null || true; wait $trainer_pid 2>/dev/null || true; exit $replay_status; fi; wait $trainer_pid; trainer_status=$?; test $trainer_status -eq 0 && grep -qx 0 data/brush-runs/lego/trainer.exit'"
depends-on = [
    "_gsplat-rust-renderer-build-brush-metrics-mac",
    "_gsplat-rust-renderer-download-nerfbaselines-data-lego",
]
cwd = "packages/gsplat-rust-renderer"
description = "Train Lego for 7k steps while Rerun 0.35.0 replays Brush eval pairs, metrics, cameras, and eight retained snapshots"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-build-viewer]
cmd = "cargo build --release --bin gsplat-rust-renderer"
cwd = "packages/gsplat-rust-renderer"
outputs = ["packages/gsplat-rust-renderer/target/release/gsplat-rust-renderer"]
description = "Build the custom Rerun viewer with the Gaussians3D visualizer"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-brush-replay-lego-live]
cmd = "zsh -c 'rm -rf data/brush-runs/lego-live && mkdir -p data/brush-runs/lego-live || exit 1; (RUST_LOG=brush_cli=info,brush_process::train_stream=info data/tools/brush-v0.3.0-metrics/brush_app data/nerfbaselines/data/lego --total-steps 7000 --export-every 50 --export-path data/brush-runs/lego-live --eval-every 500 --eval-save-to-disk > data/brush-runs/lego-live/brush.log 2>&1; trainer_status=$?; echo $trainer_status > data/brush-runs/lego-live/trainer.exit; exit $trainer_status) & trainer_pid=$!; trap \"kill $trainer_pid 2>/dev/null || true\" EXIT; python tools/visualize_brush_training.py --rr-config.application-id brush-training-live --rr-config.live --rr-config.save data/brush-runs/lego-live/training.rrd --rr-config.executable-path \"$PWD/target/release/gsplat-rust-renderer\" --scene-dir data/nerfbaselines/data/lego --export-dir data/brush-runs/lego-live --brush-log data/brush-runs/lego-live/brush.log --trainer-done-file data/brush-runs/lego-live/trainer.exit --total-iters 7000 --step-stride 50 --snapshot-stride 20 --sh-mode final --spin-speed 0.2 --eval-views-logged 4 --delete-processed-plys --delete-processed-eval-dirs; replay_status=$?; if test $replay_status -ne 0; then kill $trainer_pid 2>/dev/null || true; wait $trainer_pid 2>/dev/null || true; exit $replay_status; fi; wait $trainer_pid; trainer_status=$?; test $trainer_status -eq 0 && grep -qx 0 data/brush-runs/lego-live/trainer.exit'"
depends-on = [
    "_gsplat-rust-renderer-build-brush-metrics-mac",
    "_gsplat-rust-renderer-build-viewer",
    "_gsplat-rust-renderer-download-nerfbaselines-data-lego",
]
cwd = "packages/gsplat-rust-renderer"
description = "Train Lego while the custom headed viewer renders live Gaussians3D splats and saves the RRD"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-brush-video-rrd-lego]
cmd = "zsh -c 'rm -rf data/brush-runs/lego-dense && mkdir -p data/brush-runs/lego-dense || exit 1; (RUST_LOG=brush_cli=info,brush_process::train_stream=info data/tools/brush-v0.3.0-metrics/brush_app data/nerfbaselines/data/lego --total-steps 7000 --export-every 1 --export-path data/brush-runs/lego-dense --eval-every 25 --eval-save-to-disk > data/brush-runs/lego-dense/brush.log 2>&1; trainer_status=$?; echo $trainer_status > data/brush-runs/lego-dense/trainer.exit; exit $trainer_status) & trainer_pid=$!; trap \"kill $trainer_pid 2>/dev/null || true\" EXIT; python tools/visualize_brush_training.py --rr-config.application-id brush-training-video --rr-config.headless --rr-config.save data/brush-runs/lego-dense/training.rrd --scene-dir data/nerfbaselines/data/lego --export-dir data/brush-runs/lego-dense --brush-log data/brush-runs/lego-dense/brush.log --trainer-done-file data/brush-runs/lego-dense/trainer.exit --total-iters 7000 --step-stride 1 --snapshot-stride 1 --sh-mode final --eval-views-logged 4 --delete-processed-plys --delete-processed-eval-dirs --spin-speed 0.2 --video-layout; replay_status=$?; if test $replay_status -ne 0; then kill $trainer_pid 2>/dev/null || true; wait $trainer_pid 2>/dev/null || true; exit $replay_status; fi; wait $trainer_pid; trainer_status=$?; test $trainer_status -eq 0 && grep -qx 0 data/brush-runs/lego-dense/trainer.exit'"
depends-on = [
    "_gsplat-rust-renderer-build-brush-metrics-mac",
    "_gsplat-rust-renderer-download-nerfbaselines-data-lego",
]
cwd = "packages/gsplat-rust-renderer"
description = "Train a dense 7k Lego run and save a flat dark video-layout RRD with one DC-only intermediate snapshot per iteration"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-brush-train-truck]
cmd = """
brush_app data/tandt/truck \
  --total-steps 30000 \
  --export-every 30000 \
  --export-path data/trained \
  --export-name truck.ply
"""
depends-on = ["_gsplat-rust-renderer-download-tandt"]
cwd = "packages/gsplat-rust-renderer"
description = "Train Gaussian splats on truck scene (30K steps)"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-brush-train-train]
cmd = """
brush_app data/tandt/train \
  --total-steps 30000 \
  --export-every 30000 \
  --export-path data/trained \
  --export-name train.ply
"""
depends-on = ["_gsplat-rust-renderer-download-tandt"]
cwd = "packages/gsplat-rust-renderer"
description = "Train Gaussian splats on train scene (30K steps)"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-brush-train-lego]
cmd = """
brush_app data/nerfbaselines/data/lego \
  --total-steps 30000 \
  --export-every 30000 \
  --export-path data/trained \
  --export-name lego.ply
"""
depends-on = ["_gsplat-rust-renderer-download-nerfbaselines-data-lego"]
cwd = "packages/gsplat-rust-renderer"
description = "Train Gaussian splats on nerfbaselines lego scene (30K steps)"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-brush-train-hotdog]
cmd = """
brush_app data/nerfbaselines/data/hotdog \
  --total-steps 30000 \
  --export-every 30000 \
  --export-path data/trained \
  --export-name hotdog.ply
"""
depends-on = ["_gsplat-rust-renderer-download-nerfbaselines-data-hotdog"]
cwd = "packages/gsplat-rust-renderer"
description = "Train Gaussian splats on nerfbaselines hotdog scene (30K steps)"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-brush-train-chair]
cmd = """
brush_app data/nerfbaselines/data/chair \
  --total-steps 30000 \
  --export-every 30000 \
  --export-path data/trained \
  --export-name chair.ply
"""
depends-on = ["_gsplat-rust-renderer-download-nerfbaselines-data-chair"]
cwd = "packages/gsplat-rust-renderer"
description = "Train Gaussian splats on nerfbaselines chair scene (30K steps)"

# ── Standalone render CLI ────────────────────────────────────────────────
[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-render]
cmd = "cargo run --release --no-default-features --bin gsplat-render --"
cwd = "packages/gsplat-rust-renderer"
description = "Render a PLY at a NeRF camera position to PNG (no Rerun needed)"

[feature.gsplat-rust-renderer.tasks._gsplat-rust-renderer-build-render]
cmd = "cargo build --release --no-default-features --bin gsplat-render"
cwd = "packages/gsplat-rust-renderer"
description = "Build the standalone no-Rerun renderer"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-evaluate-checkpoints]
cmd = "python tools/evaluate_nerfbaselines.py --checkpoint-only"
depends-on = ["_gsplat-rust-renderer-download-nerfbaselines-all"]
cwd = "packages/gsplat-rust-renderer"
description = "Validate all bundled 200-image checkpoint predictions against published metrics"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-evaluate]
cmd = "python tools/evaluate_nerfbaselines.py"
depends-on = [
    "_gsplat-rust-renderer-download-nerfbaselines-all",
    "_gsplat-rust-renderer-build-render",
]
cwd = "packages/gsplat-rust-renderer"
description = "Render and evaluate all eight 200-image Blender test splits with the standalone binary"

# ── Rust tasks ───────────────────────────────────────────────────────────
[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-viewer]
cmd = "cargo run --release --bin gsplat-rust-renderer"
cwd = "packages/gsplat-rust-renderer"
description = "Launch the Rerun viewer with Gaussian splat visualization"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-fmt]
cmd = "cargo fmt --all"
cwd = "packages/gsplat-rust-renderer"
description = "Format Rust code"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-clippy]
cmd = "cargo clippy --all-targets -- -D warnings"
cwd = "packages/gsplat-rust-renderer"
description = "Run clippy on Rust code"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-rust-test]
cmd = "cargo test"
cwd = "packages/gsplat-rust-renderer"
description = "Run Rust test suite"

# ── Python demo tasks ────────────────────────────────────────────────────
[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-log-ply]
cmd = "python tools/log_gaussian_ply.py --rr-config.connect --rr-config.application-id gsplat-rust-renderer"
depends-on = ["_gsplat-rust-renderer-download-nerfbaselines-pretrained-lego"]
cwd = "packages/gsplat-rust-renderer"
description = "Load the pretrained lego PLY and log it to the running viewer"

[feature.gsplat-rust-renderer.tasks.gsplat-rust-renderer-log-scene]
cmd = "python tools/log_splats_with_cameras.py --rr-config.connect --rr-config.application-id gsplat-rust-renderer"
depends-on = [
    "_gsplat-rust-renderer-download-nerfbaselines-pretrained-lego",
    "_gsplat-rust-renderer-download-nerfbaselines-data-lego",
]
cwd = "packages/gsplat-rust-renderer"
description = "Log the pretrained lego splat + dataset cameras to the running viewer"

# ═══════════════════════════════════════════════════════════════════════════
# dpvo
# ═══════════════════════════════════════════════════════════════════════════
[feature.dpvo]
channels = ["https://prefix.dev/ai-demos", "https://prefix.dev/conda-forge"]
platforms = ["linux-64"]

[feature.dpvo.dependencies]
python = "3.11.*"
dpretrieval = { path = "packages/dpretrieval" }
eigen = ">=3.4.0,<3.5"
einops = ">=0.8.0,<0.9"
matplotlib = ">=3.8.4,<3.9"
icecream = ">=2.1.3,<2.2"
lietorch = ">=0.3.0"
numba = ">=0.60.0"
plyfile = ">=1.0.3,<1.1"
tyro = ">=0.9.1,<0.10"
ninja = ">=1.13.2,<2"

[feature.dpvo.pypi-dependencies]
dpvo = { path = "packages/dpvo", editable = true }
mini-dust3r = ">=0.1.1,<0.2"
evo = ">=1.28.0"
kornia = ">=0.7.0"
pypose = ">=0.6.0"
yacs = ">=0.1.8"
opencv-python = ">=4.9.0.80"
spaces = ">=0.32.0"

[feature.dpvo.activation.env]
PACKAGE_DIR = "packages/dpvo"

# ── Download tasks (hidden, used as depends-on) ─────────────────────────
[feature.dpvo.tasks._download-dpvo-model]
cmd = "hf download pablovela5620/dpvo dpvo.pth --repo-type model --local-dir checkpoints/"
cwd = "packages/dpvo"
outputs = ["packages/dpvo/checkpoints/dpvo.pth"]
description = "Download DPVO model checkpoint"

[feature.dpvo.tasks._download-dpvo-data]
cmd = "bash -lc 'hf download pablovela5620/dpvo-example-data movies.zip --repo-type dataset --local-dir . && unzip -o movies.zip -d data/ && rm -f movies.zip && if [ -d data/data/movies ]; then rm -rf data/movies && mv data/data/movies data/movies && rmdir data/data 2>/dev/null || true; fi'"
cwd = "packages/dpvo"
outputs = ["packages/dpvo/data/movies/IMG_0493.MOV"]
description = "Download DPVO example video data"

[feature.dpvo.tasks._download-dpvo-iphone-data]
cmd = "hf download pablovela5620/dpvo-example-data pool.MOV --repo-type dataset --local-dir data/iphone/"
cwd = "packages/dpvo"
outputs = ["packages/dpvo/data/iphone/pool.MOV"]
description = "Download DPVO iPhone example data"

# ── Build tasks ──────────────────────────────────────────────────────────
[feature.dpvo.tasks._build-dpvo-cuda-kernels]
cmd = "python setup.py build_ext --inplace"
cwd = "packages/dpvo"
description = "Build DPVO CUDA extensions (cuda_corr, cuda_ba)"
inputs = [
    "packages/dpvo/setup.py",
    "packages/dpvo/dpvo/altcorr/*.cpp",
    "packages/dpvo/dpvo/altcorr/*.cu",
    "packages/dpvo/dpvo/fastba/*.cpp",
    "packages/dpvo/dpvo/fastba/*.cu",
]
outputs = [
    "packages/dpvo/dpvo/_cuda_corr*.so",
    "packages/dpvo/dpvo/_cuda_ba*.so",
]

[feature.dpvo.tasks._dpvo-download-orb-vocab]
cmd = "bash -lc 'if [ ! -f ORBvoc.txt ]; then curl -L https://github.com/UZ-SLAMLab/ORB_SLAM3/raw/master/Vocabulary/ORBvoc.txt.tar.gz | tar xz; fi'"
cwd = "packages/dpvo"
outputs = ["packages/dpvo/ORBvoc.txt"]
description = "Download ORB vocabulary for DBoW2 loop closure"

# ── EuRoC evaluation tasks ───────────────────────────────────────────────
[feature.dpvo.tasks._dpvo-download-euroc]
cmd = "python -c \"from dpvo.api.euroc import download_euroc; download_euroc()\""
cwd = "packages/dpvo"
description = "Download EuRoC MH_01-MH_05 sequences (~2GB each)"

[feature.dpvo.tasks.dpvo-eval-euroc]
cmd = "python tools/eval_euroc.py --modes vo slam --stride 2 --trials 1"
depends-on = [
    "_build-dpvo-cuda-kernels",
    "_download-dpvo-model",
    "_dpvo-download-euroc",
]
cwd = "packages/dpvo"
description = "Evaluate DPV-SLAM on EuRoC MH sequences (VO + SLAM)"

# ── Demo tasks ───────────────────────────────────────────────────────────
[feature.dpvo.tasks.dpvo-demo]
cmd = "python tools/demo.py --imagedir data/movies/IMG_0493.MOV"
depends-on = [
    "_build-dpvo-cuda-kernels",
    "_download-dpvo-model",
    "_download-dpvo-data",
]
cwd = "packages/dpvo"
description = "Run DPVO demo on example video"

# ── App tasks ────────────────────────────────────────────────────────────
[feature.dpvo.tasks.dpvo-app]
cmd = "python tools/gradio_app.py"
depends-on = [
    "_build-dpvo-cuda-kernels",
    "_download-dpvo-model",
    "_download-dpvo-data",
    "_download-dpvo-iphone-data",
]
cwd = "packages/dpvo"
description = "Launch DPVO Gradio web UI"

# ─── slam-evals feature (VSLAM-LAB benchmark → Rerun catalog ingester) ──────
[feature.slam-evals]
platforms = ["linux-64", "linux-aarch64"]

[feature.slam-evals.dependencies]
python = "3.10.*"
pyyaml = "*"
pyarrow = ">=20.0.0,<21"
tqdm = "*"
pandas = "*"

[feature.slam-evals.pypi-dependencies]
slam-evals = { path = "packages/slam-evals", editable = true }
tyro = ">=0.9,<1"

[feature.slam-evals.activation.env]
PACKAGE_DIR = "packages/slam-evals"
VSLAM_LAB_BENCHMARK = "/home/pablo/0Dev/work/VSLAM-LAB-Benchmark"

[feature.slam-evals.tasks.slam-evals-ingest]
cmd = "python tools/ingest.py --benchmark-root $VSLAM_LAB_BENCHMARK --out ../../data/slam-evals/rrd"
cwd = "packages/slam-evals"
description = "Discover + ingest every sequence under $VSLAM_LAB_BENCHMARK into per-layer RRDs"

[feature.slam-evals.tasks.slam-evals-catalog]
cmd = "python tools/catalog.py --rrd-dir ../../data/slam-evals/rrd"
cwd = "packages/slam-evals"
description = "Mount the RRD directory as a Rerun catalog and print the segment summary"

[feature.slam-evals.tasks.slam-evals-refresh]
cmd = "python tools/catalog.py --refresh --rrd-dir ../../data/slam-evals/rrd"
cwd = "packages/slam-evals"
description = "Push edited layer files into the running catalog (append --datasets / --layers / --only filters; defaults to all)"

# ═══════════════════════════════════════════════════════════════════════════
# mamma — streaming multiview body capture (causal MAMMA pipeline)
# ═══════════════════════════════════════════════════════════════════════════
[feature.mamma]
platforms = ["linux-64"]

[feature.mamma.dependencies]
python = "3.12.*"
# The MAMMA MPI download server only talks to wget (rejects python TLS clients).
wget = "*"
onnx = "*"
onnxscript = "*"
einops = ">=0.8.0,<0.9"
tyro = ">=0.9.1,<0.10"
torchcodec = "*"
pyyaml = "*"
natsort = ">=8.4.0,<9"

[feature.mamma.pypi-dependencies]
mamma = { path = "packages/mamma", editable = true }
posekit = { path = "packages/posekit", editable = true }
trtkit = { path = "packages/trtkit", editable = true }
# Vendored sam2 fork with static metadata — see packages/sam2-streaming/VENDOR.md.
sam2 = { path = "packages/sam2-streaming", editable = true }

[feature.mamma.activation.env]
PACKAGE_DIR = "packages/mamma"

[feature.mamma.tasks._download-mamma-inputs]
cmd = "test -e data/inputs/indoors/crossing_arms/meta/global.npz || hf download pablovela5620/mamma-streaming-data --repo-type dataset --include 'inputs/**' 'golden/**' 'body_models/**' --local-dir data/"
cwd = "packages/mamma"
outputs = ["packages/mamma/data/inputs/indoors/crossing_arms/meta/global.npz"]
description = "Download crossing_arms inputs + slim golden + body models (private HF repo)"

[feature.mamma.tasks._download-mamma-weights]
cmd = "test -e data/weights/ma_2d/mamma_mask_full_cvpr.safetensors || hf download pablovela5620/mamma-streaming-data --repo-type dataset --include 'weights/**' --local-dir data/"
cwd = "packages/mamma"
outputs = ["packages/mamma/data/weights/ma_2d/mamma_mask_full_cvpr.safetensors"]
description = "Download MammaNet/YOLO/SAM2/EfficientTAM weights (private HF repo)"

[feature.mamma.tasks._download-mamma-hocap-sample]
cmd = "test -e data/hocap/sample || (mkdir -p data/hocap/ && hf download pablovela5620/hocap-sample sample.zip --repo-type dataset --local-dir data/hocap/ && python -m zipfile -e data/hocap/sample.zip data/hocap/)"
cwd = "packages/mamma"
outputs = ["packages/mamma/data/hocap/sample"]
description = "Download and extract the HoCap sample dataset"

[feature.mamma.tasks._download-mamma-assembly101-sample]
cmd = "test -e data/assembly101-720-sample || hf download pablovela5620/Assembly101-Sample --repo-type dataset --include 'assembly101-720-sample/**' --local-dir data/"
cwd = "packages/mamma"
outputs = ["packages/mamma/data/assembly101-720-sample"]
description = "Download the Assembly101 720p sample dataset"

[feature.mamma.tasks.mamma-download-dataset]
cmd = "python tools/download_dataset.py"
cwd = "packages/mamma"

[feature.mamma.tasks.mamma-demo-crossing-arms]
cmd = "python tools/demo_crossing_arms.py --tracker.expected-subjects 1"
depends-on = ["_download-mamma-inputs", "_download-mamma-weights"]
cwd = "packages/mamma"
description = "Streaming pipeline on crossing_arms (4x 4K cams), live Rerun viewer"

[feature.mamma.tasks._download-mamma-body-models]
cmd = "test -e data/body_models/smplx || hf download pablovela5620/mamma-streaming-data --repo-type dataset --include 'body_models/**' --local-dir data/"
cwd = "packages/mamma"
outputs = ["packages/mamma/data/body_models/smplx"]
description = "Download SMPL-X body models + downsampled verts (private HF repo)"

[feature.mamma.tasks.mamma-demo-hocap]
cmd = "python tools/demo_hocap.py"
depends-on = [
    "_download-mamma-hocap-sample",
    "_download-mamma-weights",
    "_download-mamma-body-models",
]
cwd = "packages/mamma"
description = "Streaming pipeline on the HoCap sample (ingestion + visual check)"

[feature.mamma.tasks.mamma-demo-assembly101]
cmd = "python tools/demo_assembly101.py"
depends-on = [
    "_download-mamma-assembly101-sample",
    "_download-mamma-weights",
    "_download-mamma-body-models",
]
cwd = "packages/mamma"
description = "Streaming pipeline on the Assembly101 720p sample (ingestion + visual check)"

[feature.mamma.tasks.mamma-validate-golden]
cmd = "python tools/validate_golden.py --rr-config.headless"
depends-on = ["_download-mamma-inputs", "_download-mamma-weights"]
cwd = "packages/mamma"
description = "Run streaming pipeline on crossing_arms frames 60:90 and gate MPJPE/PVE vs golden ma_3d"

[feature.mamma.tasks.mamma-benchmark]
cmd = "python tools/benchmark.py"
depends-on = ["_download-mamma-inputs", "_download-mamma-weights"]
cwd = "packages/mamma"
description = "Timed full-clip run: PASS if wall <= 2x clip duration (>=50% realtime) after warmup incl. Rerun logging"

[feature.mamma.tasks.mamma-goal-check]
cmd = "python tools/goal_check.py"
depends-on = [
    "_download-mamma-inputs",
    "_download-mamma-weights",
    "_download-mamma-hocap-sample",
    "_download-mamma-assembly101-sample",
]
cwd = "packages/mamma"
description = "Aggregate goal verification: golden gate, 30fps benchmark, dataset RRDs, no-disk-writes, hygiene"

# iPhone catalog pipeline, in order: sweep → serve (own shell, keep running) → register.
[feature.mamma.tasks.mamma-iphones-sweep]
cmd = "python tools/sweep_iphones_quality.py --subset all"
depends-on = ["_download-mamma-weights"]
cwd = "packages/mamma"
description = "Step 1: run the quality preset on all 42 iPhone scenes -> quality.rrd + gate.json per scene (GPU)"

[feature.mamma.tasks.mamma-iphones-serve]
cmd = "rerun server --port 51234"
cwd = "packages/mamma"
description = "Step 2: start the local in-memory Rerun catalog on :51234 (run in its own shell; keep running to register/view)"

[feature.mamma.tasks.mamma-iphones-register]
cmd = "python tools/register_catalog.py"
cwd = "packages/mamma"
description = "Step 3: register the 42 RRDs into the mamma_iphones catalog (base+props layers, names/properties from gate.json, default blueprint); needs mamma-iphones-serve running"

# ═══════════════════════════════════════════════════════════════════════════
# mvs — multiview stereo depth + live meshing
# ═══════════════════════════════════════════════════════════════════════════
[feature.mvs]
platforms = ["linux-64-cuda13", "linux-aarch64-cuda13"]

[feature.mvs.dependencies]
python = "3.12.*"
einops = ">=0.8,<0.9"
kornia = ">=0.8,<0.9"
timm = ">=1.0,<2"
tyro = "*"
# NVDEC decode of catalog AV1 samples (cuda130 builds exist; torch pin comes from `cuda`).
torchcodec = ">=0.14,<0.15"

[feature.mvs.pypi-dependencies]
mvs = { path = "packages/mvs", editable = true }
trtkit = { path = "packages/trtkit", editable = true }

[feature.mvs.activation.env]
PACKAGE_DIR = "packages/mvs"

[feature.mvs.tasks.mvs-live-mesh]
cmd = "python tools/apps/live_mesh.py"
cwd = "packages/mvs"
description = "Stream catalog AV1 segments through NVDEC and log the frames to Rerun"

[feature.mvs.tasks.mvs-download-depth-model]
cmd = "hf download pablovela5620/mvs-depth depth_model_dot.onnx --local-dir data/models"
cwd = "packages/mvs"
description = "Download the ONNX multiview depth model"

[feature.mvs.tasks.mvs-catalog-depth]
cmd = "python tools/demos/catalog_depth.py"
cwd = "packages/mvs"
depends-on = ["mvs-download-depth-model"]
description = "Predict metric depth for catalog segments and log it to Rerun"


# ─── arkitscenes-download (ARKitScenes → layered Rerun recordings) ──────────
# linux-64 only: the video transcode prefers av1_nvenc with a libsvtav1 CPU fallback.
[feature.arkitscenes-download]
platforms = ["linux-64"]

[feature.arkitscenes-download.dependencies]
python = "3.12.*"
ffmpeg = ">=8.1"
imagecodecs = ">=2024.9.22"
trimesh = "*"
pillow = "*"
curl = "*"
rich = "*"

[feature.arkitscenes-download.pypi-dependencies]
arkitscenes-download = { path = "packages/arkitscenes-download", editable = true }
tyro = ">=0.9,<1"
modal = ">=1.0"

[feature.arkitscenes-download.activation.env]
PACKAGE_DIR = "packages/arkitscenes-download"
# Modal's decorated-function stubs (ParamSpec) and the container-only boto3
# import are unavoidable false positives; baseline them.
PYREFLY_EXTRA_ARGS = "--baseline pyrefly-baseline.json"

[feature.arkitscenes-download.tasks.arkitscenes-download-sample]
cmd = "python tools/apps/download.py --download-dir data --num-random 5 --seed 42 --no-include-point-clouds"
cwd = "packages/arkitscenes-download"
description = "Download a 5-sequence ARKitScenes sample (mov + depth + calibration, no point clouds)"

[feature.arkitscenes-download.tasks.arkitscenes-download-ingest]
cmd = "python tools/apps/ingest_batch.py --workers 2"
cwd = "packages/arkitscenes-download"
depends-on = ["arkitscenes-download-sample"]
description = "Ingest every downloaded sequence into layered .rrd files under data/rrd/"

[feature.arkitscenes-download.tasks.arkitscenes-download-ca1m]
cmd = "python tools/apps/ca1m_ingest.py"
cwd = "packages/arkitscenes-download"
description = "Ingest CA-1M laser GT into stackable gt_poses and gt_depth layer RRDs"

[feature.arkitscenes-download.tasks.arkitscenes-download-gt-subdataset]
cmd = "python tools/apps/make_gt_subdataset.py"
cwd = "packages/arkitscenes-download"
description = "Create the GT-clean sub-dataset (laser GT present, bounded interior gaps) on the local catalog"

[feature.arkitscenes-download.tasks.arkitscenes-download-serve]
# Rerun keeps one handle open per registered RRD. One full corpus has
# 5015 segments * 8 layers = 40120 RRDs, so 65536 cannot hold two corpora.
cmd = "bash -c 'ulimit -n 524288 && exec rerun server --port 51235'"
cwd = "packages/arkitscenes-download"
description = "Serve a Rerun catalog for registered ARKitScenes recordings"

[feature.arkitscenes-download.tasks.arkitscenes-download-register]
cmd = "python tools/apps/register_catalog.py --rrd-dir data/rrd"
cwd = "packages/arkitscenes-download"
env = { RERUN_INSECURE_SKIP_HOST_CHECK = "1" }
description = "Register ingested layer .rrds into the catalog on :51235"

[feature.arkitscenes-download.tasks.arkitscenes-download-view]
cmd = "rerun rerun+http://127.0.0.1:51235"
cwd = "packages/arkitscenes-download"
description = "Open the native Rerun viewer on the local catalog"

# ═══════════════════════════════════════════════════════════════════════════
# gauss-surf — GausSurf splat pipeline over ARKitScenes catalog segments
# ═══════════════════════════════════════════════════════════════════════════
# Signals/catalog lane: reads the segment through the 0.36 prerelease
# dataloader, derives frame selection / normals / ultrawide depth, writes
# layer RRDs back. Explicit platforms required — see AGENTS.md.
[feature.gauss-surf]
platforms = ["linux-64"]

[feature.gauss-surf.dependencies]
# Pinned to match the pyrefly site-package-path registration (python3.12).
python = "3.12.*"
# Open3D RaycastingScene renders ultrawide depth from the PromptDA TSDF mesh.
open3d = ">=0.19.0,<0.20"
imagecodecs = ">=2024.9.22"
# arkitscenes_download.ingest imports these at package load.
trimesh = "*"
pillow = "*"
av = ">=18"
# simplecv's SegmentNvdecDecoder decodes the segment's AV1 packets on NVDEC.
torchcodec = "*"
# ffmpeg <902 links libjxl 0.11 and dlopen-fails beside the env's 0.12.
ffmpeg = { version = ">=8.1", build-number = ">=902" }
einops = "*"
# gsplat's source build (git pin below) needs ninja; nvcc comes from the cuda feature.
ninja = "*"
# Direct gsplat seed initialization uses sklearn's three-neighbor search.
scikit-learn = "*"
# Direct holdout evaluation computes SSIM through torchmetrics.
torchmetrics = "*"

[feature.gauss-surf.pypi-dependencies]
gauss-surf = { path = "packages/gauss-surf", editable = true }
arkitscenes-download = { path = "packages/arkitscenes-download", editable = true }
monopriors = { path = "packages/monoprior", editable = true }
trtkit = { path = "packages/trtkit", editable = true }
plyfile = ">=1.1,<2"
# Part 8 (gsplat port): v1.6.0 release commit, pinned as git until the PyPI sdist
# lands (then: bump the ai-demos conda recipe and drop this pin + no-build-isolation).
# Builds ~50 CUDA TUs at install time — run installs with
# TORCH_CUDA_ARCH_LIST="8.6;12.0+PTX" (not captured by the lock). uv fetches the
# glm submodule (verified 2026-08-15).
gsplat = { git = "https://github.com/nerfstudio-project/gsplat", rev = "c3d59bbb54f91d1c93f1a80dc86960c696b4a059" }

[feature.gauss-surf.pypi-options]
# gsplat's build requires torch: isolation would compile against a second,
# wrong-CUDA torch. Build against the env's conda pytorch instead.
no-build-isolation = ["gsplat"]

[feature.gauss-surf.pypi-options.dependency-overrides]
# Resolve monopriors' sam3>=0.1.0 requirement to the repository implementation.
sam3 = { path = "packages/sam3", editable = true }

[feature.gauss-surf.activation.env]
PACKAGE_DIR = "packages/gauss-surf"
PYREFLY_TARGET = "src/gauss_surf/apis src/gauss_surf/train_gsplat src/gauss_surf/catalog.py src/gauss_surf/frame_selection.py src/gauss_surf/gaussurf_geometry.py src/gauss_surf/gaussurf_losses.py src/gauss_surf/gsplat_schedule.py src/gauss_surf/normals_encoding.py src/gauss_surf/render_io.py src/gauss_surf/uw_geometry.py src/gauss_surf/__init__.py tools"

[feature.gauss-surf.tasks.gauss-surf-serve]
cmd = "bash -c 'ulimit -n 524288 && exec rerun server --port 51236'"
cwd = "packages/gauss-surf"
description = "Serve the dedicated gauss-surf development catalog on :51236"

[feature.gauss-surf.tasks.gauss-surf-frame-selection]
cmd = "python tools/apps/frame_selection.py"
cwd = "packages/gauss-surf"
env = { RERUN_INSECURE_SKIP_HOST_CHECK = "1" }
description = "Score and register the frame-selection layer for one ARKitScenes segment"

[feature.gauss-surf.tasks.gauss-surf-moge-normals]
cmd = "python tools/apps/moge_normals.py"
cwd = "packages/gauss-surf"
env = { RERUN_INSECURE_SKIP_HOST_CHECK = "1" }
description = "Infer and register MoGe v2 normals for chosen ARKitScenes wide frames"

[feature.gauss-surf.tasks.gauss-surf-ultrawide-signals]
cmd = "python tools/apps/ultrawide_signals.py"
cwd = "packages/gauss-surf"
env = { RERUN_INSECURE_SKIP_HOST_CHECK = "1" }
description = "Rectify chosen ultrawide frames and register mesh depth plus MoGe normal layers"

[feature.gauss-surf.tasks.gauss-surf-register-segment]
cmd = "python tools/apps/register_segment.py"
cwd = "packages/gauss-surf"
env = { RERUN_INSECURE_SKIP_HOST_CHECK = "1" }
description = "Reseed one ARKitScenes segment and the v2 blueprints on the development catalog"

[feature.gauss-surf.tasks.gauss-surf-train-gsplat]
cmd = "python tools/apps/train_gsplat.py"
cwd = "packages/gauss-surf"
env = { RERUN_INSECURE_SKIP_HOST_CHECK = "1" }
description = "Train the direct gsplat recipe and fused-publish all three splat layers"

[tasks.gauss-surf-segment-pipeline]
args = ["video_id", "dataset_name", "timestamp"]
depends-on = [
    { task = "gauss-surf-frame-selection", environment = "gauss-surf", args = ["--video-id", "{{ video_id }}", "--dataset-name", "{{ dataset_name }}"] },
    { task = "gauss-surf-moge-normals", environment = "gauss-surf", args = ["--video-id", "{{ video_id }}", "--dataset-name", "{{ dataset_name }}"] },
    { task = "gauss-surf-ultrawide-signals", environment = "gauss-surf", args = ["--video-id", "{{ video_id }}", "--dataset-name", "{{ dataset_name }}"] },
    { task = "gauss-surf-train-gsplat", environment = "gauss-surf", args = ["--video-id", "{{ video_id }}", "--dataset-name", "{{ dataset_name }}", "--timestamp", "{{ timestamp }}"] },
]
description = "Run signal preparation, two-call gsplat training, and fused in-process publication"

# ════════════════════════════════════════════════════════════════════════════
# pose-app — unified SAM3 + 2D pose Gradio playground
# ════════════════════════════════════════════════════════════════════════════
[feature.pose-app]
platforms = ["linux-64"]

[feature.pose-app.activation.env]
# This PACKAGE_DIR must win over posekit/mamma's bindings through feature order.
PACKAGE_DIR = "packages/posekit"

[feature.pose-app.tasks.pose-app]
cmd = "python tools/apps/gradio_app.py"
cwd = "packages/posekit"
description = "Launch the unified SAM3 + 2D pose Gradio playground"

# ═══════════════════════════════════════════════════════════════════════════
# dataforge
# ═══════════════════════════════════════════════════════════════════════════
# Explicit platforms required — see AGENTS.md "Platforms & lockfile".
[feature.dataforge]
platforms = ["linux-64", "linux-aarch64"]

[feature.dataforge.dependencies]
python = "3.12.*"
tyro = ">=0.9.1,<0.10"
# CPU torch only satisfies simplecv's module-load import.
pytorch-cpu = ">=2.8.0"

[feature.dataforge.pypi-dependencies]
dataforge = { path = "packages/dataforge", editable = true }

[feature.dataforge.activation.env]
PACKAGE_DIR = "packages/dataforge"

# ═══════════════════════════════════════════════════════════════════════════
# Environments
# ═══════════════════════════════════════════════════════════════════════════
[environments]
arkitscenes-download = { features = [
    "common",
    "arkitscenes-download",
], solve-group = "arkitscenes-download", no-default-feature = true }
arkitscenes-download-dev = { features = [
    "common",
    "arkitscenes-download",
    "dev",
], solve-group = "arkitscenes-download", no-default-feature = true }
dev = { features = [
    "ide",
    "dev",
    "common",
], solve-group = "dev", no-default-feature = true }
simplecv = { features = [
    "common",
    "cuda",
    "simplecv",
], solve-group = "simplecv", no-default-feature = true }
simplecv-dev = { features = [
    "common",
    "cuda",
    "simplecv",
    "dev",
], solve-group = "simplecv", no-default-feature = true }
# Catalog-lane envs use catalog-common (rerun-pin-free) so rerun-prerelease's pin wins.
simplecv-catalog = { features = [
    "catalog-common",
    "rerun-prerelease",
    "cuda",
    "simplecv",
], solve-group = "simplecv-catalog", no-default-feature = true }
simplecv-catalog-dev = { features = [
    "catalog-common",
    "rerun-prerelease",
    "cuda",
    "simplecv",
    "dev",
], solve-group = "simplecv-catalog", no-default-feature = true }
monoprior = { features = [
    "common",
    "cuda",
    "monoprior",
], solve-group = "monoprior", no-default-feature = true }
monoprior-dev = { features = [
    "common",
    "cuda",
    "monoprior",
    "dev",
], solve-group = "monoprior", no-default-feature = true }
prompt-da = { features = [
    "common",
    "cuda",
    "prompt-da",
    "prompt-da-demo",
], solve-group = "prompt-da", no-default-feature = true }
prompt-da-dev = { features = [
    "common",
    "cuda",
    "prompt-da",
    "dev",
], solve-group = "prompt-da", no-default-feature = true }
# Catalog-lane env: catalog-common (rerun-pin-free) so rerun-prerelease's pin wins.
prompt-da-stream = { features = [
    "catalog-common",
    "rerun-prerelease",
    "cuda",
    "prompt-da",
    "prompt-da-stream",
], solve-group = "prompt-da-stream", no-default-feature = true }
prompt-da-stream-dev = { features = [
    "catalog-common",
    "rerun-prerelease",
    "cuda",
    "prompt-da",
    "prompt-da-stream",
    "dev",
], solve-group = "prompt-da-stream", no-default-feature = true }
wilor-nano = { features = [
    "common",
    "cuda",
    "wilor-nano",
], solve-group = "wilor-nano", no-default-feature = true }
wilor-nano-dev = { features = [
    "common",
    "cuda",
    "wilor-nano",
    "dev",
], solve-group = "wilor-nano", no-default-feature = true }
sam3d-body = { features = [
    "common",
    "cuda",
    "sam3d-body",
], solve-group = "sam3d-body", no-default-feature = true }
sam3d-body-dev = { features = [
    "common",
    "cuda",
    "sam3d-body",
    "dev",
], solve-group = "sam3d-body", no-default-feature = true }
sam3 = { features = [
    "common",
    "cuda",
    "sam3",
], solve-group = "sam3", no-default-feature = true }
sam3-dev = { features = [
    "common",
    "cuda",
    "sam3",
    "dev",
], solve-group = "sam3", no-default-feature = true }
sapiens2-pose = { features = [
    "common",
    "cuda",
    "sapiens2-pose",
], solve-group = "sapiens2-pose", no-default-feature = true }
sapiens2-pose-dev = { features = [
    "common",
    "cuda",
    "sapiens2-pose",
    "dev",
], solve-group = "sapiens2-pose", no-default-feature = true }
sapiens-coco133-pose = { features = [
    "common",
    "cuda",
    "sapiens-coco133-pose",
], solve-group = "sapiens-coco133-pose", no-default-feature = true }
sapiens-coco133-pose-dev = { features = [
    "common",
    "cuda",
    "sapiens-coco133-pose",
    "dev",
], solve-group = "sapiens-coco133-pose", no-default-feature = true }
trtkit = { features = [
    "common",
    "cuda",
    "trtkit",
], solve-group = "trtkit", no-default-feature = true }
trtkit-dev = { features = [
    "common",
    "cuda",
    "trtkit",
    "dev",
], solve-group = "trtkit", no-default-feature = true }
pose-app = { features = [
    "common",
    "cuda",
    "posekit",
    "mamma",
    "pose-app",
], solve-group = "pose-app", no-default-feature = true }
pose-app-dev = { features = [
    "common",
    "cuda",
    "posekit",
    "mamma",
    "pose-app",
    "dev",
], solve-group = "pose-app", no-default-feature = true }
posekit = { features = [
    "common",
    "cuda",
    "posekit",
], solve-group = "posekit", no-default-feature = true }
posekit-dev = { features = [
    "common",
    "cuda",
    "posekit",
    "dev",
], solve-group = "posekit", no-default-feature = true }
robocap-slam = { features = [
    "common",
    "robocap-slam",
], solve-group = "robocap-slam", no-default-feature = true }
robocap-slam-dev = { features = [
    "common",
    "robocap-slam",
    "dev",
], solve-group = "robocap-slam", no-default-feature = true }
# pysfm runs on the conda CPU pycolmap build — see the feature.pysfm note.
pysfm = { features = [
    "common",
    "cuda",
    "pysfm",
], solve-group = "pysfm", no-default-feature = true }
pysfm-dev = { features = [
    "common",
    "cuda",
    "pysfm",
    "dev",
], solve-group = "pysfm", no-default-feature = true }
vistadream = { features = [
    "common",
    "cuda",
    "vistadream",
], solve-group = "vistadream", no-default-feature = true }
vistadream-dev = { features = [
    "common",
    "cuda",
    "vistadream",
    "dev",
], solve-group = "vistadream", no-default-feature = true }
pyvrs-viewer = { features = [
    "common",
    "pyvrs-viewer",
    "pyvrs-viewer-demo",
], solve-group = "pyvrs-viewer", no-default-feature = true }
pyvrs-viewer-dev = { features = [
    "common",
    "pyvrs-viewer",
    "dev",
], solve-group = "pyvrs-viewer", no-default-feature = true }
live-rerun = { features = [
    "common",
    "live-rerun",
    "live-rerun-demo",
], solve-group = "live-rerun", no-default-feature = true }
live-rerun-dev = { features = [
    "common",
    "live-rerun",
    "dev",
], solve-group = "live-rerun", no-default-feature = true }
egoexo-forge = { features = [
    "common",
    "cuda",
    "egoexo-forge",
    "egoexo-forge-demo",
], solve-group = "egoexo-forge", no-default-feature = true }
egoexo-forge-dev = { features = [
    "common",
    "cuda",
    "egoexo-forge",
    "dev",
], solve-group = "egoexo-forge", no-default-feature = true }
mv-api = { features = [
    "common",
    "cuda",
    "mv-api",
], solve-group = "mv-api", no-default-feature = true }
mv-api-dev = { features = [
    "common",
    "cuda",
    "mv-api",
    "dev",
], solve-group = "mv-api", no-default-feature = true }
mv-api-catalog = { features = [
    "catalog-common",
    "rerun-prerelease",
    "cuda",
    "mv-api",
    "mv-api-catalog",
], solve-group = "mv-api-catalog", no-default-feature = true }
mv-api-catalog-dev = { features = [
    "catalog-common",
    "rerun-prerelease",
    "cuda",
    "mv-api",
    "mv-api-catalog",
    "dev",
], solve-group = "mv-api-catalog", no-default-feature = true }
mv-api-catalog-register-mac = { features = [
    "mv-api-catalog-register-mac",
], solve-group = "mv-api-catalog-register-mac", no-default-feature = true }
mast3r-slam = { features = [
    "common",
    "cuda",
    "mast3r-slam",
], solve-group = "mast3r-slam", no-default-feature = true }
mast3r-slam-dev = { features = [
    "common",
    "cuda",
    "mast3r-slam",
    "dev",
], solve-group = "mast3r-slam", no-default-feature = true }
gsplat-rust-renderer = { features = [
    "gsplat-rust-renderer",
], solve-group = "gsplat-rust-renderer", no-default-feature = true }
gsplat-rust-renderer-dev = { features = [
    "gsplat-rust-renderer",
    "dev",
], solve-group = "gsplat-rust-renderer", no-default-feature = true }
dataforge = { features = [
    "common",
    "dataforge",
], solve-group = "dataforge", no-default-feature = true }
dataforge-dev = { features = [
    "common",
    "dataforge",
    "dev",
], solve-group = "dataforge", no-default-feature = true }
dpvo = { features = [
    "common",
    "cuda",
    "dpvo",
], solve-group = "dpvo", no-default-feature = true }
dpvo-dev = { features = [
    "common",
    "cuda",
    "dpvo",
    "dev",
], solve-group = "dpvo", no-default-feature = true }
slam-evals = { features = [
    "common",
    "slam-evals",
], solve-group = "slam-evals", no-default-feature = true }
slam-evals-dev = { features = [
    "common",
    "slam-evals",
    "dev",
], solve-group = "slam-evals", no-default-feature = true }
mamma = { features = [
    "common",
    "cuda",
    "mamma",
], solve-group = "mamma", no-default-feature = true }
mamma-dev = { features = [
    "common",
    "cuda",
    "mamma",
    "dev",
], solve-group = "mamma", no-default-feature = true }
gauss-surf = { features = [
    "catalog-common",
    "rerun-prerelease",
    "cuda",
    "gauss-surf",
], solve-group = "gauss-surf", no-default-feature = true }
gauss-surf-dev = { features = [
    "catalog-common",
    "rerun-prerelease",
    "cuda",
    "gauss-surf",
    "dev",
], solve-group = "gauss-surf", no-default-feature = true }
mvs = { features = [
    "catalog-common",
    "rerun-prerelease",
    "cuda",
    "mvs",
], solve-group = "mvs", no-default-feature = true }
mvs-dev = { features = [
    "catalog-common",
    "rerun-prerelease",
    "cuda",
    "mvs",
    "dev",
], solve-group = "mvs", no-default-feature = true }