Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
日本語の概要は準備中です。原文の説明を表示しています。
Use the GeoParquet specification and bundled inspection helpers to author, validate, distribute, or safely review geospatial Parquet data, including GeoParquet 2.0 vector metadata, external writer choices, and the alpha Parquet Raster proposal.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Use this skill when a task involves GeoParquet, Parquet GEOMETRY/GEOGRAPHY
logical types, WKB geometry columns, the Parquet geo metadata key, CRS/PROJJSON,
spatial row-group statistics, GeoParquet distribution, STAC publication, or the
alpha Parquet Raster proposal.
This repository is a specification and example suite, not an installable Python
writer package. Do not tell a user to install geoparquet as if it were a
library. For local inspection helpers, install the dependencies appropriate to
the task, then run a neutral import check:
python -m pip install "pyarrow>=22" "jsonschema>=4" "geoarrow-pyarrow>=0.2"
python -c "import pyarrow, jsonschema; print(pyarrow.__version__)"
The helper scripts are self-contained and offline by default. They do not fetch PROJJSON schemas, resolve authority registries, install external writers, or contact out-of-database raster URIs. Keep the exact writer/reader versions and raw inspection output with any conformance or publication decision.
sub-skills/validate-geoparquet/SKILL.md.
Use it for geo JSON, native logical types, WKB layout, CRS, geometry types,
bbox, and row-group geospatial statistics. It distinguishes a full 2.0 file
from metadata-only or native-type-only Parquet.sub-skills/distribute-geoparquet/SKILL.md.
Use it for GDAL/OGR, DuckDB, gpio/geoparquet-io, Sedona, compression,
ordering, row groups, spatial partitioning, STAC, and old-reader tradeoffs.sub-skills/parquet-raster/SKILL.md.
Treat it as an alpha proposal only; do not transfer vector conformance rules
to raster columns.BYTE_ARRAY geometry columns annotated GEOMETRY or GEOGRAPHY, plus a
JSON geo metadata block.Read references/troubleshooting.md for
cross-cutting recovery guidance, and read
references/repo-provenance.md before deciding
whether this graph is stale relative to a repository checkout.
This graph does not implement a general GeoParquet writer, run production-scale conversion or benchmarks, install external tools, resolve every CRS authority, or certify the alpha raster proposal. It does include safe bundled vector metadata/footer helpers; their ownership and usage are described by the validation sub-skill.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
日本語の概要は準備中です。原文の説明を表示しています。
Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.
日本語の概要は準備中です。原文の説明を表示しています。
Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.
日本語の概要は準備中です。原文の説明を表示しています。
Use Hugging Face Accelerate for PyTorch training-loop migration, distributed launch/configuration, DeepSpeed/FSDP/TPU backend setup, big-model inference/offload, checkpointing, tracking, and troubleshooting.
日本語の概要は準備中です。原文の説明を表示しています。
Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
日本語の概要は準備中です。原文の説明を表示しています。