技能创建器
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创建、改进和评估自定义技能,把专业流程转化为可重复使用的 AI 能力。
lightly【数据与研究】Use LightlySSL for self-supervised computer-vision training, model components, CLIs, embeddings, data layout, evaluation, and repository maintenance.
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Use this skill when a task names lightly, LightlySSL, self-supervised computer vision, Lightly's CLI commands, SSL transforms/losses/heads, image-folder embeddings, YOLO crop helpers, or maintenance of the LightlySSL repository.
pip install lightlypip install "lightly[timm]"pip install "lightly[video]"python - <<'PY'
import lightly
from lightly.loss import NTXentLoss
from lightly.transforms import SimCLRTransform
print(lightly.__version__, NTXentLoss, SimCLRTransform)
PY
For a richer environment smoke, run the bundled environment checker. It imports core modules, reports optional TIMM/video availability, and can do a tiny tensor check without downloads.
| Need | Read |
|---|---|
| Assemble datasets, collates, transforms, losses, projection heads, memory banks, or method-to-component mappings. | ssl-building-blocks |
| Adapt a bare PyTorch, PyTorch Lightning, or distributed Lightly SSL training recipe without downloading repo examples. | training-workflows |
Build or validate lightly-version, lightly-ssl-train, lightly-embed, lightly-magic, lightly-crop, Hydra overrides, input folders, embeddings CSVs, or YOLO crop labels. | cli-data-embedding |
| Use KNN/linear evaluation utilities or choose repository checks for changes to losses, transforms, examples, docs, notebooks, or distributed tests. | evaluation-maintenance |
make all-checks.