---

name: python-api description: "Programmatic Python API for the colorizers package: constructors, preprocessing/postprocessing helpers, tensor shape contracts, SIGGRAPH hints, and no-download smoke checks." disable-model-invocation: true metadata: disco-role: operating license: BSD 2-Clause

colorization Python API

Use this sub-skill when the task is to use the colorizers package from Python: imports, model constructors, forward calls, Lab preprocessing/postprocessing helpers, tensor/data shape contracts, SIGGRAPH hint inputs, or no-download API smoke checks.

Start here

• API surface and call signatures: references/api-reference.md
• RGB/Lab/tensor data conventions: references/data-formats.md
• Common failures and fixes: references/troubleshooting.md
• Local diagnostic helper: scripts/api_smoke.py

Routing

• Stay in this sub-skill for programmatic model construction, helper-function use, forward-signature questions, tensor shape/range debugging, and smoke tests that avoid pretrained downloads.
• For end-to-end image-file colorization, CLI invocation, saving output images, or batch output management, use the sibling automatic-colorization sub-skill instead.
• Training workflows and the unsupported Caffe branch are out of scope.

Safety defaults

• Use eccv16(pretrained=False) and siggraph17(pretrained=False) for import/API tests that must not access the network.
• Calling eccv16() or siggraph17() without arguments requests pretrained weights because both wrappers default pretrained=True.
• Keep model tensors, L tensors, SIGGRAPH hint tensors, and masks on the same device before forward; move model outputs to CPU before postprocessing when needed.