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global-histogram-transfer

global-histogram-transfer

Guides the Caffe-only Interactive Deep Colorization global histogram transfer workflow, assets, APIs, and failure modes.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

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name: global-histogram-transfer description: "Guides the Caffe-only Interactive Deep Colorization global histogram transfer workflow, assets, APIs, and failure modes." disable-model-invocation: true metadata: disco-role: operating license: MIT

global-histogram-transfer

Use this sub-skill when a task is about applying a reference image's global color histogram to a grayscale target image with Interactive Deep Colorization, explaining the global histogram notebook, or diagnosing Caffe/global model assets.

Route first

Boundaries

  • For Caffe/PyTorch/Qt/Docker/model-download setup, route to ../setup-and-models/SKILL.md.
  • For local user-hint colorization, GUI operations, masks, suggested colors, or PyTorch local-hints workflows, route to ../interactive-colorization/SKILL.md.
  • Do not claim this repository has a PyTorch global histogram transfer implementation. The global workflow here is Caffe-only.
  • Do not treat static asset checks as proof of Caffe execution; PyCaffe and downloaded weights must be available before running the native workflow.

Critical facts

  • The global colorization wrapper is ColorizeImageCaffeGlobDist(Xd=256).
  • The global colorization call is net_forward(input_ab, input_mask, glob_dist=-1).
  • Passing glob_dist=-1 zeroes the global conditioning blob and runs automatic colorization.
  • Passing a 313-bin glob_dist fills glob_ab_313_mask and enables global histogram conditioning.
  • The global statistics notebook path uses a Caffe net created from models/global_model/global_stats.prototxt and models/global_model/dummy.caffemodel, then reads gt_glob_ab_313_drop from the net output.
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