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deployment-and-projects

deployment-and-projects

Operate FastReID deployment export surfaces, optional ONNX/Caffe/TensorRT dependencies, FastRT, and extension-project registration patterns.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: deployment-and-projects description: "Operate FastReID deployment export surfaces, optional ONNX/Caffe/TensorRT dependencies, FastRT, and extension-project registration patterns." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

FastReID deployment and projects

Use this sub-skill when a FastReID task involves model export, deployment runtime checks, ONNX Runtime/Caffe/TensorRT inference, FastRT C++ TensorRT use, or extension projects such as FastAttr, FastClas, FastDistill, FastFace, FastRetri, FastTune, PartialReID, and NAIC20.

Route boundaries

  • Core model builders, tensor shapes, DefaultPredictor-style feature extraction, and checkpoint loading details belong to ../modeling-and-inference/.
  • Shared dataset registry mechanics, built-in dataset layouts, and custom dataset classes belong to ../data-and-datasets/.
  • Standard training/evaluation launch, distributed flags, resume, checkpoints, and evaluator output belong to ../training-and-evaluation/.
  • Source-only package setup, config merge, _BASE_, and model-zoo recipe selection belong to ../setup-and-configuration/.

Bundled references

  • references/deployment-workflows.md — use for ONNX, ONNX Runtime, Caffe, TensorRT, and FastRT prerequisites, export/inference interface templates, validation comparisons, and backend limitations.
  • references/project-extensions.md — use for the extension-project map, import-before-config rules, registry/config injection patterns, and project-specific dependency notes.
  • references/troubleshooting.md — use when parser help fails before argument parsing, optional deployment packages are missing, exported models disagree, TensorRT engines mismatch devices, Caffe protobuf/helpers are absent, or project imports/configs fail.

Bundled scripts

  • scripts/check_deployment_dependencies.py — safe optional-dependency probe for onnx, onnxruntime, onnxoptimizer, onnxsim, caffe, tensorrt, cv2, and torch; use it before export/runtime work or when a deployment entrypoint fails at import time.
  • scripts/project_import_probe.py — safe import probe for selected FastReID extension projects; pass an explicit FastReID application checkout with --repo-root and one or more --project values to classify registration/import failures without training.

Operating facts

  • ONNX, ONNX Runtime, Caffe, TensorRT, PyCUDA, Ray Tune, bcolz, and mxnet are optional stacks, not part of the minimum FastReID CPU inspection environment.
  • ONNX export code imports onnx, onnxoptimizer, and onnxsim before argument parsing in this FastReID version; a missing onnx package can make --help fail before showing parser output.
  • TensorRT export code imports tensorrt before argument parsing; a missing TensorRT Python package can make --help fail before showing parser output.
  • TensorRT/Caffe/FastRT workflows are hardware/runtime-gated and should not be claimed verified unless their native runtimes, drivers, model weights, and target devices are available.
  • Project packages must usually be imported before merging or building configs that name their datasets, meta-architectures, heads, backbones, or project-only config keys.
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