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name: data-and-datasets description: "Operate FastReID dataset registries, built-in layouts, custom dataset classes, dataloaders, transforms, samplers, and safe data preflight checks." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

FastReID data and datasets

Use this sub-skill when a FastReID task involves dataset roots, FASTREID_DATASETS, built-in dataset names, custom dataset registration, ImageDataset/CommDataset tuple shape, train/test dataloader APIs, transforms, samplers, or preflight checks before training/evaluation.

Start here

1. Identify the dataset name exactly as FastReID expects it, for example Market1501, DukeMTMC, MSMT17, VeRi, VehicleID, SmallVehicleID, VeRiWild, or SmallVeRiWild.
2. Resolve the dataset root that FastReID will receive: FASTREID_DATASETS if set, otherwise a relative datasets directory from the process working directory.
3. Validate the tree before launching any train/eval job:

python sub-skills/data-and-datasets/scripts/validate_dataset_layout.py --root <datasets-root> --dataset Market1501

4. If using a custom dataset, import the module that registers it before calling FastReID's train/test loader builders.

Runtime references and scripts

• references/dataset-formats.md: use for built-in dataset names, expected directory/list-file layouts, file-name parsing rules, and the canonical (img_path, pid, camid) item schema.
• references/data-api.md: use for DATASET_REGISTRY, ImageDataset, CommDataset, build_reid_train_loader, build_reid_test_loader, transform options, sampler choices, and custom dataset registration patterns.
• references/troubleshooting.md: use when FastReID cannot find datasets, parses pid/camid incorrectly, query/gallery is empty, samplers fail because of batch settings, or old dataset tests/imports conflict with this API.
• scripts/validate_dataset_layout.py: safe no-download validator for selected built-in layout roots; run it before expensive train/eval commands or when diagnosing partial dataset trees.

Route boundaries

• Training loops, schedulers, checkpoints, distributed launch, evaluator output, and train/eval command construction belong to ../training-and-evaluation/.
• Model registry, backbone/head/meta-architecture construction, predictors, feature tensors, and checkpoint loading belong to ../modeling-and-inference/.
• Source-only package setup, config inheritance, YAML merge behavior, and config recipe selection belong to ../setup-and-configuration/.
• Project-specific datasets under FastReID extension projects belong to ../deployment-and-projects/; use this sub-skill only for the shared registry/layout mechanics they rely on.

Verified operating facts

• FASTREID_DATASETS defaults to datasets when the environment variable is unset.
• Dataset records are tuples (img_path, pid, camid). Training built-ins usually prefix training pid/camid with a dataset name string before CommDataset(..., relabel=True) maps them to contiguous integers.
• Built-in registry keys include person ReID datasets (Market1501, DukeMTMC, MSMT17, CUHK03, VIPeR, GRID, iLIDS, etc.) and vehicle ReID datasets (VeRi, VehicleID, SmallVehicleID, MediumVehicleID, LargeVehicleID, VeRiWild, SmallVeRiWild, MediumVeRiWild, LargeVeRiWild).
• API signatures verified for this FastReID version include build_reid_train_loader(train_set, *, sampler=None, total_batch_size, num_workers=0) and build_reid_test_loader(test_set, test_batch_size, num_query, num_workers=4); the config system also permits calls such as build_reid_train_loader(cfg, combineall=...) and build_reid_test_loader(cfg, dataset_name=...).