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data-preparation【数据与研究】Guides Nerfstudio dataset conversion, transforms.json validation, camera conventions, device capture modes, and dataparser selection.
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Use this route before training when the task is about custom captures, camera
poses, transforms.json, ns-process-data, or choosing a dataparser.
transforms*.json schema, image/depth/mask paths, split lists, and camera conventions.nerfstudio-data, blender-data, minimal-parser, colmap, and other built-in dataparser names.training-and-configs after the dataset validates.cli-workflows first, because downloads need network and disk checks.api-extension.references/data-formats.md for transforms*.json, coordinate, depth, mask, and split fields.references/workflows.md for conversion recipes and dataparser routing.references/troubleshooting.md for COLMAP, FFmpeg, path, and schema failures.scripts/validate_nerfstudio_dataset.py to check a dataset directory or transforms*.json without modifying data.--skip-colmap valid.ns-process-data command into a new output directory.ns-train through training-and-configs.transforms*.json are relative to the dataset directory unless absolute paths are intentionally used.depth_file_path and are interpreted in millimeters by default.