easyidp.data.Lotus¶

class easyidp.data.Lotus(*, cache_root=None, notify_missing=True)¶

Dataset for the lotus plot in Tanashi, Tokyo.

Crop : lotus
Location : Tanashi, Nishi-Tokyo, Japan
Flight date : May 31, 2017
UAV model : DJI Inspire 1
Flight height : 30 m
Image number : 142
Image size : 4608 x 3456
Software : Pix4D, Metashape
Outputs : DOM, DSM, PCD

__init__(*, cache_root=None, notify_missing=True)¶

Create a lightweight handle to the lotus demo dataset.

The constructor only exposes paths. It does not download files; call download() explicitly when is_ready() returns False.

Accessible path attributes include:

.photo : raw image folder
.shp : plot ROI shapefile
.pix4d.project : Pix4D project folder
.pix4d.param : Pix4D parameter folder
.pix4d.dom : Pix4D orthomosaic GeoTIFF
.pix4d.dsm : Pix4D digital surface model GeoTIFF
.pix4d.pcd : Pix4D point cloud file
.metashape.project : Metashape project file
.metashape.param : Metashape project folder
.metashape.dom : Metashape orthomosaic GeoTIFF
.metashape.dsm : Metashape digital surface model GeoTIFF
.metashape.pcd : Metashape point cloud file

Parameters:

cache_root (Path or str, optional) – Root directory for cached datasets. Defaults to idp.config.get("data_dir").
notify_missing (bool, optional) – Retained for backward compatibility only; no longer logs warnings.

Examples

>>> lotus = idp.data.Lotus()
>>> lotus.shp
PosixPath('.../2017_tanashi_lotus/plots.shp')
>>> lotus.pix4d.dom.name
'hasu_tanashi_20170531_Ins1RGB_30m_transparent_mosaic_group1.tif'

Methods

`__init__`(*[, cache_root, notify_missing])	Create a lightweight handle to the lotus demo dataset.
`download`([mirror, force, progress])	Download this dataset to cache_root.
`dry_run`()	Return a JSON-friendly summary dict without touching the network.
`is_ready`()	Return `True` when every ready_check file exists on disk.
`path`(key)	Return the absolute `Path` for a dotted file key.

Attributes

`name`	Dataset manifest name.
`root`	Extracted dataset directory.