From 6eb701d25bb2db8653d3e4fafc1d685e06c853f7 Mon Sep 17 00:00:00 2001 From: dcodrut Date: Wed, 8 Jan 2025 18:47:20 +0100 Subject: [PATCH 01/17] add the GlacierMappingAlps dataset class --- torchgeo/datasets/__init__.py | 2 + torchgeo/datasets/glacier_mapping_alps.py | 419 ++++++++++++++++++++++ 2 files changed, 421 insertions(+) create mode 100644 torchgeo/datasets/glacier_mapping_alps.py diff --git a/torchgeo/datasets/__init__.py b/torchgeo/datasets/__init__.py index f55ef3af22c..c9cb2989d0a 100644 --- a/torchgeo/datasets/__init__.py +++ b/torchgeo/datasets/__init__.py @@ -60,6 +60,7 @@ ) from .geonrw import GeoNRW from .gid15 import GID15 +from .glacier_mapping_alps import GlacierMappingAlps from .globbiomass import GlobBiomass from .hyspecnet import HySpecNet11k from .idtrees import IDTReeS @@ -215,6 +216,7 @@ 'ForestDamage', 'GeoDataset', 'GeoNRW', + 'GlacierMappingAlps', 'GlobBiomass', 'HySpecNet11k', 'IDTReeS', diff --git a/torchgeo/datasets/glacier_mapping_alps.py b/torchgeo/datasets/glacier_mapping_alps.py new file mode 100644 index 00000000000..7ba93b9b0d9 --- /dev/null +++ b/torchgeo/datasets/glacier_mapping_alps.py @@ -0,0 +1,419 @@ +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. + +"""GlacierMappingAlps Dataset.""" + +import os +from collections.abc import Callable, Sequence +from pathlib import Path +from typing import ClassVar + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +import torch +import xarray as xr +from matplotlib.figure import Figure +from torch import Tensor + +from .errors import DatasetNotFoundError +from .geo import NonGeoDataset +from .utils import download_and_extract_archive, download_url, extract_archive + + +class GlacierMappingAlps(NonGeoDataset): + r"""A Multi-modal Dataset for Glacier Mapping (Segmentation) in the European Alps. + + The dataset consists of Sentinel-2 images from 2015 (mainly), 2016 and 2017, and binary segmentation masks for + glaciers, based on an inventory built by glaciology experts + (`Paul et al. 2020 `_). + + Given that glacier ice is not always visible in the images, due to seasonal snow, shadow/cloud cover and, most + importantly, debris cover, the dataset also includes additional features that can help in the segmentation task. + + Dataset features: + + * Sentinel-2 images (all bands, including cloud and shadow masks which can be used for loss masking) + * glacier mask (0: no glacier, 1: glacier) + * debris mask (0: no debris, 1: debris) based on a mix of three publications + (`Scherler et al. 2018 `_, + `Herreid & Pellicciotti 2020 `_, + `Linsbauer et al. 2021 `_) + * DEM (Copernicus GLO-30) + five derived features (using `xDEM `_): slope, + aspect, terrain ruggedness index, planform and profile curvatures + * dh/dt (surface elevation change) map over 2010-2015 (`Hugonnet et al. 2021 `_) + * v (surface velocity) map over 2015 (`ITS_LIVE `_) + + Other specifications: + + * temporal coverage: one acquisition per glacier, from either 2015 (mainly), 2016, or 2017 + * spatial coverage: only glaciers larger than 0.1 km\ :sup:`2`\ are considered (n=1593, after manual QC), totalling + ~1685 km\ :sup:`2`\ which represents ~93% of the total inventory area for this region + * 2251 patches sampled with overlap from the 1593 glaciers; + or 11440 for the `large` version, obtained with an increased sampling overlap + * the dataset download size is 5.8 GB (11 GB when unarchived); + or 29.5 GB (52 GB when unarchived) for the `large` version + * the dataset is provided at 10m GSD (after bilinearly resampling some of the Sentinel-2 bands and the additional + features which come at a lower resolution) + * the dataset provides fixed training, validation, and test geographical splits (70-10-20, by glacier area) + * five different splits are provided, according to a five-fold cross-validation scheme + * all the features/masks are stacked and provided as NetCDF files (one or more per glacier), structured as + `data/{glacier_id}/{glacier_id}_{patch_number}_{center_x}_{center_y}.nc` + * data is projected and geocoded in local UTM zones + + For more details check also: https://huggingface.co/datasets/dcodrut/dl4gam_alps + + If you use this dataset in your research, please cite the following paper: + + * https://doi.org/10.22541/essoar.173557607.70204641/v1 + + .. note:: + + This dataset requires the following additional library to be installed: + + * `xarray `_ + * `netcdf4 `_ + + .. versionadded:: 0.7 + """ + + r_url = 'https://huggingface.co/datasets/dcodrut/dl4gam_alps/resolve/7d20ca8a2b30c5518e086ffaa5ce37e6a66c42c1/data' + download_metadata: ClassVar[dict[str, dict[str, str]]] = { + 'dataset_small': { + 'url': f'{r_url}/patches/inv_r_128_s_128.tar.gz', + 'checksum': '3e69c47c6ff5106cd4ffaa6bb2caaaef', + }, + 'dataset_large': { + 'url': f'{r_url}/patches/inv_r_128_s_64.tar.gz', + 'checksum': '06e85a6a9e3dc6b3cdb07f928e832bc8', + }, + 'splits_csv': { + 'url': f'{r_url}/map_all_splits_all_folds.csv', + 'checksum': '862355c5c3482271dd171d31c70551b3', + }, + } + + extra_features_all = ( + 'dem', # Digital Elevation Model + 'slope', + 'aspect', + 'planform_curvature', + 'profile_curvature', + 'terrain_ruggedness_index', # DEM-based features + 'dhdt', # surface elevation change + 'v', # surface velocity + ) + + rgb_bands = ('B4', 'B3', 'B2') + all_bands = ( + 'B1', + 'B2', + 'B3', + 'B4', + 'B5', + 'B6', + 'B7', + 'B8', + 'B8A', + 'B9', + 'B10', + 'B11', + 'B12', + ) + rgb_nir_swir_bands = ('B4', 'B3', 'B2', 'B8', 'B11') # the subset used in our paper + + def __init__( + self, + root: str | os.PathLike[str] = 'data', + split: str = 'train', + cv_iter: int = 1, + version: str = 'small', + bands: Sequence[str] = rgb_nir_swir_bands, + extra_features: Sequence[str] | None = None, + transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None, + download: bool = False, + checksum: bool = False, + ) -> None: + """Initialize the dataset. + + Args: + root: root directory where dataset can be found + split: one of "train", "val", or "test" + cv_iter: one of 1, 2, 3, 4, 5 (for the five-fold geographical cross-validation scheme) + version: one of "small" or "large" (controls the sampling overlap) + bands: the Sentinel-2 bands to use as input (default: RGB + NIR + SWIR) + extra_features: additional features to include (default: None; see the class attribute for the available) + transforms: a function/transform that takes input sample and its target as entry and returns a transformed + version + download: if True, download dataset and store it in the root directory + checksum: if True, check the MD5 of the downloaded files (may be slow) + """ + self.root = Path(root) + self.split = split + self.cv_iter = cv_iter + self.version = version + self.bands = bands + self.extra_features = extra_features + self.transforms = transforms + self.download = download + self.checksum = checksum + + # sanity checks + assert split in ( + 'train', + 'val', + 'test', + ), f'Split {split} not found in the available splits' + assert cv_iter in range( + 1, 6 + ), f'Cross-validation iteration {cv_iter} has to be in [1, 2, 3, 4, 5]' + assert version in ( + 'small', + 'large', + ), f'Version {version} not found in the available versions' + for band in bands: + assert ( + band in self.all_bands + ), f'Band {band} not found in the available Sentinel-2 bands' + if self.extra_features: + for feature in self.extra_features: + assert ( + feature in self.extra_features_all + ), f'Feature {feature} not found in the available extra features' + + # set the local file paths + label = f'dataset_{version}' + self.fp_archive = self.root / f'{label}.tar.gz' + self.dir_patches = self.root / label + self.fp_splits_csv = self.root / 'splits.csv' + + # get the corresponding urls and checksums + self.url_dataset = self.download_metadata[label]['url'] + self.md5_dataset = self.download_metadata[label]['checksum'] + self.url_csv_splits = self.download_metadata['splits_csv']['url'] + self.md5_csv_splits = self.download_metadata['splits_csv']['checksum'] + + self._verify() + self._prepare_files() + + def __len__(self) -> int: + """The length of the dataset. + + It returns the number of patches in the dataset. + """ + return len(self.fp_patches) + + def __getitem__(self, index: int) -> dict[str, Tensor]: + """A single sample from the dataset. + + It loads the netcdf file for the given index, and returns a dictionary containing: + + * the Sentinel-2 image (selected bands) + * the glacier mask (binary mask with all the glaciers in the current patch) + * the debris mask + * the cloud and shadow mask + * the additional features (DEM, derived features, etc.) if required + """ + nc = xr.open_dataset( + self.fp_patches[index], decode_coords='all', mask_and_scale=True + ) + + # extract the S2 image and masks from the netcdf file + all_band_names = nc.band_data.long_name + sample = { + 'image': nc.band_data.isel( + band=[all_band_names.index(b) for b in self.bands] + ).values.astype(np.float32), + 'mask_glacier': ~np.isnan(nc.mask_all_g_id.values), + 'mask_debris': (nc['mask_debris'].values == 1), + 'mask_clouds_and_shadows': ~( + nc.band_data.isel(band=all_band_names.index('CLOUDLESS_MASK')).values + == 1 + ), + } + + # extract the additional features if needed + if self.extra_features: + for feature in self.extra_features: + assert feature in nc, f'Feature {feature} not found in the netcdf file' + data_crt_feature = nc[feature].values.astype(np.float32) + + # impute the missing values with the mean or zero (for dh/dt and surface velocity) + v_fill = ( + 0.0 if feature in ('dhdt', 'v') else np.nanmean(data_crt_feature) + ) + data_crt_feature[np.isnan(data_crt_feature)] = v_fill + + sample[feature] = data_crt_feature + + # convert to torch tensors + for k, v in sample.items(): + sample[k] = torch.from_numpy(v) + + return sample + + def _verify(self) -> None: + """Verify the integrity of the dataset.""" + if self.dir_patches.exists() and self.fp_splits_csv.exists(): + return + + # check if the archive exists + if self.fp_archive.exists(): + extract_archive(self.fp_archive, self.dir_patches) + return + + if not self.download: + raise DatasetNotFoundError(self) + + self._download() + + def _download(self) -> None: + """Download the patches and the csv with the splits.""" + # download and extract the archive + download_and_extract_archive( + url=self.url_dataset, + download_root=self.root, + extract_root=self.dir_patches, + filename=self.fp_archive.name, + md5=self.md5_dataset if self.checksum else None, + ) + + # download the splits csv + download_url( + url=self.url_csv_splits, + root=self.root, + filename='splits.csv', + md5=self.md5_csv_splits if self.checksum else None, + ) + + def _prepare_files(self) -> None: + """Prepare the files for the dataset.""" + # prepare the paths to the patches + self.fp_patches = sorted(list(self.dir_patches.rglob('*.nc'))) + + # get the glacier IDs of the current split of the cross-validation + self.df_splits = pd.read_csv(self.fp_splits_csv) + fold_name = f"fold_{self.split if self.split != 'val' else 'valid'}" + idx = self.df_splits[f'split_{self.cv_iter}'] == fold_name + glacier_ids = list(self.df_splits.loc[idx, 'entry_id']) + + # filter the patches to keep only the ones corresponding to the current split + self.fp_patches = [ + fp for fp in self.fp_patches if fp.parent.name in glacier_ids + ] + + def plot( + self, + sample: dict[str, Tensor], + show_titles: bool = True, + suptitle: str | None = None, + clip_extrema: bool = True, + ) -> Figure: + """Plot a sample from the dataset. + + Args: + sample: a sample returned by :meth:`GlacierMappingAlps.__getitem__` + show_titles: flag indicating whether to show titles above each panel + suptitle: optional string to use as a suptitle + clip_extrema: flag indicating whether to clip the lowest/highest 2.5% of the values for contrast enhancement + + Returns: + a matplotlib Figure with the rendered sample + """ + # we expect the RGB bands to be present + assert {'B4', 'B3', 'B2'}.issubset( + set(self.bands) + ), 'RGB bands not found in the available bands.' + nir_and_swir_present = {'B8', 'B11'}.issubset(set(self.bands)) + + # prepare the RGB image and the masks + idx_rgb = [self.bands.index(b) for b in ['B4', 'B3', 'B2']] + rgb_img = sample['image'][idx_rgb].permute(1, 2, 0) + images = { + 'RGB Image': rgb_img, + 'Glacier Mask': sample['mask_glacier'], + 'Debris Mask': sample['mask_debris'], + 'Clouds and Shadows Mask': sample['mask_clouds_and_shadows'], + } + + # add the SWIR-NIR-R image if the bands are present + if nir_and_swir_present: + idx_swir_nir_r = [self.bands.index(b) for b in ['B11', 'B8', 'B4']] + swir_nir_r_img = sample['image'][idx_swir_nir_r].permute(1, 2, 0) + images['SWIR-NIR-R Image'] = swir_nir_r_img + + # add the extra features if present + for extra_v, title in ( + ('prediction', 'Prediction'), + ('dem', 'DEM'), + ('slope', 'Slope'), + ('aspect', 'Aspect'), + ('planform_curvature', 'Planform Curvature'), + ('profile_curvature', 'Profile Curvature'), + ('terrain_ruggedness_index', 'Terrain Ruggedness Index'), + ('dhdt', 'dh/dt'), + ('v', 'Surface Velocity'), + ): + if extra_v in sample: + images[title] = sample[extra_v] + + cmaps = { + 'RGB Image': None, + 'SWIR-NIR-R Image': None, + 'Glacier Mask': 'gray', + 'Prediction': 'gray', + 'Debris Mask': 'gray', + 'Clouds and Shadows Mask': 'gray', + 'DEM': 'terrain', + 'Slope': 'magma', + 'Aspect': 'jet', + 'Planform Curvature': 'magma', + 'Profile Curvature': 'magma', + 'Terrain Ruggedness Index': 'magma', + 'dh/dt': 'seismic_r', + 'Surface Velocity': 'magma', + } + + # build the figure + n_imgs = len(images) + ncols = 4 if n_imgs <= 8 else 5 + nrows = int(np.ceil(n_imgs / ncols)) + fig, axs = plt.subplots(nrows, ncols, figsize=(5 * ncols, 5 * nrows)) + + for ax, k in zip(axs.flat, images): + img = images[k].numpy() + cmap = cmaps[k] + + # clip the extrema 5% of the values if needed + if clip_extrema and k not in [ + 'Glacier Mask', + 'Prediction', + 'Debris Mask', + 'Clouds and Shadows Mask', + ]: + q_lim_clip = 0.025 + img = np.clip( + img, np.quantile(img, q_lim_clip), np.quantile(img, 1 - q_lim_clip) + ) + + vmin, vmax = np.min(img), np.max(img) + # smale the images to [0,1] + if k in ['RGB Image', 'SWIR-NIR-R Image']: + img = (img - vmin) / (vmax - vmin) + + if k == 'dh/dt': # diverging colormap for the dh/dt, make it symmetric + max_abs = max(abs(vmin), abs(vmax)) + vmin, vmax = -max_abs, max_abs + + ax.imshow(img, cmap=cmap, interpolation='none', vmin=vmin, vmax=vmax) + if show_titles: + ax.set_title(k) + + # disable the axes for all plots, including the empty plots + for ax in axs.flat: + ax.axis('off') + + if suptitle: + fig.suptitle(suptitle) + + return fig From 6c986a1cdcad82bbe38ffde39f6b2bdd56e95e7a Mon Sep 17 00:00:00 2001 From: dcodrut Date: Thu, 9 Jan 2025 13:32:21 +0100 Subject: [PATCH 02/17] add doc entry --- docs/api/datasets.rst | 4 ++++ docs/api/datasets/non_geo_datasets.csv | 1 + 2 files changed, 5 insertions(+) diff --git a/docs/api/datasets.rst b/docs/api/datasets.rst index b8f2137c920..458699a5325 100644 --- a/docs/api/datasets.rst +++ b/docs/api/datasets.rst @@ -312,6 +312,10 @@ GID-15 .. autoclass:: GID15 +Glacier Mapping Alps +^^^^^^^^^^^^^^^^^^^^ +.. autoclass:: GlacierMappingAlps + HySpecNet-11k ^^^^^^^^^^^^^ diff --git a/docs/api/datasets/non_geo_datasets.csv b/docs/api/datasets/non_geo_datasets.csv index 7d7a17a4b94..cc68d0d05b0 100644 --- a/docs/api/datasets/non_geo_datasets.csv +++ b/docs/api/datasets/non_geo_datasets.csv @@ -21,6 +21,7 @@ Dataset,Task,Source,License,# Samples,# Classes,Size (px),Resolution (m),Bands `Forest Damage`_,OD,Drone imagery,"CDLA-Permissive-1.0","1,543",4,"1,500x1,500",,RGB `GeoNRW`_,S,Aerial,"CC-BY-4.0","7,783",11,"1,000x1,000",1,"RGB, DEM" `GID-15`_,S,Gaofen-2,-,150,15,"6,800x7,200",3,RGB +`Glacier Mapping Alps`_,S,"Sentinel-2","CC-BY-4.0","2,251 or 11,440","2","256x256","10","MSI" `HySpecNet-11k`_,-,EnMAP,CC0-1.0,11k,-,128,30,HSI `IDTReeS`_,"OD,C",Aerial,"CC-BY-4.0",591,33,200x200,0.1--1,RGB `Inria Aerial Image Labeling`_,S,Aerial,-,360,2,"5,000x5,000",0.3,RGB From c959d467ba9570ddb9471794ac687edaa300dc80 Mon Sep 17 00:00:00 2001 From: dcodrut Date: Thu, 9 Jan 2025 13:36:49 +0100 Subject: [PATCH 03/17] add dummy data script --- tests/data/glacier_mapping_alps/data.py | 143 ++++++++++++++++++++++++ 1 file changed, 143 insertions(+) create mode 100644 tests/data/glacier_mapping_alps/data.py diff --git a/tests/data/glacier_mapping_alps/data.py b/tests/data/glacier_mapping_alps/data.py new file mode 100644 index 00000000000..d5c7dddab1a --- /dev/null +++ b/tests/data/glacier_mapping_alps/data.py @@ -0,0 +1,143 @@ +#!/usr/bin/env python3 + +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. + +import hashlib +import shutil +from pathlib import Path + +import numpy as np +import pandas as pd +import xarray as xr + +# define the patch size +PATCH_SIZE = 16 + +# create a random generator +rg = np.random.RandomState(42) + + +def create_dummy_sample(fp: str | Path) -> None: + # create the random S2 bands data; make the last two bands as binary masks + band_data = rg.randint( + low=0, high=10000, dtype=np.int16, size=(15, PATCH_SIZE, PATCH_SIZE) + ) + band_data[-2:] = (band_data[-2:] > 5000).astype(np.int16) + + data_dict = { + 'band_data': { + 'dims': ('band', 'y', 'x'), + 'data': band_data, + 'attrs': { + 'long_name': [ + 'B1', + 'B2', + 'B3', + 'B4', + 'B5', + 'B6', + 'B7', + 'B8', + 'B8A', + 'B9', + 'B10', + 'B11', + 'B12', + 'CLOUDLESS_MASK', + 'FILL_MASK', + ], + '_FillValue': -9999, + }, + }, + 'mask_all_g_id': { # glaciers mask (with -1 for no-glacier and GLACIER_ID for glacier) + 'dims': ('y', 'x'), + 'data': rg.choice([-1, 8, 9, 30, 35], size=(PATCH_SIZE, PATCH_SIZE)).astype( + np.int32 + ), + 'attrs': {'_FillValue': -1}, + }, + 'mask_debris': { + 'dims': ('y', 'x'), + 'data': (rg.random((PATCH_SIZE, PATCH_SIZE)) > 0.5).astype(np.int8), + 'attrs': {'_FillValue': -1}, + }, + } + + # add the additional variables + for v in [ + 'dem', + 'slope', + 'aspect', + 'planform_curvature', + 'profile_curvature', + 'terrain_ruggedness_index', + 'dhdt', + 'v', + ]: + data_dict[v] = { + 'dims': ('y', 'x'), + 'data': (rg.random((PATCH_SIZE, PATCH_SIZE)) * 100).astype(np.float32), + 'attrs': {'_FillValue': -9999}, + } + + # create the xarray dataset and save it + nc = xr.Dataset.from_dict(data_dict) + nc.to_netcdf(fp) + + +def create_splits_df(fp: str | Path) -> pd.DataFrame: + # create a dataframe with the splits for the 4 glaciers + splits_df = pd.DataFrame( + { + 'entry_id': ['g_0008', 'g_0009', 'g_0030', 'g_0035'], + 'split_1': ['fold_train', 'fold_train', 'fold_valid', 'fold_test'], + 'split_2': ['fold_train', 'fold_valid', 'fold_train', 'fold_test'], + 'split_3': ['fold_train', 'fold_valid', 'fold_test', 'fold_train'], + 'split_4': ['fold_test', 'fold_valid', 'fold_train', 'fold_train'], + 'split_5': ['fold_test', 'fold_train', 'fold_train', 'fold_valid'], + } + ) + + splits_df.to_csv(fp_splits, index=False) + print(f'Splits dataframe saved to {fp_splits}') + return splits_df + + +if __name__ == '__main__': + # prepare the paths + fp_splits = Path('splits.csv') + fp_dir_ds_small = Path('dataset_small') + fp_dir_ds_large = Path('dataset_large') + + # cleanup + fp_splits.unlink(missing_ok=True) + fp_dir_ds_small.with_suffix('.tar.gz').unlink(missing_ok=True) + fp_dir_ds_large.with_suffix('.tar.gz').unlink(missing_ok=True) + shutil.rmtree(fp_dir_ds_small, ignore_errors=True) + shutil.rmtree(fp_dir_ds_large, ignore_errors=True) + + # create the splits dataframe + split_df = create_splits_df(fp_splits) + + # create the two datasets versions (small and large) with 1 and 2 patches per glacier, respectively + for fp_dir, num_patches in zip([fp_dir_ds_small, fp_dir_ds_large], [1, 2]): + for glacier_id in split_df.entry_id: + for i in range(num_patches): + fp = fp_dir / glacier_id / f'{glacier_id}_patch_{i}.nc' + fp.parent.mkdir(parents=True, exist_ok=True) + create_dummy_sample(fp=fp) + + # archive the datasets + for fp_dir in [fp_dir_ds_small, fp_dir_ds_large]: + shutil.make_archive(str(fp_dir), 'gztar', fp_dir) + + # compute checksums + for fp in [ + fp_dir_ds_small.with_suffix('.tar.gz'), + fp_dir_ds_large.with_suffix('.tar.gz'), + fp_splits, + ]: + with open(fp, 'rb') as f: + md5 = hashlib.md5(f.read()).hexdigest() + print(f'md5 for {fp}: {md5}') From 0e919c6df75e3bb54d84a4d7c04850cf2bec1144 Mon Sep 17 00:00:00 2001 From: dcodrut Date: Thu, 9 Jan 2025 13:37:50 +0100 Subject: [PATCH 04/17] add dummy data --- .../glacier_mapping_alps/dataset_large.tar.gz | Bin 0 -> 133834 bytes .../dataset_large/g_0008/g_0008_patch_0.nc | Bin 0 -> 32063 bytes .../dataset_large/g_0008/g_0008_patch_1.nc | Bin 0 -> 32063 bytes .../dataset_large/g_0009/g_0009_patch_0.nc | Bin 0 -> 32063 bytes .../dataset_large/g_0009/g_0009_patch_1.nc | Bin 0 -> 32063 bytes .../dataset_large/g_0030/g_0030_patch_0.nc | Bin 0 -> 32063 bytes .../dataset_large/g_0030/g_0030_patch_1.nc | Bin 0 -> 32063 bytes .../dataset_large/g_0035/g_0035_patch_0.nc | Bin 0 -> 32063 bytes .../dataset_large/g_0035/g_0035_patch_1.nc | Bin 0 -> 32063 bytes .../glacier_mapping_alps/dataset_small.tar.gz | Bin 0 -> 67299 bytes .../dataset_small/g_0008/g_0008_patch_0.nc | Bin 0 -> 32063 bytes .../dataset_small/g_0009/g_0009_patch_0.nc | Bin 0 -> 32063 bytes .../dataset_small/g_0030/g_0030_patch_0.nc | Bin 0 -> 32063 bytes .../dataset_small/g_0035/g_0035_patch_0.nc | Bin 0 -> 32063 bytes tests/data/glacier_mapping_alps/splits.csv | 5 +++++ 15 files changed, 5 insertions(+) create mode 100644 tests/data/glacier_mapping_alps/dataset_large.tar.gz create mode 100644 tests/data/glacier_mapping_alps/dataset_large/g_0008/g_0008_patch_0.nc create mode 100644 tests/data/glacier_mapping_alps/dataset_large/g_0008/g_0008_patch_1.nc create mode 100644 tests/data/glacier_mapping_alps/dataset_large/g_0009/g_0009_patch_0.nc create mode 100644 tests/data/glacier_mapping_alps/dataset_large/g_0009/g_0009_patch_1.nc create mode 100644 tests/data/glacier_mapping_alps/dataset_large/g_0030/g_0030_patch_0.nc create mode 100644 tests/data/glacier_mapping_alps/dataset_large/g_0030/g_0030_patch_1.nc create mode 100644 tests/data/glacier_mapping_alps/dataset_large/g_0035/g_0035_patch_0.nc create mode 100644 tests/data/glacier_mapping_alps/dataset_large/g_0035/g_0035_patch_1.nc create mode 100644 tests/data/glacier_mapping_alps/dataset_small.tar.gz create mode 100644 tests/data/glacier_mapping_alps/dataset_small/g_0008/g_0008_patch_0.nc create mode 100644 tests/data/glacier_mapping_alps/dataset_small/g_0009/g_0009_patch_0.nc create mode 100644 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zJre={Z_k#9*IJd%f)Vet2>kbVS+DuG1^;hYjMyK zVkQ5_%fw2Yc)dZ$6Z1;~CoD$bgvAJ)uo!_0zJ%QF{L~8U8GF#On6(gfZVb$rIoz@L z^C}RnuZH5snP5juDAc{~?R9rf92|Zz1$xHDLDK_q==0p8DE;1k6i(R-3dKc-d#oGO zacqY5cNPF^;%W#VRRW9etD%4Xdlc8u$MK9Y0<}LL3+OFb{KhJm7^z?4jsH@j`yomP-y&qSP~$Fbk%BTJzNf> zNb4Y0UJMWGyF;&nAlMQ$9#Y=#g4$un(2L1Y5OA9Wk5V?Fpz92Dr1cmm8=MU*Q@H@5 zKyVC;0r#sm7_@OanA9Q|PHpYn)!ZLFblVD)h5KQw{XW{XFAPm{?%+Fre+CHNML|Ks zLTH@23WASpg1ikq;PV4A-0CqMn9FK`xb8h9Ss95s+x;PZ+c3zS(hus7YmBykbHd#T zsCr>MJlX38pNiK*z05_>`^HQtuuX?g9>LIj=01m5H3iO8Ibrx1}L=CROsm(w1)Sd@P!)62tqH4Ixn3BE?0 z)j?Vpu0i;|q(XqcXhPZ4jY2C1tU^*>#X>!n$3fJ%kU^o$I6}#EU_kX(osY zZ9y`13qk;YX+mHiu0p2p)z(NI8b3(?01wwdKr9wX{=|OnWgF*d4 zjY1EVe?l+HuR@Gsz(Ry@t3ulmz(5w~ghEa7oI=22#6nTs6+*!0he0fsszNaN{XyVI zZ$dfs8$vbiAVMyFl0pub5JGaDib8y6w?F0E0YW%D|3O~Fl|oFV`$4l*eL{1zi9%zq hgF;48aY9~lB|>ge6+&p$VM3MJ%Ru@muR Date: Thu, 9 Jan 2025 13:39:55 +0100 Subject: [PATCH 05/17] unit tests --- tests/datasets/test_glacier_mapping_alps.py | 117 ++++++++++++++++++++ 1 file changed, 117 insertions(+) create mode 100644 tests/datasets/test_glacier_mapping_alps.py diff --git a/tests/datasets/test_glacier_mapping_alps.py b/tests/datasets/test_glacier_mapping_alps.py new file mode 100644 index 00000000000..bb0376c0c5c --- /dev/null +++ b/tests/datasets/test_glacier_mapping_alps.py @@ -0,0 +1,117 @@ +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. + +import shutil +from pathlib import Path + +import matplotlib.pyplot as plt +import pytest +import torch +import torch.nn as nn +from _pytest.fixtures import SubRequest +from pytest import MonkeyPatch + +from torchgeo.datasets import DatasetNotFoundError, GlacierMappingAlps + + +class TestGlacierMappingAlps: + @pytest.fixture( + params=zip( + ['train', 'val', 'test'], + [1, 3, 5], + ['small', 'small', 'large'], + [ + GlacierMappingAlps.rgb_bands, + GlacierMappingAlps.rgb_nir_swir_bands, + GlacierMappingAlps.all_bands, + ], + [None, ['dem'], GlacierMappingAlps.extra_features_all], + ) + ) + def dataset( + self, monkeypatch: MonkeyPatch, tmp_path: Path, request: SubRequest + ) -> GlacierMappingAlps: + r_url = Path('tests', 'data', 'glacier_mapping_alps') + download_metadata = { + 'dataset_small': { + 'url': str(r_url / 'dataset_small.tar.gz'), + 'checksum': '35f85360b943caa8661d9fb573b0f0b5', + }, + 'dataset_large': { + 'url': str(r_url / 'dataset_large.tar.gz'), + 'checksum': '636be5be35b8bd1e7771e9010503e4bc', + }, + 'splits_csv': { + 'url': str(r_url / 'splits.csv'), + 'checksum': '973367465c8ab322d0cf544a345b02f5', + }, + } + + monkeypatch.setattr(GlacierMappingAlps, 'download_metadata', download_metadata) + root = tmp_path + split, cv_iter, version, bands, extra_features = request.param + transforms = nn.Identity() + return GlacierMappingAlps( + root, + split, + cv_iter, + version, + bands, + extra_features, + transforms, + download=True, + checksum=True, + ) + + def test_getitem(self, dataset: GlacierMappingAlps) -> None: + x = dataset[0] + assert isinstance(x, dict) + + var_names = ['image', 'mask_glacier', 'mask_debris', 'mask_clouds_and_shadows'] + if dataset.extra_features: + var_names += list(dataset.extra_features) + for v in var_names: + assert v in x + assert isinstance(x[v], torch.Tensor) + + # check if all variables have the same spatial dimensions as the image + assert x['image'].shape[-2:] == x[v].shape[-2:] + + # check the first dimension of the image tensor + assert x['image'].shape[0] == len(dataset.bands) + + def test_len(self, dataset: GlacierMappingAlps) -> None: + num_glaciers_per_fold = 2 if dataset.split == 'train' else 1 + num_patches_per_glacier = 1 if dataset.version == 'small' else 2 + assert len(dataset) == num_glaciers_per_fold * num_patches_per_glacier + + def test_not_downloaded(self, tmp_path: Path) -> None: + with pytest.raises(DatasetNotFoundError, match='Dataset not found'): + GlacierMappingAlps(tmp_path) + + def test_already_downloaded_and_extracted( + self, dataset: GlacierMappingAlps + ) -> None: + GlacierMappingAlps(root=dataset.root, download=False, version=dataset.version) + + def test_already_downloaded_but_not_yet_extracted(self, tmp_path: Path) -> None: + fp_archive = Path( + 'tests', 'data', 'glacier_mapping_alps', 'dataset_small.tar.gz' + ) + shutil.copyfile(fp_archive, Path(str(tmp_path), fp_archive.name)) + fp_splits = Path('tests', 'data', 'glacier_mapping_alps', 'splits.csv') + shutil.copyfile(fp_splits, Path(str(tmp_path), fp_splits.name)) + GlacierMappingAlps(root=str(tmp_path), download=False) + + def test_invalid_split(self) -> None: + with pytest.raises(AssertionError): + GlacierMappingAlps(split='foo') + + def test_plot(self, dataset: GlacierMappingAlps) -> None: + dataset.plot(dataset[0], suptitle='Test') + plt.close() + + sample = dataset[0] + sample['prediction'] = torch.clone(sample['mask_glacier']) + dataset.plot(sample, suptitle='Test with prediction') + plt.close() From 871d0808a89a013b1f12f926ed2278c9e554f28c Mon Sep 17 00:00:00 2001 From: dcodrut Date: Thu, 9 Jan 2025 22:48:54 +0100 Subject: [PATCH 06/17] fix doc strings; refactoring --- tests/datasets/test_glacier_mapping_alps.py | 2 +- torchgeo/datasets/glacier_mapping_alps.py | 107 ++++++++++---------- 2 files changed, 56 insertions(+), 53 deletions(-) diff --git a/tests/datasets/test_glacier_mapping_alps.py b/tests/datasets/test_glacier_mapping_alps.py index bb0376c0c5c..1cb819f8ac0 100644 --- a/tests/datasets/test_glacier_mapping_alps.py +++ b/tests/datasets/test_glacier_mapping_alps.py @@ -25,7 +25,7 @@ class TestGlacierMappingAlps: GlacierMappingAlps.rgb_nir_swir_bands, GlacierMappingAlps.all_bands, ], - [None, ['dem'], GlacierMappingAlps.extra_features_all], + [None, ['dem'], GlacierMappingAlps.valid_extra_features], ) ) def dataset( diff --git a/torchgeo/datasets/glacier_mapping_alps.py b/torchgeo/datasets/glacier_mapping_alps.py index 7ba93b9b0d9..7f8013ec6e5 100644 --- a/torchgeo/datasets/glacier_mapping_alps.py +++ b/torchgeo/datasets/glacier_mapping_alps.py @@ -93,17 +93,6 @@ class GlacierMappingAlps(NonGeoDataset): }, } - extra_features_all = ( - 'dem', # Digital Elevation Model - 'slope', - 'aspect', - 'planform_curvature', - 'profile_curvature', - 'terrain_ruggedness_index', # DEM-based features - 'dhdt', # surface elevation change - 'v', # surface velocity - ) - rgb_bands = ('B4', 'B3', 'B2') all_bands = ( 'B1', @@ -122,6 +111,20 @@ class GlacierMappingAlps(NonGeoDataset): ) rgb_nir_swir_bands = ('B4', 'B3', 'B2', 'B8', 'B11') # the subset used in our paper + valid_extra_features = ( + 'dem', # Digital Elevation Model + 'slope', + 'aspect', + 'planform_curvature', + 'profile_curvature', + 'terrain_ruggedness_index', # DEM-based features + 'dhdt', # surface elevation change + 'v', # surface velocity + ) + valid_splits = ('train', 'val', 'test') + valid_versions = ('small', 'large') + valid_cv_iters = (1, 2, 3, 4, 5) + def __init__( self, root: str | os.PathLike[str] = 'data', @@ -147,6 +150,11 @@ def __init__( version download: if True, download dataset and store it in the root directory checksum: if True, check the MD5 of the downloaded files (may be slow) + + Raises: + AssertionError: if the ``split``, ``cv_iter``, ``version``, ``bands`` or ``extra_features`` are invalid + DatasetNotFoundError: If dataset is not found and *download* is False. + DependencyNotFoundError: If xarray is not installed. """ self.root = Path(root) self.split = split @@ -159,27 +167,20 @@ def __init__( self.checksum = checksum # sanity checks - assert split in ( - 'train', - 'val', - 'test', - ), f'Split {split} not found in the available splits' - assert cv_iter in range( - 1, 6 - ), f'Cross-validation iteration {cv_iter} has to be in [1, 2, 3, 4, 5]' - assert version in ( - 'small', - 'large', - ), f'Version {version} not found in the available versions' + assert split in self.valid_splits, f'Split {split} not in: {self.valid_splits}' + assert ( + cv_iter in self.valid_cv_iters + ), f'Cross-validation iteration {cv_iter} not in: {self.valid_cv_iters}' + assert ( + version in self.valid_versions + ), f'Version {version} not in: {self.valid_versions}' for band in bands: - assert ( - band in self.all_bands - ), f'Band {band} not found in the available Sentinel-2 bands' - if self.extra_features: - for feature in self.extra_features: + assert band in self.all_bands, f'Band {band} not in: {self.all_bands}' + if extra_features: + for feature in extra_features: assert ( - feature in self.extra_features_all - ), f'Feature {feature} not found in the available extra features' + feature in self.valid_extra_features + ), f'Feature {feature} not in: {self.valid_extra_features}' # set the local file paths label = f'dataset_{version}' @@ -199,20 +200,25 @@ def __init__( def __len__(self) -> int: """The length of the dataset. - It returns the number of patches in the dataset. + Returns: + the number of patches in the dataset """ return len(self.fp_patches) def __getitem__(self, index: int) -> dict[str, Tensor]: - """A single sample from the dataset. + """It loads the netcdf file for the given index and returns the sample as a dict. - It loads the netcdf file for the given index, and returns a dictionary containing: + Args: + index: index of the sample to return - * the Sentinel-2 image (selected bands) - * the glacier mask (binary mask with all the glaciers in the current patch) - * the debris mask - * the cloud and shadow mask - * the additional features (DEM, derived features, etc.) if required + Returns: + dict: a dictionary containing the sample with the following: + + * the Sentinel-2 image (selected bands) + * the glacier mask (binary mask with all the glaciers in the current patch) + * the debris mask + * the cloud and shadow mask + * the additional features (DEM, derived features, etc.) if required """ nc = xr.open_dataset( self.fp_patches[index], decode_coords='all', mask_and_scale=True @@ -220,31 +226,28 @@ def __getitem__(self, index: int) -> dict[str, Tensor]: # extract the S2 image and masks from the netcdf file all_band_names = nc.band_data.long_name + idx_img = [all_band_names.index(b) for b in self.bands] + image = nc.band_data.isel(band=idx_img).values.astype(np.float32) + id_cloud_mask = all_band_names.index('CLOUDLESS_MASK') + mask_clouds_and_shadows = ~(nc.band_data.isel(band=id_cloud_mask).values == 1) sample = { - 'image': nc.band_data.isel( - band=[all_band_names.index(b) for b in self.bands] - ).values.astype(np.float32), + 'image': image, 'mask_glacier': ~np.isnan(nc.mask_all_g_id.values), - 'mask_debris': (nc['mask_debris'].values == 1), - 'mask_clouds_and_shadows': ~( - nc.band_data.isel(band=all_band_names.index('CLOUDLESS_MASK')).values - == 1 - ), + 'mask_debris': (nc.mask_debris.values == 1), + 'mask_clouds_and_shadows': mask_clouds_and_shadows, } # extract the additional features if needed if self.extra_features: for feature in self.extra_features: assert feature in nc, f'Feature {feature} not found in the netcdf file' - data_crt_feature = nc[feature].values.astype(np.float32) + vals = nc[feature].values.astype(np.float32) # impute the missing values with the mean or zero (for dh/dt and surface velocity) - v_fill = ( - 0.0 if feature in ('dhdt', 'v') else np.nanmean(data_crt_feature) - ) - data_crt_feature[np.isnan(data_crt_feature)] = v_fill + v_fill = 0.0 if feature in ('dhdt', 'v') else np.nanmean(vals) + vals[np.isnan(vals)] = v_fill - sample[feature] = data_crt_feature + sample[feature] = vals # convert to torch tensors for k, v in sample.items(): From 5d7b27a7f1510b0c6c32e208237cbae0888472e0 Mon Sep 17 00:00:00 2001 From: dcodrut Date: Thu, 9 Jan 2025 23:11:58 +0100 Subject: [PATCH 07/17] lazy import for xarray --- requirements/datasets.txt | 2 ++ tests/datasets/test_glacier_mapping_alps.py | 3 +++ torchgeo/datasets/glacier_mapping_alps.py | 9 +++++++-- 3 files changed, 12 insertions(+), 2 deletions(-) diff --git a/requirements/datasets.txt b/requirements/datasets.txt index 11a82e9276c..9cfdcbe5d3c 100644 --- a/requirements/datasets.txt +++ b/requirements/datasets.txt @@ -7,3 +7,5 @@ pycocotools==2.0.8 pyvista==0.44.2 scikit-image==0.25.0 scipy==1.14.1 +xarray==2024.11.0 +netcdf4==1.7.2 diff --git a/tests/datasets/test_glacier_mapping_alps.py b/tests/datasets/test_glacier_mapping_alps.py index 1cb819f8ac0..94294adb78f 100644 --- a/tests/datasets/test_glacier_mapping_alps.py +++ b/tests/datasets/test_glacier_mapping_alps.py @@ -13,6 +13,9 @@ from torchgeo.datasets import DatasetNotFoundError, GlacierMappingAlps +pytest.importorskip('xarray', minversion='2024.11.0') +pytest.importorskip('netCDF4', minversion='1.7.2') + class TestGlacierMappingAlps: @pytest.fixture( diff --git a/torchgeo/datasets/glacier_mapping_alps.py b/torchgeo/datasets/glacier_mapping_alps.py index 7f8013ec6e5..fd656a5fbab 100644 --- a/torchgeo/datasets/glacier_mapping_alps.py +++ b/torchgeo/datasets/glacier_mapping_alps.py @@ -12,13 +12,17 @@ import numpy as np import pandas as pd import torch -import xarray as xr from matplotlib.figure import Figure from torch import Tensor from .errors import DatasetNotFoundError from .geo import NonGeoDataset -from .utils import download_and_extract_archive, download_url, extract_archive +from .utils import ( + download_and_extract_archive, + download_url, + extract_archive, + lazy_import, +) class GlacierMappingAlps(NonGeoDataset): @@ -220,6 +224,7 @@ def __getitem__(self, index: int) -> dict[str, Tensor]: * the cloud and shadow mask * the additional features (DEM, derived features, etc.) if required """ + xr = lazy_import('xarray') nc = xr.open_dataset( self.fp_patches[index], decode_coords='all', mask_and_scale=True ) From 890af531313f6cf7af52b3ec4873fa2c4384357f Mon Sep 17 00:00:00 2001 From: dcodrut Date: Mon, 13 Jan 2025 22:45:13 +0100 Subject: [PATCH 08/17] reformat --- torchgeo/datasets/glacier_mapping_alps.py | 26 +++++++++++------------ 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/torchgeo/datasets/glacier_mapping_alps.py b/torchgeo/datasets/glacier_mapping_alps.py index fd656a5fbab..2ebc959f715 100644 --- a/torchgeo/datasets/glacier_mapping_alps.py +++ b/torchgeo/datasets/glacier_mapping_alps.py @@ -172,19 +172,19 @@ def __init__( # sanity checks assert split in self.valid_splits, f'Split {split} not in: {self.valid_splits}' - assert ( - cv_iter in self.valid_cv_iters - ), f'Cross-validation iteration {cv_iter} not in: {self.valid_cv_iters}' - assert ( - version in self.valid_versions - ), f'Version {version} not in: {self.valid_versions}' + assert cv_iter in self.valid_cv_iters, ( + f'Cross-validation iteration {cv_iter} not in: {self.valid_cv_iters}' + ) + assert version in self.valid_versions, ( + f'Version {version} not in: {self.valid_versions}' + ) for band in bands: assert band in self.all_bands, f'Band {band} not in: {self.all_bands}' if extra_features: for feature in extra_features: - assert ( - feature in self.valid_extra_features - ), f'Feature {feature} not in: {self.valid_extra_features}' + assert feature in self.valid_extra_features, ( + f'Feature {feature} not in: {self.valid_extra_features}' + ) # set the local file paths label = f'dataset_{version}' @@ -301,7 +301,7 @@ def _prepare_files(self) -> None: # get the glacier IDs of the current split of the cross-validation self.df_splits = pd.read_csv(self.fp_splits_csv) - fold_name = f"fold_{self.split if self.split != 'val' else 'valid'}" + fold_name = f'fold_{self.split if self.split != "val" else "valid"}' idx = self.df_splits[f'split_{self.cv_iter}'] == fold_name glacier_ids = list(self.df_splits.loc[idx, 'entry_id']) @@ -329,9 +329,9 @@ def plot( a matplotlib Figure with the rendered sample """ # we expect the RGB bands to be present - assert {'B4', 'B3', 'B2'}.issubset( - set(self.bands) - ), 'RGB bands not found in the available bands.' + assert {'B4', 'B3', 'B2'}.issubset(set(self.bands)), ( + 'RGB bands not found in the available bands.' + ) nir_and_swir_present = {'B8', 'B11'}.issubset(set(self.bands)) # prepare the RGB image and the masks From cb3a9bc337e0b9a8737d546aad41bd499b1c090e Mon Sep 17 00:00:00 2001 From: dcodrut Date: Tue, 14 Jan 2025 20:18:33 +0100 Subject: [PATCH 09/17] fix typo --- torchgeo/datasets/glacier_mapping_alps.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/torchgeo/datasets/glacier_mapping_alps.py b/torchgeo/datasets/glacier_mapping_alps.py index 2ebc959f715..a86eb3c04fb 100644 --- a/torchgeo/datasets/glacier_mapping_alps.py +++ b/torchgeo/datasets/glacier_mapping_alps.py @@ -73,7 +73,7 @@ class GlacierMappingAlps(NonGeoDataset): .. note:: - This dataset requires the following additional library to be installed: + This dataset requires the following additional libraries to be installed: * `xarray `_ * `netcdf4 `_ From b1202fd65adadb0a0f20cfd151927b25d5b7ea66 Mon Sep 17 00:00:00 2001 From: dcodrut Date: Sun, 19 Jan 2025 22:47:47 +0100 Subject: [PATCH 10/17] sort alphabetically --- requirements/datasets.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements/datasets.txt b/requirements/datasets.txt index d2be8e65a52..180cdcf14b7 100644 --- a/requirements/datasets.txt +++ b/requirements/datasets.txt @@ -1,6 +1,7 @@ # datasets h5py==3.12.1 laspy==2.5.4 +netcdf4==1.7.2 opencv-python==4.10.0.84 pandas[parquet]==2.2.3 pycocotools==2.0.8 @@ -8,4 +9,3 @@ pyvista==0.44.2 scikit-image==0.25.0 scipy==1.15.0 xarray==2024.11.0 -netcdf4==1.7.2 From c7ec25c5e144e010fba4148320be66395b70a25d Mon Sep 17 00:00:00 2001 From: dcodrut Date: Sun, 19 Jan 2025 22:53:52 +0100 Subject: [PATCH 11/17] add minimum versions --- pyproject.toml | 4 ++++ tests/datasets/test_glacier_mapping_alps.py | 4 ++-- 2 files changed, 6 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 8d7fcc89183..33d68b3efb8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -87,6 +87,8 @@ datasets = [ "h5py>=3.6", # laspy 2+ required for laspy.read "laspy>=2", + # netcdf4 1.5.4+ required for xarray.open_dataset with engine="netcdf4" + "netcdf4>=1.5.4", # opencv-python 4.5.4+ required for Python 3.10 wheels "opencv-python>=4.5.4", # pandas 2+ required for parquet extra @@ -99,6 +101,8 @@ datasets = [ "scikit-image>=0.19", # scipy 1.7.2+ required for Python 3.10 wheels "scipy>=1.7.2", + # xarray 2023.9+ required for xarray.open_dataset + "xarray>=2023.9", ] docs = [ # ipywidgets 7+ required by nbsphinx diff --git a/tests/datasets/test_glacier_mapping_alps.py b/tests/datasets/test_glacier_mapping_alps.py index 94294adb78f..d072eb43363 100644 --- a/tests/datasets/test_glacier_mapping_alps.py +++ b/tests/datasets/test_glacier_mapping_alps.py @@ -13,8 +13,8 @@ from torchgeo.datasets import DatasetNotFoundError, GlacierMappingAlps -pytest.importorskip('xarray', minversion='2024.11.0') -pytest.importorskip('netCDF4', minversion='1.7.2') +pytest.importorskip('xarray', minversion='2023.9') +pytest.importorskip('netCDF4', minversion='1.5.4') class TestGlacierMappingAlps: From 4b9ba74850450a94557b3617d696e980997350bf Mon Sep 17 00:00:00 2001 From: dcodrut Date: Sun, 19 Jan 2025 23:02:55 +0100 Subject: [PATCH 12/17] rename dataset to DL4GAMAlps --- docs/api/datasets.rst | 6 +-- docs/api/datasets/non_geo_datasets.csv | 2 +- .../data.py | 0 .../dataset_large.tar.gz | Bin .../dataset_large/g_0008/g_0008_patch_0.nc | Bin .../dataset_large/g_0008/g_0008_patch_1.nc | Bin .../dataset_large/g_0009/g_0009_patch_0.nc | Bin .../dataset_large/g_0009/g_0009_patch_1.nc | Bin .../dataset_large/g_0030/g_0030_patch_0.nc | Bin .../dataset_large/g_0030/g_0030_patch_1.nc | Bin .../dataset_large/g_0035/g_0035_patch_0.nc | Bin .../dataset_large/g_0035/g_0035_patch_1.nc | Bin .../dataset_small.tar.gz | Bin .../dataset_small/g_0008/g_0008_patch_0.nc | Bin .../dataset_small/g_0009/g_0009_patch_0.nc | Bin .../dataset_small/g_0030/g_0030_patch_0.nc | Bin .../dataset_small/g_0035/g_0035_patch_0.nc | Bin .../splits.csv | 0 ...er_mapping_alps.py => test_dl4gam_alps.py} | 44 +++++++----------- torchgeo/datasets/__init__.py | 4 +- ...glacier_mapping_alps.py => dl4gam_alps.py} | 6 +-- 21 files changed, 27 insertions(+), 35 deletions(-) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/data.py (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_large.tar.gz (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_large/g_0008/g_0008_patch_0.nc (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_large/g_0008/g_0008_patch_1.nc (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_large/g_0009/g_0009_patch_0.nc (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_large/g_0009/g_0009_patch_1.nc (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_large/g_0030/g_0030_patch_0.nc (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_large/g_0030/g_0030_patch_1.nc (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_large/g_0035/g_0035_patch_0.nc (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_large/g_0035/g_0035_patch_1.nc (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_small.tar.gz (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_small/g_0008/g_0008_patch_0.nc (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_small/g_0009/g_0009_patch_0.nc (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_small/g_0030/g_0030_patch_0.nc (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/dataset_small/g_0035/g_0035_patch_0.nc (100%) rename tests/data/{glacier_mapping_alps => dl4gam_alps}/splits.csv (100%) rename tests/datasets/{test_glacier_mapping_alps.py => test_dl4gam_alps.py} (70%) rename torchgeo/datasets/{glacier_mapping_alps.py => dl4gam_alps.py} (99%) diff --git a/docs/api/datasets.rst b/docs/api/datasets.rst index 656909190ab..527243e9628 100644 --- a/docs/api/datasets.rst +++ b/docs/api/datasets.rst @@ -312,9 +312,9 @@ GID-15 .. autoclass:: GID15 -Glacier Mapping Alps -^^^^^^^^^^^^^^^^^^^^ -.. autoclass:: GlacierMappingAlps +DL4GAM Alps +^^^^^^^^^^^ +.. autoclass:: DL4GAMAlps HySpecNet-11k ^^^^^^^^^^^^^ diff --git a/docs/api/datasets/non_geo_datasets.csv b/docs/api/datasets/non_geo_datasets.csv index 5b70fb768a6..345a76b180c 100644 --- a/docs/api/datasets/non_geo_datasets.csv +++ b/docs/api/datasets/non_geo_datasets.csv @@ -21,7 +21,7 @@ Dataset,Task,Source,License,# Samples,# Classes,Size (px),Resolution (m),Bands `Forest Damage`_,OD,Drone imagery,"CDLA-Permissive-1.0","1,543",4,"1,500x1,500",,RGB `GeoNRW`_,S,Aerial,"CC-BY-4.0","7,783",11,"1,000x1,000",1,"RGB, DEM" `GID-15`_,S,Gaofen-2,-,150,15,"6,800x7,200",3,RGB -`Glacier Mapping Alps`_,S,"Sentinel-2","CC-BY-4.0","2,251 or 11,440","2","256x256","10","MSI" +`DL4GAM Alps`_,S,"Sentinel-2","CC-BY-4.0","2,251 or 11,440","2","256x256","10","MSI" `HySpecNet-11k`_,-,EnMAP,CC0-1.0,11k,-,128,30,HSI `IDTReeS`_,"OD,C",Aerial,"CC-BY-4.0",591,33,200x200,0.1--1,RGB `Inria Aerial Image Labeling`_,S,Aerial,-,360,2,"5,000x5,000",0.3,RGB diff --git a/tests/data/glacier_mapping_alps/data.py b/tests/data/dl4gam_alps/data.py similarity index 100% rename from tests/data/glacier_mapping_alps/data.py rename to tests/data/dl4gam_alps/data.py diff --git a/tests/data/glacier_mapping_alps/dataset_large.tar.gz b/tests/data/dl4gam_alps/dataset_large.tar.gz similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_large.tar.gz rename to tests/data/dl4gam_alps/dataset_large.tar.gz diff --git a/tests/data/glacier_mapping_alps/dataset_large/g_0008/g_0008_patch_0.nc b/tests/data/dl4gam_alps/dataset_large/g_0008/g_0008_patch_0.nc similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_large/g_0008/g_0008_patch_0.nc rename to tests/data/dl4gam_alps/dataset_large/g_0008/g_0008_patch_0.nc diff --git a/tests/data/glacier_mapping_alps/dataset_large/g_0008/g_0008_patch_1.nc b/tests/data/dl4gam_alps/dataset_large/g_0008/g_0008_patch_1.nc similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_large/g_0008/g_0008_patch_1.nc rename to tests/data/dl4gam_alps/dataset_large/g_0008/g_0008_patch_1.nc diff --git a/tests/data/glacier_mapping_alps/dataset_large/g_0009/g_0009_patch_0.nc b/tests/data/dl4gam_alps/dataset_large/g_0009/g_0009_patch_0.nc similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_large/g_0009/g_0009_patch_0.nc rename to tests/data/dl4gam_alps/dataset_large/g_0009/g_0009_patch_0.nc diff --git a/tests/data/glacier_mapping_alps/dataset_large/g_0009/g_0009_patch_1.nc b/tests/data/dl4gam_alps/dataset_large/g_0009/g_0009_patch_1.nc similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_large/g_0009/g_0009_patch_1.nc rename to tests/data/dl4gam_alps/dataset_large/g_0009/g_0009_patch_1.nc diff --git a/tests/data/glacier_mapping_alps/dataset_large/g_0030/g_0030_patch_0.nc b/tests/data/dl4gam_alps/dataset_large/g_0030/g_0030_patch_0.nc similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_large/g_0030/g_0030_patch_0.nc rename to tests/data/dl4gam_alps/dataset_large/g_0030/g_0030_patch_0.nc diff --git a/tests/data/glacier_mapping_alps/dataset_large/g_0030/g_0030_patch_1.nc b/tests/data/dl4gam_alps/dataset_large/g_0030/g_0030_patch_1.nc similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_large/g_0030/g_0030_patch_1.nc rename to tests/data/dl4gam_alps/dataset_large/g_0030/g_0030_patch_1.nc diff --git a/tests/data/glacier_mapping_alps/dataset_large/g_0035/g_0035_patch_0.nc b/tests/data/dl4gam_alps/dataset_large/g_0035/g_0035_patch_0.nc similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_large/g_0035/g_0035_patch_0.nc rename to tests/data/dl4gam_alps/dataset_large/g_0035/g_0035_patch_0.nc diff --git a/tests/data/glacier_mapping_alps/dataset_large/g_0035/g_0035_patch_1.nc b/tests/data/dl4gam_alps/dataset_large/g_0035/g_0035_patch_1.nc similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_large/g_0035/g_0035_patch_1.nc rename to tests/data/dl4gam_alps/dataset_large/g_0035/g_0035_patch_1.nc diff --git a/tests/data/glacier_mapping_alps/dataset_small.tar.gz b/tests/data/dl4gam_alps/dataset_small.tar.gz similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_small.tar.gz rename to tests/data/dl4gam_alps/dataset_small.tar.gz diff --git a/tests/data/glacier_mapping_alps/dataset_small/g_0008/g_0008_patch_0.nc b/tests/data/dl4gam_alps/dataset_small/g_0008/g_0008_patch_0.nc similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_small/g_0008/g_0008_patch_0.nc rename to tests/data/dl4gam_alps/dataset_small/g_0008/g_0008_patch_0.nc diff --git a/tests/data/glacier_mapping_alps/dataset_small/g_0009/g_0009_patch_0.nc b/tests/data/dl4gam_alps/dataset_small/g_0009/g_0009_patch_0.nc similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_small/g_0009/g_0009_patch_0.nc rename to tests/data/dl4gam_alps/dataset_small/g_0009/g_0009_patch_0.nc diff --git a/tests/data/glacier_mapping_alps/dataset_small/g_0030/g_0030_patch_0.nc b/tests/data/dl4gam_alps/dataset_small/g_0030/g_0030_patch_0.nc similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_small/g_0030/g_0030_patch_0.nc rename to tests/data/dl4gam_alps/dataset_small/g_0030/g_0030_patch_0.nc diff --git a/tests/data/glacier_mapping_alps/dataset_small/g_0035/g_0035_patch_0.nc b/tests/data/dl4gam_alps/dataset_small/g_0035/g_0035_patch_0.nc similarity index 100% rename from tests/data/glacier_mapping_alps/dataset_small/g_0035/g_0035_patch_0.nc rename to tests/data/dl4gam_alps/dataset_small/g_0035/g_0035_patch_0.nc diff --git a/tests/data/glacier_mapping_alps/splits.csv b/tests/data/dl4gam_alps/splits.csv similarity index 100% rename from tests/data/glacier_mapping_alps/splits.csv rename to tests/data/dl4gam_alps/splits.csv diff --git a/tests/datasets/test_glacier_mapping_alps.py b/tests/datasets/test_dl4gam_alps.py similarity index 70% rename from tests/datasets/test_glacier_mapping_alps.py rename to tests/datasets/test_dl4gam_alps.py index d072eb43363..abf39899468 100644 --- a/tests/datasets/test_glacier_mapping_alps.py +++ b/tests/datasets/test_dl4gam_alps.py @@ -11,30 +11,26 @@ from _pytest.fixtures import SubRequest from pytest import MonkeyPatch -from torchgeo.datasets import DatasetNotFoundError, GlacierMappingAlps +from torchgeo.datasets import DatasetNotFoundError, DL4GAMAlps pytest.importorskip('xarray', minversion='2023.9') pytest.importorskip('netCDF4', minversion='1.5.4') -class TestGlacierMappingAlps: +class TestDL4GAMAlps: @pytest.fixture( params=zip( ['train', 'val', 'test'], [1, 3, 5], ['small', 'small', 'large'], - [ - GlacierMappingAlps.rgb_bands, - GlacierMappingAlps.rgb_nir_swir_bands, - GlacierMappingAlps.all_bands, - ], - [None, ['dem'], GlacierMappingAlps.valid_extra_features], + [DL4GAMAlps.rgb_bands, DL4GAMAlps.rgb_nir_swir_bands, DL4GAMAlps.all_bands], + [None, ['dem'], DL4GAMAlps.valid_extra_features], ) ) def dataset( self, monkeypatch: MonkeyPatch, tmp_path: Path, request: SubRequest - ) -> GlacierMappingAlps: - r_url = Path('tests', 'data', 'glacier_mapping_alps') + ) -> DL4GAMAlps: + r_url = Path('tests', 'data', 'dl4gam_alps') download_metadata = { 'dataset_small': { 'url': str(r_url / 'dataset_small.tar.gz'), @@ -50,11 +46,11 @@ def dataset( }, } - monkeypatch.setattr(GlacierMappingAlps, 'download_metadata', download_metadata) + monkeypatch.setattr(DL4GAMAlps, 'download_metadata', download_metadata) root = tmp_path split, cv_iter, version, bands, extra_features = request.param transforms = nn.Identity() - return GlacierMappingAlps( + return DL4GAMAlps( root, split, cv_iter, @@ -66,7 +62,7 @@ def dataset( checksum=True, ) - def test_getitem(self, dataset: GlacierMappingAlps) -> None: + def test_getitem(self, dataset: DL4GAMAlps) -> None: x = dataset[0] assert isinstance(x, dict) @@ -83,34 +79,30 @@ def test_getitem(self, dataset: GlacierMappingAlps) -> None: # check the first dimension of the image tensor assert x['image'].shape[0] == len(dataset.bands) - def test_len(self, dataset: GlacierMappingAlps) -> None: + def test_len(self, dataset: DL4GAMAlps) -> None: num_glaciers_per_fold = 2 if dataset.split == 'train' else 1 num_patches_per_glacier = 1 if dataset.version == 'small' else 2 assert len(dataset) == num_glaciers_per_fold * num_patches_per_glacier def test_not_downloaded(self, tmp_path: Path) -> None: with pytest.raises(DatasetNotFoundError, match='Dataset not found'): - GlacierMappingAlps(tmp_path) + DL4GAMAlps(tmp_path) - def test_already_downloaded_and_extracted( - self, dataset: GlacierMappingAlps - ) -> None: - GlacierMappingAlps(root=dataset.root, download=False, version=dataset.version) + def test_already_downloaded_and_extracted(self, dataset: DL4GAMAlps) -> None: + DL4GAMAlps(root=dataset.root, download=False, version=dataset.version) def test_already_downloaded_but_not_yet_extracted(self, tmp_path: Path) -> None: - fp_archive = Path( - 'tests', 'data', 'glacier_mapping_alps', 'dataset_small.tar.gz' - ) + fp_archive = Path('tests', 'data', 'dl4gam_alps', 'dataset_small.tar.gz') shutil.copyfile(fp_archive, Path(str(tmp_path), fp_archive.name)) - fp_splits = Path('tests', 'data', 'glacier_mapping_alps', 'splits.csv') + fp_splits = Path('tests', 'data', 'dl4gam_alps', 'splits.csv') shutil.copyfile(fp_splits, Path(str(tmp_path), fp_splits.name)) - GlacierMappingAlps(root=str(tmp_path), download=False) + DL4GAMAlps(root=str(tmp_path), download=False) def test_invalid_split(self) -> None: with pytest.raises(AssertionError): - GlacierMappingAlps(split='foo') + DL4GAMAlps(split='foo') - def test_plot(self, dataset: GlacierMappingAlps) -> None: + def test_plot(self, dataset: DL4GAMAlps) -> None: dataset.plot(dataset[0], suptitle='Test') plt.close() diff --git a/torchgeo/datasets/__init__.py b/torchgeo/datasets/__init__.py index 8c2e362b6c1..dcf24ed3096 100644 --- a/torchgeo/datasets/__init__.py +++ b/torchgeo/datasets/__init__.py @@ -36,6 +36,7 @@ from .deepglobelandcover import DeepGlobeLandCover from .dfc2022 import DFC2022 from .digital_typhoon import DigitalTyphoon +from .dl4gam_alps import DL4GAMAlps from .eddmaps import EDDMapS from .enviroatlas import EnviroAtlas from .errors import DatasetNotFoundError, DependencyNotFoundError, RGBBandsMissingError @@ -60,7 +61,6 @@ ) from .geonrw import GeoNRW from .gid15 import GID15 -from .glacier_mapping_alps import GlacierMappingAlps from .globbiomass import GlobBiomass from .hyspecnet import HySpecNet11k from .idtrees import IDTReeS @@ -202,6 +202,7 @@ 'ChesapeakeWV', 'CloudCoverDetection', 'CropHarvest', + 'DL4GAMAlps', 'DatasetNotFoundError', 'DeepGlobeLandCover', 'DependencyNotFoundError', @@ -218,7 +219,6 @@ 'ForestDamage', 'GeoDataset', 'GeoNRW', - 'GlacierMappingAlps', 'GlobBiomass', 'HySpecNet11k', 'IDTReeS', diff --git a/torchgeo/datasets/glacier_mapping_alps.py b/torchgeo/datasets/dl4gam_alps.py similarity index 99% rename from torchgeo/datasets/glacier_mapping_alps.py rename to torchgeo/datasets/dl4gam_alps.py index a86eb3c04fb..818ed0dee9d 100644 --- a/torchgeo/datasets/glacier_mapping_alps.py +++ b/torchgeo/datasets/dl4gam_alps.py @@ -1,7 +1,7 @@ # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. -"""GlacierMappingAlps Dataset.""" +"""DL4GAMAlps Dataset.""" import os from collections.abc import Callable, Sequence @@ -25,7 +25,7 @@ ) -class GlacierMappingAlps(NonGeoDataset): +class DL4GAMAlps(NonGeoDataset): r"""A Multi-modal Dataset for Glacier Mapping (Segmentation) in the European Alps. The dataset consists of Sentinel-2 images from 2015 (mainly), 2016 and 2017, and binary segmentation masks for @@ -320,7 +320,7 @@ def plot( """Plot a sample from the dataset. Args: - sample: a sample returned by :meth:`GlacierMappingAlps.__getitem__` + sample: a sample returned by :meth:`DL4GAMAlps.__getitem__` show_titles: flag indicating whether to show titles above each panel suptitle: optional string to use as a suptitle clip_extrema: flag indicating whether to clip the lowest/highest 2.5% of the values for contrast enhancement From e9675b1eaeb99ff184d85a5853abcb09f7fea270 Mon Sep 17 00:00:00 2001 From: dcodrut Date: Sun, 19 Jan 2025 23:34:28 +0100 Subject: [PATCH 13/17] add an earlier import for tests to fail quicker --- torchgeo/datasets/dl4gam_alps.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/torchgeo/datasets/dl4gam_alps.py b/torchgeo/datasets/dl4gam_alps.py index 818ed0dee9d..79fcdceb361 100644 --- a/torchgeo/datasets/dl4gam_alps.py +++ b/torchgeo/datasets/dl4gam_alps.py @@ -160,6 +160,8 @@ def __init__( DatasetNotFoundError: If dataset is not found and *download* is False. DependencyNotFoundError: If xarray is not installed. """ + lazy_import('xarray') + self.root = Path(root) self.split = split self.cv_iter = cv_iter From 874409dffa77babe7aaf3b2f37e9f4e3b8a8aab3 Mon Sep 17 00:00:00 2001 From: dcodrut Date: Sun, 19 Jan 2025 23:40:20 +0100 Subject: [PATCH 14/17] fix (transforms were not applied) --- torchgeo/datasets/dl4gam_alps.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/torchgeo/datasets/dl4gam_alps.py b/torchgeo/datasets/dl4gam_alps.py index 79fcdceb361..e2b2f912fd0 100644 --- a/torchgeo/datasets/dl4gam_alps.py +++ b/torchgeo/datasets/dl4gam_alps.py @@ -260,6 +260,9 @@ def __getitem__(self, index: int) -> dict[str, Tensor]: for k, v in sample.items(): sample[k] = torch.from_numpy(v) + if self.transforms is not None: + sample = self.transforms(sample) + return sample def _verify(self) -> None: From 86bb37423855ea4d7ed75a482b5b15bec413b20b Mon Sep 17 00:00:00 2001 From: dcodrut Date: Sun, 19 Jan 2025 23:45:38 +0100 Subject: [PATCH 15/17] doc update --- torchgeo/datasets/dl4gam_alps.py | 80 +++++++++++++++++++------------- 1 file changed, 49 insertions(+), 31 deletions(-) diff --git a/torchgeo/datasets/dl4gam_alps.py b/torchgeo/datasets/dl4gam_alps.py index e2b2f912fd0..a476ef508f8 100644 --- a/torchgeo/datasets/dl4gam_alps.py +++ b/torchgeo/datasets/dl4gam_alps.py @@ -28,40 +28,50 @@ class DL4GAMAlps(NonGeoDataset): r"""A Multi-modal Dataset for Glacier Mapping (Segmentation) in the European Alps. - The dataset consists of Sentinel-2 images from 2015 (mainly), 2016 and 2017, and binary segmentation masks for - glaciers, based on an inventory built by glaciology experts - (`Paul et al. 2020 `_). + The dataset consists of Sentinel-2 images from 2015 (mainly), 2016 and 2017, and + binary segmentation masks for glaciers, based on an inventory built by glaciology + experts (`Paul et al. 2020 `_). - Given that glacier ice is not always visible in the images, due to seasonal snow, shadow/cloud cover and, most - importantly, debris cover, the dataset also includes additional features that can help in the segmentation task. + Given that glacier ice is not always visible in the images, due to seasonal snow, + shadow/cloud cover and, most importantly, debris cover, the dataset also includes + additional features that can help in the segmentation task. Dataset features: - * Sentinel-2 images (all bands, including cloud and shadow masks which can be used for loss masking) + * Sentinel-2 images (all bands, including cloud and shadow masks which can be used + for loss masking) * glacier mask (0: no glacier, 1: glacier) * debris mask (0: no debris, 1: debris) based on a mix of three publications (`Scherler et al. 2018 `_, `Herreid & Pellicciotti 2020 `_, - `Linsbauer et al. 2021 `_) - * DEM (Copernicus GLO-30) + five derived features (using `xDEM `_): slope, + `Linsbauer et al. 2021 + `_) + * DEM (Copernicus GLO-30) + five derived features + (using `xDEM `_): slope, aspect, terrain ruggedness index, planform and profile curvatures - * dh/dt (surface elevation change) map over 2010-2015 (`Hugonnet et al. 2021 `_) + * dh/dt (surface elevation change) map over 2010-2015 + (`Hugonnet et al. 2021 `_) * v (surface velocity) map over 2015 (`ITS_LIVE `_) Other specifications: - * temporal coverage: one acquisition per glacier, from either 2015 (mainly), 2016, or 2017 - * spatial coverage: only glaciers larger than 0.1 km\ :sup:`2`\ are considered (n=1593, after manual QC), totalling - ~1685 km\ :sup:`2`\ which represents ~93% of the total inventory area for this region + * temporal coverage: one acquisition per glacier, from either 2015 (mainly), 2016, + or 2017 + * spatial coverage: only glaciers larger than 0.1 km\ :sup:`2`\ are considered + (n=1593, after manual QC), totalling ~1685 km\ :sup:`2`\ which represents ~93% of + the total inventory area for this region * 2251 patches sampled with overlap from the 1593 glaciers; or 11440 for the `large` version, obtained with an increased sampling overlap * the dataset download size is 5.8 GB (11 GB when unarchived); or 29.5 GB (52 GB when unarchived) for the `large` version - * the dataset is provided at 10m GSD (after bilinearly resampling some of the Sentinel-2 bands and the additional - features which come at a lower resolution) - * the dataset provides fixed training, validation, and test geographical splits (70-10-20, by glacier area) - * five different splits are provided, according to a five-fold cross-validation scheme - * all the features/masks are stacked and provided as NetCDF files (one or more per glacier), structured as + * the dataset is provided at 10m GSD (after bilinearly resampling some of the + Sentinel-2 bands and the additional features which come at a lower resolution) + * the dataset provides fixed training, validation, and test geographical splits + (70-10-20, by glacier area) + * five different splits are provided, according to a five-fold cross-validation + scheme + * all the features/masks are stacked and provided as NetCDF files (one or more per + glacier), structured as `data/{glacier_id}/{glacier_id}_{patch_number}_{center_x}_{center_y}.nc` * data is projected and geocoded in local UTM zones @@ -75,13 +85,16 @@ class DL4GAMAlps(NonGeoDataset): This dataset requires the following additional libraries to be installed: - * `xarray `_ - * `netcdf4 `_ + * `xarray `_ + * `netcdf4 `_ .. versionadded:: 0.7 """ - r_url = 'https://huggingface.co/datasets/dcodrut/dl4gam_alps/resolve/7d20ca8a2b30c5518e086ffaa5ce37e6a66c42c1/data' + r_url = ( + 'https://huggingface.co/datasets/dcodrut/dl4gam_alps/resolve/' + '7d20ca8a2b30c5518e086ffaa5ce37e6a66c42c1/data' + ) download_metadata: ClassVar[dict[str, dict[str, str]]] = { 'dataset_small': { 'url': f'{r_url}/patches/inv_r_128_s_128.tar.gz', @@ -146,19 +159,21 @@ def __init__( Args: root: root directory where dataset can be found split: one of "train", "val", or "test" - cv_iter: one of 1, 2, 3, 4, 5 (for the five-fold geographical cross-validation scheme) + cv_iter: one of 1, 2, 3, 4, 5 (for the five-fold geographical + cross-validation scheme) version: one of "small" or "large" (controls the sampling overlap) bands: the Sentinel-2 bands to use as input (default: RGB + NIR + SWIR) - extra_features: additional features to include (default: None; see the class attribute for the available) - transforms: a function/transform that takes input sample and its target as entry and returns a transformed - version + extra_features: additional features to include (default: None; see the class + attribute for the available) + transforms: a function/transform that takes input sample and its target as + entry and returns a transformed version download: if True, download dataset and store it in the root directory checksum: if True, check the MD5 of the downloaded files (may be slow) Raises: - AssertionError: if the ``split``, ``cv_iter``, ``version``, ``bands`` or ``extra_features`` are invalid - DatasetNotFoundError: If dataset is not found and *download* is False. - DependencyNotFoundError: If xarray is not installed. + AssertionError: if any parameters are invalid. + DatasetNotFoundError: if dataset is not found and *download* is False. + DependencyNotFoundError: if xarray is not installed. """ lazy_import('xarray') @@ -212,7 +227,7 @@ def __len__(self) -> int: return len(self.fp_patches) def __getitem__(self, index: int) -> dict[str, Tensor]: - """It loads the netcdf file for the given index and returns the sample as a dict. + """Load the NetCDF file for the given index and return the sample as a dict. Args: index: index of the sample to return @@ -221,7 +236,8 @@ def __getitem__(self, index: int) -> dict[str, Tensor]: dict: a dictionary containing the sample with the following: * the Sentinel-2 image (selected bands) - * the glacier mask (binary mask with all the glaciers in the current patch) + * the glacier mask (binary mask with all the glaciers in the current + patch) * the debris mask * the cloud and shadow mask * the additional features (DEM, derived features, etc.) if required @@ -250,7 +266,8 @@ def __getitem__(self, index: int) -> dict[str, Tensor]: assert feature in nc, f'Feature {feature} not found in the netcdf file' vals = nc[feature].values.astype(np.float32) - # impute the missing values with the mean or zero (for dh/dt and surface velocity) + # impute the missing values with the mean + # or zero (for dh/dt and surface velocity) v_fill = 0.0 if feature in ('dhdt', 'v') else np.nanmean(vals) vals[np.isnan(vals)] = v_fill @@ -328,7 +345,8 @@ def plot( sample: a sample returned by :meth:`DL4GAMAlps.__getitem__` show_titles: flag indicating whether to show titles above each panel suptitle: optional string to use as a suptitle - clip_extrema: flag indicating whether to clip the lowest/highest 2.5% of the values for contrast enhancement + clip_extrema: flag indicating whether to clip the lowest/highest 2.5% of the + values for contrast enhancement Returns: a matplotlib Figure with the rendered sample From 98da8588181b208824aa36c6100c1e347098bce4 Mon Sep 17 00:00:00 2001 From: dcodrut Date: Mon, 20 Jan 2025 13:27:19 +0100 Subject: [PATCH 16/17] set utils.Path as type hint --- torchgeo/datasets/dl4gam_alps.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/torchgeo/datasets/dl4gam_alps.py b/torchgeo/datasets/dl4gam_alps.py index a476ef508f8..b73f9ebc525 100644 --- a/torchgeo/datasets/dl4gam_alps.py +++ b/torchgeo/datasets/dl4gam_alps.py @@ -3,9 +3,8 @@ """DL4GAMAlps Dataset.""" -import os +import pathlib from collections.abc import Callable, Sequence -from pathlib import Path from typing import ClassVar import matplotlib.pyplot as plt @@ -18,6 +17,7 @@ from .errors import DatasetNotFoundError from .geo import NonGeoDataset from .utils import ( + Path, download_and_extract_archive, download_url, extract_archive, @@ -144,7 +144,7 @@ class DL4GAMAlps(NonGeoDataset): def __init__( self, - root: str | os.PathLike[str] = 'data', + root: Path = 'data', split: str = 'train', cv_iter: int = 1, version: str = 'small', @@ -177,7 +177,7 @@ def __init__( """ lazy_import('xarray') - self.root = Path(root) + self.root = pathlib.Path(root) self.split = split self.cv_iter = cv_iter self.version = version From 640f72a39588f148148894444ad7817be9c88891 Mon Sep 17 00:00:00 2001 From: dcodrut Date: Mon, 20 Jan 2025 17:38:17 +0100 Subject: [PATCH 17/17] fix typo --- torchgeo/datasets/dl4gam_alps.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/torchgeo/datasets/dl4gam_alps.py b/torchgeo/datasets/dl4gam_alps.py index b73f9ebc525..263c614be4b 100644 --- a/torchgeo/datasets/dl4gam_alps.py +++ b/torchgeo/datasets/dl4gam_alps.py @@ -428,7 +428,7 @@ def plot( ) vmin, vmax = np.min(img), np.max(img) - # smale the images to [0,1] + # scale the images to [0,1] if k in ['RGB Image', 'SWIR-NIR-R Image']: img = (img - vmin) / (vmax - vmin)