Add iNaturalist dataset

docs/api/datasets.rst

@@ -77,6 +77,11 @@ GlobBiomass
 
 .. autoclass:: GlobBiomass
 
+iNaturalist
+^^^^^^^^^^^
+
+.. autoclass:: INaturalist
+
 Landsat
 ^^^^^^^
 

tests/data/inaturalist/data.py

@@ -0,0 +1,58 @@
+#!/usr/bin/env python3
+
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+import pandas as pd
+
+filename = "observations-012345.csv"
+
+# User can select which columns to export. The following are the default columns.
+# Not all columns may exist in the actual dataset.
+size = 4
+data = {
+    "id": [""] * size,
+    "observed_on_string": [""] * size,
+    "observed_on": ["", "", "2022-05-07", "2022-05-07"],
+    "time_observed_at": ["", "", "", "2022-05-07 11:02:53 +0100"],
+    "time_zone": ["Central Time (US & Canada)"] * size,
+    "user_id": [123] * size,
+    "user_login": ["darwin"] * size,
+    "created_at": ["2022-05-07 11:02:53 +0100"] * size,
+    "updated_at": ["2022-05-07 11:02:53 +0100"] * size,
+    "quality_grade": ["research"] * size,
+    "license": ["CCO"] * size,
+    "url": ["https://inaturalist.org/observations/123"] * size,
+    "image_url": [
+        "https://inaturalist-open-data.s3.amazonaws.com/photos/123/medium.jpg"
+    ]
+    * size,
+    "sound_url": ["https://static.inaturalist.org/sounds/123.m4a?123"] * size,
+    "tag_list": ["Chicago"] * size,
+    "description": [""] * size,
+    "num_identification_agreements": [1] * size,
+    "num_identification_disagreements": [0] * size,
+    "captive_cultivated": ["false"] * size,
+    "oauth_application_id": [""] * size,
+    "place_guess": ["Chicago"] * size,
+    "latitude": [41.881832] * size,
+    "longitude": [""] + [-87.623177] * (size - 1),
+    "positional_accuracy": [5] * size,
+    "private_place_guess": [""] * size,
+    "private_latitude": [""] * size,
+    "private_longitude": [""] * size,
+    "public_positional_accuracy": [5] * size,
+    "geoprivacy": [""] * size,
+    "taxon_geoprivacy": [""] * size,
+    "coordinates_obscured": ["false"] * size,
+    "positioning_method": ["gps"] * size,
+    "positioning_device": ["gps"] * size,
+    "species_guess": ["Homo sapiens"] * size,
+    "scientific_name": ["Homo sapiens"] * size,
+    "common_name": ["human"] * size,
+    "iconic_taxon_name": ["Animalia"] * size,
+    "taxon_id": [123] * size,
+}
+
+df = pd.DataFrame(data)
+df.to_csv(filename, index=False)

tests/data/inaturalist/observations-012345.csv

@@ -0,0 +1,5 @@
+id,observed_on_string,observed_on,time_observed_at,time_zone,user_id,user_login,created_at,updated_at,quality_grade,license,url,image_url,sound_url,tag_list,description,num_identification_agreements,num_identification_disagreements,captive_cultivated,oauth_application_id,place_guess,latitude,longitude,positional_accuracy,private_place_guess,private_latitude,private_longitude,public_positional_accuracy,geoprivacy,taxon_geoprivacy,coordinates_obscured,positioning_method,positioning_device,species_guess,scientific_name,common_name,iconic_taxon_name,taxon_id
+,,,,Central Time (US & Canada),123,darwin,2022-05-07 11:02:53 +0100,2022-05-07 11:02:53 +0100,research,CCO,https://inaturalist.org/observations/123,https://inaturalist-open-data.s3.amazonaws.com/photos/123/medium.jpg,https://static.inaturalist.org/sounds/123.m4a?123,Chicago,,1,0,false,,Chicago,41.881832,,5,,,,5,,,false,gps,gps,Homo sapiens,Homo sapiens,human,Animalia,123
+,,,,Central Time (US & Canada),123,darwin,2022-05-07 11:02:53 +0100,2022-05-07 11:02:53 +0100,research,CCO,https://inaturalist.org/observations/123,https://inaturalist-open-data.s3.amazonaws.com/photos/123/medium.jpg,https://static.inaturalist.org/sounds/123.m4a?123,Chicago,,1,0,false,,Chicago,41.881832,-87.623177,5,,,,5,,,false,gps,gps,Homo sapiens,Homo sapiens,human,Animalia,123
+,,2022-05-07,,Central Time (US & Canada),123,darwin,2022-05-07 11:02:53 +0100,2022-05-07 11:02:53 +0100,research,CCO,https://inaturalist.org/observations/123,https://inaturalist-open-data.s3.amazonaws.com/photos/123/medium.jpg,https://static.inaturalist.org/sounds/123.m4a?123,Chicago,,1,0,false,,Chicago,41.881832,-87.623177,5,,,,5,,,false,gps,gps,Homo sapiens,Homo sapiens,human,Animalia,123
+,,2022-05-07,2022-05-07 11:02:53 +0100,Central Time (US & Canada),123,darwin,2022-05-07 11:02:53 +0100,2022-05-07 11:02:53 +0100,research,CCO,https://inaturalist.org/observations/123,https://inaturalist-open-data.s3.amazonaws.com/photos/123/medium.jpg,https://static.inaturalist.org/sounds/123.m4a?123,Chicago,,1,0,false,,Chicago,41.881832,-87.623177,5,,,,5,,,false,gps,gps,Homo sapiens,Homo sapiens,human,Animalia,123

tests/datasets/test_inaturalist.py

@@ -0,0 +1,72 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+import builtins
+import os
+from pathlib import Path
+from typing import Any
+
+import pytest
+from _pytest.monkeypatch import MonkeyPatch
+
+from torchgeo.datasets import (
+    BoundingBox,
+    INaturalist,
+    IntersectionDataset,
+    UnionDataset,
+)
+
+pytest.importorskip("pandas", minversion="0.23.2")
+
+
+class TestINaturalist:
+    @pytest.fixture(scope="class")
+    def dataset(self) -> INaturalist:
+        root = os.path.join("tests", "data", "inaturalist")
+        return INaturalist(root)
+
+    def test_getitem(self, dataset: INaturalist) -> None:
+        x = dataset[dataset.bounds]
+        assert isinstance(x, dict)
+
+    def test_len(self, dataset: INaturalist) -> None:
+        assert len(dataset) == 3
+
+    def test_and(self, dataset: INaturalist) -> None:
+        ds = dataset & dataset
+        assert isinstance(ds, IntersectionDataset)
+
+    def test_or(self, dataset: INaturalist) -> None:
+        ds = dataset | dataset
+        assert isinstance(ds, UnionDataset)
+
+    def test_no_data(self, tmp_path: Path) -> None:
+        with pytest.raises(FileNotFoundError, match="Dataset not found"):
+            INaturalist(str(tmp_path))
+
+    @pytest.fixture
+    def mock_missing_module(self, monkeypatch: MonkeyPatch) -> None:
+        import_orig = builtins.__import__
+
+        def mocked_import(name: str, *args: Any, **kwargs: Any) -> Any:
+            if name == "pandas":
+                raise ImportError()
+            return import_orig(name, *args, **kwargs)
+
+        monkeypatch.setattr(builtins, "__import__", mocked_import)
+
+    def test_mock_missing_module(
+        self, dataset: INaturalist, mock_missing_module: None
+    ) -> None:
+        with pytest.raises(
+            ImportError,
+            match="pandas is not installed and is required to use this dataset",
+        ):
+            INaturalist(dataset.root)
+
+    def test_invalid_query(self, dataset: INaturalist) -> None:
+        query = BoundingBox(0, 0, 0, 0, 0, 0)
+        with pytest.raises(
+            IndexError, match="query: .* not found in index with bounds:"
+        ):
+            dataset[query]

torchgeo/datasets/__init__.py

@@ -48,6 +48,7 @@
 from .gid15 import GID15
 from .globbiomass import GlobBiomass
 from .idtrees import IDTReeS
+from .inaturalist import INaturalist
 from .inria import InriaAerialImageLabeling
 from .landcoverai import LandCoverAI
 from .landsat import (
@@ -121,6 +122,7 @@
     "EUDEM",
     "GBIF",
     "GlobBiomass",
+    "INaturalist",
     "Landsat",
     "Landsat1",
     "Landsat2",

torchgeo/datasets/inaturalist.py

@@ -0,0 +1,123 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+"""Dataset for iNaturalist."""
+
+import glob
+import os
+import sys
+from typing import Any, Dict
+
+from rasterio.crs import CRS
+
+from .geo import GeoDataset
+from .utils import BoundingBox, disambiguate_timestamp
+
+
+class INaturalist(GeoDataset):
+    """Dataset for iNaturalist.
+
+    `iNaturalist <https://www.inaturalist.org/>`_ is a joint initiative of the
+    California Academy of Sciences and the National Geographic Society. It allows
+    citizen scientists to upload observations of organisms that can be downloaded by
+    scientists and researchers.
+
+    If you use an iNaturalist dataset in your research, please cite it according to:
+
+    * https://www.inaturalist.org/pages/help#cite
+
+    .. note::
+       This dataset requires the following additional library to be installed:
+
+       * `pandas <https://pypi.org/project/pandas/>`_ to load CSV files
+
+    .. versionadded:: 0.3
+    """
+
+    res = 0
+    _crs = CRS.from_epsg(4326)  # Lat/Lon
+
+    def __init__(self, root: str = "data") -> None:
+        """Initialize a new Dataset instance.
+
+        Args:
+            root: root directory where dataset can be found
+
+        Raises:
+            FileNotFoundError: if no files are found in ``root``
+            ImportError: if pandas is not installed
+        """
+        super().__init__()
+
+        self.root = root
+
+        files = glob.glob(os.path.join(root, "**.csv"))
+        if not files:
+            raise FileNotFoundError(f"Dataset not found in `root={self.root}`")
+
+        try:
+            import pandas as pd  # noqa: F401
+        except ImportError:
+            raise ImportError(
+                "pandas is not installed and is required to use this dataset"
+            )
+
+        # Read CSV file
+        data = pd.read_csv(
+            files[0],
+            engine="c",
+            usecols=["observed_on", "time_observed_at", "latitude", "longitude"],
+        )
+
+        # Dataset contains many possible timestamps:
+        #
+        # * observed_on_string: no consistent format (can't use)
+        # * observed_on: day precision (better)
+        # * time_observed_at: second precision (best)
+        # * created_at: when observation was submitted (shouldn't use)
+        # * updated_at: when submission was updated (shouldn't use)
+        #
+        # The created_at/updated_at timestamps can be years after the actual submission,
+        # so they shouldn't be used, even if observed_on/time_observed_at are missing.
+
+        # Convert from pandas DataFrame to rtree Index
+        i = 0
+        for date, time, y, x in data.itertuples(index=False, name=None):
+            # Skip rows without lat/lon
+            if pd.isna(y) or pd.isna(x):
+                continue
+
+            if not pd.isna(time):
+                mint, maxt = disambiguate_timestamp(time, "%Y-%m-%d %H:%M:%S %z")
+            elif not pd.isna(date):
+                mint, maxt = disambiguate_timestamp(date, "%Y-%m-%d")
+            else:
+                mint, maxt = 0, sys.maxsize
+
+            coords = (x, x, y, y, mint, maxt)
+            self.index.insert(i, coords)
+            i += 1
+
+    def __getitem__(self, query: BoundingBox) -> Dict[str, Any]:
+        """Retrieve metadata indexed by query.
+
+        Args:
+            query: (minx, maxx, miny, maxy, mint, maxt) coordinates to index
+
+        Returns:
+            sample of metadata at that index
+
+        Raises:
+            IndexError: if query is not found in the index
+        """
+        hits = self.index.intersection(tuple(query), objects=True)
+        bboxes = [hit.bbox for hit in hits]
+
+        if not bboxes:
+            raise IndexError(
+                f"query: {query} not found in index with bounds: {self.bounds}"
+            )
+
+        sample = {"crs": self.crs, "bbox": bboxes}
+
+        return sample