Add own data to CDL dataset. (#429)

* add own data

* data.py with cmap

* remove .img test data format

tests/data/cdl/data.py

@@ -0,0 +1,69 @@
+#!/usr/bin/env python3
+
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+import hashlib
+import os
+import random
+import shutil
+
+import numpy as np
+import rasterio
+
+SIZE = 32
+
+np.random.seed(0)
+random.seed(0)
+
+
+def create_file(path: str, dtype: str, num_channels: int) -> None:
+    profile = {}
+    profile["driver"] = "GTiff"
+    profile["dtype"] = dtype
+    profile["count"] = num_channels
+    profile["crs"] = "epsg:4326"
+    profile["transform"] = rasterio.transform.from_bounds(0, 0, 1, 1, 1, 1)
+    profile["height"] = SIZE
+    profile["width"] = SIZE
+    profile["compress"] = "lzw"
+    profile["predictor"] = 2
+
+    Z = np.random.randint(size=(SIZE, SIZE), low=0, high=8)
+
+    src = rasterio.open(path, "w", **profile)
+    for i in range(1, profile["count"] + 1):
+        src.write(Z, i)
+
+
+directories = ["2020_30m_cdls", "2021_30m_cdls"]
+raster_extensions = [[".tif", ".tif.ovr"], [".tif", ".tif.ovr"]]
+
+
+if __name__ == "__main__":
+
+    for dir, extensions in zip(directories, raster_extensions):
+        filename = dir + ".zip"
+
+        # Remove old data
+        if os.path.isdir(dir):
+            shutil.rmtree(dir)
+
+        os.makedirs(os.path.join(os.getcwd(), dir))
+
+        for e in extensions:
+            create_file(
+                os.path.join(dir, filename.replace(".zip", e)),
+                dtype="int8",
+                num_channels=1,
+            )
+
+        # Compress data
+        shutil.make_archive(filename.replace(".zip", ""), "zip", ".", dir)
+
+        # Compute checksums
+        with open(filename, "rb") as f:
+            md5 = hashlib.md5(f.read()).hexdigest()
+            print(f"{filename}: {md5}")
+
+        shutil.rmtree(dir)

tests/datasets/test_cdl.py

@@ -31,9 +31,21 @@ def dataset(
         monkeypatch.setattr(  # type: ignore[attr-defined]
             torchgeo.datasets.cdl, "download_url", download_url
         )
+        cmap = {
+            0: (0, 0, 0, 0),
+            1: (255, 211, 0, 255),
+            2: (255, 38, 38, 255),
+            3: (0, 168, 228, 255),
+            4: (255, 158, 11, 255),
+            5: (38, 112, 0, 255),
+            6: (255, 255, 0, 255),
+            7: (0, 0, 0, 255),
+            8: (0, 0, 0, 255),
+        }
+        monkeypatch.setattr(CDL, "cmap", cmap)  # type: ignore[attr-defined]
         md5s = [
-            (2021, "0693f0bb10deb79c69bcafe4aa1635b7"),
-            (2020, "7695292902a8672d16ac034d4d560d84"),
+            (2021, "4618f054004110ea11b19541b4b9f734"),
+            (2020, "593a86e62e3dd44438d536dc2442c082"),
         ]
         monkeypatch.setattr(CDL, "md5s", md5s)  # type: ignore[attr-defined]
         url = os.path.join("tests", "data", "cdl", "{}_30m_cdls.zip")

torchgeo/datasets/cdl.py

@@ -5,7 +5,7 @@
 
 import glob
 import os
-from typing import Any, Callable, Dict, Optional
+from typing import Any, Callable, Dict, Optional, Tuple
 
 from rasterio.crs import CRS
 
@@ -57,6 +57,8 @@ class CDL(RasterDataset):
         (2008, "0610f2f17ab60a9fbb3baeb7543993a4"),
     ]
 
+    cmap: Dict[int, Tuple[int, int, int, int]] = {}
+
     def __init__(
         self,
         root: str = "data",