Add instructions for generating fake images

tests/data/README.md

@@ -0,0 +1,44 @@
+This directory contains fake data used to test torchgeo. Depending on the type of dataset, fake data can be created in one of two ways:
+
+## GeoDataset
+
+GeoDataset data can be created like so. We first open an existing data example and use it to copy the driver/CRS/transform to the fake data.
+
+```python
+import os
+
+import numpy as np
+import rasterio
+
+ROOT = "/mnt/blobfuse/adam-scratch/landsat8"
+FILENAME = "LC08_L2SP_023032_20210622_20210629_02_T1_SR_B1.TIF"
+Z = np.array([[0, 0], [0, 0]], dtype=np.uint16)
+
+src = rasterio.open(os.path.join(ROOT, FILENAME))
+dst = rasterio.open(FILENAME, "w", driver=src.driver, height=Z.shape[0], width=Z.shape[1], count=1, dtype=Z.dtype, crs=src.crs, transform=src.transform)
+dst.write(Z, 1)
+```
+
+If the dataset expects multiple files, you can simply copy and rename the file you created.
+
+## VisionDataset
+
+VisionDataset data can be created like so.
+
+### RGB images
+
+```python
+from PIL import Image
+
+img = Image.new("RGB", (1, 1))
+img.save("01.png")
+```
+
+### Grayscale images
+
+```python
+from PIL import Image
+
+img = Image.new("L", (1, 1))
+img.save("02.jpg")
+```