train: associate ground-truth paths w/ input paths

requirements.txt

@@ -5,6 +5,7 @@ numpy==1.12.1
 olefile==0.44
 opencv-contrib-python==3.2.0.7
 packaging==16.8
+pathlib==1.0.1
 Pillow==4.1.1
 py==1.4.33
 pyparsing==2.2.0

train

@@ -0,0 +1,38 @@
+#!/usr/bin/env python
+
+from argparse import ArgumentParser
+from pathlib import Path
+
+p = ArgumentParser(description="Train the neural network.")
+p.add_argument(
+    "dir",
+    type=str,
+    help="directory containing the training files",
+)
+p.add_argument(
+    "--truth-subdir",
+    default="ground truth",
+    type=str,
+    help="subdirectory of training directory containing ground truth files",
+)
+p.add_argument(
+    "--input-subdir",
+    default="rainy image",
+    type=str,
+    help="subdirectory of training directory containing training input files",
+)
+p.add_argument(
+    "--ext",
+    default=".jpg",
+    type=str,
+    help="truth and input file extensions",
+)
+
+if __name__ == "__main__":
+    a = p.parse_args()
+
+    paths_truth_to_inputs = {
+        t: Path(a.dir, a.input_subdir).glob(t.stem + "_[0-9]*" + a.ext)
+        for t in Path(a.dir, a.truth_subdir).iterdir()
+        if t.suffix == a.ext
+    }