little update

scripts/evaluate_semantic_segmentation.py

@@ -1,6 +1,6 @@
 """
 Evaluation script for semantic segmentation for dronescapes. Outputs F1Score and mIoU for the 8 classes and each frame.
-Usage: ./evaluate_semantic_segmentation.py y_dir gt_dir -o results.csv
+Usage: ./evaluate_semantic_segmentation.py y_dir gt_dir --classes C1 C2 ... Cn -o results.csv
 """
 import sys
 import os
@@ -84,17 +84,19 @@ def main(args: Namespace):
     if not args.output_path.exists():
         sema_repr = partial(SemanticRepresentation, classes=args.classes, color_map=[[0, 0, 0]] * len(args.classes))
         reader = MultiTaskDataset(temp_dir, handle_missing_data="drop", task_types={"pred": sema_repr, "gt": sema_repr})
-        df = compute_raw_stats_per_class(reader, args.classes)
-        res = pd.concat([do_one_class(df, class_name) for class_name in args.classes])
-        res.to_csv(args.output_path)
+        raw_stats = compute_raw_stats_per_class(reader, args.classes)
         logger.info(f"Stored raw metrics file to: '{args.output_path}'")
+        raw_stats.to_csv(args.output_path)
     else:
-        logger.info(f"Loading raw metris from: '{args.output_path}'. Delete this file if you want to recompute.")
-        res = pd.read_csv(args.output_path, index_col=0)
+        logger.info(f"Loading raw metrics from: '{args.output_path}'. Delete this file if you want to recompute.")
+        raw_stats = pd.read_csv(args.output_path, index_col=0)
+
+    metrics_per_class = pd.concat([do_one_class(raw_stats, class_name) for class_name in args.classes])
 
     final_agg = []
     for scene in args.scenes:
-        final_agg.append(compute_final_per_scene(res, scene, classes=args.classes, class_weights=args.class_weights))
+        final_agg.append(compute_final_per_scene(metrics_per_class, scene, classes=args.classes,
+                                                 class_weights=args.class_weights))
     final_agg = pd.DataFrame(final_agg, columns=["scene", "iou", "f1"]).set_index("scene")
     if len(args.scenes) > 1:
         final_agg.loc["mean"] = final_agg.mean()