From 4d6e9c13dc59f0394e24895f8ab970033f2eb91a Mon Sep 17 00:00:00 2001
From: Andre Anjos <andre.dos.anjos@gmail.com>
Date: Sat, 7 Oct 2023 14:06:54 +0200
Subject: [PATCH] [saliencymap_evaluator] Improve TODO comments with more ideas
---
src/ptbench/engine/saliencymap_evaluator.py | 7 +++----
1 file changed, 3 insertions(+), 4 deletions(-)
diff --git a/src/ptbench/engine/saliencymap_evaluator.py b/src/ptbench/engine/saliencymap_evaluator.py
index 7871cefb..9a5fc156 100644
--- a/src/ptbench/engine/saliencymap_evaluator.py
+++ b/src/ptbench/engine/saliencymap_evaluator.py
@@ -93,8 +93,6 @@ def _extract_bounding_box(
* width (pixels)
* height (pixels)
"""
- # opencv implementation:
- # x, y, w, h = cv2.boundingRect(mask.astype(numpy.uint8))
x, y, x2, y2 = torchvision.ops.masks_to_boxes(torch.tensor(mask)[None, :])[
0
]
@@ -330,14 +328,15 @@ def run(
retval: dict[str, list[typing.Any]] = {}
+ # TODO: This loads the images from the dataset, but they are not useful at
+ # this point. Possibly using the contents of ``datamodule.splits`` can
+ # substantially speed this up.
for dataset_name, dataset_loader in datamodule.predict_dataloader().items():
logger.info(
f"Estimating interpretability metrics for dataset `{dataset_name}`..."
)
retval[dataset_name] = []
- # TODO: This loads the images from the dataset, but they are not useful at
- # this point...
for sample in tqdm(
dataset_loader, desc="batches", leave=False, disable=None
):
--
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