From c32f4c082611901371f262a0ea23222d80bf4030 Mon Sep 17 00:00:00 2001
From: Andre Anjos <andre.dos.anjos@gmail.com>
Date: Thu, 19 Mar 2020 18:04:47 +0100
Subject: [PATCH] [all] Removed unused variables; Fix other return values
---
bob/ip/binseg/modeling/backbones/mobilenetv2.py | 2 +-
bob/ip/binseg/modeling/losses.py | 2 +-
bob/ip/binseg/utils/evaluate.py | 2 --
bob/ip/binseg/utils/plot.py | 1 -
4 files changed, 2 insertions(+), 5 deletions(-)
diff --git a/bob/ip/binseg/modeling/backbones/mobilenetv2.py b/bob/ip/binseg/modeling/backbones/mobilenetv2.py
index 2f4b8851..9e6cd245 100644
--- a/bob/ip/binseg/modeling/backbones/mobilenetv2.py
+++ b/bob/ip/binseg/modeling/backbones/mobilenetv2.py
@@ -83,7 +83,7 @@ class MobileNetV2(torch.nn.Module):
self.m2u = m2u
block = InvertedResidual
input_channel = 32
- last_channel = 1280
+ #last_channel = 1280
interverted_residual_setting = [
# t, c, n, s
[1, 16, 1, 1],
diff --git a/bob/ip/binseg/modeling/losses.py b/bob/ip/binseg/modeling/losses.py
index e2aa27b8..2f435c14 100644
--- a/bob/ip/binseg/modeling/losses.py
+++ b/bob/ip/binseg/modeling/losses.py
@@ -239,7 +239,7 @@ class HEDSoftJaccardBCELogitsLoss(_Loss):
loss = self.alpha * bceloss + (1 - self.alpha) * (1 - softjaccard)
loss_over_all_inputs.append(loss.unsqueeze(0))
final_loss = torch.cat(loss_over_all_inputs).mean()
- return loss
+ return final_loss
class MixJacLoss(_Loss):
diff --git a/bob/ip/binseg/utils/evaluate.py b/bob/ip/binseg/utils/evaluate.py
index 5015e5b3..11cb4c51 100644
--- a/bob/ip/binseg/utils/evaluate.py
+++ b/bob/ip/binseg/utils/evaluate.py
@@ -124,10 +124,8 @@ def do_eval(
# Collect overall metrics
metrics = []
- num_images = len(data_loader)
for samples in tqdm(data_loader):
names = samples[0]
- images = samples[1]
ground_truths = samples[2]
if prediction_extension is None:
diff --git a/bob/ip/binseg/utils/plot.py b/bob/ip/binseg/utils/plot.py
index ba85ba3d..caf75c65 100644
--- a/bob/ip/binseg/utils/plot.py
+++ b/bob/ip/binseg/utils/plot.py
@@ -354,7 +354,6 @@ def plot_overview(outputfolders, title):
re_ups = []
re_lows = []
names = []
- params = []
for folder in outputfolders:
# metrics
metrics_path = os.path.join(folder, "results/Metrics.csv")
--
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