From 7e80b2c95f5067274e5464f123770a93ad64e72a Mon Sep 17 00:00:00 2001
From: "Daniel.Frisinghelli" <daniel.frisinghelli@eurac.edu>
Date: Wed, 3 Feb 2021 17:39:53 +0100
Subject: [PATCH] Fixed a bug: NoData class is now skipped in class
distribution.
---
pysegcnn/core/dataset.py | 13 +++++++------
1 file changed, 7 insertions(+), 6 deletions(-)
diff --git a/pysegcnn/core/dataset.py b/pysegcnn/core/dataset.py
index b4ed855..b9c2107 100644
--- a/pysegcnn/core/dataset.py
+++ b/pysegcnn/core/dataset.py
@@ -32,7 +32,6 @@ import pathlib
# externals
import numpy as np
-import pandas as pd
import torch
from torch.utils.data import Dataset
@@ -41,8 +40,7 @@ from pysegcnn.core.constants import (MultiSpectralSensor, Landsat8, Sentinel2,
Label, SparcsLabels, Cloud95Labels,
AlcdLabels)
from pysegcnn.core.utils import (img2np, is_divisible, tile_topleft_corner,
- parse_landsat_scene, parse_sentinel2_scene,
- array_replace)
+ parse_landsat_scene, parse_sentinel2_scene)
# module level logger
LOGGER = logging.getLogger(__name__)
@@ -632,10 +630,13 @@ class ImageDataset(Dataset):
def class_distribution(self):
- # initialize dictionary of class spectral distribution
# exclude NoData class
+ labels = {k: v for k, v in self.labels.items() if
+ v['label'] != 'No data'}
+
+ # initialize dictionary of class spectral distribution
cls_ds = {k: np.empty(shape=(0, len(self.use_bands)), dtype=np.float32)
- for k, v in self.labels.items() if v['label'] != 'No data'}
+ for k, v in labels.items()}
# iterate over the samples of the dataset
for i in range(len(self)):
@@ -644,7 +645,7 @@ class ImageDataset(Dataset):
x, y = self[i]
# iterate over the different classes
- for k, v in self.labels.items():
+ for k, v in labels.items():
# get values equal to the current class
mask = np.where(y == k)
--
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