--- a
+++ b/data/etis.py
@@ -0,0 +1,38 @@
+from os import listdir
+from os.path import join
+
+import matplotlib.pyplot as plt
+from PIL.Image import open
+from torch.utils.data import Dataset, DataLoader
+from torchvision import transforms
+import data.augmentation as aug
+
+
+class EtisDataset(Dataset):
+    """
+        Dataset class that fetches Etis-LaribPolypDB images with the associated segmentation mask.
+        Used for testing.
+    """
+
+    def __init__(self, path):
+        super(EtisDataset, self).__init__()
+        self.path = path
+        self.len = len(listdir(join(self.path, "ETIS-LaribPolypDB")))
+        self.common_transforms = aug.pipeline_tranforms()
+
+    def __len__(self):
+        return self.len
+
+    def __getitem__(self, index):
+        image = self.common_transforms(
+            open(join(self.path, "ETIS-LaribPolypDB/{}.jpg".format(index + 1))).convert("RGB"))
+        mask = self.common_transforms(
+            open(join(self.path, "GroundTruth/p{}.jpg".format(index + 1))).convert("RGB"))
+        mask = (mask > 0.5).float()
+        return image, mask, index + 1
+
+
+def test_etis():
+    for x, y, in DataLoader(EtisDataset("Datasets/ETIS-LaribPolypDB")):
+        plt.imshow(x)
+        plt.show()