Uploaded dataset template

caltech_dataset.py

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+from torchvision.datasets import VisionDataset
+
+from PIL import Image
+
+import os
+import os.path
+import sys
+
+
+def pil_loader(path):
+    # open path as file to avoid ResourceWarning (https://github.com/python-pillow/Pillow/issues/835)
+    with open(path, 'rb') as f:
+        img = Image.open(f)
+        return img.convert('RGB')
+
+
+class Caltech(VisionDataset):
+    def __init__(self, root, split='train', transform=None, target_transform=None):
+        super(Caltech, self).__init__(root, transform=transform, target_transform=target_transform)
+
+        self.split = split # This defines the split you are going to use
+                           # (split files are called 'train.txt' and 'test.txt')
+
+        '''
+        - Here you should implement the logic for reading the splits files and accessing elements
+        - If the RAM size allows it, it is faster to store all data in memory
+        - PyTorch Dataset classes use indexes to read elements
+        - You should provide a way for the __getitem__ method to access the image-label pair
+          through the index
+        - Labels should start from 0, so for Caltech you will have lables 0...100 (excluding the background class) 
+        '''
+
+    def __getitem__(self, index):
+        '''
+        __getitem__ should access an element through its index
+        Args:
+            index (int): Index
+
+        Returns:
+            tuple: (sample, target) where target is class_index of the target class.
+        '''
+
+        image, label = ... # Provide a way to access image and label via index
+                           # Image should be a PIL Image
+                           # label can be int
+
+        # Applies preprocessing when accessing the image
+        if self.transform is not None:
+            image = self.transform(image)
+
+        return image, label
+
+    def __len__(self):
+        '''
+        The __len__ method returns the length of the dataset
+        It is mandatory, as this is used by several other components
+        '''
+        length = ... # Provide a way to get the length (number of elements) of the dataset
+        return length