init

datasets/stanford_cars.py

@@ -0,0 +1,48 @@
+import os
+from scipy.io import loadmat
+
+from .oxford_pets import OxfordPets
+from .utils import Datum, DatasetBase
+
+
+template = ['a photo of a {}.']
+
+
+class StanfordCars(DatasetBase):
+
+    dataset_dir = 'stanford_cars'
+
+    def __init__(self, root, num_shots):
+        self.dataset_dir = os.path.join(root, self.dataset_dir)
+        self.split_path = os.path.join(self.dataset_dir, 'split_zhou_StanfordCars.json')
+
+        self.template = template
+
+        train, val, test = OxfordPets.read_split(self.split_path, self.dataset_dir)
+        train = self.generate_fewshot_dataset(train, num_shots=num_shots)
+
+        super().__init__(train_x=train, val=val, test=test)
+    
+    def read_data(self, image_dir, anno_file, meta_file):
+        anno_file = loadmat(anno_file)['annotations'][0]
+        meta_file = loadmat(meta_file)['class_names'][0]
+        items = []
+
+        for i in range(len(anno_file)):
+            imname = anno_file[i]['fname'][0]
+            impath = os.path.join(self.dataset_dir, image_dir, imname)
+            label = anno_file[i]['class'][0, 0]
+            label = int(label) - 1 # convert to 0-based index
+            classname = meta_file[label][0]
+            names = classname.split(' ')
+            year = names.pop(-1)
+            names.insert(0, year)
+            classname = ' '.join(names)
+            item = Datum(
+                impath=impath,
+                label=label,
+                classname=classname
+            )
+            items.append(item)
+        
+        return items