init

datasets/ucf101.py

@@ -0,0 +1,51 @@
+import os
+
+from .utils import Datum, DatasetBase, read_json, write_json, build_data_loader
+
+from .oxford_pets import OxfordPets
+
+
+template = ['a photo of a person doing {}.']
+
+
+class UCF101(DatasetBase):
+
+    dataset_dir = 'ucf101'
+
+    def __init__(self, root, num_shots):
+        self.dataset_dir = os.path.join(root, self.dataset_dir)
+        self.image_dir = os.path.join(self.dataset_dir, 'UCF-101-midframes')
+        self.split_path = os.path.join(self.dataset_dir, 'split_zhou_UCF101.json')
+
+        self.template = template
+
+        train, val, test = OxfordPets.read_split(self.split_path, self.image_dir)
+        train = self.generate_fewshot_dataset(train, num_shots=num_shots)
+
+        super().__init__(train_x=train, val=val, test=test)
+    
+    def read_data(self, cname2lab, text_file):
+        text_file = os.path.join(self.dataset_dir, text_file)
+        items = []
+
+        with open(text_file, 'r') as f:
+            lines = f.readlines()
+            for line in lines:
+                line = line.strip().split(' ')[0] # trainlist: filename, label
+                action, filename = line.split('/')
+                label = cname2lab[action]
+
+                elements = re.findall('[A-Z][^A-Z]*', action)
+                renamed_action = '_'.join(elements)
+
+                filename = filename.replace('.avi', '.jpg')
+                impath = os.path.join(self.image_dir, renamed_action, filename)
+
+                item = Datum(
+                    impath=impath,
+                    label=label,
+                    classname=renamed_action
+                )
+                items.append(item)
+        
+        return items