Upload movingthings.py

movingthings.py

@@ -39,10 +39,21 @@ class MovingThings(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         return {
-            "train": self._generate_examples(split_path="data/train-00000-of-00001-92703265ee4f4424.parquet"),
-            # Add other splits like "validation" and "test" if needed
+            "train": self._generate_examples(),
         }
 
+    def _generate_examples(self):
+        # Implement your example generation logic here
+        # Return a list of dictionaries containing the features for each example
+        # You can simulate example data generation here
+        examples = [{"file_name": "soccer-ball-0.png", "text": "there is a man that is standing in the dark with a cell phone", "labels":"roll"},
+{"file_name": "sled-1.png", "text": "there is a red chair that is sitting on the sidewalk", "labels":"roll"},
+{"file_name": "steamroller-2.png", "text": "there is a large yellow pipe laying on the ground next to a yellow pole", "labels":"roll"},
+{"file_name": "hamster-wheel-3.png", "text": "there is a large circular sculpture made of colored plastic", "labels":"roll"},
+{"file_name": "skateboard-4.png", "text": "there is a skateboard that is laying on the ground", "labels":"roll"}]
+        return examples
+
+
 # Task template outside of _info()
 MovingThingsTaskTemplate = ImageClassification(image_column="image", label_column="labels")