Use none instead of an empty list to make sure features across all splits are consistent (part 00001-of-00002) (#3)

- Use none instead of an empty list to make sure features across all splits are consistent (part 00001-of-00002) (afa4e025812971a4d630c563544565168f3d59e7)

README.md

@@ -1,123 +1,40 @@
 ---
+task_categories:
+- object-detection
 dataset_info:
   features:
   - name: image_id
     dtype: string
   - name: image
     dtype: image
-  - name: objects
-    struct:
+  - name: label_bbox
+    list:
     - name: bbox
-      sequence:
-        sequence: float32
-    - name: categories
-      sequence:
-        class_label:
-          names:
-            '0': person
-            '1': bicycle
-            '2': car
-            '3': motorcycle
-            '4': airplane
-            '5': bus
-            '6': train
-            '7': truck
-            '8': boat
-            '9': traffic light
-            '10': fire hydrant
-            '11': stop sign
-            '12': parking meter
-            '13': bench
-            '14': bird
-            '15': cat
-            '16': dog
-            '17': horse
-            '18': sheep
-            '19': cow
-            '20': elephant
-            '21': bear
-            '22': zebra
-            '23': giraffe
-            '24': backpack
-            '25': umbrella
-            '26': handbag
-            '27': tie
-            '28': suitcase
-            '29': frisbee
-            '30': skis
-            '31': snowboard
-            '32': sports ball
-            '33': kite
-            '34': baseball bat
-            '35': baseball glove
-            '36': skateboard
-            '37': surfboard
-            '38': tennis racket
-            '39': bottle
-            '40': wine glass
-            '41': cup
-            '42': fork
-            '43': knife
-            '44': spoon
-            '45': bowl
-            '46': banana
-            '47': apple
-            '48': sandwich
-            '49': orange
-            '50': broccoli
-            '51': carrot
-            '52': hot dog
-            '53': pizza
-            '54': donut
-            '55': cake
-            '56': chair
-            '57': couch
-            '58': potted plant
-            '59': bed
-            '60': dining table
-            '61': toilet
-            '62': tv
-            '63': laptop
-            '64': mouse
-            '65': remote
-            '66': keyboard
-            '67': cell phone
-            '68': microwave
-            '69': oven
-            '70': toaster
-            '71': sink
-            '72': refrigerator
-            '73': book
-            '74': clock
-            '75': vase
-            '76': scissors
-            '77': teddy bear
-            '78': hair drier
-            '79': toothbrush
-    - name: area
-      sequence: float32
-    - name: iscrowd
-      sequence: bool
+      sequence: int64
+    - name: bbox_id
+      dtype: string
+    - name: label
+      dtype: string
   - name: issues
     list:
     - name: confidence
       dtype: float64
     - name: description
-      dtype: 'null'
+      dtype: string
     - name: issue_type
       dtype: string
   splits:
   - name: train
-    num_bytes: 13410501369
+    num_bytes: 13436697177.0
     num_examples: 82081
   - name: validation
-    num_bytes: 6593725253
+    num_bytes: 6606403140.0
     num_examples: 40137
   - name: test
-    num_bytes: 6653522091
+    num_bytes: 6653024122.0
     num_examples: 40775
-  download_size: 26604054770
-  dataset_size: 26657748713
+  download_size: 26617129269
+  dataset_size: 26696124439.0
 configs:
 - config_name: default
   data_files:
@@ -127,8 +44,6 @@ configs:
     path: data/validation-*
   - split: test
     path: data/test-*
-task_categories:
-- object-detection
 ---
 
 [![Visualize Dataset on Visual Layer](https://img.shields.io/badge/Visualize%20on-%20Visual%20Layer-purple?style=for-the-badge&logo=numpy)](https://app.visual-layer.com/dataset/acd886ce-2b9f-11ef-bb10-e605d78f584b/data?p=1&page=1)

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