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README.md

@@ -23,34 +23,130 @@ dataset_info:
         class_label:
           names:
             '0': uno-deck
-            '1': '0'
-            '2': '1'
-            '3': '2'
-            '4': '3'
-            '5': '4'
-            '6': '5'
-            '7': '6'
-            '8': '7'
-            '9': '8'
-            '10': '9'
-            '11': '10'
-            '12': '11'
-            '13': '12'
-            '14': '13'
-            '15': '14'
-  splits:
-  - name: train
-    num_bytes: 434752245.0
-    num_examples: 6295
-  - name: validation
-    num_bytes: 61926629.0
-    num_examples: 899
-  - name: test
-    num_bytes: 123728246.0
-    num_examples: 1798
-  download_size: 619494243
-  dataset_size: 620407120.0
+            '1': 0
+            '2': 1
+            '3': 2
+            '4': 3
+            '5': 4
+            '6': 5
+            '7': 6
+            '8': 7
+            '9': 8
+            '10': 9
+            '11': 10
+            '12': 11
+            '13': 12
+            '14': 13
+            '15': 14
+annotations_creators:
+- crowdsourced
+language_creators:
+- found
+language:
+- en
+license:
+- cc
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- object-detection
+task_ids: []
+pretty_name: uno-deck
+tags:
+- rf100
 ---
-# Dataset Card for "uno-deck"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+# Dataset Card for uno-deck
+
+** The original COCO dataset is stored at `dataset.tar.gz`**
+
+## Dataset Description
+
+- **Homepage:** https://universe.roboflow.com/object-detection/uno-deck
+- **Point of Contact:** francesco.zuppichini@gmail.com
+
+### Dataset Summary
+
+uno-deck
+
+### Supported Tasks and Leaderboards
+
+- `object-detection`: The dataset can be used to train a model for Object Detection.
+
+### Languages
+
+English
+
+## Dataset Structure
+
+### Data Instances
+
+A data point comprises an image and its object annotations.
+
+```
+{
+  'image_id': 15,
+  'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x640 at 0x2373B065C18>,
+  'width': 964043,
+  'height': 640,
+  'objects': {
+    'id': [114, 115, 116, 117], 
+    'area': [3796, 1596, 152768, 81002],
+    'bbox': [
+      [302.0, 109.0, 73.0, 52.0],
+      [810.0, 100.0, 57.0, 28.0],
+      [160.0, 31.0, 248.0, 616.0],
+      [741.0, 68.0, 202.0, 401.0]
+    ], 
+    'category': [4, 4, 0, 0]
+  }
+}
+```
+
+### Data Fields
+
+- `image`: the image id
+- `image`: `PIL.Image.Image` object containing the image. Note that when accessing the image column: `dataset[0]["image"]` the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the `"image"` column, *i.e.* `dataset[0]["image"]` should **always** be preferred over `dataset["image"][0]`
+- `width`: the image width
+- `height`: the image height
+- `objects`: a dictionary containing bounding box metadata for the objects present on the image
+  - `id`: the annotation id
+  - `area`: the area of the bounding box
+  - `bbox`: the object's bounding box (in the [coco](https://albumentations.ai/docs/getting_started/bounding_boxes_augmentation/#coco) format)
+  - `category`: the object's category.
+
+
+#### Who are the annotators?
+
+Annotators are Roboflow users
+
+## Additional Information
+
+### Licensing Information
+
+See original homepage https://universe.roboflow.com/object-detection/uno-deck
+
+### Citation Information
+
+```
+@misc{ uno-deck,
+    title = { uno deck Dataset },
+    type = { Open Source Dataset },
+    author = { Roboflow 100 },
+    howpublished = { \url{ https://universe.roboflow.com/object-detection/uno-deck } },
+    url = { https://universe.roboflow.com/object-detection/uno-deck },
+    journal = { Roboflow Universe },
+    publisher = { Roboflow },
+    year = { 2022 },
+    month = { nov },
+    note = { visited on 2023-03-29 },
+}"
+```
+
+### Contributions
+
+Thanks to [@mariosasko](https://github.com/mariosasko) for adding this dataset.