Duplicate from Francesco/cloud-types

Co-authored-by: Zuppichini <Francesco@users.noreply.huggingface.co>

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README.md

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+---
+dataset_info:
+  features:
+  - name: image_id
+    dtype: int64
+  - name: image
+    dtype: image
+  - name: width
+    dtype: int32
+  - name: height
+    dtype: int32
+  - name: objects
+    sequence:
+    - name: id
+      dtype: int64
+    - name: area
+      dtype: int64
+    - name: bbox
+      sequence: float32
+      length: 4
+    - name: category
+      dtype:
+        class_label:
+          names:
+            '0': cloud-types
+            '1': Fish
+            '2': Flower
+            '3': Gravel
+            '4': Sugar
+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: cloud-types
+tags:
+- rf100
+---
+
+# Dataset Card for cloud-types
+
+** The original COCO dataset is stored at `dataset.tar.gz`**
+
+## Dataset Description
+
+- **Homepage:** https://universe.roboflow.com/object-detection/cloud-types
+- **Point of Contact:** francesco.zuppichini@gmail.com
+
+### Dataset Summary
+
+cloud-types
+
+### 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/cloud-types
+
+### Citation Information
+
+```
+@misc{ cloud-types,
+    title = { cloud types Dataset },
+    type = { Open Source Dataset },
+    author = { Roboflow 100 },
+    howpublished = { \url{ https://universe.roboflow.com/object-detection/cloud-types } },
+    url = { https://universe.roboflow.com/object-detection/cloud-types },
+    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.

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dataset_info.json

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+{"description": "\ncloud types - v1 release\n==============================\n\nThis dataset was exported via roboflow.com on July 25, 2022 at 8:10 PM GMT\n\nRoboflow is an end-to-end computer vision platform that helps you\n* collaborate with your team on computer vision projects\n* collect & organize images\n* understand unstructured image data\n* annotate, and create datasets\n* export, train, and deploy computer vision models\n* use active learning to improve your dataset over time\n\nIt includes 5040 images.\nCloud-types are annotated in COCO format.\n\nThe following pre-processing was applied to each image:\n* Auto-orientation of pixel data (with EXIF-orientation stripping)\n* Resize to 640x640 (Stretch)\n\nNo image augmentation techniques were applied.\n\n\n", "citation": "@misc{ cloud-types,\n    title = { cloud types Dataset },\n    type = { Open Source Dataset },\n    author = { Roboflow 100 },\n    howpublished = { \\url{ https://universe.roboflow.com/object-detection/cloud-types } },\n    url = { https://universe.roboflow.com/object-detection/cloud-types },\n    journal = { Roboflow Universe },\n    publisher = { Roboflow },\n    year = { 2022 },\n    month = { nov },\n    note = { visited on 2023-03-29 },\n}\"", "homepage": "https://universe.roboflow.com/object-detection/cloud-types", "license": "CC BY 4.0", "features": {"image_id": {"dtype": "int64", "_type": "Value"}, "image": {"_type": "Image"}, "width": {"dtype": "int32", "_type": "Value"}, "height": {"dtype": "int32", "_type": "Value"}, "objects": {"feature": {"id": {"dtype": "int64", "_type": "Value"}, "area": {"dtype": "int64", "_type": "Value"}, "bbox": {"feature": {"dtype": "float32", "_type": "Value"}, "length": 4, "_type": "Sequence"}, "category": {"names": ["cloud-types", "Fish", "Flower", "Gravel", "Sugar"], "_type": "ClassLabel"}}, "_type": "Sequence"}}, "builder_name": "dataset", "config_name": "default", "version": {"version_str": "1.0.0", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 318742745, "num_examples": 3528, "dataset_name": "dataset"}, "validation": {"name": "validation", "num_bytes": 45555030, "num_examples": 504, "dataset_name": "dataset"}, "test": {"name": "test", "num_bytes": 91459396, "num_examples": 1008, "dataset_name": "dataset"}}, "download_checksums": {"https://huggingface.co/datasets/Francesco/cloud-types/resolve/main/dataset.tar.gz": {"num_bytes": 454436466, "checksum": null}}, "download_size": 454436466, "dataset_size": 455757171, "size_in_bytes": 910193637}