Datasets:
Tasks:
Object Detection
Languages:
English
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
crowdsourced
Source Datasets:
original
License:
| 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': pieces | |
| '1': joint | |
| '2': side | |
| 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: cell-towers | |
| tags: | |
| - rf100 | |
| # Dataset Card for cell-towers | |
| ** The original COCO dataset is stored at `dataset.tar.gz`** | |
| ## Dataset Description | |
| - **Homepage:** https://universe.roboflow.com/object-detection/cell-towers | |
| - **Point of Contact:** francesco.zuppichini@gmail.com | |
| ### Dataset Summary | |
| cell-towers | |
| ### 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/cell-towers | |
| ### Citation Information | |
| ``` | |
| @misc{ cell-towers, | |
| title = { cell towers Dataset }, | |
| type = { Open Source Dataset }, | |
| author = { Roboflow 100 }, | |
| howpublished = { \url{ https://universe.roboflow.com/object-detection/cell-towers } }, | |
| url = { https://universe.roboflow.com/object-detection/cell-towers }, | |
| 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. |