Francesco/smoke-uvylj
收藏资源简介：
--- 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': smoke-0 '1': smoke 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: smoke-uvylj tags: - rf100 --- # Dataset Card for smoke-uvylj ** The original COCO dataset is stored at `dataset.tar.gz`** ## Dataset Description - **Homepage:** https://universe.roboflow.com/object-detection/smoke-uvylj - **Point of Contact:** francesco.zuppichini@gmail.com ### Dataset Summary smoke-uvylj ### 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/smoke-uvylj ### Citation Information ``` @misc{ smoke-uvylj, title = { smoke uvylj Dataset }, type = { Open Source Dataset }, author = { Roboflow 100 }, howpublished = { \url{ https://universe.roboflow.com/object-detection/smoke-uvylj } }, url = { https://universe.roboflow.com/object-detection/smoke-uvylj }, 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.
--- dataset_info: 特征: - 名称: image_id 数据类型: int64 - 名称: image 数据类型: 图像 - 名称: width 数据类型: int32 - 名称: height 数据类型: int32 - 名称: objects 序列类型: - 名称: id 数据类型: int64 - 名称: area 数据类型: int64 - 名称: bbox 序列类型: float32 长度: 4 - 名称: category 数据类型: 类别标签: 名称映射: '0': smoke-0 '1': smoke 标注创建者: - 众包 语言创建者: - 采集自公开数据源 语言: - 英语 许可协议: - CC 多语言属性: - 单语言 样本量范围: - 1000 < 样本数 < 10000 源数据集: - 原生数据集 任务类别: - 目标检测 任务子项: [] 数据集简称: smoke-uvylj 标签: - RF100 --- # smoke-uvylj 数据集卡片 **原始COCO格式数据集存储于`dataset.tar.gz`** ## 数据集说明 - **主页**: https://universe.roboflow.com/object-detection/smoke-uvylj - **联系方式**: francesco.zuppichini@gmail.com ### 数据集概述 smoke-uvylj ### 支持任务与排行榜 - `目标检测`: 该数据集可用于训练目标检测模型。 ### 语言 英语 ## 数据集结构 ### 数据实例 每个数据样本包含一幅图像及其目标标注信息。 { '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] } } ### 数据字段说明 - `image_id`: 图像唯一标识符 - `image`: 包含图像的`PIL.Image.Image`对象。请注意，当访问图像列时：`dataset[0]["image"]`会自动对图像文件进行解码。解码大量图像文件可能会耗费大量时间，因此建议优先通过样本索引再指定图像列进行查询，即**始终优先使用`dataset[0]["image"]`而非`dataset["image"][0]`** - `width`: 图像宽度 - `height`: 图像高度 - `objects`: 包含图像中目标的边界框元数据的字典 - `id`: 标注编号 - `area`: 边界框的面积 - `bbox`: 目标的边界框（采用[COCO](https://albumentations.ai/docs/getting_started/bounding_boxes_augmentation/#coco)格式） - `category`: 目标所属类别。 #### 标注人员说明 标注人员为Roboflow平台用户。 ## 附加信息 ### 许可信息 详见原主页: https://universe.roboflow.com/object-detection/smoke-uvylj ### 引用信息 @misc{ smoke-uvylj, title = { smoke uvylj 数据集 }, type = { 开源数据集 }, author = { Roboflow 100 }, howpublished = { url{ https://universe.roboflow.com/object-detection/smoke-uvylj } }, url = { https://universe.roboflow.com/object-detection/smoke-uvylj }, journal = { Roboflow Universe }, publisher = { Roboflow }, year = { 2022 }, month = { 11月 }, note = { 访问于 2023-03-29 }, } ### 贡献致谢 感谢[@mariosasko](https://github.com/mariosasko)为本数据集的收录提供支持。
数据集概述
数据集名称
- 名称: smoke-uvylj
数据集特征
- 特征:
image_id: 整数类型image: 图像类型width: 整数类型height: 整数类型objects: 序列类型，包含以下子特征:id: 整数类型area: 整数类型bbox: 序列类型，长度为4，浮点数类型category: 类别标签，包含类别名称
数据集结构
- 数据实例:
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每个数据点包含一张图片及其对象标注信息。
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示例结构:
{ 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] } }
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数据字段
image: 图片对象width: 图片宽度height: 图片高度objects: 包含对象信息的字典id: 标注IDarea: 边界框面积bbox: 对象边界框category: 对象类别
数据集用途
- 任务: 对象检测
数据集详情
- 语言: 英语
- 许可证: cc
- 多语言性: 单语种
- 大小类别: 1K<n<10K
- 来源: 原始数据集
- 标签: rf100
