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NaiveDev/coco-2017-instance

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Hugging Face2024-02-01 更新2025-11-02 收录
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https://hf-mirror.com/datasets/NaiveDev/coco-2017-instance
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--- dataset_info: features: - name: image dtype: image - name: annotations dtype: image - name: objects struct: - 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 - name: height dtype: int64 - name: width dtype: int64 - name: date_captured dtype: string - name: license dtype: class_label: names: '0': Attribution-NonCommercial-ShareAlike License '1': Attribution-NonCommercial License '2': Attribution-NonCommercial-NoDerivs License '3': Attribution License '4': Attribution-ShareAlike License '5': Attribution-NoDerivs License '6': No known '7': United States Government Work - name: coco_url dtype: string - name: flickr_url dtype: string splits: - name: train num_bytes: 19938543197.152 num_examples: 117266 - name: validation num_bytes: 811750075.52 num_examples: 4952 - name: test num_bytes: 6492416417.58 num_examples: 40670 download_size: 26960423195 dataset_size: 27242709690.252 --- # Dataset Card for "coco-2017-instance" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

数据集信息: 特征: - 名称:图像(image),数据类型:图像 - 名称:标注(annotations),数据类型:图像 - 名称:目标对象(objects),为结构化字段,包含: - 边界框(bbox):序列类型,元素为单精度浮点数(float32) - 类别(categories):序列类型,元素为分类标签,对应名称如下: '0': 人(person) '1': 自行车(bicycle) '2': 轿车(car) '3': 摩托车(motorcycle) '4': 飞机(airplane) '5': 公共汽车(bus) '6': 火车(train) '7': 卡车(truck) '8': 船只(boat) '9': 交通信号灯(traffic light) '10': 消防栓(fire hydrant) '11': 停车让行标志(stop sign) '12': 停车计时器(parking meter) '13': 长椅(bench) '14': 鸟类(bird) '15': 猫(cat) '16': 狗(dog) '17': 马(horse) '18': 绵羊(sheep) '19': 奶牛(cow) '20': 大象(elephant) '21': 熊(bear) '22': 斑马(zebra) '23': 长颈鹿(giraffe) '24': 背包(backpack) '25': 雨伞(umbrella) '26': 手提包(handbag) '27': 领带(tie) '28': 行李箱(suitcase) '29': 飞盘(frisbee) '30': 滑雪板(skis) '31': 单板滑雪板(snowboard) '32': 运动球类(sports ball) '33': 风筝(kite) '34': 棒球棒(baseball bat) '35': 棒球手套(baseball glove) '36': 滑板(skateboard) '37': 冲浪板(surfboard) '38': 网球拍(tennis racket) '39': 瓶子(bottle) '40': 葡萄酒杯(wine glass) '41': 杯子(cup) '42': 叉子(fork) '43': 餐刀(knife) '44': 勺子(spoon) '45': 碗(bowl) '46': 香蕉(banana) '47': 苹果(apple) '48': 三明治(sandwich) '49': 橙子(orange) '50': 西兰花(broccoli) '51': 胡萝卜(carrot) '52': 热狗(hot dog) '53': 披萨(pizza) '54': 甜甜圈(donut) '55': 蛋糕(cake) '56': 椅子(chair) '57': 长沙发(couch) '58': 盆栽植物(potted plant) '59': 床(bed) '60': 餐桌(dining table) '61': 马桶(toilet) '62': 电视机(tv) '63': 笔记本电脑(laptop) '64': 鼠标(mouse) '65': 遥控器(remote) '66': 键盘(keyboard) '67': 手机(cell phone) '68': 微波炉(microwave) '69': 烤箱(oven) '70': 烤面包机(toaster) '71': 水槽(sink) '72': 冰箱(refrigerator) '73': 书籍(book) '74': 时钟(clock) '75': 花瓶(vase) '76': 剪刀(scissors) '77': 泰迪熊(teddy bear) '78': 吹风机(hair drier) '79': 牙刷(toothbrush) - 目标面积(area):序列类型,元素为单精度浮点数(float32) - 是否为群体目标(iscrowd):序列类型,元素为布尔值 - 名称:图像高度(height),数据类型:64位整型(int64) - 名称:图像宽度(width),数据类型:64位整型(int64) - 名称:拍摄日期(date_captured),数据类型:字符串 - 名称:许可证(license),为分类标签类型,对应名称如下: '0': 署名-非商业使用-相同方式共享许可(Attribution-NonCommercial-ShareAlike License) '1': 署名-非商业使用许可(Attribution-NonCommercial License) '2': 署名-非商业使用-禁止演绎许可(Attribution-NonCommercial-NoDerivs License) '3': 署名许可(Attribution License) '4': 署名-相同方式共享许可(Attribution-ShareAlike License) '5': 署名-禁止演绎许可(Attribution-NoDerivs License) '6': 无已知版权限制(No known) '7': 美国政府作品(United States Government Work) - 名称:COCO官方链接(coco_url),数据类型:字符串 - 名称:Flickr平台链接(flickr_url),数据类型:字符串 数据集划分: - 划分名称:训练集(train),占用字节数:19938543197.152,样本数量:117266 - 划分名称:验证集(validation),占用字节数:811750075.52,样本数量:4952 - 划分名称:测试集(test),占用字节数:6492416417.58,样本数量:40670 下载总大小:26960423195 字节 数据集总占用大小:27242709690.252 字节 --- # "coco-2017-instance"数据集卡片 [需补充更多信息](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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