fsuarez/autotrain-data-logo_identifier_v5_short

该数据集是用于图像分类任务的，具体项目名称为logo_identifier_v5_short。数据集由AutoTrain自动处理，包含训练集和验证集两个部分。数据实例由图像和对应的目标标签组成，图像为RGB格式的PIL图像，目标标签为ClassLabel类型，包含多个品牌名称。数据集的语言代码为unk，表示未知。

This dataset is designed for image classification tasks, with its official project name being logo_identifier_v5_short. It was automatically processed via AutoTrain, and is split into two subsets: the training set and the validation set. Each data sample consists of an image and its corresponding target label. The images are RGB-formatted PIL images, while the target labels are of the ClassLabel type, encompassing multiple brand names. The language code assigned to this dataset is "unk", which stands for unknown.

原始信息汇总

AutoTrain Dataset for project: logo_identifier_v5_short

数据集描述

该数据集由AutoTrain自动处理，用于项目logo_identifier_v5_short。

语言

数据集的语言BCP-47代码为unk。

数据集结构

数据实例

数据集的一个样本如下：

json [ { "image": "<86x100 RGB PIL image>", "target": 48 }, { "image": "<128x128 RGB PIL image>", "target": 36 } ]

数据集字段

数据集包含以下字段（也称为“特征”）：

json { "image": "Image(decode=True, id=None)", "target": "ClassLabel(names=[20thTelevision, 3M, 7Eleven, Acer, AmericanExpress, Amul, Anthem, ApolloHospitals, Apple, Armani, Asahi, Asus, Atari, Audi, Avon, Booking, Bosch, Bridgestone, British Airways, Budweiser, Burberry, BurgerKing, BuzzFeed, Canon, CocaColaZero, Coleman, Coles, Converse, CornFlakes, Corona, CostcoWholesale, Crayola, Credit Agricole, Crocs, Crunchyroll, Ctrip, Dropbox, Ducati, DunkinDonuts, Duracell, Dyson, Ethereum, ExxonMobil, FoxNews, FreddieMac, Fujitsu, Goodyear, Grubhub, Gucci, Huawei, Hudson Bay Company, HugoBoss, Hulu, Hyundai, Instagram, Intel, John Lewis & Partners, Johnson&Johnson, Kingston, LouisVuitton, Lowes, Lufthansa, Lululemon, Luxottica, MorganStanley, Motorola, MountainDew, Moutai, Movistar, Msci, Muji, Nike, Nissan, Nokia, Nvidia, Orange, Oreo, Porsche, Power China, Prada, Pringles, Publix, Puma, Purina, PwC, Qualcomm, Rolex, Rolls-Royce, RoyalCaribbean, Spotify, Sprite, Starbucks, StateBankofIndia, StateGrid, Subaru, Subway, Suning, Supreme, Suzuki, Total SA, TotalEnergies, Toyota, TripAdvisor, Twitch, Twitter, UnitedHealthCare, Universal, Volkswagen, Volvo, Wikipedia, Wipro, Wuliangye, Xiaomi, Youtube, Zoom, hennessy, iHeartRadio, koolAid], id=None)" }

数据集分割

该数据集分为训练集和验证集，分割大小如下：

分割名称	样本数量
train	6814
valid	1768