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Datasets:
fsuarez
/
autotrain-data-logo_identifier_v4_short

Tasks:
Image Classification
Modalities:
Image
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Processed data from AutoTrain data processor ([2023-11-07 16:04 ]

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  1. README.md +53 -0
  2. processed/dataset_dict.json +1 -0
  3. processed/train/data-00000-of-00001.arrow +3 -0
  4. processed/train/dataset_info.json +143 -0
  5. processed/train/state.json +16 -0
  6. processed/valid/data-00000-of-00001.arrow +3 -0
  7. processed/valid/dataset_info.json +143 -0
  8. processed/valid/state.json +16 -0
README.md ADDED
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+ ---
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+ task_categories:
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+ - image-classification
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+
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+ ---
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+ # AutoTrain Dataset for project: logo_identifier_v4_short
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+
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+ ## Dataset Description
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+
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+ This dataset has been automatically processed by AutoTrain for project logo_identifier_v4_short.
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+
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+ ### Languages
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+
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+ The BCP-47 code for the dataset's language is unk.
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ A sample from this dataset looks as follows:
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+
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+ ```json
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+ [
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+ {
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+ "image": "<128x128 RGB PIL image>",
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+ "target": 98
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+ },
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+ {
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+ "image": "<100x100 RGB PIL image>",
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+ "target": 99
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+ }
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+ ]
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+ ```
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+
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+ ### Dataset Fields
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+
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+ The dataset has the following fields (also called "features"):
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+
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+ ```json
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+ {
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+ "image": "Image(decode=True, id=None)",
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+ "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', 'SumitomoGroup', '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)"
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+ }
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+ ```
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+
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+ ### Dataset Splits
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+
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+ This dataset is split into a train and validation split. The split sizes are as follow:
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+
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+ | Split name | Num samples |
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+ | ------------ | ------------------- |
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+ | train | 6884 |
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+ | valid | 1786 |
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+ "Duracell",
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+ "Dyson",
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