autotrain-data-processor commited on
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Processed data from AutoTrain data processor ([2023-02-02 22:46 ]

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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: csgo-weapon-classification2
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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 csgo-weapon-classification2.
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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": "<1768x718 RGB PIL image>",
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+ "target": 0
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+ },
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+ {
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+ "image": "<716x375 RGBA PIL image>",
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+ "target": 0
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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=['AK-47', 'AWP', 'Famas', 'Galil-AR', 'Glock', 'M4A1', 'M4A4', 'P-90', 'SG-553', 'UMP', 'USP'], 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 | 1100 |
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+ | valid | 275 |
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+ {"splits": ["train", "valid"]}
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+ {
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+ "citation": "",
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+ "description": "AutoTrain generated dataset",
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+ "features": {
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+ "image": {
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+ "_type": "Image"
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+ },
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+ "target": {
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+ "names": [
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+ "AK-47",
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+ "AWP",
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+ "Famas",
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+ "Galil-AR",
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+ "Glock",
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+ "M4A1",
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+ "M4A4",
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+ "P-90",
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+ "SG-553",
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+ "UMP",
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+ "USP"
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+ ],
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