| --- |
| task_categories: |
| - image-classification |
|
|
| --- |
| # Dataset for project: csgo-weapon-classification |
|
|
| ## Dataset Description |
|
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| This dataset has for project csgo-weapon-classification was collected with the help of a bulk google image downloader. |
|
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| ### Languages |
|
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| The BCP-47 code for the dataset's language is unk. |
|
|
| ## Dataset Structure |
|
|
| ### Data Instances |
|
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| A sample from this dataset looks as follows: |
|
|
| ```json |
| [ |
| { |
| "image": "<1768x718 RGB PIL image>", |
| "target": 0 |
| }, |
| { |
| "image": "<716x375 RGBA PIL image>", |
| "target": 0 |
| } |
| ] |
| ``` |
|
|
| ### Dataset Fields |
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| The dataset has the following fields (also called "features"): |
|
|
| ```json |
| { |
| "image": "Image(decode=True, id=None)", |
| "target": "ClassLabel(names=['AK-47', 'AWP', 'Famas', 'Galil-AR', 'Glock', 'M4A1', 'M4A4', 'P-90', 'SG-553', 'UMP', 'USP'], id=None)" |
| } |
| ``` |
|
|
| ### Dataset Splits |
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| This dataset is split into a train and validation split. The split sizes are as follow: |
|
|
| | Split name | Num samples | |
| | ------------ | ------------------- | |
| | train | 1100 | |
| | valid | 275 | |
|
|
