|
--- |
|
task_categories: |
|
- image-classification |
|
|
|
--- |
|
# Dataset for project: csgo-weapon-classification |
|
|
|
## Dataset Description |
|
|
|
This dataset has for project csgo-weapon-classification was collected with the help of a bulk google image downloader. |
|
|
|
### Languages |
|
|
|
The BCP-47 code for the dataset's language is unk. |
|
|
|
## Dataset Structure |
|
|
|
### Data Instances |
|
|
|
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 |
|
|
|
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 |
|
|
|
This dataset is split into a train and validation split. The split sizes are as follow: |
|
|
|
| Split name | Num samples | |
|
| ------------ | ------------------- | |
|
| train | 1100 | |
|
| valid | 275 | |
|
|