# Gameplay Images
## Dataset Description
- **Homepage:** [kaggle](https://www.kaggle.com/datasets/aditmagotra/gameplay-images)
- **Download Size** 2.50 GiB
- **Generated Size** 1.68 GiB
- **Total Size** 4.19 GiB

A dataset from [kaggle](https://www.kaggle.com/datasets/aditmagotra/gameplay-images).

This is a dataset of 10 very famous video games in the world.

These include

- Among Us
- Apex Legends
- Fortnite
- Forza Horizon
- Free Fire
- Genshin Impact
- God of War
- Minecraft
- Roblox
- Terraria

There are 1000 images per class and all are sized `640 x 360`. They are in the `.png` format.

This Dataset was made by saving frames every few seconds from famous gameplay videos on Youtube.

※ This dataset was uploaded in January 2022. Game content updated after that will not be included.

### License

CC-BY-4.0

## Dataset Structure

### Data Instance

```python
>>> from datasets import load_dataset

>>> dataset = load_dataset("Bingsu/Gameplay_Images")
DatasetDict({
    train: Dataset({
        features: ['image', 'label'],
        num_rows: 10000
    })
})
```
```python
>>> dataset["train"].features
{'image': Image(decode=True, id=None),
 'label': ClassLabel(num_classes=10, names=['Among Us', 'Apex Legends', 'Fortnite', 'Forza Horizon', 'Free Fire', 'Genshin Impact', 'God of War', 'Minecraft', 'Roblox', 'Terraria'], id=None)}
```

### Data Size

download: 2.50 GiB<br>
generated: 1.68 GiB<br>
total: 4.19 GiB

### Data Fields

- image: `Image`
    - A `PIL.Image.Image object` containing the image. size=640x360
    - Note that when accessing the image column: `dataset[0]["image"]` the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. `dataset[0]["image"]` should always be preferred over `dataset["image"][0]`.
- label: an int classification label.

Class Label Mappings:

```json
{
    "Among Us": 0,
    "Apex Legends": 1,
    "Fortnite": 2,
    "Forza Horizon": 3,
    "Free Fire": 4,
    "Genshin Impact": 5,
    "God of War": 6,
    "Minecraft": 7,
    "Roblox": 8,
    "Terraria": 9
}
```

```python
>>> dataset["train"][0]
{'image': <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=640x360>,
 'label': 0}
```


### Data Splits

|            |   train  |
| ---------- | -------- |
| # of data  |    10000 |

### Note

#### train_test_split

```python
>>> ds_new = dataset["train"].train_test_split(0.2, seed=42, stratify_by_column="label")
>>> ds_new
DatasetDict({
    train: Dataset({
        features: ['image', 'label'],
        num_rows: 8000
    })
    test: Dataset({
        features: ['image', 'label'],
        num_rows: 2000
    })
})
```

task_categories:image-classification multilinguality:monolingual size_categories:1K<n<10K language:en license:cc-by-4.0 region:us
{"language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "task_categories": ["image-classification"], "pretty_name": "Gameplay Images"}
TAGS
#task_categories-image-classification #multilinguality-monolingual #size_categories-1K<n<10K #language-English #license-cc-by-4.0 #region-us 

Gameplay Images
===============


Dataset Description
-------------------


* Homepage: kaggle
* Download Size 2.50 GiB
* Generated Size 1.68 GiB
* Total Size 4.19 GiB


A dataset from kaggle.


This is a dataset of 10 very famous video games in the world.


These include


* Among Us
* Apex Legends
* Fortnite
* Forza Horizon
* Free Fire
* Genshin Impact
* God of War
* Minecraft
* Roblox
* Terraria


There are 1000 images per class and all are sized '640 x 360'. They are in the '.png' format.


This Dataset was made by saving frames every few seconds from famous gameplay videos on Youtube.


※ This dataset was uploaded in January 2022. Game content updated after that will not be included.


### License


CC-BY-4.0


Dataset Structure
-----------------


### Data Instance


### Data Size


download: 2.50 GiB  

generated: 1.68 GiB  

total: 4.19 GiB


### Data Fields


* image: 'Image'
	+ A 'PIL.Image.Image object' containing the image. size=640x360
	+ Note that when accessing the image column: 'dataset[0]["image"]' the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. 'dataset[0]["image"]' should always be preferred over 'dataset["image"][0]'.
* label: an int classification label.


Class Label Mappings:


### Data Splits



### Note


#### train\_test\_split



### License


CC-BY-4.0


Dataset Structure
----------------- ### Data Instance ### Data Size


download: 2.50 GiB  

generated: 1.68 GiB  

total: 4.19 GiB ### Data Fields


* image: 'Image'
	+ A 'PIL.Image.Image object' containing the image. size=640x360
	+ Note that when accessing the image column: 'dataset[0]["image"]' the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. 'dataset[0]["image"]' should always be preferred over 'dataset["image"][0]'.
* label: an int classification label.


Class Label Mappings: ### Data Splits ### Note #### train\_test\_split
TAGS
#task_categories-image-classification #multilinguality-monolingual #size_categories-1K<n<10K #language-English #license-cc-by-4.0 #region-us 
 ### License


CC-BY-4.0


Dataset Structure
----------------- ### Data Instance ### Data Size


download: 2.50 GiB  

generated: 1.68 GiB  

total: 4.19 GiB ### Data Fields


* image: 'Image'
	+ A 'PIL.Image.Image object' containing the image. size=640x360
	+ Note that when accessing the image column: 'dataset[0]["image"]' the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. 'dataset[0]["image"]' should always be preferred over 'dataset["image"][0]'.
* label: an int classification label.


Class Label Mappings: ### Data Splits ### Note #### train\_test\_split
passage: TAGS
#task_categories-image-classification #multilinguality-monolingual #size_categories-1K<n<10K #language-English #license-cc-by-4.0 #region-us 
### License


CC-BY-4.0


Dataset Structure
-----------------### Data Instance### Data Size


download: 2.50 GiB  

generated: 1.68 GiB  

total: 4.19 GiB### Data Fields


* image: 'Image'
	+ A 'PIL.Image.Image object' containing the image. size=640x360
	+ Note that when accessing the image column: 'dataset[0]["image"]' the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. 'dataset[0]["image"]' should always be preferred over 'dataset["image"][0]'.
* label: an int classification label.


Class Label Mappings:### Data Splits### Note#### train\_test\_split