Datasets:
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license: apache-2.0
task_categories:
- image-classification
language:
- en
tags:
- color-detection
- big
pretty_name: datadive
size_categories:
- 100K<n<1M
---
# datadive
**Datadive** is a large-scale **color detection dataset** containing **360,000 images**. Each image is 128x128 pixels and generated with a variety of colors, shapes, and realistic background effects. It’s ideal for testing and training models related to **color recognition, object detection, and image classification**.
## Dataset Details
- **Number of images:** 360,000
- **Image size:** 128 x 128 pixels
- **Categories / Colors:** red, green, blue, yellow, cyan, orange, black, white, gray, lime, navy, brown
- **Format:** PNG
- **Purpose:** Color detection, classification, and computer vision experiments
## Features
- Randomized **backgrounds**: solid, gradient, noise, corruption, and perlin noise.
- Random **shapes**: circles, rectangles, and triangles.
- **Lighting, shadow, and noise effects** applied for realism.
- Optional **texture overlays** for variety (stored in the `textures/` folder).
## Structure
```
datadive/
├── banner.png
├── black/
│ ├── black_1.png
│ ├── black_2.png
│ └── ...
├── blue/
│ ├── blue_1.png
│ └── ...
├── ...
├── red/
├── white/
└── yellow/
```
Each color has its own folder containing 30,000 images.
## Usage
### Using Hugging Face `datasets` (if stored as Parquet)
```python
from datasets import load_dataset
import io
from PIL import Image
dataset = load_dataset("Mafu-Labs/datadive", split="train")
for example in dataset:
img_bytes = example["image"]
img = Image.open(io.BytesIO(img_bytes))
img.show()
```
### Direct file access
```python
from PIL import Image
img = Image.open("datadive/blue/blue_1.png")
img.show()
```
## License
This dataset is released under the **Apache 2.0 License**. |