README.md

---
license: mit
task_categories:
- image-text-to-text
- image-feature-extraction
language:
- en
pretty_name: Colorbar Range Dataset
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: image_id
    dtype: string
  - name: label
    struct:
    - name: Blue
      sequence: int64
    - name: Green
      sequence: int64
    - name: Yellow
      sequence: int64
    - name: Orange
      sequence: int64
    - name: Dark Orange
      sequence: int64
    - name: Red
      sequence: int64
    - name: Dark Red
      sequence: int64
    - name: Magenta
      sequence: int64
    - name: Pink
      sequence: int64
    - name: Purple
      sequence: int64
  - name: image
    dtype: image
  splits:
  - name: train
    num_bytes: 956621.0
    num_examples: 80
  download_size: 942355
  dataset_size: 956621.0
---

# Colorbar Range Dataset

This dataset contains vertical colorbar images annotated with structured
numeric ranges for each color segment. These colorbars are commonly used in
scientific plots, heatmaps, and machine learning visualizations.

Each image is paired with metadata describing the numeric range represented
by each color.

---

## Dataset Structure

Each sample contains:

- `image` : Colorbar image (PNG)
- `image_id` : Unique identifier for the image
- `label` (or `ranges`) : Dictionary mapping color name → numeric range

### Example Annotation

```json
{
  "Blue": [0, 10],
  "Green": [10, 15],
  "Yellow": [15, 20],
  "Orange": [20, 25],
  "Red": [25, 30]
}
```
---
---
license: mit
task_categories:
- image-text-to-text
- image-feature-extraction
language:
- en
pretty_name: Colorbar Range Dataset
---

---

# Colorbar Range Dataset

This dataset contains vertical colorbar images annotated with structured
numeric ranges for each color segment. These colorbars are commonly used in
scientific plots, heatmaps, and machine learning visualizations.

---

## How to Use

### 1. Install Dependencies

```bash
pip install datasets pillow

```
### 2. Load the Dataset from Hugging Face

```bash
from datasets import load_dataset

dataset = load_dataset(
    "menasi11/colorbar-range-dataset",
    split="train"
)

sample = dataset[0]
sample["image"].show()


```