---
license: mit
language:
- en
pretty_name: Logolens Industeries for Logo Classification
size_categories:
- n<1K
---

# Dataset Name: LogoLens Industries

## Dataset Summary
The `logolens-industries` dataset provides a comprehensive classification of industries based on the Global Industry Classification Standard (GICS). This dataset is designed for tasks such as industry-specific logo analysis, branding research, and AI-based categorization of visual or textual elements.

- **Version**: 1.0.0
- **Homepage**: [Hugging Face Dataset Page](https://huggingface.co/datasets/tiny-factories/logolens-industries)
- **License**: MIT

---

## Supported Tasks and Use Cases
This dataset can be used for:
- **Classification**: Categorize logos, companies, or products into industries and subcategories.
- **Analysis**: Identify trends in specific industry segments.
- **Prediction**: Train AI models to predict industry association based on input data.

---

## Dataset Structure
The dataset consists of a flattened structure for better usability, including the following fields:

| Field               | Type          | Description                                                         | Example                             |
|---------------------|---------------|---------------------------------------------------------------------|-------------------------------------|
| `name`              | `string`      | Name of the industry.                                               | "Energy"                            |
| `description`       | `string`      | Brief description of the industry.                                  | "Companies involved in energy..."  |
| `subcategories`     | `list[string]`| Subcategories within the industry.                                  | "Energy Equipment & Services..."   |
| `code`              | `string`      | Industry code (if available).                                       | "10"                                |
| `geographical_scope`| `string`      | The geographical scope of the industry (e.g., global or regional).  | "Global"                            |

---

## Example Rows
### Example 1: Energy Industry
```json
{
  "name": "Energy",
  "description": "Companies involved in energy equipment and services, oil, gas, and consumable fuels",
  "subcategories": "Energy Equipment & Services, Oil, Gas & Consumable Fuels, Renewable Energy Equipment, Energy Storage",
  "code": "10",
  "geographical_scope": "Global"
}
```

### Example 2: Information Technology
```json
{
  "name": "Information Technology",
  "description": "Companies that develop or distribute technological products and services",
  "subcategories": "Software & Services, Technology Hardware & Equipment, Semiconductors",
  "code": "45",
  "geographical_scope": "Global"
}
```

---

## Usage
Here’s how to load and use the dataset with the Hugging Face `datasets` library:

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("tiny-factories/logolens-industries")

# View a sample
print(dataset["train"][0])
```

---

## Dataset Creation
This dataset was created by curating industry classifications based on GICS standards. The descriptions and subcategories were verified to ensure alignment with real-world industry use cases.

---

## Considerations for Use
- **Biases**: This dataset is based on GICS classifications, which may not represent all industries globally.
- **Limitations**: Industry descriptions may overlap, and subcategories could vary based on different classification systems.

---

## Citation
```bibtex
@misc{logolens-industries,
  author = {gndclouds},
  title = {LogoLens Industries Dataset},
  year = {2024}
}
```

---

## License
This dataset is licensed under the MIT License.