Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
parquet
Languages:
English
Size:
10K - 100K
License:
license: apache-2.0 | |
language: | |
- en | |
task_categories: | |
- image-classification | |
size_categories: | |
- 10K<n<100K | |
tags: | |
- Human | |
- Non-Human | |
- biology | |
# Human-vs-NonHuman Dataset | |
## Dataset Description | |
The **Human-vs-NonHuman** dataset is a collection of images designed for **image classification** tasks. The dataset consists of labeled images categorized into two classes: | |
1. **Human (Label: 0)** | |
2. **Non-Human (Label: 1)** | |
The dataset is useful for training and evaluating models in tasks such as **human detection**, **biological classification**, and **AI-assisted filtering systems**. | |
## Dataset Details | |
- **Total Samples**: 15,635 images | |
- **Image Size**: 224x224 pixels | |
- **Classes**: | |
- **Human (0)** | |
- **Non-Human (1)** | |
- **File Format**: PNG/JPG (Auto-converted to Parquet) | |
- **Dataset Size**: 116MB | |
## Usage | |
You can use this dataset with Hugging Face's `datasets` library as follows: | |
```python | |
from datasets import load_dataset | |
dataset = load_dataset("prithivMLmods/Human-vs-NonHuman") | |
``` |