semvec/pypi-packages huggingface dataset:
dinohash-onnx 0.1.0
Generate perceptual hashes for images using DinoHash
License: MIT
Requires Python: >=3.10
Keywords: cryptography, machine-learning, phash, computer-vision, onnx

# DINOHash ONNX

Python implementation of DINOHash using ONNX Runtime, from https://www.arxiv.org/abs/2503.11195

This is a Python port of the Node.js implementation, providing perceptual image hashing using ONNX models.

## Installation

```bash
uv add dinohash-onnx
```

## Usage

```python
from dinohash_onnx import DINOHash
import os

hash = DINOHash()
hash_hex = hash.hash(image_path)
print(f"Hex: {hash_hex}")
```

## Example

See `examples/example.py` for a complete working example.

## License

MIT

## Citation

If you use this library in your research, please cite:

```bibtex
@article{dinohash2025,
  title={DINOHash: Perceptual Image Hashing with Vision Transformers},
  journal={arXiv preprint arXiv:2503.11195},
  year={2025}
}
```
Spark 0.3.2
Spark AI Development Kit
License: MIT
Requires Python: <4.0,>=3.12

# Spark

Spark is an Python ADK (AI Development Kit).

## Get started

    pip install spark

## Running examples

See [examples/README.md](examples/README.md) for more details.

If you already installed spark with (pip install spark), you can run examples directly:

    python examples/e001_hello.py

If you clone the repo:

```bash
python -m examples.e001_hello
```