Metadata-Version: 2.4
Name: datasetlens
Version: 0.3.0
Summary: Dataset inspection toolkit for text and image datasets
Author: PrinceZaman-2005, airinrs
License-Expression: Apache-2.0
Keywords: dataset,inspection,image,text,validation
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy==2.5.3
Requires-Dist: pandas==3.0.5
Requires-Dist: charset-normalizer==3.5.1
Requires-Dist: langdetect==1.0.9
Requires-Dist: pillow>=10.0.0
Dynamic: license-file

# DatasetLens 🔍

Open-source dataset inspection and quality analysis toolkit for ML datasets.

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## Introduction

**Inspect your datasets before training models!**

DatasetLens helps you understand what is inside your datasets before they reach your training pipeline.

It can help identify:

* File formats
* Dataset composition
* Supported and unsupported files
* Broken or corrupt files
* Duplicate files
* Encoding and language information
* Dataset-level statistics

The goal is simple: **"Know your dataset before you train your model."**

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## Project Status

🚧 **Early Development**

DatasetLens is actively evolving.

* **v0.1.0-alpha** — Early development build (**Deleted,** due to crashes)
* **v0.2.0-alphs** — Stable text-only build <----- Typo error must not die! 💀
* **v0.3.0-alpha** — Image inspection added

Current development is focused on stability, inspection quality, and expanding supported modalities.


> **Star this repo for upcoming features or issue a request instead! 🐱**

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## Quick List

### Implemented

* Text Inspector ✅
* Image Inspector ✅

### In Development

* Duplicate Detection
* Advanced Text Inspection
* Advanced Image Inspection

### Future Modalities

* 3D Voxel
* Point Clouds
* TIFF
* Audio
* Video
* Graph
* NLP

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## Documentation

For deeper project information:

* 📚 [`Documents.md`](Documents.md) — Project documentation and technical information
* 👥 [`CONTRIBUTORS.md`](CONTRIBUTORS.md) — Contributors and acknowledgements

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