Metadata-Version: 2.4
Name: cleanframes
Version: 0.1.0
Summary: A professional tool for cleaning duplicate or near-duplicate image frames using perceptual hashing and embeddings.
Home-page: https://github.com/abdullahalmutairi/cleanframes
Author: Abdullah Almutairi
Author-email: abdullah@example.com
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch
Requires-Dist: torchvision
Requires-Dist: transformers
Requires-Dist: timm
Requires-Dist: open_clip_torch
Requires-Dist: scikit-learn
Requires-Dist: tqdm
Requires-Dist: pillow
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: imagehash
Requires-Dist: matplotlib
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# CleanFrames

CleanFrames is a professional tool for removing duplicate or near-duplicate image frames using:
- MD5 (byte-level duplicates)
- Perceptual hashing (visual similarity)
- Deep embeddings (semantic redundancy)

## Installation

```bash
pip install cleanframes
```

## Usage
```
from clean_frames import CleanFrame

cleaner = CleanFrame(device='mps')
embeddings, paths = cleaner.SwinEmbedding("path/to/images")
cleaner.cleanframes(paths, embeddings_list=[("swin", embeddings)], threshold=0.95)
```
