forgeryscope 0.0.1

Tools for the competition

Forgeryscope

A Python package for panel detection, embedding, and matching using deep learning.

A simplified and refactored version of my winning solution for the Kaggle Scientific Image Forgery Detection competition.

Features

• Panel Detection - Extract panels from images using YOLO-based detection
• Image Embedding - Generate embeddings using PyTorch models
• Panel Matching - Match corresponding panels using LightGlue

Installation

pip install forgeryscope

Quick Start

from forgeryscope import PanelExtractor, Embedder, LightGlueOverlap

# Extract panels from an image
extractor = PanelExtractor()
panels = extractor.extract("image.jpg")

# Generate embeddings
embedder = Embedder()
embeddings = embedder.embed(panels)

# Match panels across images
matcher = LightGlueOverlap()
matches = matcher.match(embeddings1, embeddings2)

Requirements

• Python >= 3.8
• PyTorch >= 1.9.0
• torchvision >= 0.10.0
• OpenCV >= 4.5.0
• And other dependencies listed in pyproject.toml

License

This project is licensed under the MIT License - see the LICENSE file for details.

Author

Uladzislau Leketush ([e-mail])