PhotoHolmes: a Python library for forgery detection in digital images

• URL: http://arxiv.org/abs/2412.14969v1
• Date: Thu, 19 Dec 2024 15:47:31 GMT
• Title: PhotoHolmes: a Python library for forgery detection in digital images
• Authors: Julián O'Flaherty, Rodrigo Paganini, Juan Pablo Sotelo, Julieta Umpiérrez, Marina Gardella, Matías Tailanian, Pablo Musé,
• Abstract summary: PhotoHolmes is an open-source library designed to easily run and benchmark forgery detection methods on digital images. PhotoHolmes includes a command-line interface (CLI) to easily run the methods implemented in the library on any suspicious image.
• Score: 0.9423257767158634
• License:
• Abstract: In this paper, we introduce PhotoHolmes, an open-source Python library designed to easily run and benchmark forgery detection methods on digital images. The library includes implementations of popular and state-of-the-art methods, dataset integration tools, and evaluation metrics. Utilizing the Benchmark tool in PhotoHolmes, users can effortlessly compare various methods. This facilitates an accurate and reproducible comparison between their own methods and those in the existing literature. Furthermore, PhotoHolmes includes a command-line interface (CLI) to easily run the methods implemented in the library on any suspicious image. As such, image forgery methods become more accessible to the community. The library has been built with extensibility and modularity in mind, which makes adding new methods, datasets and metrics to the library a straightforward process. The source code is available at https://github.com/photoholmes/photoholmes.

Related papers

• PyPulse: A Python Library for Biosignal Imputation [58.35269251730328]
  We introduce PyPulse, a Python package for imputation of biosignals in both clinical and wearable sensor settings. PyPulse's framework provides a modular and extendable framework with high ease-of-use for a broad userbase, including non-machine-learning bioresearchers. We released PyPulse under the MIT License on Github and PyPI.
  arXiv  Detail & Related papers  (2024-12-09T11:00:55Z)
• A Python library for efficient computation of molecular fingerprints [0.0]
  We create a Python library that computes molecular fingerprints efficiently and delivers an interface that is comprehensive. The library enables the user to perform computation on large datasets using parallelism. We show that using molecular fingerprints we can achieve results comparable to state-of-the-art ML solutions.
  arXiv  Detail & Related papers  (2024-03-27T19:02:09Z)
• GRLib: An Open-Source Hand Gesture Detection and Recognition Python Library [0.0]
  We present GRLib: an open-source Python library able to detect and classify static and dynamic hand gestures. The library can be trained on existing data for improved classification robustness. It was found that the library outperforms another publicly available HGR system - MediaPipe Solutions.
  arXiv  Detail & Related papers  (2023-10-23T13:24:21Z)
• PyGOD: A Python Library for Graph Outlier Detection [56.33769221859135]
  PyGOD is an open-source library for detecting outliers in graph data. It supports a wide array of leading graph-based methods for outlier detection. PyGOD is released under a BSD 2-Clause license at https://pygod.org and at the Python Package Index (PyPI)
  arXiv  Detail & Related papers  (2022-04-26T06:15:21Z)
• LibFewShot: A Comprehensive Library for Few-shot Learning [78.58842209282724]
  Few-shot learning, especially few-shot image classification, has received increasing attention and witnessed significant advances in recent years. Some recent studies implicitly show that many generic techniques or tricks, such as data augmentation, pre-training, knowledge distillation, and self-supervision, may greatly boost the performance of a few-shot learning method. We propose a comprehensive library for few-shot learning (LibFewShot) by re-implementing seventeen state-of-the-art few-shot learning methods in a unified framework with the same single intrinsic in PyTorch.
  arXiv  Detail & Related papers  (2021-09-10T14:12:37Z)
• Solo-learn: A Library of Self-supervised Methods for Visual Representation Learning [83.02597612195966]
  solo-learn is a library of self-supervised methods for visual representation learning. Implemented in Python, using Pytorch and Pytorch lightning, the library fits both research and industry needs.
  arXiv  Detail & Related papers  (2021-08-03T22:19:55Z)
• Small-Text: Active Learning for Text Classification in Python [23.87081733039124]
  small-text is an easy-to-use active learning library for Python. It offers pool-based active learning for single- and multi-label text classification.
  arXiv  Detail & Related papers  (2021-07-21T19:23:56Z)
• SacreROUGE: An Open-Source Library for Using and Developing Summarization Evaluation Metrics [74.28810048824519]
  SacreROUGE is an open-source library for using and developing summarization evaluation metrics. The library provides Python wrappers around the official implementations of existing evaluation metrics. It provides functionality to evaluate how well any metric implemented in the library correlates to human-annotated judgments.
  arXiv  Detail & Related papers  (2020-07-10T13:26:37Z)
• PyRetri: A PyTorch-based Library for Unsupervised Image Retrieval by Deep Convolutional Neural Networks [49.35908338404728]
  PyRetri is an open source library for deep learning based unsupervised image retrieval. It encapsulates the retrieval process in several stages and provides functionality that covers various prominent methods for each stage.
  arXiv  Detail & Related papers  (2020-05-02T10:17:18Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.