Metadata-Extractor - Metadata Extractor Script can be used to read in exif metadata

Overview

Metadata Extractor

The exifextract script can be used to read in exif metadata from all .jpg images in a given directory location and save the formattted result to a .csv file. This program extracts a pre-specified number of relevant exif tags (fields) for each image read.

Below is an example of the .csv output.

example .csv output

Adversarial Framework for (non-) Parametric Image Stylisation Mosaics

Fully Adversarial Mosaics (FAMOS) Pytorch implementation of the paper "Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Imag

Zalando Research 120 Dec 24, 2022
Tweesent-back - Tweesent backend uses fastAPI as the web framework

TweeSent Backend Tweesent backend. This repo uses fastAPI as the web framework.

0 Mar 26, 2022
基于tensorflow 2.x的图片识别工具集

Classification.tf2 基于tensorflow 2.x的图片识别工具集 功能 粗粒度场景图片分类 细粒度场景图片分类 其他场景图片分类 模型部署 tensorflow serving本地推理和docker部署 tensorRT onnx ... 数据集 https://hyper.a

Wei Qi 1 Nov 03, 2021
HybridNets: End-to-End Perception Network

HybridNets: End2End Perception Network HybridNets Network Architecture. HybridNets: End-to-End Perception Network by Dat Vu, Bao Ngo, Hung Phan 📧 FPT

Thanh Dat Vu 370 Dec 29, 2022
MLJetReconstruction - using machine learning to reconstruct jets for CMS

MLJetReconstruction - using machine learning to reconstruct jets for CMS The C++ data extraction code used here was based heavily on that foundv here.

ALPhA Davidson 0 Nov 17, 2021
A whale detector design for the Kaggle whale-detector challenge!

CNN (InceptionV1) + STFT based Whale Detection Algorithm So, this repository is my PyTorch solution for the Kaggle whale-detection challenge. The obje

Tarin Ziyaee 92 Sep 28, 2021
BEAMetrics: Benchmark to Evaluate Automatic Metrics in Natural Language Generation

BEAMetrics: Benchmark to Evaluate Automatic Metrics in Natural Language Generation Installing The Dependencies $ conda create --name beametrics python

7 Jul 04, 2022
The offcial repository for 'CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos', SIGIR2022

CharacterBERT-DR The offcial repository for CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos, Sh

ielab 11 Nov 15, 2022
Deep Ensemble Learning with Jet-Like architecture

Ransomware analysis using DEL with jet-like architecture comprising two CNN wings, a sparse AE tail, a non-linear PCA to produce a diverse feature space, and an MLP nose

Ahsen Nazir 2 Feb 06, 2022
Target Propagation via Regularized Inversion

Target Propagation via Regularized Inversion The present code implements an ideal formulation of target propagation using regularized inverses compute

Vincent Roulet 0 Dec 02, 2021
🔊 Audio and fastai v2

Fastaudio An audio module for fastai v2. We want to help you build audio machine learning applications while minimizing the need for audio domain expe

152 Dec 28, 2022
A High-Quality Real Time Upscaler for Anime Video

Anime4K Anime4K is a set of open-source, high-quality real-time anime upscaling/denoising algorithms that can be implemented in any programming langua

15.7k Jan 06, 2023
Scalable machine learning based time series forecasting

mlforecast Scalable machine learning based time series forecasting. Install PyPI pip install mlforecast Optional dependencies If you want more functio

Nixtla 145 Dec 24, 2022
Linear Variational State Space Filters

Linear Variational State Space Filters To set up the environment, use the provided scripts in the docker/ folder to build and run the codebase inside

0 Dec 13, 2021
Forecasting with Gradient Boosted Time Series Decomposition

ThymeBoost ThymeBoost combines time series decomposition with gradient boosting to provide a flexible mix-and-match time series framework for spicy fo

131 Jan 08, 2023
deep learning for image processing including classification and object-detection etc.

深度学习在图像处理中的应用教程 前言 本教程是对本人研究生期间的研究内容进行整理总结,总结的同时也希望能够帮助更多的小伙伴。后期如果有学习到新的知识也会与大家一起分享。 本教程会以视频的方式进行分享,教学流程如下: 1)介绍网络的结构与创新点 2)使用Pytorch进行网络的搭建与训练 3)使用Te

WuZhe 13.6k Jan 04, 2023
A library for Deep Learning Implementations and utils

deeply A Deep Learning library Table of Contents Features Quick Start Usage License Features Python 2.7+ and Python 3.4+ compatible. Quick Start $ pip

Achilles Rasquinha 1 Dec 12, 2022
Unsupervised Learning of Video Representations using LSTMs

Unsupervised Learning of Video Representations using LSTMs Code for paper Unsupervised Learning of Video Representations using LSTMs by Nitish Srivast

Elman Mansimov 341 Dec 20, 2022
CL-Gym: Full-Featured PyTorch Library for Continual Learning

CL-Gym: Full-Featured PyTorch Library for Continual Learning CL-Gym is a small yet very flexible library for continual learning research and developme

Iman Mirzadeh 36 Dec 25, 2022
Generate image analogies using neural matching and blending

neural image analogies This is basically an implementation of this "Image Analogies" paper, In our case, we use feature maps from VGG16. The patch mat

Adam Wentz 3.5k Jan 08, 2023