PyTorch experiments with the Zalando fashion-mnist dataset

Overview

zalando-pytorch

PyTorch experiments with the Zalando fashion-mnist dataset

Project Organization

├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── docs               <- A default Sphinx project; see sphinx-doc.org for details
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
│
├── references         <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── src                <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module
│   │
│   ├── data           <- Scripts to download or generate data
│   │   └── make_dataset.py
│   │
│   ├── features       <- Scripts to turn raw data into features for modeling
│   │   └── build_features.py
│   │
│   ├── models         <- Scripts to train models and then use trained models to make
│   │   │                 predictions
│   │   ├── predict_model.py
│   │   └── train_model.py
│   │
│   └── visualization  <- Scripts to create exploratory and results oriented visualizations
│       └── visualize.py
│
└── tox.ini            <- tox file with settings for running tox; see tox.testrun.org

Project based on the cookiecutter data science project template. #cookiecutterdatascience

Owner
Federico Baldassarre
Passionate about AI, data science, and SW Engineering, BSc in Computer Engineering @unibo Bologna, MSc in Machine Learning + PhD candidate at @KTH Stockholm
Federico Baldassarre
Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2

Graph Transformer - Pytorch Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2. This was recently used by bot

Phil Wang 97 Dec 28, 2022
Implementation of UNet on the Joey ML framework

Independent Research Project - Code Joey can be cloned from here https://github.com/devitocodes/joey/. Devito and other dependencies such as PyTorch a

Navjot Kukreja 1 Oct 21, 2021
U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI

U-Net for brain segmentation U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI based on a deep learning segmentation alg

562 Jan 02, 2023
Algorithm to texture 3D reconstructions from multi-view stereo images

MVS-Texturing Welcome to our project that textures 3D reconstructions from images. This project focuses on 3D reconstructions generated using structur

Nils Moehrle 766 Jan 04, 2023
DeepSpamReview: Detection of Fake Reviews on Online Review Platforms using Deep Learning Architectures. Summer Internship project at CoreView Systems.

Detection of Fake Reviews on Online Review Platforms using Deep Learning Architectures Dataset: https://s3.amazonaws.com/fast-ai-nlp/yelp_review_polar

Ashish Salunkhe 37 Dec 17, 2022
PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence) and pre-trained model on ImageNet dataset

Reference-Based-Sketch-Image-Colorization-ImageNet This is a PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization usin

Yuzhi ZHAO 11 Jul 28, 2022
E2EDNA2 - An automated pipeline for simulation of DNA aptamers complexed with small molecules and short peptides

E2EDNA2 - An automated pipeline for simulation of DNA aptamers complexed with small molecules and short peptides

11 Nov 08, 2022
Pytorch code for "Text-Independent Speaker Verification Using 3D Convolutional Neural Networks".

:speaker: Deep Learning & 3D Convolutional Neural Networks for Speaker Verification

Amirsina Torfi 114 Dec 18, 2022
Line-level Handwritten Text Recognition (HTR) system implemented with TensorFlow.

Line-level Handwritten Text Recognition with TensorFlow This model is an extended version of the Simple HTR system implemented by @Harald Scheidl and

Hoàng Tùng Lâm (Linus) 72 May 07, 2022
The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

Deep High-Resolution Representation Learning for Human Pose Estimation (CVPR 2019) News [2020/07/05] A very nice blog from Towards Data Science introd

Leo Xiao 3.9k Jan 05, 2023
Edison AT is software Depression Assistant personal.

Edison AT Edison AT is software / program Depression Assistant personal. Feature: Analyze emotional real-time from face. Audio Edison(Comingsoon relea

Ananda Rauf 2 Apr 24, 2022
(JMLR'19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

Python Outlier Detection (PyOD) Deployment & Documentation & Stats Build Status & Coverage & Maintainability & License PyOD is a comprehensive and sca

Yue Zhao 6.6k Jan 03, 2023
[CVPR'22] COAP: Learning Compositional Occupancy of People

COAP: Compositional Articulated Occupancy of People Paper | Video | Project Page This is the official implementation of the CVPR 2022 paper COAP: Lear

Marko Mihajlovic 111 Dec 11, 2022
[WACV21] Code for our paper: Samuel, Atzmon and Chechik, "From Generalized zero-shot learning to long-tail with class descriptors"

DRAGON: From Generalized zero-shot learning to long-tail with class descriptors Paper Project Website Video Overview DRAGON learns to correct the bias

Dvir Samuel 25 Dec 06, 2022
【CVPR 2021, Variational Inference Framework, PyTorch】 From Rain Generation to Rain Removal

From Rain Generation to Rain Removal (CVPR2021) Hong Wang, Zongsheng Yue, Qi Xie, Qian Zhao, Yefeng Zheng, and Deyu Meng [PDF&&Supplementary Material]

Hong Wang 48 Nov 23, 2022
Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋

How to eat TensorFlow2 in 30 days ? 🔥 🔥 Click here for Chinese Version(中文版) 《10天吃掉那只pyspark》 🚀 github项目地址: https://github.com/lyhue1991/eat_pyspark

lyhue1991 9.7k Jan 01, 2023
[CVPR'21] FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space

FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space by Quande Liu, Cheng Chen, Ji

Quande Liu 178 Jan 06, 2023
Tackling the Class Imbalance Problem of Deep Learning Based Head and Neck Organ Segmentation

Info This is the code repository of the work Tackling the Class Imbalance Problem of Deep Learning Based Head and Neck Organ Segmentation from Elias T

2 Apr 20, 2022
Semantic Segmentation of images using PixelLib with help of Pascalvoc dataset trained with Deeplabv3+ framework.

CARscan- Approach 1 - Segmentation of images by detecting contours. It failed because in images with elements along with cars were also getting detect

Padmanabha Banerjee 5 Jul 29, 2021
Adversarial-autoencoders - Tensorflow implementation of Adversarial Autoencoders

Adversarial Autoencoders (AAE) Tensorflow implementation of Adversarial Autoencoders (ICLR 2016) Similar to variational autoencoder (VAE), AAE imposes

Qian Ge 236 Nov 13, 2022