iris - Open Source Photos Platform Powered by PyTorch

Overview
Comments
  • 404 error on frontend

    404 error on frontend

    in brouser:

    graphql:1 Failed to load resource: the server responded with a status of 404 (Not Found)

    in console:

    frontend | 2021/11/05 09:51:37 [error] 36#36: *11 open() "/usr/share/nginx/html/graphql" failed (2: No such file or directory), client: 172.21.0.1, server: localhost, request: "POST /graphql HTTP/1.1", host: "localhost:5000", referrer: "http://localhost:5000/explore"

    WAIDW?

    frontend 
    opened by Nehc 5
  • [frontend] Show maps with pins for each place on `/explore/places`

    [frontend] Show maps with pins for each place on `/explore/places`

    • [ ] Use open street maps to show pins on each lat, long in /explore/place entities list
    • [ ] Should be a static image and should not be interactive map
    opened by prabhuomkar 1
  • [frontend] Upload Button and Explore Section List

    [frontend] Upload Button and Explore Section List

    • [x] Add upload button in Header
    • [x] Add Image Lists
    • [x] Make sure for places images have border-radius: 50% and for rest its border-radius: 4 or 8px
    opened by prabhuomkar 1
  • [frontend] Theming using `@rmwc/theme`

    [frontend] Theming using `@rmwc/theme`

    • [x] Install @rmwc/theme
    • [x] Delete unwanted custom tags which are used only due to colors
    • [x] Use <ThemeProvider /> by @rmwc and set colors via that as props
    opened by prabhuomkar 1
  • [frontend] Explore section template design

    [frontend] Explore section template design

    • [x] Add 3 single rows with SEE ALL button on top
    • [x] Name 3 rows with titles as:
      • [x] People
      • [x] Places
      • [x] Things
    • [x] Each section then will have its own page as:
      • [x] /explore/people
      • [x] /explore/places
      • [x] /explore/things
    opened by prabhuomkar 1
  • [api] Configure GitHub Action

    [api] Configure GitHub Action

    • [x] Added GitHub Action workflow for api folder
    • [x] Following tasks should be included on every PR and master:
      • [x] make lint check
      • [x] make generate check
      • [x] make build check
    opened by prabhuomkar 1
  • [frontend] Configure GitHub Action

    [frontend] Configure GitHub Action

    • [x] Added GitHub Action workflow for frontend folder
    • [x] Following tasks should be included on every PR and master:
      • [x] npm run build check
      • [x] npm run lint check
      • [x] npm test check
    opened by prabhuomkar 1
  • [worker] Using TorchScript Modules for Things Classification

    [worker] Using TorchScript Modules for Things Classification

    • Show examples for converting two SOTA models into TorchScript modules
    • Should return class names directly as result by making use of imagenet classes list
    opened by prabhuomkar 0
  • [api/worker] Invoking Worker Pipeline Components based on Environment Config

    [api/worker] Invoking Worker Pipeline Components based on Environment Config

    • Add environment variables for disabling invoking of worker pipeline components People, Places, Things
    • This should also disable similar entities from showing on UI (even if there is data generated for the same, but don't delete existing data)
    • This actions should go via queue and should be used for invoking those respective components
    opened by prabhuomkar 0
  • Github Actions for publishing Docker images to Docker Hub

    Github Actions for publishing Docker images to Docker Hub

    Docker Images should be built using 2 step process to reduce the image size:

    • [x] API - https://github.com/prabhuomkar/iris/commit/111ebc8fd51ac1eaf0d63f6a700e6d09c99c48f3
    • [x] Worker - #111

    Docker Images will be named as follows:

    • Frontend: prabhuomkar/iris-frontend:<tag>
    • GraphQL: prabhuomkar/iris-graphql:<tag>
    • Worker: prabhuomkar/iris-worker:<tag>
    • ML: prabhuomkar/iris-ml:<tag>
    opened by prabhuomkar 0
Releases(v2021.12.31)
  • v2021.12.31(Jan 1, 2022)

    What's Changed

    • Added environment variables in docker-compose.yaml by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/65
    • Added Queries and Mutations for Favourites by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/67
    • Added mutation for updating mediaItem description by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/69
    • Added image description and fixed image preview for People by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/75
    • Added Queriea and Mutations for Albums by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/72
    • Added starring/unstarring photo feature and added /favourites page by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/78
    • Refactored GraphQL API and broke down Schema Files by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/79
    • Update to imports and some minor changes done by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/82
    • #70 : Queries and Mutation for Delete by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/81
    • #77: Added On This Day Query by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/80
    • Added move to trash and restore feature by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/86
    • #83: Added albumID as a arg while uploading by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/87
    • Added albums and item count to /albums by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/89
    • Handle complex operations which comes with Deleting MediaItem by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/91
    • #90: Added mutation for adding or removing mediaItems from the album by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/92
    • #96: Return album ID in createAlbum mutation by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/97
    • #85: Added Create Album Feature by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/95
    • Added remove photos from album feature by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/98
    • Added missing people entity association for displayMediaItem by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/99
    • fixed add/remove album issue by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/100

    Full Changelog: https://github.com/prabhuomkar/iris/compare/v2021.11.01...v2021.12.31

    Source code(tar.gz)
    Source code(zip)
  • v2021.11.01(Nov 4, 2021)

    What's Changed

    • done issue #4 and issue #8 by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/9
    • Added seaweedfs client with file upload and basic info stored by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/11
    • Entity Queries, Docs and Architecture Diagram by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/17
    • Added pub/sub messaging between API and ML service by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/20
    • issue#10 explore section and upload button list by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/12
    • Metadata extraction from image files by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/22
    • LatLong calculation from Image metadata by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/23
    • Generate Places Entities using Image Metadata by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/26
    • Queue manual ack of messages by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/30
    • added image upload functionality by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/27
    • basic home section with dates and images issue#15 by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/31
    • Issue#15 by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/33
    • Fixed creationTime calc, worker metadata, UI. Fixes sorting by creationTime by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/35
    • Backend fixes for queries and showing entity info per mediaItem by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/36
    • Finished with Entity Things by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/38
    • some ui fixes done by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/39
    • Issue 41 by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/43
    • Search Queries and Worker Fixes by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/44
    • Finishing touches for ML Handlers by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/49
    • Entity people component and some refactoring by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/50
    • Added Update Entity Query and People Entity Component Finishes by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/51
    • Added explore people, edit people and some ui changes done by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/52
    • Some optimization work for worker and ml logging linter fix by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/53
    • Added photos sorting logic by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/54
    • Did some concurrency level optimizations in worker by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/55
    • minor changes done by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/56
    • Minor changes done by @akshaypithadiya in https://github.com/prabhuomkar/iris/pull/57
    • Release Fixes by @prabhuomkar in https://github.com/prabhuomkar/iris/pull/58

    New Contributors

    • @akshaypithadiya made their first contribution in https://github.com/prabhuomkar/iris/pull/9
    • @prabhuomkar made their first contribution in https://github.com/prabhuomkar/iris/pull/11

    Full Changelog: https://github.com/prabhuomkar/iris/commits/v2021.11.01

    Source code(tar.gz)
    Source code(zip)
A fast MoE impl for PyTorch

An easy-to-use and efficient system to support the Mixture of Experts (MoE) model for PyTorch.

Rick Ho 873 Jan 09, 2023
Source code and data from the RecSys 2020 article "Carousel Personalization in Music Streaming Apps with Contextual Bandits" by W. Bendada, G. Salha and T. Bontempelli

Carousel Personalization in Music Streaming Apps with Contextual Bandits - RecSys 2020 This repository provides Python code and data to reproduce expe

Deezer 48 Jan 02, 2023
Group-Free 3D Object Detection via Transformers

Group-Free 3D Object Detection via Transformers By Ze Liu, Zheng Zhang, Yue Cao, Han Hu, Xin Tong. This repo is the official implementation of "Group-

Ze Liu 213 Dec 07, 2022
SIR model parameter estimation using a novel algorithm for differentiated uniformization.

TenSIR Parameter estimation on epidemic data under the SIR model using a novel algorithm for differentiated uniformization of Markov transition rate m

The Spang Lab 4 Nov 30, 2022
This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEECH" submitted to ICASSP 2022

CPC_DeepCluster This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEEC

LEAP Lab 2 Sep 15, 2022
Point Cloud Denoising input segmentation output raw point-cloud valid/clear fog rain de-noised Abstract Lidar sensors are frequently used in environme

Point Cloud Denoising input segmentation output raw point-cloud valid/clear fog rain de-noised Abstract Lidar sensors are frequently used in environme

75 Nov 24, 2022
Trash Sorter Extraordinaire is a software which efficiently detects the different types of waste in a pile of random trash through feeding it pictures or videos.

Trash-Sorter-Extraordinaire Trash Sorter Extraordinaire is a software which efficiently detects the different types of waste in a pile of random trash

Rameen Mahmood 1 Nov 07, 2021
A self-supervised 3D representation learning framework named viewpoint bottleneck.

Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck Paper Created by Liyi Luo, Beiwen Tian, Hao Zhao and Guyue Zhou from Institute for AI In

63 Aug 11, 2022
Code for the paper "TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks"

TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks This is a Python3 / Pytorch implementation of TadGAN paper. The associated

Arun 92 Dec 03, 2022
Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras

Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras which will then be used to generate residuals

Federico Lopez 2 Jan 14, 2022
Additional environments compatible with OpenAI gym

Decentralized Control of Quadrotor Swarms with End-to-end Deep Reinforcement Learning A codebase for training reinforcement learning policies for quad

Zhehui Huang 40 Dec 06, 2022
Python Auto-ML Package for Tabular Datasets

Tabular-AutoML AutoML Package for tabular datasets Tabular dataset tuning is now hassle free! Run one liner command and get best tuning and processed

Sagnik Roy 18 Nov 20, 2022
High dimensional black-box optimizer using Latent Action Monte Carlo Tree Search algorithm

LA-MCTS The code is based of paper Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search. Component LA-MCTS has thr

Meta Research 18 Oct 24, 2022
3D-Reconstruction 基于深度学习方法的单目多视图三维重建

基于深度学习方法的单目多视图三维重建 Part I 三维重建 代码:Part1 技术文档:[Markdown] [PDF] 原始图像:Original Images 点云结果:Point Cloud Results-1

HMT_Curo 19 Dec 26, 2022
2021 Artificial Intelligence Diabetes Datathon

A.I.D.D. 2021 2021 Artificial Intelligence Diabetes Datathon A.I.D.D. 2021은 ‘2021 인공지능 학습용 데이터 구축사업’을 통해 만들어진 학습용 데이터를 활용하여 당뇨병을 효과적으로 예측할 수 있는가에 대한 A

2 Dec 27, 2021
A program that can analyze videos according to the weights you select

MaskMonitor A program that can analyze videos according to the weights you select 下載 訓練完的 weight檔案 執行 MaskDetection.py 內部可更改 輸入來源(鏡頭, 影片, 圖片) 以及輸出條件(人

Patrick_star 1 Nov 07, 2021
HNN: Human (Hollywood) Neural Network

HNN: Human (Hollywood) Neural Network Learn the top 1000 actors on IMDB with your very own low cost, highly parallel, CUDAless biological neural netwo

Madhava Jay 0 Dec 21, 2021
TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations

TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations Requirements python 3.6 torch 1.9 numpy 1.19 Quick Start The experimen

DMIRLAB 4 Oct 16, 2022
A python library for self-supervised learning on images.

Lightly is a computer vision framework for self-supervised learning. We, at Lightly, are passionate engineers who want to make deep learning more effi

Lightly 2k Jan 08, 2023
Learnable Boundary Guided Adversarial Training (ICCV2021)

Learnable Boundary Guided Adversarial Training This repository contains the implementation code for the ICCV2021 paper: Learnable Boundary Guided Adve

DV Lab 27 Sep 25, 2022