LoL Runes Recommender With Python

Overview

LoL-Runes-Recommender

Para ejecutar la aplicación se debe llamar a execute_app.py , acá hay dos modos:

  • El modo 'get_runes' es la app final para los usuarios" en donde se ingresa una imagen de un campeón de League of Legends como consulta y se retorna los set de runas adecuados para él
    • El comando de ejecución es: python execute_app.py get_runes [cropped_image_path]

-El modo 'full_execution' sirve para realizar debugging de la app y benchmarking de tiempos. n este modo se precomputan los descriptores sift, se generan crops aleatorios de imágenes se realiza match de vectores sift con un dataset extenso y se anotan los resultados en un archivo .txt - El comando de ejecución es

`python execute_app.py full_execution [original_images_folder_path] [sift_descriptors_folder_path] [cropped_images_folder_path] [results_text_file]`

Sobre los descriptores del proyecto

Para realizar la comparación entre el screenshot del usuario y el dataset se aplica la detección de puntos de interés mediante descriptores SIFT

Los descriptores SIFT calculados para las imágenes del proyecto utilizan el método de diferencias gaussianas (Difference of Gaussians). Además al momento de comparar las imágenes de los campeones con descriptores locales se restringen los matches entre keypoints, seleccionando solos los de menor distancia con respecto a un umbral Esto solo funciona con casos "fáciles", cuando la aparición del objeto es muy parecida a la consulta, el cual es el caso del proyecto.

Owner
Sebastián Salinas
Computer Science Engineering Student at University of Chile
Sebastián Salinas
Filtering variational quantum algorithms for combinatorial optimization

Current gate-based quantum computers have the potential to provide a computational advantage if algorithms use quantum hardware efficiently.

1 Feb 09, 2022
code for Fast Point Cloud Registration with Optimal Transport

robot This is the repository for the paper "Accurate Point Cloud Registration with Robust Optimal Transport". We are in the process of refactoring the

28 Jan 04, 2023
Unofficial implementation of HiFi-GAN+ from the paper "Bandwidth Extension is All You Need" by Su, et al.

HiFi-GAN+ This project is an unoffical implementation of the HiFi-GAN+ model for audio bandwidth extension, from the paper Bandwidth Extension is All

Brent M. Spell 134 Dec 30, 2022
Detecting drunk people through thermal images using Deep Learning (CNN)

Drunk Detection CNN Detecting drunk people through thermal images using Deep Learning (CNN) Dataset We used thermal images provided by Electronics Lab

Giacomo Ferretti 3 Oct 27, 2022
Vertex AI: Serverless framework for MLOPs (ESP / ENG)

Vertex AI: Serverless framework for MLOPs (ESP / ENG) Español Qué es esto? Este repo contiene un pipeline end to end diseñado usando el SDK de Kubeflo

Hernán Escudero 2 Apr 28, 2022
TransVTSpotter: End-to-end Video Text Spotter with Transformer

TransVTSpotter: End-to-end Video Text Spotter with Transformer Introduction A Multilingual, Open World Video Text Dataset and End-to-end Video Text Sp

weijiawu 66 Dec 26, 2022
Minimal fastai code needed for working with pytorch

fastai_minima A mimal version of fastai with the barebones needed to work with Pytorch #all_slow Install pip install fastai_minima How to use This lib

Zachary Mueller 14 Oct 21, 2022
ATAC: Adversarially Trained Actor Critic

ATAC: Adversarially Trained Actor Critic Adversarially Trained Actor Critic for Offline Reinforcement Learning by Ching-An Cheng*, Tengyang Xie*, Nan

Microsoft 41 Dec 08, 2022
Linear image-to-image translation

Linear (Un)supervised Image-to-Image Translation Examples for linear orthogonal transformations in PCA domain, learned without pairing supervision. Tr

Eitan Richardson 40 Aug 31, 2022
Generative Art Using Neural Visual Grammars and Dual Encoders

Generative Art Using Neural Visual Grammars and Dual Encoders Arnheim 1 The original algorithm from the paper Generative Art Using Neural Visual Gramm

DeepMind 231 Jan 05, 2023
Implementation of Monocular Direct Sparse Localization in a Prior 3D Surfel Map (DSL)

DSL Project page: https://sites.google.com/view/dsl-ram-lab/ Monocular Direct Sparse Localization in a Prior 3D Surfel Map Authors: Haoyang Ye, Huaiya

Haoyang Ye 93 Nov 30, 2022
Official pytorch implementation of DeformSyncNet: Deformation Transfer via Synchronized Shape Deformation Spaces

DeformSyncNet: Deformation Transfer via Synchronized Shape Deformation Spaces Minhyuk Sung*, Zhenyu Jiang*, Panos Achlioptas, Niloy J. Mitra, Leonidas

Zhenyu Jiang 21 Aug 30, 2022
A python comtrade load library accelerated by go

Comtrade-GRPC Code for python used is mainly from dparrini/python-comtrade. Just patch the code in BinaryDatReader.parse for parsing a little more eff

Bo 1 Dec 27, 2021
DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks

DECAF (DEbiasing CAusal Fairness) Code Author: Trent Kyono This repository contains the code used for the "DECAF: Generating Fair Synthetic Data Using

van_der_Schaar \LAB 7 Nov 24, 2022
TensorFlow2 Classification Model Zoo playing with TensorFlow2 on the CIFAR-10 dataset.

Training CIFAR-10 with TensorFlow2(TF2) TensorFlow2 Classification Model Zoo. I'm playing with TensorFlow2 on the CIFAR-10 dataset. Architectures LeNe

Chia-Hung Yuan 16 Sep 27, 2022
Code for our TKDE paper "Understanding WeChat User Preferences and “Wow” Diffusion"

wechat-wow-analysis Understanding WeChat User Preferences and “Wow” Diffusion. Fanjin Zhang, Jie Tang, Xueyi Liu, Zhenyu Hou, Yuxiao Dong, Jing Zhang,

18 Sep 16, 2022
Multi-Scale Progressive Fusion Network for Single Image Deraining

Multi-Scale Progressive Fusion Network for Single Image Deraining (MSPFN) This is an implementation of the MSPFN model proposed in the paper (Multi-Sc

Kuijiang 128 Nov 21, 2022
Source code for Fixed-Point GAN for Cloud Detection

FCD: Fixed-Point GAN for Cloud Detection PyTorch source code of Nyborg & Assent (2020). Abstract The detection of clouds in satellite images is an ess

Joachim Nyborg 8 Dec 22, 2022
Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language (NeurIPS 2021)

VRDP (NeurIPS 2021) Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language Mingyu Ding, Zhenfang Chen, Tao Du, Pin

Mingyu Ding 36 Sep 20, 2022
Dynamic hair modeling from monocular videos using deep neural networks

Dynamic Hair Modeling The source code of the networks for our paper "Dynamic hair modeling from monocular videos using deep neural networks" (SIGGRAPH

53 Oct 18, 2022