Code of the lileonardo team for the 2021 Emotion and Theme Recognition in Music task of MediaEval 2021

Overview

Emotion and Theme Recognition in Music

The repository contains code for the submission of the lileonardo team to the 2021 Emotion and Theme Recognition in Music task of MediaEval 2021 (results).

Requirements

  • python >= 3.7
  • pip install -r requirements.txt in a virtual environment
  • Download data from the MTG-Jamendo Dataset in data/jamendo. Audio files go to data/jamendo/mp3 and melspecs to data/jamendo/melspecs.
  • Process 128 bands mel spectrograms and store them in data/jamendo/melspecs2 by running:
    python preprocess.py experiments/preprocessing/melspecs2.json

Usage

Run python main.py experiments/DIR where DIR contains the parameters.

Parameters are overridable by command line arguments:

python main.py --help
usage: main.py [-h] [--data_dir DATA] [--num_workers NUM] [--restart_training] [--restore_name NAME]
               [--num_epochs EPOCHS] [--learning_rate LR] [--weight_decay WD] [--dropout DROPOUT]
               [--batch_size BS] [--manual_seed SEED] [--model MODEL] [--loss LOSS]
               [--calculate_stats]
               DIRECTORY

Train according to parameters in DIRECTORY

positional arguments:
  DIRECTORY            path of the directory containing parameters

optional arguments:
  -h, --help           show this help message and exit
  --data_dir DATA      path of the directory containing data (default: data)
  --num_workers NUM    number of workers for dataloader (default: 4)
  --restart_training   overwrite previous training (default is to resume previous training)
  --restore_name NAME  name of checkpoint to restore (default: last)
  --num_epochs EPOCHS  override number of epochs in parameters
  --learning_rate LR   override learning rate
  --weight_decay WD    override weight decay
  --dropout DROPOUT    override dropout
  --batch_size BS      override batch size
  --manual_seed SEED   override manual seed
  --model MODEL        override model
  --loss LOSS          override loss
  --calculate_stats    recalculate mean and std of data (default is to calculate only when they
                       don't exist in parameters)

Ensemble predictions

The predictions are averaged by running:

python average.py --outputs experiments/convs-m96*/predictions/test-last-swa-outputs.npy --targets experiments/convs-m96*/predictions/test-last-swa-targets.npy --preds_path predictions/convs.npy
python average.py --outputs experiments/filters-m128*/predictions/test-last-swa-outputs.npy --targets experiments/filters-m128*/predictions/test-last-swa-targets.npy --preds_path predictions/filters.npy
python average.py --outputs predictions/convs.npy predictions/filters.npy --targets predictions/targets.npy
You might also like...
This repo contains implementation of different architectures for emotion recognition in conversations.
This repo contains implementation of different architectures for emotion recognition in conversations.

Emotion Recognition in Conversations Updates 🔥 🔥 🔥 Date Announcements 03/08/2021 🎆 🎆 We have released a new dataset M2H2: A Multimodal Multiparty

Testing the Facial Emotion Recognition (FER) algorithm on animations
Testing the Facial Emotion Recognition (FER) algorithm on animations

PegHeads-Tutorial-3 Testing the Facial Emotion Recognition (FER) algorithm on animations

 Tensorflow Implementation for
Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition"

Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition" Pre-trained Deep Convo

Emotion Recognition from Facial Images
Emotion Recognition from Facial Images

Reconhecimento de Emoções a partir de imagens faciais Este projeto implementa um classificador simples que utiliza técncias de deep learning e transfe

E2e music remastering system - End-to-end Music Remastering System Using Self-supervised and Adversarial Training
E2e music remastering system - End-to-end Music Remastering System Using Self-supervised and Adversarial Training

End-to-end Music Remastering System This repository includes source code and pre

 Source code for our paper
Source code for our paper "Improving Empathetic Response Generation by Recognizing Emotion Cause in Conversations"

Source code for our paper "Improving Empathetic Response Generation by Recognizing Emotion Cause in Conversations" this repository is maintained by bo

Music source separation is a task to separate audio recordings into individual sources

Music Source Separation Music source separation is a task to separate audio recordings into individual sources. This repository is an PyTorch implmeme

PyTorch implementation of ECCV 2020 paper "Foley Music: Learning to Generate Music from Videos "

Foley Music: Learning to Generate Music from Videos This repo holds the code for the framework presented on ECCV 2020. Foley Music: Learning to Genera

Implement face detection, and age and gender classification, and emotion classification.
Implement face detection, and age and gender classification, and emotion classification.

YOLO Keras Face Detection Implement Face detection, and Age and Gender Classification, and Emotion Classification. (image from wider face dataset) Ove

Owner
Vincent Bour
Vincent Bour
HackBMU-5.0-Team-Ctrl-Alt-Elite - HackBMU 5.0 Team Ctrl Alt Elite

HackBMU-5.0-Team-Ctrl-Alt-Elite The search is over. We present to you ‘Health-A-

null 3 Feb 19, 2022
Rank1 Conversation Emotion Detection Task

Rank1-Conversation_Emotion_Detection_Task accuracy macro-f1 recall 0.826 0.7544 0.719 基于预训练模型和时序预测模型的对话情感探测任务 1 摘要 针对对话情感探测任务,本文将其分为文本分类和时间序列预测两个子任务,分

Yuchen Han 2 Nov 28, 2021
Deepface is a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for python

deepface Deepface is a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for python. It is a hybrid

Kushal Shingote 2 Feb 10, 2022
GDSC-ML Team Interview Task

GDSC-ML-Team---Interview-Task Task 1 : Clean or Messy room In this task we have to classify the given test images as clean or messy. - Link for datase

Aayush. 1 Jan 19, 2022
DexterRedTool - Dexter's Red Team Tool that creates cronjob/task scheduler to consistently creates users

DexterRedTool Author: Dexter Delandro CSEC 473 - Spring 2022 This tool persisten

null 2 Feb 16, 2022
Method for facial emotion recognition compitition of Xunfei and Datawhale .

人脸情绪识别挑战赛-第3名-W03KFgNOc-源代码、模型以及说明文档 队名:W03KFgNOc 排名:3 正确率: 0.75564 队员:yyMoming,xkwang,RichardoMu。 比赛链接:人脸情绪识别挑战赛 文章地址:link emotion 该项目分别训练八个模型并生成csv文

null 6 Oct 17, 2022
Face Recognition and Emotion Detector Device

Face Recognition and Emotion Detector Device Orange PI 1 Python 3.10.0 + Django 3.2.9 Project's file explanation Django manage.py Django commands hand

BootyAss 2 Dec 21, 2021
A real-time speech emotion recognition application using Scikit-learn and gradio

Speech-Emotion-Recognition-App A real-time speech emotion recognition application using Scikit-learn and gradio. Requirements librosa==0.6.3 numpy sou

Son Tran 6 Oct 4, 2022
Speech Emotion Recognition with Fusion of Acoustic- and Linguistic-Feature-Based Decisions

APSIPA-SER-with-A-and-T This code is the implementation of Speech Emotion Recognition (SER) with acoustic and linguistic features. The network model i

kenro515 3 Jan 4, 2023
An Api for Emotion recognition.

PLAYEMO Playemo was built from the ground-up with Flask, a python tool that makes it easy for developers to build APIs. Use Cases Is Python your langu

greek geek 2 Jul 16, 2022