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
Owner
Vincent Bour
Vincent Bour
Face recognize and crop them

Face Recognize Cropping Module Source 아이디어 Face Alignment with OpenCV and Python Requirement 필요 라이브러리 imutil dlib python-opence (cv2) Usage 사용 방법 open

Cho Moon Gi 1 Feb 15, 2022
Official PyTorch implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation

U-GAT-IT — Official PyTorch Implementation : Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Imag

Hyeonwoo Kang 2.4k Jan 04, 2023
Sinkformers: Transformers with Doubly Stochastic Attention

Code for the paper : "Sinkformers: Transformers with Doubly Stochastic Attention" Paper You will find our paper here. Compat This package has been dev

Michael E. Sander 31 Dec 29, 2022
Official Repository for Machine Learning class - Physics Without Frontiers 2021

PWF 2021 Física Sin Fronteras es un proyecto del Centro Internacional de Física Teórica (ICTP) en Trieste Italia. El ICTP es un centro dedicado a fome

36 Aug 06, 2022
An implementation of the "Attention is all you need" paper without extra bells and whistles, or difficult syntax

Simple Transformer An implementation of the "Attention is all you need" paper without extra bells and whistles, or difficult syntax. Note: The only ex

29 Jun 16, 2022
Pretrained Pytorch face detection (MTCNN) and recognition (InceptionResnet) models

Face Recognition Using Pytorch Python 3.7 3.6 3.5 Status This is a repository for Inception Resnet (V1) models in pytorch, pretrained on VGGFace2 and

Tim Esler 3.3k Jan 04, 2023
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks

StackGAN Pytorch implementation Inception score evaluation StackGAN-v2-pytorch Tensorflow implementation for reproducing main results in the paper Sta

Han Zhang 1.8k Dec 21, 2022
Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences

Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences This repository is an official PyTorch implementation of Neighbor

DIVE Lab, Texas A&M University 8 Jun 12, 2022
Multispectral Object Detection with Yolov5

Multispectral-Object-Detection Intro Official Code for Cross-Modality Fusion Transformer for Multispectral Object Detection. Multispectral Object Dete

Richard Fang 121 Jan 01, 2023
SweiNet is an uncertainty-quantifying shear wave speed (SWS) estimator for ultrasound shear wave elasticity (SWE) imaging.

SweiNet SweiNet is an uncertainty-quantifying shear wave speed (SWS) estimator for ultrasound shear wave elasticity (SWE) imaging. SweiNet takes as in

Felix Jin 3 Mar 31, 2022
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions

torch-imle Concise and self-contained PyTorch library implementing the I-MLE gradient estimator proposed in our NeurIPS 2021 paper Implicit MLE: Backp

UCL Natural Language Processing 249 Jan 03, 2023
Dados coletados e programas desenvolvidos no processo de iniciação científica

Iniciacao_cientifica_FAPESP_2020-14845-6 Dados coletados e programas desenvolvidos no processo de iniciação científica Os arquivos .py são os programa

1 Jan 10, 2022
Implementation of CVPR'21: RfD-Net: Point Scene Understanding by Semantic Instance Reconstruction

RfD-Net [Project Page] [Paper] [Video] RfD-Net: Point Scene Understanding by Semantic Instance Reconstruction Yinyu Nie, Ji Hou, Xiaoguang Han, Matthi

Yinyu Nie 162 Jan 06, 2023
This is code to fit per-pixel environment map with spherical Gaussian lobes, using LBFGS optimization

Spherical Gaussian Optimization This is code to fit per-pixel environment map with spherical Gaussian lobes, using LBFGS optimization. This code has b

41 Dec 14, 2022
The full training script for Enformer (Tensorflow Sonnet) on TPU clusters

Enformer TPU training script (wip) The full training script for Enformer (Tensorflow Sonnet) on TPU clusters, in an effort to migrate the model to pyt

Phil Wang 10 Oct 19, 2022
pq is a jq-like Pickle file viewer

pq PQ is a jq-like viewer/processing tool for pickle files. howto # pq '' file.pkl {'other': 456, 'test': 123} # pq 'table' file.pkl |other|test| | 45

3 Mar 15, 2022
Joint Gaussian Graphical Model Estimation: A Survey

Joint Gaussian Graphical Model Estimation: A Survey Test Models Fused graphical lasso [1] Group graphical lasso [1] Graphical lasso [1] Doubly joint s

Koyejo Lab 1 Aug 10, 2022
Match SafeGraph POIs with Data collected through a cultural resource survey in Washington DC.

Match SafeGraph POI data with Cultural Resource Places in Washington DC Match SafeGraph POIs with Data collected through a cultural resource survey in

Changjie Chen 1 Jan 05, 2022
Official PyTorch implementation of N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras (ICCV 2021)

N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras Official PyTorch implementation of N-ImageNet: Towards Robust, Fine-Gra

32 Dec 26, 2022
Neuron Merging: Compensating for Pruned Neurons (NeurIPS 2020)

Neuron Merging: Compensating for Pruned Neurons Pytorch implementation of Neuron Merging: Compensating for Pruned Neurons, accepted at 34th Conference

Woojeong Kim 33 Dec 30, 2022