Codebase for ECCV18 "The Sound of Pixels"

Overview

Sound-of-Pixels

Codebase for ECCV18 "The Sound of Pixels".

*This repository is under construction, but the core parts are already there.

Environment

The code is developed under the following configurations.

  • Hardware: 1-4 GPUs (change [--num_gpus NUM_GPUS] accordingly)
  • Software: Ubuntu 16.04.3 LTS, CUDA>=8.0, Python>=3.5, PyTorch>=0.4.0

Training

  1. Prepare video dataset.

    a. Download MUSIC dataset from: https://github.com/roudimit/MUSIC_dataset

    b. Download videos.

  2. Preprocess videos. You can do it in your own way as long as the index files are similar.

    a. Extract frames at 8fps and waveforms at 11025Hz from videos. We have following directory structure:

    data
    ├── audio
    |   ├── acoustic_guitar
    │   |   ├── M3dekVSwNjY.mp3
    │   |   ├── ...
    │   ├── trumpet
    │   |   ├── STKXyBGSGyE.mp3
    │   |   ├── ...
    │   ├── ...
    |
    └── frames
    |   ├── acoustic_guitar
    │   |   ├── M3dekVSwNjY.mp4
    │   |   |   ├── 000001.jpg
    │   |   |   ├── ...
    │   |   ├── ...
    │   ├── trumpet
    │   |   ├── STKXyBGSGyE.mp4
    │   |   |   ├── 000001.jpg
    │   |   |   ├── ...
    │   |   ├── ...
    │   ├── ...
    

    b. Make training/validation index files by running:

    python scripts/create_index_files.py
    

    It will create index files train.csv/val.csv with the following format:

    ./data/audio/acoustic_guitar/M3dekVSwNjY.mp3,./data/frames/acoustic_guitar/M3dekVSwNjY.mp4,1580
    ./data/audio/trumpet/STKXyBGSGyE.mp3,./data/frames/trumpet/STKXyBGSGyE.mp4,493
    

    For each row, it stores the information: AUDIO_PATH,FRAMES_PATH,NUMBER_FRAMES

  3. Train the default model.

./scripts/train_MUSIC.sh
  1. During training, visualizations are saved in HTML format under ckpt/MODEL_ID/visualization/.

Evaluation

  1. (Optional) Download our trained model weights for evaluation.
./scripts/download_trained_model.sh
  1. Evaluate the trained model performance.
./scripts/eval_MUSIC.sh

Reference

If you use the code or dataset from the project, please cite:

    @InProceedings{Zhao_2018_ECCV,
        author = {Zhao, Hang and Gan, Chuang and Rouditchenko, Andrew and Vondrick, Carl and McDermott, Josh and Torralba, Antonio},
        title = {The Sound of Pixels},
        booktitle = {The European Conference on Computer Vision (ECCV)},
        month = {September},
        year = {2018}
    }
Owner
Hang Zhao
Assistant Professor at Tsinghua University, MIT PhD in Computer Vision
Hang Zhao
Jetson Nano-based smart camera system that measures crowd face mask usage in real-time.

MaskCam MaskCam is a prototype reference design for a Jetson Nano-based smart camera system that measures crowd face mask usage in real-time, with all

BDTI 212 Dec 29, 2022
Bag of Tricks for Natural Policy Gradient Reinforcement Learning

Bag of Tricks for Natural Policy Gradient Reinforcement Learning [ArXiv] Setup Python 3.8.0 pip install -r req.txt Mujoco 200 license Main Files main.

Brennan Gebotys 1 Oct 10, 2022
Official pytorch implementation of Active Learning for deep object detection via probabilistic modeling (ICCV 2021)

Active Learning for Deep Object Detection via Probabilistic Modeling This repository is the official PyTorch implementation of Active Learning for Dee

NVIDIA Research Projects 130 Jan 06, 2023
PyTorch for Semantic Segmentation

PyTorch for Semantic Segmentation This repository contains some models for semantic segmentation and the pipeline of training and testing models, impl

Zijun Deng 1.7k Jan 06, 2023
Honours project, on creating a depth estimation map from two stereo images of featureless regions

image-processing This module generates depth maps for shape-blocked-out images Install If working with anaconda, then from the root directory: conda e

2 Oct 17, 2022
Enhancing Knowledge Tracing via Adversarial Training

Enhancing Knowledge Tracing via Adversarial Training This repository contains source code for the paper "Enhancing Knowledge Tracing via Adversarial T

Xiaopeng Guo 14 Oct 24, 2022
Official implementation for the paper: Generating Smooth Pose Sequences for Diverse Human Motion Prediction

Generating Smooth Pose Sequences for Diverse Human Motion Prediction This is official implementation for the paper Generating Smooth Pose Sequences fo

Wei Mao 28 Dec 10, 2022
PolyTrack: Tracking with Bounding Polygons

PolyTrack: Tracking with Bounding Polygons Abstract In this paper, we present a novel method called PolyTrack for fast multi-object tracking and segme

Gaspar Faure 13 Sep 15, 2022
Predicting the duration of arrival delays for commercial flights.

Flight Delay Prediction Our objective is to predict arrival delays of commercial flights. According to the US Department of Transportation, about 21%

Jordan Silke 1 Jan 11, 2022
Config files for my GitHub profile.

Canalyst Candas Data Science Library Name Canalyst Candas Description Built by a former PM / analyst to give anyone with a little bit of Python knowle

Canalyst Candas 13 Jun 24, 2022
Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation

Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation This is the implementation of the approach describ

Taosha Fan 47 Nov 15, 2022
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)

PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J

AI Wizards for Software Management (AWSM) Research Group 14 Nov 13, 2022
Oriented Object Detection: Oriented RepPoints + Swin Transformer/ReResNet

Oriented RepPoints for Aerial Object Detection The code for the implementation of “Oriented RepPoints + Swin Transformer/ReResNet”. Introduction Based

96 Dec 13, 2022
Official Implementation of "DialogLM: Pre-trained Model for Long Dialogue Understanding and Summarization."

DialogLM Code for AAAI 2022 paper: DialogLM: Pre-trained Model for Long Dialogue Understanding and Summarization. Pre-trained Models We release two ve

Microsoft 92 Dec 19, 2022
Winners of the Facebook Image Similarity Challenge

Winners of the Facebook Image Similarity Challenge

DrivenData 111 Jan 05, 2023
MGFN: Multi-Graph Fusion Networks for Urban Region Embedding was accepted by IJCAI-2022.

Multi-Graph Fusion Networks for Urban Region Embedding (IJCAI-22) This is the implementation of Multi-Graph Fusion Networks for Urban Region Embedding

202 Nov 18, 2022
The official implementation of A Unified Game-Theoretic Interpretation of Adversarial Robustness.

This repository is the official implementation of A Unified Game-Theoretic Interpretation of Adversarial Robustness. Requirements pip install -r requi

Jie Ren 17 Dec 12, 2022
Code accompanying paper: Meta-Learning to Improve Pre-Training

Meta-Learning to Improve Pre-Training This folder contains code to run experiments in the paper Meta-Learning to Improve Pre-Training, NeurIPS 2021. P

28 Dec 31, 2022
Kindle is an easy model build package for PyTorch.

Kindle is an easy model build package for PyTorch. Building a deep learning model became so simple that almost all model can be made by copy and paste from other existing model codes. So why code? wh

Jongkuk Lim 77 Nov 11, 2022
PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".

Sharpness-aware Quantization for Deep Neural Networks This is the official repository for our paper: Sharpness-aware Quantization for Deep Neural Netw

Zhuang AI Group 30 Dec 19, 2022