juliagusak / Dataloaders
Pytorch and TensorFlow data loaders for several audio datasets
Stars: ✭ 97
Programming Languages
python
139335 projects - #7 most used programming language
Projects that are alternatives of or similar to Dataloaders
Audio-Classification-using-CNN-MLP
Multi class audio classification using Deep Learning (MLP, CNN): The objective of this project is to build a multi class classifier to identify sound of a bee, cricket or noise.
Stars: ✭ 36 (-62.89%)
Mutual labels: dataset, audio-processing
Continuum
A clean and simple data loading library for Continual Learning
Stars: ✭ 136 (+40.21%)
Mutual labels: dataset, dataloader
Crnn With Stn
implement CRNN in Keras with Spatial Transformer Network
Stars: ✭ 83 (-14.43%)
Mutual labels: dataset
Ml Pyxis
Tool for reading and writing datasets of tensors in a Lightning Memory-Mapped Database (LMDB). Designed to manage machine learning datasets with fast reading speeds.
Stars: ✭ 93 (-4.12%)
Mutual labels: dataset
Cesi
WWW 2018: CESI: Canonicalizing Open Knowledge Bases using Embeddings and Side Information
Stars: ✭ 85 (-12.37%)
Mutual labels: dataset
Keypointnet
KeypointNet: A Large-scale 3D Keypoint Dataset Aggregated from Numerous Human Annotations (CVPR2020)
Stars: ✭ 84 (-13.4%)
Mutual labels: dataset
Body reconstruction references
Paper, dataset and code collection on human body reconstruction
Stars: ✭ 96 (-1.03%)
Mutual labels: dataset
Sigsep Mus Db
Python parser and tools for MUSDB18 Music Separation Dataset
Stars: ✭ 85 (-12.37%)
Mutual labels: dataset
Face landmark dnn
Face Landmark Detector based on Mobilenet V1
Stars: ✭ 92 (-5.15%)
Mutual labels: dataset
Julius
Open-Source Large Vocabulary Continuous Speech Recognition Engine
Stars: ✭ 1,258 (+1196.91%)
Mutual labels: audio-processing
Conmask
ConMask model described in paper Open-world Knowledge Graph Completion.
Stars: ✭ 84 (-13.4%)
Mutual labels: dataset
Core50
CORe50: a new Dataset and Benchmark for Continual Learning
Stars: ✭ 91 (-6.19%)
Mutual labels: dataset
Ccpd
[ECCV 2018] CCPD: a diverse and well-annotated dataset for license plate detection and recognition
Stars: ✭ 1,252 (+1190.72%)
Mutual labels: dataset
Pytreebank
😡😇 Stanford Sentiment Treebank loader in Python
Stars: ✭ 93 (-4.12%)
Mutual labels: dataset
Fashion Mnist
A MNIST-like fashion product database. Benchmark 👇
Stars: ✭ 9,675 (+9874.23%)
Mutual labels: dataset
Hands Detection
Hands video tracker using the Tensorflow Object Detection API and Faster RCNN model. The data used is the Hand Dataset from University of Oxford.
Stars: ✭ 87 (-10.31%)
Mutual labels: dataset
Bond
BOND: BERT-Assisted Open-Domain Name Entity Recognition with Distant Supervision
Stars: ✭ 96 (-1.03%)
Mutual labels: dataset
dataloaders
Pytorch and TFRecords data loaders for several audio datasets
Datasets
- ESC - dataset of environmental sounds
- [x] ESC Downloader
- [x] Pytorch DataSet
- [x] TFRecords Loader
- LibriSpeech - corpus of read English speech
- [x] LibriSpeech downloader for PyTorch
- [x] PyTorch DataSet
- [x] PyTorch DataSet for TFRecord
- [x] PyTorch DataLoaders for TFRecord
- [x] TFRecords Loader
- [x] TFRecords Generator
- NSynth - dataset of annotated musical notes
- [x] NSynth downloader and generator of *.h5py and *.tfrecord formats
- [x] TFRecord reader
- [x] PyTorch Dataset
- [x] PyTorch Dataset for TFrecord
- [x] PyTorch DataLoaders for TFRecord
- VoxCeleb2 - human speech, extracted from YouTube interview videos
- [ ] Pytorch loader
- [ ] TFRecords loader
- GTZAN - audio tracks from a variety of sources annotated with genre class
- [x] GTZAN Downloader
- [x] PyTorch DataSet
- CallCenter - audio tracks with human and non-human speech
- [x] PyTorch DataSet
For validation we frequently use the following scheme:
- Read 10 random crops from a file;
- Predict a class for each crop;
- Averaging results.
For this scheme we've done additional DataLoaders for PyTorch:
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].