podgorskiy/DareBlopy

Data Reading Blocks for Python

43
/ 100
Emerging

This tool helps deep learning practitioners efficiently load image and other data for training models. It takes collections of files, often small images, stored in ZIP archives or TFRecords, and outputs them as high-performance arrays ready for model training. Machine learning engineers and data scientists working with large datasets will find this useful for accelerating their data pipelines.

104 stars. No commits in the last 6 months. Available on PyPI.

Use this if you are a deep learning engineer or data scientist struggling with slow data loading, especially from archives or network-attached storage, during model training.

Not ideal if your primary concern is traditional file system operations or if your datasets are not primarily composed of many small files like images.

deep-learning machine-learning-engineering data-pipeline-optimization image-recognition-training dataset-preparation
Stale 6m
Maintenance 0 / 25
Adoption 9 / 25
Maturity 25 / 25
Community 9 / 25

How are scores calculated?

Stars

104

Forks

6

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Dec 07, 2020

Commits (30d)

0

Dependencies

1

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