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Reliably download millions of images efficiently

License: MIT License

Python 3.46% Jupyter Notebook 96.54%

downloadconceptualcaptions's Introduction

Download Conceptual Captions Data

Place data from: https://ai.google.com/research/ConceptualCaptions/download in this folder

Train_GCC-training.tsv Training Split (3,318,333)

Validation_GCC-1.1.0-Validation.tsv Validation Split (15,840)

Test Split (~12,500) human approved image caption pairs is not public.

run download_data.py

Images will be in training and validation folders. You can stop and resume, the settings for splitting downloads into chunks / threads are not optimal, but it maxed out my connection so i kept them as is.

Note: A previous version of this script used a different file naming scheme, this changed and if you are resuming a previously started download, you will get duplicates.

A bunch of them will fail to download, and return web pages instead. These will need to be cleaned up later. See downloaded_validation_report.tsv after it downloads for HTTP errors. Around 8% of images are gone, based on validation set results. Setting the user agent could fix some errors too maybe - not sure if any requests are rejected by sites based on this.

It should take about a day or two to download the training data, keep an eye on disk space.

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