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COCO-Text Dataset
Load the COCO-Text dataset in Python with one line of code in seconds and plug it in TensorFlow and PyTorch with Activeloop Hub.
Visualization of the COCO-Text Train Dataset on the Activeloop Platform

COCO-Text dataset

What is COCO-Text Dataset?

The COCO-Text (Common Objects in Context - Text) Dataset objective is to solve scene text detection and recognition using the largest scene text dataset. The dataset was created using real scene imagery. The dataset is structured around three tasks such as End-To-End Recognition, Cropped Word Recognition, and Text Localization.
The dataset created using images of complex everyday scenes and contains various other images which were collected by not keeping in mind of text tasks, this has resulted in presence of vast and diverse amount of text instances in these images.
The dataset was annotated with location in terms of bounding box, fine-grained classification into machine printed text and handwritten text, classification into legible and illegible text, script of the text, and transcriptions of legible text. Currently, the dataset contains total of 173,589 labeled text regions in over 63,686 images.

Download COCO-Text Dataset in Python

Instead of downloading the COCO-Text dataset in Python, you can effortlessly load it in Python via our open-source package Hub with just one line of code.

Load COCO-Text Train Subset Dataset in Python

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import hub
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ds = hub.load("hub://activeloop/coco-text-train")
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Load COCO-Text Test Subset Dataset in Python

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import hub
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ds = hub.load("hub://activeloop/coco-text-test")
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COCO-Text Dataset Structure

COCO-Text Data Fields

  • images: tensor containing images of the dataset
  • masks: tensor containing masks of respective image
  • boxes: tensor containing bounding boxes of respective image
  • languages: tensor containing language of the text
  • legibilities: tensor containing legibility of the text
  • classes: tensor containing class of the text
  • utf8_strings: tensor containing text of the image
  • areas: tensor containing the area of the text region
  • images_meta: tensor containing image metadata

How to use COCO-Text Dataset with PyTorch and TensorFlow in Python

Train a model on COCO-Text dataset with PyTorch in Python

Let's use Hub's built-in PyTorch one-line dataloader to connect the data to the compute:
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dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)
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Train a model on COCO-Text dataset with TensorFlow in Python

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dataloader = ds.tensorflow()
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Additional Information about COCO-Text Dataset

COCO-Text Dataset Description

COCO-Text Dataset Curators

Veit, A., Matera, T., Neumann, L., Matas, J., & Belongie

COCO-Text Dataset Licensing Information

The annotations in this dataset belong to the SE(3) Computer Vision Group at Cornell Tech and are licensed under a Creative Commons Attribution 4.0 License.

COCO-Text Dataset Citation Information

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@article{veit2016coco,
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title={Coco-text: Dataset and benchmark for text detection and recognition in natural images},
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author={Veit, Andreas and Matera, Tomas and Neumann, Lukas and Matas, Jiri and Belongie, Serge},
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journal={arXiv preprint arXiv:1601.07140},
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year={2016}
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}
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