Large-scale Street View Text with Partial Labeling (ICDAR-2019 LSVT)

Ground Truth

Transcription for the LSVT dataset

2019-05-29 (v. 1)

Contact author

Yipeng Sun

Baidu Inc, Beijing, China

sunyipeng@baidu.com

13264022002

+86 10 56082834


This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

Keywords

Description

For all images with full annotations in the dataset, we create a single JSON file to store the ground-truths in a structured format, following the naming convention:

    gt_[image_id], image_id refers to the index of the image in the dataset.

In the JSON file, each gt_[image_id] corresponds to a list, where each line in the list correspond to one word in the image and gives its bounding box coordinates, transcription, and illegibility flag in the following format:

{

    “gt_1”: [

        {“points”: [[x1, y1], [x2, y2], …, [xn, yn]], “transcription” : “trans1”, "illegibility": false },

        {“points”: [[x1, y1], [x2, y2], …, [xn, yn]], “transcription” : “trans2”, " illegibility ": false }],

    “gt_2”: [

        {“points”: [[x1, y1], [x2, y2], …, [xn, yn]] , “transcription” : “trans3”, " illegibility ": false }],

    ……

}

where x1, y1, x2, y2, …, xn, yn in “points” are the coordinates of the polygon bounding boxes, which could be 4, 8, 12 polygon vertices. The “transcription” denotes the text of each text line, and “illegibility” represents “Do Not Care” text region when it’s set “true”, which does not influence the results.

 

Similar to full annotations ground-truths, for images with weak annotations in the dataset, we store all the ground-truths in a single JSON file. In the JSON file, each gt_[image_id]corresponds to one word which we refer to as `text-of-interest' in the images:

{

    “gt_0”: [{ “transcription” : “trans1” }],

    “gt_1”: [{“transcription” : “trans2” }],

    “gt_2”: [{“transcription” : “trans3” }],

    ……

}

The LSVT dataset can be download at: http://bjyz-ai.epc.baidu.com/broad/download?dataset=lsvt

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