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Large Korean & Hindi Scene Text OCR Dataset – 104,000+ Natural Images
Korean OCR dataset
Hindi OCR dataset
Scene text OCR dataset
Multilingual OCR images
OCR training data for AI
This dataset contains 104,320 images of Korean and Hindi text in natural scenes. The collecting scenes include packaging, posters, tickets, reminders, menus, building signs, and similar real-world environments. The dataset features diverse scenes, multiple shooting angles and multiple lighting conditions. For annotation, line-level polygon bounding box (or tetragon or rectangular bounding boxes) annotation, transcription and text attributes (language type) for the texts; vertical-level polygon bounding box (or tetragon or rectangular bounding boxes) annotation, transcription and text attributes (language type) for the text. The dataset can be used for Korean and Hindi OCR tasks in natural scenes.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
Specifications
Data size
76,861 images of Korean, 555,913 bounding boxes; 27,459 images of Hindi, 200,453 bounding boxes
Collecting environment
including packaging, posters, tickets, reminders, menus, building signs, etc.
looking up angle, looking down angle, eye-level angle
Language distribution
Korean, Hindi, English (a few)
Data format
the image data format is .jpg, the annotation file format is .json
Bounding box shape distribution
315,822 tetragon bounding boxes and 240,091 polygon bounding boxes of Korean; 780 tetragon bounding boxes, 199,671 polygon bounding boxes and 2 rectangle bounding boxes of Hindi
Annotation content
line-level polygon bounding box (or tetragon bounding box, rectangle bounding box) annotation, transcription and text attributes (language type) for the texts; vertical-level polygon bounding box (or tetragon bounding box, rectangle bounding box) annotation, transcription and text attributes (language type) for the text
Accuracy
The error bound of each vertex of a bounding box is within 5 pixels, which is a qualified annotation, the accuracy of bounding boxes is not less than 95%; The texts transcription accuracy is not less than 95%.
Specifications
Sample
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