Datasets:
Modalities:
Image
Formats:
imagefolder
Size:
1K - 10K
tags: | |
- text-recognition | |
- dataset | |
- text-detection | |
- scene-text | |
- scene-text-recognition | |
- scene-text-detection | |
- text-detection-recognition | |
- icdar | |
- total-text | |
- curve-text | |
task_categories: | |
- text-retrieval | |
- text-classification | |
language: | |
- en | |
- zh | |
size_categories: | |
- 10K<n<100K | |
# TextOCR Dataset | |
## Version 0.1 | |
### Training Set | |
- **Word Annotations:** 714,770 (272MB) | |
- **Images:** 21,778 (6.6GB) | |
### Validation Set | |
- **Word Annotations:** 107,802 (39MB) | |
- **Images:** 3,124 | |
### Test Set | |
- **Metadata:** 1MB | |
- **Images:** 3,232 (926MB) | |
## General Information | |
- **License:** Data is available under CC BY 4.0 license. | |
- **Important Note:** Numbers in the papers should be reported on the v0.1 test set. | |
## Images | |
- Training and validation set images are sourced from the OpenImages train set, while test set images come from the OpenImages test set. | |
- Validation set's images are contained in the zip for the training set's images. | |
- **Note:** Some images in OpenImages are rotated; please check the Rotation field in the Image IDs files for train and test. | |
## Dataset Format | |
The JSON format mostly follows COCO-Text v2, except the "mask" field in "anns" is named as "points" for the polygon annotation. | |
### Details | |
- **Points:** A list of 2D coordinates like `[x1, y1, x2, y2, ...]`. Note that (x1, y1) is always the top-left corner of the text (in its own orientation), and the order of the points is clockwise. | |
- **BBox:** Contains a horizontal box converted from "points" for convenience, and "area" is computed based on the width and height of the "bbox". | |
- **Annotation:** In cases when the text is illegible or not in English, the polygon is annotated normally but the word will be annotated as a single "." symbol. Annotations are case-sensitive and can include punctuation. | |
## Annotation Details | |
- Annotators were instructed to draw exactly 4 points (quadrilaterals) whenever possible, and only draw more than 4 points when necessary (for cases like curved text). | |
## Relationship with TextVQA/TextCaps | |
- The image IDs in TextOCR match the IDs in TextVQA. | |
- The train/val/test splits are the same as TextVQA/TextCaps. However, due to privacy reasons, we removed 274 images from TextVQA while creating TextOCR. | |
## TextOCR JSON Files Example | |
```json | |
{ | |
"imgs": { | |
"OpenImages_ImageID_1": { | |
"id": "OpenImages_ImageID_1", | |
"width": "INT, Width of the image", | |
"height": "INT, Height of the image", | |
"set": "Split train|val|test", | |
"filename": "train|test/OpenImages_ImageID_1.jpg" | |
}, | |
"OpenImages_ImageID_2": { | |
"..." | |
} | |
}, | |
"anns": { | |
"OpenImages_ImageID_1_1": { | |
"id": "STR, OpenImages_ImageID_1_1, Specifies the nth annotation for an image", | |
"image_id": "OpenImages_ImageID_1", | |
"bbox": [ | |
"FLOAT x1", | |
"FLOAT y1", | |
"FLOAT x2", | |
"FLOAT y2" | |
], | |
"points": [ | |
"FLOAT x1", | |
"FLOAT y1", | |
"FLOAT x2", | |
"FLOAT y2", | |
"...", | |
"FLOAT xN", | |
"FLOAT yN" | |
], | |
"utf8_string": "text for this annotation", | |
"area": "FLOAT, area of this box" | |
}, | |
"OpenImages_ImageID_1_2": { | |
"..." | |
} | |
}, | |
"img2Anns": { | |
"OpenImages_ImageID_1": [ | |
"OpenImages_ImageID_1_1", | |
"OpenImages_ImageID_1_2", | |
"OpenImages_ImageID_1_2" | |
], | |
"OpenImages_ImageID_N": [ | |
"..." | |
] | |
} | |
} |