A super-resolution dataset consists of paired LR-HR scene text images.

TextZoom Dataset (allocated by size):

Paper: arxiv

Data: Badiu NetDisk. password: kybq

The LR images in TextZoom is much more challenging than synthetic LR images(BICUBIC).

We allocate our dataset into 3 part following difficulty: easy, medium and hard subset. The misalignment and ambiguity increases as the difficulty increases.

For each pair of LR-HR images, we provide the annotation of the case sensitive character string (including punctuation), the type of the bounding box, and the original focal lengths.

Other data

• Cropped text images from SR_RAW (allocated by original images): BaiduNet Disk. password: ykbq

• Cropped text images from RealSR (allocated by original images): BaiduNet Disk. password: f615

• Annotation of SR_RAW (bounding boxs and word labels): Baidu NetDisk. password: kmme

• Annotation of RealSR (bounding boxs and word labels): Baidu NetDisk. password: i52c

    architecture of json: (sr_raw.json and real_sr.json have the same arch)

    'position' is the bounding box,

    'rawFileName' is the original image name, you need to download the RealSR dataset.

    'words' is the word label.

    'type' means the direction of bounding box, 'td' means top down, 'vn' means negative vertical (counterclockwise 90 degrees), 
    'vp' means positive vertical (clockwise 90 degrees), 'h' means horizontal.

    
    with open('real_sr.json') as f:
        d=json.load(f)
    d['0']=
    {'channal': '3',
     'height':  '2300',
     'id':      'cbe0e4cba6ba6cd42d8ed4779087214a',
     'polygons': {'wordRect': 
                 [{'line-type': 'straight',
                    'position': [{'x': '247.94625', 'y': '186.31634'},
                     {'x': '99.29263', 'y': '186.60167'},
                     {'x': '99.29263', 'y': '165.77304'},
                     {'x': '247.94625', 'y': '166.34369'}],
                    'type': 'td',
                    'valid': 'true',
                    **'words': 'QU04029757'**},
                   {'line-type': 'straight',
                    'position': [{'x': '63.18353', 'y': '703.61181'},
                     {'x': '61.66713', 'y': '542.87290'},
                     {'x': '127.88347', 'y': '540.85103'},
                     {'x': '130.41081', 'y': '702.60087'}],
                    'type': 'vn',
                    'valid': 'true',
                    'words': '100'},
                   ...
                   ]},
     'rawFilePath':   'test',
     'rawFilename':   'Canon_046_HR.png',
     'result_version': '1.0',
     'rotate':    '0',
     'valid':     'true',
     'width':     '2500',
     'wordRect-validity': 'true'}