v1.3.2

• 30 May 2021 - Version 1.3.2
  • Faster greedy decoder (thanks @samayala22)
  • Fix bug when text box's aspect ratio is disproportional (thanks iQuartic for bug report)

v1.3.1

• 24 April 2021 - Version 1.3.1
  • Add support for PIL image (thanks @prays)
  • Add Tajik language (tjk)
  • Update argument setting for command line
  • Add x_ths and y_ths to control merging behavior when paragraph=True

v1.3

• 21 March 2021 - Version 1.3
  • Second-generation models: multiple times smaller size, multiple times faster inference, additional characters, comparable accuracy to the first generation models.
    EasyOCR will choose the latest model by default but you can also specify which model to use by passing recog_network argument when creating Reader instance.
    For example, reader = easyocr.Reader(['en','fr'], recog_network = 'latin_g1') will use the 1st generation Latin model.
  • List of all models: Model hub

v1.2.5

• 22 February 2021 - Version 1.2.5
  • Add dynamic quantization for faster CPU inference (it is enabled by default for CPU mode)
  • More sensible confident score

v1.2.4

• 7 February 2021 - Version 1.2.4
  • Faster CPU inference speed by using dynamic input shape (recognition rate increases by around 100% for images with a lot of text)

1.2.3

• 1 February 2021 - Version 1.2.3
  • Add setLanguageList method to Reader class. This is a convenient api for changing languages (within the same model) after creating class instance.
  • Small change on text box merging. (thanks z-pc, see PR)
  • Basic Demo on website

1.2.2

• 5 January 2021 - Version 1.2.2
  • Add optimal_num_chars to detect method. If specified, bounding boxes with estimated number of characters near this value are returned first. (thanks @adamfrees)
  • Add rotation_info to readtext method. Allow EasyOCR to rotate each text box and return the one with the best confident score. Eligible values are 90, 180 and 270. For example, try [90, 180 ,270] for all possible text orientations. (thanks @mijoo308)
  • Update documentation.

v1.2

New language supports for Telugu and Kannada. These are experimental lite recognition models. Their file sizes are only around 7% of other models and they are ~6x faster at inference with CPU.

This release is also a preparation for user-created models/architectures in the future.

1.1.10

• 12 October 2020 - Version 1.1.10
  • Faster beamsearch decoder (thanks @amitbcp)
  • Better code structure (thanks @susmith98)
  • New language supports for Haryanvi(bgc), Sanskrit(sa) (Devanagari Script) and Manipuri(mni) (Bengari Script)
• 31 August 2020 - Version 1.1.9
  • Add detect and recognize method for performing text detection and recognition separately

v1.1.8

• 23 August 2020 - Version 1.1.8
  • 20 new language supports for Bengali, Assamese, Abaza, Adyghe, Kabardian, Avar,
    Dargwa, Ingush, Chechen, Lak, Lezgian, Tabassaran, Bihari, Maithili, Angika,
    Bhojpuri, Magahi, Nagpuri, Newari, Goan Konkani
  • Support RGBA input format
  • Add min_size argument for readtext: for filtering out small text box