Easyocr

- 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](https://www.jaided.ai/easyocr/modelhub)

- 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

- 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 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](https://github.com/z-pc), see [PR](https://github.com/JaidedAI/EasyOCR/pull/338))
- [Basic Demo on website](https://www.jaided.ai/easyocr)

- 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](https://github.com/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](https://github.com/mijoo308))
- Update [documentation](https://www.jaided.ai/easyocr/documentation).

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.