Metadata-Version: 2.1
Name: wow-ocr
Version: 0.0.2
Summary: A packaged OCR model to read texts into WoW screenshots
Author-email: Geo <geoffrey.menon38@gmail.com>
License: Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in
        all copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
        THE SOFTWARE.
Project-URL: Homepage, https://github.com/geo-tp/wow-ocr
Keywords: ocr,wow,screenshot
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Provides-Extra: dev
License-File: LICENSE

WoW Screenshot OCR
==============

Deep learning OCR models to read text from WoW screenshots. Based on a detector that spots text frames from screenshots, and a recognizer that reads text from detected frames.

- Chat
- Combat log
- Nameplates
- UI frames
- Map

Installation
-----

### ```pip install wow-ocr```


Usage
----

Models will use pre trained weights, you don't have to train anything. [Try it on Colab](https://colab.research.google.com/drive/1w4YIS--7qSzdSrwKPcQfqO988PlrxuCM?usp=sharing)

```
import wow_ocr

# Init pipeline, detector and recognizer models with pre trained weights
pipeline = wow_ocr.pipeline.Pipeline()


# Screenshots example
images = [
    wow_ocr.tools.read(url)
    for url in [
        "https://image_url.com/1.jpg",
        "https://image_url.com/2.jpg",
    ]
]

# Results - Image to Text
prediction_groups = pipeline.recognize(images)
# # Each list of predictions in prediction_groups is a list of
# # (word, box) tuples.

```

![](p1.webp)
![](p2.webp)
