| Name | wow-ocr JSON |
| Version |
0.0.3
JSON |
| download |
| home_page | |
| Summary | A packaged OCR model to read texts into WoW screenshots |
| upload_time | 2023-06-04 15:06:56 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.9 |
| 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. |
| keywords |
ocr
wow
screenshot
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
WoW Screenshot OCR
==============
Deep learning OCR models to read text from WoW screenshots. Based on a detector that spots text frames, and a recognizer that reads text from detected frames.
- Chat
- Combat log
- Nameplates
- UI frames
- Map
Installation
-----
### ```pip install wow-ocr```
Usage
----
Models 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.
```
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