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
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.
Metadata
Release files for wow-ocr 0.0.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| wow-ocr-0.0.3.tar.gz | 21.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| wow_ocr-0.0.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 43.3 kB
Release files / wow-ocr-0.0.3.tar.gz
| Download URL | wow-ocr-0.0.3.tar.gz |
|---|---|
| Size | 21.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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No |
| Uploaded via |
twine/4.0.2 CPython/3.10.6
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Release files / wow_ocr-0.0.3-py3-none-any.whl
| Download URL | wow_ocr-0.0.3-py3-none-any.whl |
|---|---|
| Size | 22.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.6
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