Metadata-Version: 2.1
Name: aspose-ocr-models-textinwild-python-net
Version: 23.12.1
Summary: Aspose.OCR for Python is a powerful yet easy-to-use and cost-effective API for extracting text from scanned images, photos, screenshots, PDF documents, and other files.
Home-page: https://products.aspose.com/ocr/
Author: Aspose
License: https://company.aspose.com/legal/eula
Keywords: OCR, Recognize text, diacritic, Python, Aspose
Platform: win32
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: License :: Other/Proprietary License
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Python: >=3.5,<3.12
Description-Content-Type: text/markdown

[Product Page](https://products.aspose.com/ocr/python-net/) | [Documentation](https://docs.aspose.com/ocr/python-net/) | [Demos](https://products.aspose.app/ocr/family) | [Blog](https://blog.aspose.com/categories/aspose.ocr-product-family/) | [API Reference](https://reference.aspose.com/ocr/python-net/) | [Search](https://search.aspose.com/) | [Free Support](https://forum.aspose.com/c/ocr/16) | [Temporary License](https://purchase.aspose.com/temporary-license)

Try our [Free Online Apps](https://products.aspose.app/ocr/family) demonstrating some of the most popular Aspose.OCR functionality.

**Aspose.OCR.Models.TextInWild for Python via .NET** This extension to Aspose.OCR for Python via .NET adds a specialized recognition model and methods to accurately extract text from street photos, traffic camera images, ID cards, driver licenses, and other images with sparse text and noisy/colored backgrounds. This is useful for improving OCR accuracy in specific business cases:

- Segment and identify road signs and signboards within street images.
- Locate price tags and interpret the extracted text as prices.
- Find and aggregate regions of interest on food labels, such as nutritional information or ingredient lists.
- Identify and analyze car license plates.
- Extract text from menus and catalogs.


Check out the [Landing Pages](https://products.aspose.com/ocr/python-net/) of **Aspose.OCR for Python via .NET** for a more detailed description of the features and possibilities of the library.

##Important considerations:

- This package requires Aspose.OCR for Python via.NET to function properly. It cannot be used separately from the core API.
- The model only works with Latin letters and numbers.


## Get Started

Run ```pip install aspose-ocr-python-net``` and ```pip install aspose-ocr-models-textinwild-python-net``` to fetch the package. If you already have **Aspose.OCR for Python via .NET** and want to get the latest version, please run ```pip install --upgrade aspose-ocr-python-net```.

To learn more about **Aspose.OCR for Python via .NET** and explore the basic requirements and features of the library, check out the following [Aspose.OCR for Python via .NET Documentation](https://docs.aspose.com/ocr/python-net/) pages for other use cases.

### Code snippet

**Aspose.OCR for Python via .NET** is extremely easy to use, regardless of the application's scale and complexity. Let's try to create a very simple application that can extract text from images and output it to the console.

1. Install  the latest version of the *aspose-ocr* package using pip.
2. Import `aspose.ocr` module into the application.
3. Create an instance of `AsposeOcr` class.
4. Create an instance of `OcrInput` class and add one or more images to it.
5. Extract text from the street photo using `recognize_street_photo` method.
6. Output the extracted text to the console.

Full code:

```python
import aspose.ocr as ocr

# Initialize OCR engine
api = AsposeOcr()

# Initialize OCR input
input = OcrInput(InputType.SINGLE_IMAGE)
input.add("1.png")
input.add("2.jpg")

# Recognize images
result = api.recognize_street_photo(input)

# Print result
print(result[0].recognition_text)
print(result[1].recognition_text)
```

[Product Page](https://products.aspose.com/ocr/python-net/) | [Documentation](https://docs.aspose.com/ocr/python-net/) | [Demos](https://products.aspose.app/ocr/family) | [Blog](https://blog.aspose.com/categories/aspose.ocr-product-family/) | [API Reference](https://reference.aspose.com/ocr/python-net/) | [Search](https://search.aspose.com/) | [Free Support](https://forum.aspose.com/c/ocr/16) | [Temporary License](https://purchase.aspose.com/temporary-license)
