---
title: "OCR"
url: https://docs.catalyst.zoho.com/en/sdk/python/v1/zia-services/ocr/
description: "This page describes the method to use the Optical Character Recognition feature to detect textual characters in your Python application with sample code snippets"
last_updated: 2025-11-19T15:07:41Z
service: Zia Services
type: general
related_links:
  - name: "OCR - API"
    url: /en/api/code-reference/zia-services/ocr/#OCR
  - name: "SDK Scopes"
    url: /en/sdk/python/v1/sdk-scopes
---

# Optical Character Recognition

[Zia Optical Character Recognition](https://docs.catalyst.zoho.com/en/zia-services/help/optical-character-recognition/introduction) electronically detects textual characters in images or digital documents, and converts them into machine-encoded text. Zia OCR can recognize text in nine international languages and 10 Indian languages. You can check the list of languages and language codes from the [ API documentation](https://docs.catalyst.zoho.com/en/api/code-reference/zia-services/ocr/#OCR).

> **Note:**Catalyst does not store any of the files you upload in its systems. The files you upload are used for one-time processing only. They are not used for ML model training purposes either. Catalyst components are fully compliant with all applicable data protection and privacy laws.

You must specify the path to the image or document file that needs to be processed for OCR as a parameter to the `open()` method. This opens the file and returns a file object as a response.

**Allowed file formats:** ._jpg_, ._jpeg_, ._png_, ._tiff_, ._bmp_, ._pdf_

**File size limit:** 20 MB

You must pass the file path, model type, and languages as arguments to the `extract_optical_characters()` method. However, the model type and language values are optional. By default, it is passed as the `OCR` model type, and the languages are automatically detected if they are not specified.

To know more about the component instance `zia` used below, please refer to [this help section](https://docs.catalyst.zoho.com/en/sdk/python/v1/zia-services/get-component-instance/).

**Parameters Used**

<table class="content-table">
	<thead>
		<tr>
			<th class="w20p">Parameter Name</th>
			<th class="w20p">Data Type</th>
      <th class="w60p">Definition</th>
		</tr>
	</thead>
	<tbody>
    <tr>
			<td>`img`</td>
			<td>Image</td>
			<td>A **Mandatory** parameter. Will store the image that has to be analyzed.</td>
		</tr>
      <tr>
			<td>`language`</td>
			<td>String</td>
			<td>A **Mandatory** parameter. Will store the language to be identified.</td>
		</tr>
      <tr>
			<td>`modelType`</td>
			<td>String</td>
			<td>A **Mandatory** parameter. Will store the default value as "OCR".</td>
		</tr>
	</tbody>
</table>

```python
# OCR Implementation
zia = app.zia()
img = open("sample.webp", "rb")
result = zia.extract_optical_characters(img, {"language": "eng", "modelType": "OCR"})

```

A sample response is shown below :

```json
{
   "confidence":95,
   "text":"This is a lot of 12 point text to test the\nocr code and see if it works on all types\nof file format\n\nThe quick brown dog jumped over the\nlazy fox. The quick brown dog jumped\nover the lazy fox. The quick brown dog\njumped over the lazy fox. The quick\nbrown dog jumped over the lazy fox"
}

```

> **Info :** Refer to the [SDK Scopes table](https://docs.catalyst.zoho.com/en/sdk/python/v1/sdk-scopes) to determine the required permission level for performing the above operation.