---
title: "Face Analytics"
url: https://docs.catalyst.zoho.com/en/sdk/python/v1/zia-services/face-analytics/
description: "This page describes the method to use the Face Analytics feature to detect faces with specified criteria in your Python application with sample code snippets"
last_updated: 2026-06-09T07:46:16Z
service: Zia Services
type: general
related_links:
  - name: "Face Analytics - API"
    url: /en/api/code-reference/zia-services/face-analytics/#FaceAnalytics
  - name: "SDK Scopes"
    url: /en/sdk/python/v1/sdk-scopes
---

# Face Analytics

[Zia Face Analytics](https://docs.catalyst.zoho.com/en/zia-services/help/face-analytics/introduction) performs facial detection in images, and analyzes the facial features to provide information such as the gender, age, and emotion of the
detected faces.

You must provide a .webp/.jpeg or .png file as the input to the `open()` method to perform Face Analytics on that image. This opens the provided file and returns a file object as a response. 

The `analyse_face()` method accepts the input image as its argument. You can also specify the
analysis mode as `basic`, `moderate`, or `advanced`. You
can also specify the attributes `age`, `smile`, or
`gender` as `true` to detect or `false` to not detect.
These values are optional. All attributes are detected and the `advanced` mode is processed by
default.

Refer to the [API documentation](https://docs.catalyst.zoho.com/en/api/code-reference/zia-services/face-analytics/#FaceAnalytics) for the request and response formats.

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/).

The response returns the prediction of the enabled attributes, the coordinates and landmarks of facial features of each
face, and the confidence score of each analysis.

**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 of the face to be analyzed.</td>
		</tr>
    <tr>
		<td>`mode`</td>
      <td>String</td>
			<td>A **Optional** parameter. Will store the analysis mode values - "basic", "moderate" or "advanced".</td>
	 </tr>
      <tr>
		<td>`age`</td>
      <td>Boolean</td>
			<td>A **Optional** parameter. Will decide whether to determine age or not. Values accepted are "Yes" or "No"</td>
		</tr>
         <tr>
		<td>`emotion`</td>
      <td>Boolean</td>
			<td>A **Optional** parameter. Will decide whether to determine emotion or not. Values accepted are "Yes" or "No"</td>
		</tr>
      <tr>
		<td>`gender`</td>
      <td>Boolean</td>
			<td>A **Optional** parameter. Will decide whether to determine gender or not. Values accepted are "True" or "False"</td>
		</tr>
	</tbody>
</table>

```python
# Face Analytics implementation
zia = app.zia()
img = open("sample.webp", "rb")
result = zia.analyse_face(
    img, {"mode": "moderate", "age": True, "emotion": True, "gender": False}
)

```

A sample response is shown below :

```json
{
   "faces_count":1,
   "faces":[
      {
         "co_ordinates":[
            "401",
            "193",
            "494",
            "313"
         ],
         "emotion":{
            "confidence":{
               "smiling":"0.75",
               "not_smiling":"0.25"
            },
            "prediction":"smiling"
         },
         "gender":{
            
         },
         "confidence":1,
         "id":"0",
         "landmarks":{
            "right_eye":[
               [
                  "467",
                  "230"
               ]
            ],
            "nose":[
               [
                  "451",
                  "264"
               ]
            ],
            "mouth_right":[
               [
                  "474",
                  "278"
               ]
            ],
            "left_eye":[
               [
                  "426",
                  "239"
               ]
            ],
            "mouth_left":[
               [
                  "434",
                  "283"
               ]
            ]
         },
         "age":{
            "confidence":{
               "20-29":"0.73",
               "30-39":"0.08",
               "0-2":"0.0",
               "40-49":"0.0",
               "50-59":"0.0",
               ">70":"0.0",
               "60-69":"0.0",
               "10-19":"0.17",
               "3-9":"0.0"
            },
            "prediction":"20-29"
         }
      }
   ]
}

```

> **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.