How to detect faces in photo in Python

Automatically detecting faces in a photograph has never been easier. Our image procession API lets you instantly harness the power of machine learning to trivialize this task in minutes. Let’s take a quick look at how to do this.

First step is to install the API client using pip installer.

pip install git+https://github.com/Cloudmersive/Cloudmersive.APIClient.Python.ImageRecognition.git

Second, call face_locate:

from __future__ import print_function
import time
import cloudmersive_image_api_client
from cloudmersive_image_api_client.rest import ApiException
from pprint import pprint
# Configure API key authorization: Apikey
configuration = cloudmersive_image_api_client.Configuration()
configuration.api_key['Apikey'] = 'YOUR_API_KEY'
# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['Apikey'] = 'Bearer'
# create an instance of the API class
api_instance = cloudmersive_image_api_client.FaceApi(cloudmersive_image_api_client.ApiClient(configuration))
image_file = '/path/to/file' # file | Image file to perform the operation on.  Common file formats such as PNG, JPEG are supported.
try:
    # Find faces in an image
    api_response = api_instance.face_locate(image_file)
    pprint(api_response)
except ApiException as e:
    print("Exception when calling FaceApi->face_locate: %s\n" % e)

And that’s it. No really, that’s all you’ve got to do. Let’s look at a quick example using the following image:

Our result looks like this:

{
  "ErrorDetails": null,
  "Successful": true,
  "Faces": [
    {
      "LeftX": 521,
      "TopY": 494,
      "RightX": 646,
      "BottomY": 618
    },
    {
      "LeftX": 300,
      "TopY": 507,
      "RightX": 424,
      "BottomY": 632
    }
  ],
  "FaceCount": 2
}

As you can see, it specifies the corners of each face as well as the number of total faces.