Quickstart: Detect faces in an image using the Face REST API and Python

In this quickstart, you will use the Azure Face REST API with Python to detect human faces in an image. The script will draw frames around the faces and superimpose gender and age information on the image.

A man and a woman, each with a rectangle drawn around their faces and age and sex displayed on the image

If you don't have an Azure subscription, create a free account before you begin.

Prerequisites

Run the Jupyter notebook

You can run this quickstart as a Jupyter notebook on MyBinder. To launch Binder, select the button below. Then follow the instructions in the notebook.

Binder

Create and run the sample

Alternately, you can run this quickstart from the command line with the following steps:

  1. Copy the following code into a text editor.
  2. Make the following changes in code where needed:
    1. Replace the value of subscription_key with your subscription key.
    2. Edit the value of face_api_url to include the endpoint URL for your Face API resource.
    3. Optionally, replace the value of image_url with the URL of a different image that you want to analyze.
  3. Save the code as a file with an .py extension. For example, detect-face.py.
  4. Open a command prompt window.
  5. At the prompt, use the python command to run the sample. For example, python detect-face.py.
import requests
import json

# set to your own subscription key value
subscription_key = None
assert subscription_key

# replace <My Endpoint String> with the string from your endpoint URL
face_api_url = 'https://<My Endpoint String>.com/face/v1.0/detect'

image_url = 'https://upload.wikimedia.org/wikipedia/commons/3/37/Dagestani_man_and_woman.jpg'

headers = {'Ocp-Apim-Subscription-Key': subscription_key}

params = {
    'returnFaceId': 'true',
    'returnFaceLandmarks': 'false',
    'returnFaceAttributes': 'age,gender,headPose,smile,facialHair,glasses,emotion,hair,makeup,occlusion,accessories,blur,exposure,noise',
}

response = requests.post(face_api_url, params=params,
                         headers=headers, json={"url": image_url})
print(json.dumps(response.json()))

Examine the response

A successful response is returned in JSON.

[
  {
    "faceId": "e93e0db1-036e-4819-b5b6-4f39e0f73509",
    "faceRectangle": {
      "top": 621,
      "left": 616,
      "width": 195,
      "height": 195
    },
    "faceAttributes": {
      "smile": 0,
      "headPose": {
        "pitch": 0,
        "roll": 6.8,
        "yaw": 3.7
      },
      "gender": "male",
      "age": 37,
      "facialHair": {
        "moustache": 0.4,
        "beard": 0.4,
        "sideburns": 0.1
      },
      "glasses": "NoGlasses",
      "emotion": {
        "anger": 0,
        "contempt": 0,
        "disgust": 0,
        "fear": 0,
        "happiness": 0,
        "neutral": 0.999,
        "sadness": 0.001,
        "surprise": 0
      },
      "blur": {
        "blurLevel": "high",
        "value": 0.89
      },
      "exposure": {
        "exposureLevel": "goodExposure",
        "value": 0.51
      },
      "noise": {
        "noiseLevel": "medium",
        "value": 0.59
      },
      "makeup": {
        "eyeMakeup": true,
        "lipMakeup": false
      },
      "accessories": [],
      "occlusion": {
        "foreheadOccluded": false,
        "eyeOccluded": false,
        "mouthOccluded": false
      },
      "hair": {
        "bald": 0.04,
        "invisible": false,
        "hairColor": [
          {
            "color": "black",
            "confidence": 0.98
          },
          {
            "color": "brown",
            "confidence": 0.87
          },
          {
            "color": "gray",
            "confidence": 0.85
          },
          {
            "color": "other",
            "confidence": 0.25
          },
          {
            "color": "blond",
            "confidence": 0.07
          },
          {
            "color": "red",
            "confidence": 0.02
          }
        ]
      }
    }
  },
  {
    "faceId": "37c7c4bc-fda3-4d8d-94e8-b85b8deaf878",
    "faceRectangle": {
      "top": 693,
      "left": 1503,
      "width": 180,
      "height": 180
    },
    "faceAttributes": {
      "smile": 0.003,
      "headPose": {
        "pitch": 0,
        "roll": 2,
        "yaw": -2.2
      },
      "gender": "female",
      "age": 56,
      "facialHair": {
        "moustache": 0,
        "beard": 0,
        "sideburns": 0
      },
      "glasses": "NoGlasses",
      "emotion": {
        "anger": 0,
        "contempt": 0.001,
        "disgust": 0,
        "fear": 0,
        "happiness": 0.003,
        "neutral": 0.984,
        "sadness": 0.011,
        "surprise": 0
      },
      "blur": {
        "blurLevel": "high",
        "value": 0.83
      },
      "exposure": {
        "exposureLevel": "goodExposure",
        "value": 0.41
      },
      "noise": {
        "noiseLevel": "high",
        "value": 0.76
      },
      "makeup": {
        "eyeMakeup": false,
        "lipMakeup": false
      },
      "accessories": [],
      "occlusion": {
        "foreheadOccluded": false,
        "eyeOccluded": false,
        "mouthOccluded": false
      },
      "hair": {
        "bald": 0.06,
        "invisible": false,
        "hairColor": [
          {
            "color": "black",
            "confidence": 0.99
          },
          {
            "color": "gray",
            "confidence": 0.89
          },
          {
            "color": "other",
            "confidence": 0.64
          },
          {
            "color": "brown",
            "confidence": 0.34
          },
          {
            "color": "blond",
            "confidence": 0.07
          },
          {
            "color": "red",
            "confidence": 0.03
          }
        ]
      }
    }
  }
]

Next steps

Next, explore the Face API reference documentation to learn more about the supported scenarios.