Blur faces in imagery with Google Cloud Vision

blur_faces.py

import cv2
import io
import json
import numpy as np
import os

from google.cloud import vision
from PIL import Image, ImageDraw
from StringIO import StringIO

# Load the image into memory
def load_image(img_filename):
  with io.open(img_filename, 'rb') as image_file:
    content = image_file.read()
  return content

# Helper function to label an image
def label_image(client, content):
  image = client.image(content=content)
  # Perform face detection on the image file
  faces = image.detect_faces()
  return faces

# Blur faces in the image
def blur_image(image_content, faces, output_path):
    img = Image.open(StringIO(image_content))
    img = np.array(img)
    # RGB/BGR channel flip for PIL-OpenCV compatibility
    img = img[:, :, ::-1]
    for face in faces:
      box = [(bound.x_coordinate, bound.y_coordinate)
               for bound in face.bounds.vertices]
      top_left = box[0]
      bottom_right = box[2]
      x = top_left[0]
      y = top_left[1]
      w = bottom_right[0] - top_left[0]
      h = bottom_right[1] - top_left[1]

      roi = img[y:y+h, x:x+w]
      roi_blurred = cv2.blur(roi, (15,15))
      img[y:y+h, x:x+w] = roi_blurred

    return img

# Mapping between blurred and unblurred imagery
def image_path_to_output_path(image_path):
    fname, ext = image_path.split('.')
    fname += '_blurred'
    output_path = '.'.join([fname, ext])
    return output_path


# Instantiate a client
vision_client = vision.Client()

# Set up image paths
image_paths = ['img/car.png']

for image_path in image_paths:
  output_path = image_path_to_output_path(image_path)

  print 'Loading {}'.format(image_path)
  image_content = load_image(image_path)

  print 'Labeling {}'.format(image_path)
  faces = label_image(vision_client, image_content)

  print 'Blurring {}'.format(image_path)
  blurred = blur_image(image_content, faces, output_path)

  print 'Saving {}'.format(output_path)
  cv2.imwrite(output_path, blurred)

  # If you need to rate limit (10 req/sec), uncomment this
  # time.sleep(0.1)