VisionAPI & Functions

faces.py

# opencv-python
# google-cloud-storage
# google-cloud-vision

from google.cloud import storage
from google.cloud import vision
import numpy as np
import cv2 as cv
import logging
import os
import io


def hello_gcs(event, context):
    """Triggered by a change to a Cloud Storage bucket.
    Args:
         event (dict): Event payload.
         context (google.cloud.functions.Context): Metadata for the event.
    """
    file = event
    sclient = storage.Client()
    vclient = vision.ImageAnnotatorClient()

    logging.info('Downloading image GCloud -> /tmp...')

    img_name = os.path.split(file['name'])[-1]
    img_src = '/tmp/' + img_name

    bucket_src = sclient.get_bucket(file['bucket'])
    blob_img = storage.Blob(file['name'], bucket_src)
    blob_img.download_to_filename(img_src)

    logging.info('Getting face information at VisionAPI...')

    with io.open(img_src, 'rb') as image_file:
        content = image_file.read()
    image = vision.types.Image(content=content)

    response = vclient.face_detection(image=image)
    faces = response.face_annotations

    logging.info('Computing faces ROI...')

    img = cv.imread(img_src)
    face_img = []

    for face in faces:
        x = [vertex.x for vertex in face.bounding_poly.vertices]
        y = [vertex.y for vertex in face.bounding_poly.vertices]
        x_min = min(x)
        x_max = max(x)
        y_min = min(y)
        y_max = max(y)

        fimg = img[y_min:y_max, x_min:x_max].copy()
        gray = cv.cvtColor(fimg, cv.COLOR_RGB2GRAY)
        face_img.append(gray)

        logging.info('Uploading faces...')

    bucket_dst = sclient.get_bucket('up_teaching_face')

    for i, face in enumerate(face_img):
        cv.imwrite('/tmp/face.png', face)
        blob_face = storage.Blob(img_name + '.' + str(i) + '.png', bucket_dst)
        blob_face.upload_from_filename('/tmp/face.png')

    logging.info('done.')