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Christmas card maker with OpenCV

For Christmas we made an example deployment that takes an image as input and returns a Christmas card version of the image. The deployment uses OpenCV to detect faces in the image and uses that to give everyone a Santa hat. It also adds some general Christmas decorations to the image.

The Christmas deployment

This deployment takes an image input_image as input, and returns a Christmas card image festive_image. We have put the here for your reference:

import cv2
import numpy as np
import cvzone

class Deployment:

    def __init__(self, base_directory, context):
        print("Initialising My Deployment")
        # Loading overlay images and classifier
        self.christmas_hat_image = cv2.imread("christmas_hat2.png", cv2.IMREAD_UNCHANGED)
        self.christmas_border = cv2.imread("christmas_border.png", cv2.IMREAD_UNCHANGED)
        self.christmas_decoration = cv2.imread("christmas_decoration.png", cv2.IMREAD_UNCHANGED)
        self.cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")

    def request(self, data):
        print("Processing request for My Deployment")
        print("Reading input image.")
        frame = cv2.imread(data["input_image"])

        # Getting dimensions of the base image
            height, width, channels = frame.shape
            height, width = frame.shape

        print("Adding Christmas frame and decoration to image.")
        border_resize = cv2.resize(self.christmas_border, (width, height))
        decoration_resize = cv2.resize(self.christmas_decoration, (width, int(height/4)))
        frame = cvzone.overlayPNG(frame, border_resize, [0,0])
        frame = cvzone.overlayPNG(frame, decoration_resize, [0,0])

        print("Detecting faces.")
        gray_scale = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        faces = self.cascade.detectMultiScale(gray_scale)

        print("Giving everyone a Christmas hat.")
        for (x, y, w, h) in faces:
            if ((w > 0.045*width) and (h > 0.045*height)):

                overlay_resize = cv2.resize(self.christmas_hat_image, (int(w*1.6), int(h*1.6)))

                    # This is a better offset for the Christmas hat, but if a face is near the top of the screen it
                    # will give an error. So then we use a smaller offset.
                    frame = cvzone.overlayPNG(frame, overlay_resize, [int(x-w/3), int(y-(0.7)*h)])
                    frame = cvzone.overlayPNG(frame, overlay_resize, [int(x-w/3), int(y-h/2)])
        cv2.imwrite("christmas_image.png", frame)

        return {
            "festive_image": "christmas_image.png"

The deployment works in 4 steps:

  • Resize & overlay Christmas decoration images on the input image
  • Detect faces in input image (using Haar cascades)
  • Put Christmas hats above the faces
  • Save the resulting image and return it as output

Running the example in UbiOps

To deploy this example model to your own UbiOps environment you can log in to the WebApp and create a new deployment in the deployment tab. You will be prompted to fill in certain parameters, you can use the following:

Deployment configuration
Name christmas-model
Description A Christmas card maker. Accepts PNG or JPEG images.
Input fields: name = input_image, datatype = blob
Output fields: name = festive_image, datatype = blob
Version name v1
Description leave blank
Language python 3.8
Upload code deployment zip do not unzip!
Advances parameters Leave on default settings

After uploading the code, and with that creating the deployment version, UbiOps will start deploying. Once you're deployment version is available you can make requests to it. You can use any input image with people on it as long as it is PNG or JPEG.

Enough space for Christmas hats

For the model to work correctly there needs to be enough space above each face in the input image to put the Christmas hat. Otherwise the request might fail.