A quick guide on how to deploy a face blurring at scale.

β‹… Marcin Laskowski
face blurring deployment on syndicai

Learn how to deploy a face blurring algorithm at scale with Syndicai platform without any configuration and infrastructure setup.

Introduction

Our face is the most fundamental and highly visible element of our identity. People recognize us when they see our face or a photo of our face. According to GDPR, a European Union regulatory law, face images are categorized as sensitive data and need to be protected. 

However, protecting visual data is not a trivial thing and we are not really aware of how important it is. Talking about private data we are thinking about GPS and cookies in most cases, while images are not really relevant. For instance, playing with amazing facebook facial filters, nobody care about the fact that those videos are stored somewhere. We only think about nice look at that time πŸ˜‰

As the amount of data processed increases, we must think about our privacy. From the technological point of view, there are some tools and algorithms that helps to keep data private when used by AI or consumed by marketing platforms. One of them is face blurring algorithm that we will try to explore in the following tutorial.

After going through development, deployment and later integration phase in the following article you will have a basic understanding of how to easily deploy a face blurring model into production.

Let’s start!

πŸ’‘ Explore
If you are interested in the traditional AI model You can also explore the tutorial on how to deploy yolov5 model or how to deploy deoldify model.

Step 1: Develop a super resolution model

The main goal of the following step is to build and train a model, in our case it is face blurring algorithm, and later upload the code on GitHub.

The idea of the algorithm is to anonymize the face by blurring it, thereby making it impossible to identify the face. Such an algorithm could be applied for privacy and identity protection in public/private areas, protecting children online, photo journalism and news reporting and many more. A model takes image or video with people as input, recognize faces and draw a blurred rectangle on the face so that the person is hard to recognize.

face blurring syndicai
Face Blurring input image (left) and output (right) | 2019 Oscars Winners

In the following tutorial we will use the implementation written in OpenCV by Adrian Rosebrock that uses Gaussian blur. The whole pipeline is pretty straight forward. First we need to perform facial recognition, later crop the space with the face, apply blur and finally store the blurred face back in the original image.

You can either follow steps in the tutorial or use a ready-made code to run a model.

Since we don’t have to train anything, our model is ready to go. We just need to upload the code to your git repository before we go the next step.

Step 2: Deploy a super resolution model

Model is trained so in the next step we will prepare that model and connect repo to the platform.

AI model deployment is highly dependent on the use-case. In our tutorial we will deploy a face blurring model using Syndicai platform that allows us easily deliver our model to production in a secure and scalable way.

πŸ’‘ Explore
Check out the article about AI model deployment if you want to learn about different types of AI model delivery to production.

Prepare a model

Our model is already trained and uploaded to the Git repository. Now, we need to somehow define how the model will interact with input / output data when deployed as a webservice.

However, we will not create a webservice, because Syndicai will do it for us. The only thing that we need to do is to create additional syndicai.py and requirements.txt files placing them in the main directory at the end.

The first file, syndicai.py, is the python script that consists of PythonPredictor class. It is responsible for taking the input, parsing through the model and sending response.

In this case, both input and output are in the base64 format, and the content of the file looks as follows.

import os
import io
import base64
import cv2
import numpy as np

from PIL import Image
from imageio import imread
from pyimagesearch.face_blurring import anonymize_face_pixelate
from pyimagesearch.face_blurring import anonymize_face_simple


args = {
	"face": "./face_detector",
	"method": "simple",
	"blocks": 20,
	"confidence": 0.5
}

class PythonPredictor:

	def __init__(self, config):
		# load our serialized face detector model from disk
		print("[INFO] loading face detector model...")
		prototxtPath = os.path.sep.join([args["face"], "deploy.prototxt"])
		weightsPath = os.path.sep.join([args["face"],
			"res10_300x300_ssd_iter_140000.caffemodel"])
		self.net = cv2.dnn.readNet(prototxtPath, weightsPath)

	def predict(self, payload):
		# load the input image from disk, clone it, and grab the image spatial
		# dimensions
		img = imread(io.BytesIO(base64.b64decode(payload["base64"])))  # numpy array (width, hight, 3)
		image = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
		orig = image.copy()
		(h, w) = image.shape[:2]

		# construct a blob from the image
		blob = cv2.dnn.blobFromImage(image, 1.0, (300, 300),
			(104.0, 177.0, 123.0))

		# pass the blob through the network and obtain the face detections
		print("[INFO] computing face detections...")
		self.net.setInput(blob)
		detections = self.net.forward()

		# loop over the detections
		for i in range(0, detections.shape[2]):
			# extract the confidence (i.e., probability) associated with the
			# detection
			confidence = detections[0, 0, i, 2]

			# filter out weak detections by ensuring the confidence is greater
			# than the minimum confidence
			if confidence > args["confidence"]:
				# compute the (x, y)-coordinates of the bounding box for the
				# object
				box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
				(startX, startY, endX, endY) = box.astype("int")

				# extract the face ROI
				face = image[startY:endY, startX:endX]

				# check to see if we are applying the "simple" face blurring
				# method
				if args["method"] == "simple":
					face = anonymize_face_simple(face, factor=3.0)

				# otherwise, we must be applying the "pixelated" face
				# anonymization method
				else:
					face = anonymize_face_pixelate(face,
						blocks=args["blocks"])

				# store the blurred face in the output image
				image[startY:endY, startX:endX] = face
		
		image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
		img = Image.fromarray(image)

		im_file = io.BytesIO()
		img.save(im_file, format="PNG")
		im_bytes = base64.b64encode(im_file.getvalue()).decode("utf-8") 

		return im_bytes

The second file, required to recreate the model environment. It consists of a list of libraries and their versions.

opencv-python==4.2.0.34
numpy==1.18.4

Connect a git repo

When all necessary files are placed in the repo we are ready for the actual deployment.

You can use your own repository for this, or the one with the Syndicai’s sample models that already contains a prepared face blurring model.

In order to connect your repo just go to https://app.syndicai.co/, login, click New Model on the Overview page, and follow the steps in the form.

deploy a model on Syndicai
Connect your git repository in order to deploy a model on Syndicai

As soon as you finish, you will notice that the infrastructure will start building. You will have to wait a few minutes for the model to become Active.

Face Blurring algorithm deployed on Syndicai
Face Blurring algorithm deployed on Syndicai

If you see the blue badge Active next to the name of your model it means that your model is deployed to production in the scalable way!

As you could notice using Syndicai does not required you to create a webservice, build a docker, setup any configuration files for the infrastructure.

It’s amazing, isn’t it?

πŸ“š Learn
For more information about the model preparation or deployment process go to Syndicai Docs.

Step 3: Integrate a model

After the model has been deployed, you can access it using the REST API. This can be done via the platform or the terminal.

In order to test it out quickly on the Platform, go to the model Overview page and paste the sample input script in the Run a model section.

{
	"base64": "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"
}

Remember that your model has to be Active in order to work! As the output, you should also get base64 with blurred images.

If you get a correct response you are ready to go with the model integration. Go to the model Integrate page and use the code snippet to implement the REST API in your website, mobile app, or some platform.

For the purpose of this tutorial we have already created a template with a sample React app. It allows you very easily interact with your deployed model. You can try it on the Syndicai Showcase page and get a feeling of that great experience.

face blurring showcase
Face Blurring sample demo | showcase.syndicai.co

In addition, you can fork the repository with the showcase page, because the whole code is open-sourced.

Conclusion

In summary, in the above tutorial you had a chance to deploy a face blurring algorithm on the syndicai platform without any infrastructure setup and webservice configuration.

The main goal of that tutorial was to show you a faster and simpler way of AI model delivery to production in the scalable way.

* * *

If you found that tutorial helpful, or have some questions, please let us know via mail or join us on slack. We would love to hear your feedback.

We would also like to inspire you via our AI models Showcase page and give you a warm invitation to try out our MLOps platform that significantly speeds up the work of AI Teams.