This article share the technique used by PixLab to port the real-time face detection runtime written in pure C of the SOD Computer Vision library to WebAssembly to achieve real-time face detection on the browser.

The final result including the WASM binary, face model and the exported Javascript interfaces are available to download here and ready to be integrated into existing projects in-need for real-time face detection in the browser.

The full article is available to consult here.

The PixLab Computer Vision team is pleased to announce that a milestone have been reached for the Not Safe For Work API endpoint. Over the course of the last 12 months, the /nsfw API endpoint have already analyzed millions of our user's media files with high accuracy.

For those not familiar with this endpoint. /nsfw let you detect not suitable for work (i.e. nudity & adult) content in a given image or video frame. NSFW is of particular interest, if mixed with some media processing API endpoints like /blur, /encrypt or /mogrify to censor images on the fly according to their nsfw score.

A typical blurred image with a high NSFW score should look like the following:

To obtain such image result, two endpoints were actually used:

• /NSFW is the analysis endpoint that must be called first. It does perform nudity & adult content detection and return a score value between 0..1. The more this value approaches 1, the more your picture/frame is highly nsfw.
• /blur is called later only if the nsfw score value returned earlier is greater than certain threshold. In our case, it is set to 0.5.

The Python code below was used to generate the blurred picture programmatically without any human intervention. This can help you automate things such as verifying user's uploads:

import requests
import json

# Target Image: Change to any link (Possibly adult) you want or switch to POST if you want to upload your image directly, refer to the sample set for more info.
img = 'https://i.redd.it/oetdn9wc13by.jpg' 
# Your PixLab key
key = 'Pixlab_Key'

# Censor an image according to its NSFW score
req = requests.get('https://api.pixlab.io/nsfw',params={'img':img,'key':key})
reply = req.json()
if reply['status'] != 200:
    print (reply['error'])
elif reply['score'] < 0.5 :
    print ("No adult content were detected on this picture")
else:
    # Highly NSFW picture
    print ("Censoring NSFW picture...")
    # Call blur with the highest possible radius and sigma
    req = requests.get('https://api.pixlab.io/blur',params={'img':img,'key':key,'rad':50,'sig':30})
    reply = req.json()
    if reply['status'] != 200:
        print (reply['error'])
    else:
        print ("Censored image: "+ reply['link'])

Finally, the official endpoint documentation is available to consult at https://pixlab.io/cmd?id=nsfw and a set of working samples in various programming language are available at the PixLab samples pages.

The SOD development team just published a new computer vision article on how to detect vehicles registration plates without heavy Machine Learning techniques, just standard image processing routines already implemented in the SOD library. The article is available to consult here.