WebRTC is a Technology I came across recently. It can for example be used to stream video and audio from a server like an EC2 instance to a browser. In addition WebRTC provides a channel to send generic data between the server and the browser. Creating applications using WebRTC bears the problem of how to create automated UI tests reacing to the content of the stream. This post describes a concept how to do this using Selenium and OpenCV.
Selenium is a framework to automate browser based UI tests. UI Developers use it to create regression tests for their designs. OpenCV is a library that can be used to detect and classify objects in images.
Using both tools we are able to create a test that can react to the content of a WebRTC stream. The test can for example check if a video stream is showing a certain object.
This is a minimal example showing the interaction between selenium and OpenCV. It opens a browser, takes a screenshot, detects faces in the screenshot and draws rectangles around them. To make it work you need to download the haarcascade_frontalface_default.xml file and place it in the same directory as the script and install the selenium and openCV modules.
pip install selenium opencv-python ```python: from selenium import webdriver import cv2 # Initialize Selenium and open a webpage driver = webdriver.Chrome() driver.get('https://en.wikipedia.org/wiki/Jean-Luc_Picard') # Take a screenshot and save it as 'screenshot.png' screenshot = driver.get_screenshot_as_png() screenshot_path = "screenshot.png" with open(screenshot_path, "wb") as file: file.write(screenshot) # Process the image using OpenCV image = cv2.imread(screenshot_path) # Initialize Haar cascade for face detection face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # Detect faces faces = face_cascade.detectMultiScale(gray_image, 1.1, 4) # Draw rectangles around detected faces for (x, y, w, h) in faces: cv2.rectangle(image, (x, y), (x+w, y+h), (255, 0, 0), 2) # Save the processed image cv2.imwrite("faces_detected.png", image) # Close the browser driver.quit()