El Bruno

Hi !

I always write this from scratch, so it seems that I’ll drop this one here. So next time I search for this, I’ll find myself.

	import os
	import cv2
	import time
	# init camera
	execution_path = os.getcwd()
	camera = cv2.VideoCapture(0)
	while True:
	# Init and FPS process
	start_time = time.time()
	# Grab a single frame of video
	ret, frame = camera.read()
	# calculate FPS >> FPS = 1 / time to process loop
	fpsInfo = "FPS: " + str(1.0 / (time.time() – start_time))
	print(fpsInfo)
	cv2.putText(frame, fpsInfo, (10, 10), cv2.FONT_HERSHEY_SIMPLEX, 0.4, (255, 255, 255), 1)
	# Display the resulting image
	cv2.imshow('Video', frame)
	# Hit 'q' on the keyboard to quit!
	if cv2.waitKey(1) & 0xFF == ord('q'):
	break
	# Release handle to the webcam
	camera.release()
	cv2.destroyAllWindows()

view raw PythonWebCamFeed.py hosted with ❤ by GitHub

And with some extra lines, we can even detect faces and display some face landmarks:

This is the base of some many image recognition scenarios, so I hope this will save me some local search time 😀

Happy coding!

Greetings @ Toronto

El Bruno

References

My posts on Face Recognition using Python

1. Detecting Faces with 20 lines in Python
2. Face Recognition with 20 lines in Python
3. Detecting Facial Features with 20 lines in Python
4. Facial Features and Face Recognition with 20 lines in Python
5. Performance improvements with code
6. More performance improvements, lowering the camera resolution

And some general Python posts

• Anaconda distribution https://www.anaconda.com/distribution/
• El Bruno, Can’t install TensorFlow on Anaconda, maybe is the Visual Studio distribution https://elbruno.com/2019/09/09/python-cant-install-tensorflow-on-anaconda-maybe-is-the-visual-studio-distribution/
• El Bruno, Anaconda, How to create a custom #Python virtual environment and use it in Jupyter notebooks (a kernel!) https://elbruno.com/2019/09/10/anaconda-how-to-create-a-custom-python-virtual-environment-and-use-it-in-jupyter-notebooks-a-kernel/
• My steps to install a virtual environment with TensorFlow, Keras and more https://elbruno.com/2019/09/12/anaconda-my-steps-to-install-a-virtual-environment-with-tensorflow-keras-and-more/
• Let’s use a Face Recognition demo app for a performance comparison between RaspberryPi3 and RaspberryPi4 https://elbruno.com/2019/08/19/python-lets-use-a-facerecognition-demo-app-for-a-performance-comparison-between-raspberrypi3-and-raspberrypi4/
• Detecting Hololens in realtime in webcam feed using ImageAI and OpenCV with performance improvements https://elbruno.com/2019/08/12/python-detecting-hololens-in-realtime-in-webcam-feed-using-imageai-and-opencv-with-performance-improvements/