python opencv example

facemesh.py

from cvzone.FaceMeshModule import FaceMeshDetector
import cv2

cap = cv2.VideoCapture(0)
detector = FaceMeshDetector(maxFaces=2)
while True:
    success, img = cap.read()
    img, faces = detector.findFaceMesh(img)
    if faces:
        print(faces[0])
    cv2.imshow("Image", img)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()

removebg.py

import numpy as np
import cv2
import logging
from cvzone import FPS
from cvzone.SelfiSegmentationModule import SelfiSegmentation
from scipy.ndimage import gaussian_filter  # for blurring the background image
import pyvirtualcam  # exports as a live video stream

# will be used to add fps counter in the generated video
fpsReader = FPS()

# NOTE : pyvirtualcam uses v4l2loopback virtual cameras on Linux.
# To create a v4l2loopback virtual camera on Ubuntu, run the following:
#    sudo apt install v4l2loopback-dkms
#    sudo modprobe v4l2loopback devices=1

# NOTE : On my particular setup I had to do the following :
#    sudo modprobe -r v4l2loopback
#    sudo modprobe  v4l2loopback video_nr=5
virtualdevice = "/dev/video5"
windowname=virtualdevice # the name of the window

segmentor = SelfiSegmentation()

# initialize video from the webcam
video = cv2.VideoCapture(0)  # under linux it opens /dev/video0

ret, frame = video.read()
W,H = frame.shape[1], frame.shape[0]
logging.debug(f'size={W}x{H}')

with pyvirtualcam.Camera(
    width=W, height=H, fps=30, device=virtualdevice
) as vcam:
    while True:

        # load next frame
        ret, frame = video.read()
        if not ret:
            raise Exception("video.read() failed")

        # Compute a blurred version of the video frame
        blurred = gaussian_filter(frame, sigma=12)

        # Detect persons & replace the background by the blurred image
        result = segmentor.removeBG(frame, blurred, threshold=0.8)

        # Add FPS count
        fps, result = fpsReader.update(
            result, pos=(5, 15), color=(0, 255, 0), scale=1, thickness=1
        )

        # Send the frame to the virtual camera
        vcam.send(result)
        vcam.sleep_until_next_frame()

        cv2.imshow(windowname, result)

        # 'q' exits the loop
        if cv2.waitKey(1) & 0xFF == ord("q"):
            break

        # closing the window exits the loop
        if cv2.getWindowProperty(windowname, cv2.WND_PROP_VISIBLE) == 0:
            break

# cleanup
cv2.destroyAllWindows()
video.release()

requirements.txt

numpy==1.24.1
opencv-python==4.7.0.68
pyvirtualcam==0.10.2
mediapipe==0.9.0.1
cvzone==1.5.6
scipy==1.10.0