pyfakewebcam Il y a divers projets qui font ça sur GitHub, celui ci à cette qualité de marcher!

• https://codingshiksha.com/python/python-3-pyfakewebcam-script-to-build-fake-webcam-with-custom-background-image-gui-desktop-app-full-project-for-beginners/
• https://github.com/jremmons/pyfakewebcam
• https://github.com/umlaeute/v4l2loopback

A voir, nécessaire mais peut-être pas suffisant:

sudo apt install v4l2loopback-utils

sudo apt install python3-pip
python3 -m pip install --upgrade pip
sudo apt install python3-venv
 
cd /le/dossier/de/votre/projet
python3 -m venv mon_env
source mon_env/bin/activate
python3 -m pip install opencv-python pyfakewebcam

cam_relay.py

"""
Insert the v4l2loopback kernel module.
modprobe v4l2loopback devices=2
will create two fake webcam devices
"""
import time
import pyfakewebcam
import cv2
import numpy as np
 
cap = cv2.VideoCapture(0)
camera = pyfakewebcam.FakeWebcam('/dev/video1', 640, 480)
while True:
    ret, image = cap.read()
    if ret:
        # # gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        camera.schedule_frame(image)
    if cv2.waitKey(1) == 27:
        break
 
"""
Run the following command to see the output of the fake webcam.
ffplay /dev/video1
or open a camera in vlc
"""

Exécuter le script avec:

cd /le/dossier/de/votre/projet
modprobe v4l2loopback devices=2
./mon_env/bin/python3 cam_relay.py

Dans un autre terminal

ffplay /dev/video1

Il faudra peut-être adapter les numéro de /dev/video

cd /le/dossier/de/votre/projet
source mon_env/bin/activate
python3 -m pip install depthai numpy

sender_oak_depth.py

import cv2
import depthai as dai
import numpy as np
import pyfakewebcam
 
pipeline = dai.Pipeline()
# Define a source - two mono (grayscale) cameras
left = pipeline.createMonoCamera()
left.setResolution(dai.MonoCameraProperties.SensorResolution.THE_400_P)
left.setBoardSocket(dai.CameraBoardSocket.LEFT)
 
right = pipeline.createMonoCamera()
right.setResolution(dai.MonoCameraProperties.SensorResolution.THE_400_P)
right.setBoardSocket(dai.CameraBoardSocket.RIGHT)
 
# Create a node that will produce the depth map
# (using disparity output as it's easier to visualize depth this way)
depth = pipeline.createStereoDepth()
depth.setConfidenceThreshold(200)
 
# Options: MEDIAN_OFF, KERNEL_3x3, KERNEL_5x5, KERNEL_7x7 (default)
median = dai.StereoDepthProperties.MedianFilter.KERNEL_7x7 # For depth filtering
depth.setMedianFilter(median)
 
# Better handling for occlusions:
depth.setLeftRightCheck(False)
# Closer-in minimum depth, disparity range is doubled:
depth.setExtendedDisparity(False)
# Better accuracy for longer distance, fractional disparity 32-levels:
depth.setSubpixel(False)
 
left.out.link(depth.left)
right.out.link(depth.right)
 
# Create output
xout = pipeline.createXLinkOut()
xout.setStreamName("disparity")
depth.disparity.link(xout.input)
 
camera = pyfakewebcam.FakeWebcam('/dev/video1', 640, 480)
 
with dai.Device(pipeline) as device:
    device.startPipeline()
 
    # Output queue will be used to get the disparity frames from the outputs defined above
    q = device.getOutputQueue(name="disparity", maxSize=4, blocking=False)
 
    while True:
        inDepth = q.get()  # blocking call, will wait until a new data has arrived
        frame = inDepth.getFrame()
        frame = cv2.normalize(frame, None, 0, 255, cv2.NORM_MINMAX)
 
        depth_gray_image = cv2.resize(np.asanyarray(frame), (640, 480),
                                interpolation = cv2.INTER_AREA)
        # v4l2 doit être RGB
        color = cv2.cvtColor(depth_gray_image, cv2.COLOR_GRAY2RGB)
        camera.schedule_frame(color)
 
        if cv2.waitKey(1) == 27:
            break

Exécuter le script avec:

cd /le/dossier/de/votre/projet
modprobe v4l2loopback devices=2
./mon_env/bin/python3 sender_oak_depth.py

Ouvrir /dev/video1 dans VLC

Pour l'installation, voir https://github.com/sergeLabo/grande_echelle#installation

cd /le/dossier/de/votre/projet
source mon_env/bin/activate
python3 -m pip install  pyrealsense2 numpy

sender_rs_depth.py

import os
import time
import pyfakewebcam
import cv2
import numpy as np
import pyrealsense2 as rs
 
class MyRealSense:
    """Initialise la caméra et permet d'accéder aux images"""
    def __init__(self):
        self.width = 1280
        self.height = 720
        self.pose_loop = 1
        self.pipeline = rs.pipeline()
        config = rs.config()
        pipeline_wrapper = rs.pipeline_wrapper(self.pipeline)
        try:
            pipeline_profile = config.resolve(pipeline_wrapper)
        except:
            print('\n\nPas de Capteur Realsense connecté\n\n')
            os._exit(0)
        device = pipeline_profile.get_device()
        config.enable_stream(   rs.stream.color,
                                width=self.width,
                                height=self.height,
                                format=rs.format.bgr8,
                                framerate=30)
        config.enable_stream(   rs.stream.depth,
                                width=self.width,
                                height=self.height,
                                format=rs.format.z16,
                                framerate=30)
        self.pipeline.start(config)
        self.align = rs.align(rs.stream.color)
        unaligned_frames = self.pipeline.wait_for_frames()
        frames = self.align.process(unaligned_frames)
        depth = frames.get_depth_frame()
        self.depth_intrinsic = depth.profile.as_video_stream_profile().intrinsics
        # Affichage de la taille des images
        color_frame = frames.get_color_frame()
        img = np.asanyarray(color_frame.get_data())
        print(f"Taille des images:"
              f"     {img.shape[1]}x{img.shape[0]}")
        self.camera = pyfakewebcam.FakeWebcam('/dev/video1', 640, 480)
 
    def run(self):
        """Boucle infinie, quitter avec Echap dans la fenêtre OpenCV"""
        while self.pose_loop:
            frames = self.pipeline.wait_for_frames(timeout_ms=80)
            # Align the depth frame to color frame
            aligned_frames = self.align.process(frames)
            depth_color_frame = aligned_frames.get_depth_frame()
 
            # Convert 16bit data: à vérifier, c'est bon pour gray, en RGB ?
            detph_color_16bit = np.array(depth_color_frame, dtype=np.uint16)
            detph_color_16bit *= 256
            self.camera.schedule_frame(detph_color_16bit)
 
            if cv2.waitKey(1) == 27:
                break
 
if __name__ == '__main__':
    mrs = MyRealSense()
    mrs.run()

Exécuter le script avec:

cd /le/dossier/de/votre/projet
modprobe v4l2loopback devices=2
./mon_env/bin/python3 sender_oak_depth.py

Ouvrir /dev/video1 dans VLC
ou

receiver.py

import cv2
cap = cv2.VideoCapture(2)
while 1:
    ret, image = cap.read()
    if ret:
        cv2.imshow("frame", image)
    if cv2.waitKey(1) == 27:
        break