• github.com librealsense doc linux

sudo apt-key adv --keyserver keys.gnupg.net --recv-key F6E65AC044F831AC80A06380C8B3A55A6F3EFCDE || sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-key F6E65AC044F831AC80A06380C8B3A55A6F3EFCDE
sudo add-apt-repository "deb http://realsense-hw-public.s3.amazonaws.com/Debian/apt-repo bionic main" -u
sudo apt-get install librealsense2-dkms
sudo apt-get install librealsense2-utils

Tester avec:

realsense-viewer

• https://github.com/IntelRealSense/librealsense/tree/master/wrappers/python#installation

import pyrealsense2 as rs

• opencv_viewer_example.py

opencv_viewer_example.py

## License: Apache 2.0. See LICENSE file in root directory.
## Copyright(c) 2015-2017 Intel Corporation. All Rights Reserved.
 
###############################################
##      Open CV and Numpy integration        ##
###############################################
 
import pyrealsense2 as rs
import numpy as np
import cv2
 
# Configure depth and color streams
pipeline = rs.pipeline()
config = rs.config()
 
# Get device product line for setting a supporting resolution
pipeline_wrapper = rs.pipeline_wrapper(pipeline)
pipeline_profile = config.resolve(pipeline_wrapper)
device = pipeline_profile.get_device()
device_product_line = str(device.get_info(rs.camera_info.product_line))
 
config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)
 
if device_product_line == 'L500':
    config.enable_stream(rs.stream.color, 960, 540, rs.format.bgr8, 30)
else:
    config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 30)
 
# Start streaming
pipeline.start(config)
 
try:
    while True:
 
        # Wait for a coherent pair of frames: depth and color
        frames = pipeline.wait_for_frames()
        depth_frame = frames.get_depth_frame()
        color_frame = frames.get_color_frame()
        if not depth_frame or not color_frame:
            continue
 
        # Convert images to numpy arrays
        depth_image = np.asanyarray(depth_frame.get_data())
        color_image = np.asanyarray(color_frame.get_data())
 
        # Apply colormap on depth image (image must be converted to 8-bit per pixel first)
        depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_JET)
 
        depth_colormap_dim = depth_colormap.shape
        color_colormap_dim = color_image.shape
 
        # If depth and color resolutions are different, resize color image to match depth image for display
        if depth_colormap_dim != color_colormap_dim:
            resized_color_image = cv2.resize(color_image, dsize=(depth_colormap_dim[1], depth_colormap_dim[0]), interpolation=cv2.INTER_AREA)
            images = np.hstack((resized_color_image, depth_colormap))
        else:
            images = np.hstack((color_image, depth_colormap))
 
        # Show images
        cv2.namedWindow('RealSense', cv2.WINDOW_AUTOSIZE)
        cv2.imshow('RealSense', images)
        cv2.waitKey(1)
 
finally:
 
    # Stop streaming
    pipeline.stop()

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