机器学习和深度学习|RealSense D435 的开发日记(pyrealsense小实战项目）深度学习|python

欢迎来到机器学习的世界
博客主页：卿云阁
欢迎关注点赞收藏??留言
本文由卿云阁原创！
本阶段属于练气阶段，希望各位仙友顺利完成突破
首发时间：2021年6月22日
??希望可以和大家一起完成进阶之路！
作者水平很有限，如果发现错误，请留言轰炸哦！万分感谢！
6月22日星期三天气晴

文章图片

一、使用 OpenCV 和 Numpy 的帮助渲染深度和彩色图像

## 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))found_rgb = False for s in device.sensors: if s.get_info(rs.camera_info.name) == 'RGB Camera': found_rgb = True break if not found_rgb: print("The demo requires Depth camera with Color sensor") exit(0)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()

文章图片

二、通过将深度图像与彩色图像对齐并执行简单计算以剥离背景来执行背景删除的方法
## License: Apache 2.0. See LICENSE file in root directory. ## Copyright(c) 2017 Intel Corporation. All Rights Reserved.##################################################### ##Align Depth to Color## ###################################################### First import the library import pyrealsense2 as rs # Import Numpy for easy array manipulation import numpy as np # Import OpenCV for easy image rendering import cv2# Create a pipeline pipeline = rs.pipeline()# Create a config and configure the pipeline to stream #different resolutions of color and depth streams 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))found_rgb = False for s in device.sensors: if s.get_info(rs.camera_info.name) == 'RGB Camera': found_rgb = True break if not found_rgb: print("The demo requires Depth camera with Color sensor") exit(0)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 profile = pipeline.start(config)# Getting the depth sensor's depth scale (see rs-align example for explanation) depth_sensor = profile.get_device().first_depth_sensor() depth_scale = depth_sensor.get_depth_scale() print("Depth Scale is: " , depth_scale)# We will be removing the background of objects more than #clipping_distance_in_meters meters away clipping_distance_in_meters = 1 #1 meter clipping_distance = clipping_distance_in_meters / depth_scale# Create an align object # rs.align allows us to perform alignment of depth frames to others frames # The "align_to" is the stream type to which we plan to align depth frames. align_to = rs.stream.color align = rs.align(align_to)# Streaming loop try: while True: # Get frameset of color and depth frames = pipeline.wait_for_frames() # frames.get_depth_frame() is a 640x360 depth image# Align the depth frame to color frame aligned_frames = align.process(frames)# Get aligned frames aligned_depth_frame = aligned_frames.get_depth_frame() # aligned_depth_frame is a 640x480 depth image color_frame = aligned_frames.get_color_frame()# Validate that both frames are valid if not aligned_depth_frame or not color_frame: continuedepth_image = np.asanyarray(aligned_depth_frame.get_data()) color_image = np.asanyarray(color_frame.get_data())# Remove background - Set pixels further than clipping_distance to grey grey_color = 153 depth_image_3d = np.dstack((depth_image,depth_image,depth_image)) #depth image is 1 channel, color is 3 channels bg_removed = np.where((depth_image_3d > clipping_distance) | (depth_image_3d <= 0), grey_color, color_image)# Render images: #depth align to color on left #depth on right depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_JET) images = np.hstack((bg_removed, depth_colormap))cv2.namedWindow('Align Example', cv2.WINDOW_NORMAL) cv2.imshow('Align Example', images) key = cv2.waitKey(1) # Press esc or 'q' to close the image window if key & 0xFF == ord('q') or key == 27: cv2.destroyAllWindows() break finally: pipeline.stop()

文章图片

三、使用多个摄像头计算物体的长度、宽度和高度的简单演示 【机器学习和深度学习|RealSense D435 的开发日记(pyrealsense小实战项目）】librealsense/wrappers/python/examples at master · IntelRealSense/librealsense (github.com)
文章图片
https://github.com/IntelRealSense/librealsense/tree/master/wrappers/python/examples

机器学习和深度学习|RealSense D435 的开发日记(pyrealsense小实战项目）

推荐阅读

高三复读生该如何减压？身心健康才是成功教育！

ps褶皱文字怎么做 photoshop制作褶皱文字效果的操作步骤

昆仑山在哪昆仑山的位置

日异月殊的意思日异月殊的出处

高效能慢生活践行第626天1103-2020

等额本息和等额本金哪个划算等额本息和等额本金哪个划算30年

浴盐多久用一次好

板鞋五个洞系鞋带的方法板鞋五个洞系鞋带的方法图解

血见愁的功效与作用血见愁

烫头发的药水

适合旅游的时候用的相机

天魔劫天劫

盈滨海岸一米海岸

用完脱毛仪之后可以用身体乳么

苦苣菜的做法和功效

电视坏了可以改成什么样的，电视坏了可以改成什么样的电视

虎牙直播一直正在加载，虎牙直播一直正在加载怎么回事

建安文学对后代文学有何积极影响

2022年5月希腊移民入境人数激增

想回农村养兔子最少得养多少？