[Intel Realsense D435] Implementar visualización, grabación y guardado de video (Python)

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Recientemente, estoy aprendiendo a usar la cámara de profundidad Intel Realsense D435, por lo que registraré el proceso de desarrollo del programa.

El siguiente es el procedimiento general:

'''
使用realsense相机录制视频
'''

#!/usr/bin/env python
# coding=utf-8
import time
import pyrealsense2 as rs
import numpy as np
import cv2

class Camera(object):
    '''
    realsense相机处理类
    '''
    def __init__(self, width=1280, height=720, fps=30):
        self.width = width
        self.height = height
        self.pipeline = rs.pipeline()
        self.config = rs.config()
        self.config.enable_stream(rs.stream.color, self.width, self.height, rs.format.bgr8, fps)
        self.config.enable_stream(rs.stream.depth, self.width, self.height, rs.format.z16,  fps)
        # self.align = rs.align(rs.stream.color) # depth2rgb
        self.pipeline.start(self.config)  # 开始连接相机


    def get_frame(self):
        frames = self.pipeline.wait_for_frames() # 获得frame (包括彩色，深度图)
        # 创建对齐对象
        align_to = rs.stream.color            # rs.align允许我们执行深度帧与其他帧的对齐
        align = rs.align(align_to)            # “align_to”是我们计划对齐深度帧的流类型。
        aligned_frames = align.process(frames)
        # 获取对齐的帧
        aligned_depth_frame = aligned_frames.get_depth_frame()  # aligned_depth_frame是对齐的深度图
        color_frame = aligned_frames.get_color_frame()
        colorizer = rs.colorizer()
        depthx_image = np.asanyarray(aligned_depth_frame.get_data())
        color_image = np.asanyarray(color_frame.get_data())
        colorizer_depth = np.asanyarray(colorizer.colorize(aligned_depth_frame).get_data())
        return color_image, depthx_image,colorizer_depth

    def release(self):
        self.pipeline.stop()
if __name__=='__main__':

    # 视频保存路径
    video_path = f'D://Realsense//rgb_data//{int(time.time())}.mp4'
    video_depth_path = f'D://Realsense//depth_data//{int(time.time())}_depth.mp4'
    video_depthcolor_path = f'D://Realsense//depthcolor_data//{int(time.time())}_depthcolor.mp4'
    video_depthcolor_camera_path = f'D://Realsense//camera_colordepth//{int(time.time())}_depthcolor.mp4'
    # 初始化参数
    fps, w, h = 30, 1280, 720
    mp4 = cv2.VideoWriter_fourcc(*'mp4v') # 视频格式
    wr  = cv2.VideoWriter(video_path, mp4, fps, (w, h), isColor=True) # 视频保存而建立对象
    wr_depth = cv2.VideoWriter(video_depth_path, mp4, fps, (w, h), isColor=False)
    wr_depthcolor = cv2.VideoWriter(video_depthcolor_path, mp4, fps, (w, h), isColor=True)
    wr_camera_colordepth = cv2.VideoWriter(video_depthcolor_camera_path, mp4, fps, (w, h), isColor=True)

    cam = Camera(w, h, fps)
    print('录制视频请按: s, 保存视频或退出请按：q')
    flag_V = 0
    while True:
            color_image, depth_image, colorizer_depth = cam.get_frame() # 读取图像帧，包括RGB图和深度图
		 #深度图数据格式转换，uint16→uint8
            depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_JET)
            images = np.hstack((color_image, depth_colormap))   
            cv2.namedWindow('RealSense', cv2.WINDOW_AUTOSIZE)
            cv2.imshow('RealSense', colorizer_depth)

            # print('ll')
            key = cv2.waitKey(1)
            if key & 0xFF == ord('s') :
                flag_V = 1
            if flag_V == 1:
                wr.write(color_image)                # 保存RGB图像帧
                wr_depth.write(depth_image)          # 保存基于灰度深度图
                wr_depthcolor.write(depth_colormap)  # 保存计算所得着色深度图
                wr_camera_colordepth.write(colorizer_depth)  # 保存相机自行计算的着色深度图
                print('...录制视频中...')
            if key & 0xFF == ord('q') or key == 27:
                cv2.destroyAllWindows()
                print('...录制结束/直接退出...')
                break
    wr_depthcolor.release()
    wr_depth.release()
    wr.release()
    wr_camera_colordepth.release()
    cam.release()
    print(f'，若保存视频，则视频保存在：{video_path}')

Los pasos se desglosan de la siguiente manera:

①Referencia de biblioteca

'''
使用realsense相机录制视频
'''

#!/usr/bin/env python
# coding=utf-8
import time
import pyrealsense2 as rs
import numpy as np
import cv2

②Inicialización de la cámara, adquisición y corte de datos de flujo de imágenes: implementado por clases.

class Camera(object):
    '''
    realsense相机处理类
    '''
    def __init__(self, width=1280, height=720, fps=30):
        self.width = width
        self.height = height
        self.pipeline = rs.pipeline()
        self.config = rs.config()
        self.config.enable_stream(rs.stream.color, self.width, self.height, rs.format.bgr8, fps)
        self.config.enable_stream(rs.stream.depth, self.width, self.height, rs.format.z16,  fps)
        self.pipeline.start(self.config)  # 开始连接相机


    def get_frame(self):
        frames = self.pipeline.wait_for_frames() # 获得frame (包括彩色，深度图)
        # 创建对齐对象
        align_to = rs.stream.color            # rs.align允许我们执行深度帧与其他帧的对齐
        align = rs.align(align_to)            # “align_to”是我们计划对齐深度帧的流类型。
        aligned_frames = align.process(frames)
        # 获取对齐的帧
        aligned_depth_frame = aligned_frames.get_depth_frame()  # aligned_depth_frame是对齐的深度图
        color_frame = aligned_frames.get_color_frame()
        colorizer = rs.colorizer()
        depthx_image = np.asanyarray(aligned_depth_frame.get_data())
        color_image = np.asanyarray(color_frame.get_data())
        colorizer_depth = np.asanyarray(colorizer.colorize(aligned_depth_frame).get_data())
        return color_image, depthx_image,colorizer_depth

    def release(self):
        self.pipeline.stop()

③El programa principal guarda videos: grabe según los comandos del teclado y la ruta de guardado debe modificarse según las condiciones locales.

if __name__=='__main__':

    # 视频保存路径
    video_path = f'D://Realsense//rgb_data//{int(time.time())}.mp4'
    video_depth_path = f'D://Realsense//depth_data//{int(time.time())}_depth.mp4'
    video_depthcolor_path = f'D://Realsense//depthcolor_data//{int(time.time())}_depthcolor.mp4'
    video_depthcolor_camera_path = f'D://Realsense//camera_colordepth//{int(time.time())}_depthcolor.mp4'
    # 初始化参数
    fps, w, h = 30, 1280, 720
    mp4 = cv2.VideoWriter_fourcc(*'mp4v') # 视频格式
    wr  = cv2.VideoWriter(video_path, mp4, fps, (w, h), isColor=True) # 视频保存而建立对象
    wr_depth = cv2.VideoWriter(video_depth_path, mp4, fps, (w, h), isColor=False)
    wr_depthcolor = cv2.VideoWriter(video_depthcolor_path, mp4, fps, (w, h), isColor=True)
    wr_camera_colordepth = cv2.VideoWriter(video_depthcolor_camera_path, mp4, fps, (w, h), isColor=True)

    cam = Camera(w, h, fps)
    print('录制视频请按: s, 保存视频或退出请按：q')
    flag_V = 0
    while True:
            color_image, depth_image, colorizer_depth = cam.get_frame() # 读取图像帧，包括RGB图和深度图
		 #深度图数据格式转换，uint16→uint8
            depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_JET)
            images = np.hstack((color_image, depth_colormap))   
            cv2.namedWindow('RealSense', cv2.WINDOW_AUTOSIZE)
            cv2.imshow('RealSense', images)

            # print('ll')
            key = cv2.waitKey(1)
            if key & 0xFF == ord('s') :
                flag_V = 1
            if flag_V == 1:
                wr.write(color_image)                # 保存RGB图像帧
                wr_depth.write(depth_image)          # 保存基于灰度深度图
                wr_depthcolor.write(depth_colormap)  # 保存计算所得着色深度图
                wr_camera_colordepth.write(colorizer_depth)  # 保存相机自行计算的着色深度图
                print('...录制视频中...')
            if key & 0xFF == ord('q') or key == 27:
                cv2.destroyAllWindows()
                print('...录制结束/直接退出...')
                break
    wr_depthcolor.release()
    wr_depth.release()
    wr.release()
    wr_camera_colordepth.release()
    cam.release()
    print(f'，若保存视频，则视频保存在：{video_path}')

Captura de pantalla de grabación de video:

imagen RGB

Mapa de profundidad y mapa de pseudocolor