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1.py
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1.py
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import argparse
import datetime
import open3d as o3d
import numpy as np
class RecorderWithCallback:
def __init__(self, config, device, filename, align_depth_to_color):
# Global flags
self.flag_exit = False
self.flag_record = False
self.filename = filename
self.align_depth_to_color = align_depth_to_color
self.recorder = o3d.io.AzureKinectRecorder(config, device)
if not self.recorder.init_sensor():
raise RuntimeError('Failed to connect to sensor')
def escape_callback(self, vis):
self.flag_exit = True
if self.recorder.is_record_created():
print('Recording finished.')
else:
print('Nothing has been recorded.')
return False
def space_callback(self, vis): # 空格键用于录制交互
if self.flag_record: # 停止
print('Recording paused. '
'Press [Space] to continue. '
'Press [ESC] to save and exit.')
self.flag_record = False
elif not self.recorder.is_record_created(): # 开始
if self.recorder.open_record(self.filename):
print('Recording started. '
'Press [SPACE] to pause. '
'Press [ESC] to save and exit.')
self.flag_record = True
else: #继续
print('Recording resumed, video may be discontinuous. '
'Press [SPACE] to pause. '
'Press [ESC] to save and exit.')
self.flag_record = True
return False
def run(self):
glfw_key_escape = 256
glfw_key_space = 32
vis = o3d.visualization.VisualizerWithKeyCallback()
vis.register_key_callback(glfw_key_escape, self.escape_callback)
vis.register_key_callback(glfw_key_space, self.space_callback)
vis.create_window('recorder', 1920, 540)
print("Recorder initialized. Press [SPACE] to start. "
"Press [ESC] to save and exit.")
vis_geometry_added = False
while not self.flag_exit:
rgbd = self.recorder.record_frame(self.flag_record,
self.align_depth_to_color) # 录制函数,flag_record通过空格键控制
# if rgbd is not None:
# print(rgbd.color.shape)
if rgbd is None:
continue
color_image = rgbd.color
depth_image = rgbd.depth
print(np.array(depth_image.Image).shape)
print(type(depth_image.Image))
rgbd_image = o3d.geometry.RGBDImage.create_from_color_and_depth(
color_image, depth_image,
convert_rgb_to_intensity=False)
print(np.array(rgbd_image).shape)
if not vis_geometry_added:
vis.add_geometry(rgbd)
vis_geometry_added = True
vis.update_geometry(rgbd)
vis.poll_events()
vis.update_renderer()
self.recorder.close_record() # 停止录制,flag_exit通过Esc键控制
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Azure kinect mkv recorder.')
parser.add_argument('--config', type=str, help='input json kinect config')
parser.add_argument('--output',default='data/cs.npy', type=str, help='output mkv filename')
parser.add_argument('--list',
action='store_true',
help='list available azure kinect sensors')
parser.add_argument('--device',
type=int,
default=0,
help='input kinect device id')
parser.add_argument('-a',
'--align_depth_to_color',
default= True,
action='store_true',
help='enable align depth image to color')
# '-a'的'-'代表可选,'store_true'默认False,命令行开启后为True
args = parser.parse_args()
if args.list:
o3d.io.AzureKinectSensor.list_devices()
exit()
if args.config is not None:
config = o3d.io.read_azure_kinect_sensor_config(args.config)
else:
config = o3d.io.AzureKinectSensorConfig()
if args.output is not None:
filename = args.output
else:
filename = '{date:%Y-%m-%d-%H-%M-%S}.mkv'.format(
date=datetime.datetime.now())
print('Prepare writing to {}'.format(filename))
device = args.device
if device < 0 or device > 255:
print('Unsupported device id, fall back to 0')
device = 0
r = RecorderWithCallback(config, device, filename,
args.align_depth_to_color)
r.run()
# import open3d as o3d
# # 创建回放器对象
# playback = o3d.io.AzureKinectPlayback()
# # 打开录制文件
# filename = "data/cs.mkv"
# success = playback.open(filename)
# if not success:
# print(f"Failed to open file {filename}")
# exit()
# # 启动回放
# while True:
# # 获取一帧RGBD数据
# rgbd = playback.read_frame()
# # 回放结束
# if not rgbd:
# break
# # 如果有数据,将RGBD图像显示出来
# o3d.visualization.draw_geometries([rgbd])
# # 关闭回放
# playback.close()
import cv2
import numpy as np
# 定义视频文件路径
filename = 'data/cs.mkv'
# 创建一个视频捕获对象
cap = cv2.VideoCapture(filename)
# 检查是否成功打开视频文件
if not cap.isOpened():
print("Unable to open file:", filename)
exit()
# 处理视频文件的每一帧
frames = []
while True:
# 捕获一帧数据
ret, frame = cap.read()
# 视频结束
if not ret:
break
# 将数据转换成Numpy数组
frame = np.array(frame)
# 将这一帧数据存储到列表中
frames.append(frame)
# 关闭视频文件
cap.release()
# 打印视频数据的维度
print(f"Video data shape: {np.array(frames).shape}")