Files
diffusion_policy/diffusion_policy/real_world/multi_realsense.py
2023-03-07 16:07:15 -05:00

225 lines
7.6 KiB
Python

from typing import List, Optional, Union, Dict, Callable
import numbers
import time
import pathlib
from multiprocessing.managers import SharedMemoryManager
import numpy as np
import pyrealsense2 as rs
from diffusion_policy.real_world.single_realsense import SingleRealsense
from diffusion_policy.real_world.video_recorder import VideoRecorder
class MultiRealsense:
def __init__(self,
serial_numbers: Optional[List[str]]=None,
shm_manager: Optional[SharedMemoryManager]=None,
resolution=(1280,720),
capture_fps=30,
put_fps=None,
put_downsample=True,
record_fps=None,
enable_color=True,
enable_depth=False,
enable_infrared=False,
get_max_k=30,
advanced_mode_config: Optional[Union[dict, List[dict]]]=None,
transform: Optional[Union[Callable[[Dict], Dict], List[Callable]]]=None,
vis_transform: Optional[Union[Callable[[Dict], Dict], List[Callable]]]=None,
recording_transform: Optional[Union[Callable[[Dict], Dict], List[Callable]]]=None,
video_recorder: Optional[Union[VideoRecorder, List[VideoRecorder]]]=None,
verbose=False
):
if shm_manager is None:
shm_manager = SharedMemoryManager()
shm_manager.start()
if serial_numbers is None:
serial_numbers = SingleRealsense.get_connected_devices_serial()
n_cameras = len(serial_numbers)
advanced_mode_config = repeat_to_list(
advanced_mode_config, n_cameras, dict)
transform = repeat_to_list(
transform, n_cameras, Callable)
vis_transform = repeat_to_list(
vis_transform, n_cameras, Callable)
recording_transform = repeat_to_list(
recording_transform, n_cameras, Callable)
video_recorder = repeat_to_list(
video_recorder, n_cameras, VideoRecorder)
cameras = dict()
for i, serial in enumerate(serial_numbers):
cameras[serial] = SingleRealsense(
shm_manager=shm_manager,
serial_number=serial,
resolution=resolution,
capture_fps=capture_fps,
put_fps=put_fps,
put_downsample=put_downsample,
record_fps=record_fps,
enable_color=enable_color,
enable_depth=enable_depth,
enable_infrared=enable_infrared,
get_max_k=get_max_k,
advanced_mode_config=advanced_mode_config[i],
transform=transform[i],
vis_transform=vis_transform[i],
recording_transform=recording_transform[i],
video_recorder=video_recorder[i],
verbose=verbose
)
self.cameras = cameras
self.shm_manager = shm_manager
def __enter__(self):
self.start()
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.stop()
@property
def n_cameras(self):
return len(self.cameras)
@property
def is_ready(self):
is_ready = True
for camera in self.cameras.values():
if not camera.is_ready:
is_ready = False
return is_ready
def start(self, wait=True, put_start_time=None):
if put_start_time is None:
put_start_time = time.time()
for camera in self.cameras.values():
camera.start(wait=False, put_start_time=put_start_time)
if wait:
self.start_wait()
def stop(self, wait=True):
for camera in self.cameras.values():
camera.stop(wait=False)
if wait:
self.stop_wait()
def start_wait(self):
for camera in self.cameras.values():
camera.start_wait()
def stop_wait(self):
for camera in self.cameras.values():
camera.join()
def get(self, k=None, out=None) -> Dict[int, Dict[str, np.ndarray]]:
"""
Return order T,H,W,C
{
0: {
'rgb': (T,H,W,C),
'timestamp': (T,)
},
1: ...
}
"""
if out is None:
out = dict()
for i, camera in enumerate(self.cameras.values()):
this_out = None
if i in out:
this_out = out[i]
this_out = camera.get(k=k, out=this_out)
out[i] = this_out
return out
def get_vis(self, out=None):
results = list()
for i, camera in enumerate(self.cameras.values()):
this_out = None
if out is not None:
this_out = dict()
for key, v in out.items():
# use the slicing trick to maintain the array
# when v is 1D
this_out[key] = v[i:i+1].reshape(v.shape[1:])
this_out = camera.get_vis(out=this_out)
if out is None:
results.append(this_out)
if out is None:
out = dict()
for key in results[0].keys():
out[key] = np.stack([x[key] for x in results])
return out
def set_color_option(self, option, value):
n_camera = len(self.cameras)
value = repeat_to_list(value, n_camera, numbers.Number)
for i, camera in enumerate(self.cameras.values()):
camera.set_color_option(option, value[i])
def set_exposure(self, exposure=None, gain=None):
"""
exposure: (1, 10000) 100us unit. (0.1 ms, 1/10000s)
gain: (0, 128)
"""
if exposure is None and gain is None:
# auto exposure
self.set_color_option(rs.option.enable_auto_exposure, 1.0)
else:
# manual exposure
self.set_color_option(rs.option.enable_auto_exposure, 0.0)
if exposure is not None:
self.set_color_option(rs.option.exposure, exposure)
if gain is not None:
self.set_color_option(rs.option.gain, gain)
def set_white_balance(self, white_balance=None):
if white_balance is None:
self.set_color_option(rs.option.enable_auto_white_balance, 1.0)
else:
self.set_color_option(rs.option.enable_auto_white_balance, 0.0)
self.set_color_option(rs.option.white_balance, white_balance)
def get_intrinsics(self):
return np.array([c.get_intrinsics() for c in self.cameras.values()])
def get_depth_scale(self):
return np.array([c.get_depth_scale() for c in self.cameras.values()])
def start_recording(self, video_path: Union[str, List[str]], start_time: float):
if isinstance(video_path, str):
# directory
video_dir = pathlib.Path(video_path)
assert video_dir.parent.is_dir()
video_dir.mkdir(parents=True, exist_ok=True)
video_path = list()
for i in range(self.n_cameras):
video_path.append(
str(video_dir.joinpath(f'{i}.mp4').absolute()))
assert len(video_path) == self.n_cameras
for i, camera in enumerate(self.cameras.values()):
camera.start_recording(video_path[i], start_time)
def stop_recording(self):
for i, camera in enumerate(self.cameras.values()):
camera.stop_recording()
def restart_put(self, start_time):
for camera in self.cameras.values():
camera.restart_put(start_time)
def repeat_to_list(x, n: int, cls):
if x is None:
x = [None] * n
if isinstance(x, cls):
x = [x] * n
assert len(x) == n
return x