如何使用 OpenCV 将 PyBullet 模拟坐标投影到渲染帧像素坐标？
How to project PyBullet simulation coordinates to rendered Frame pixel coordinates using OpenCV?
如何将 PyBullet 中的对象位置转换为像素坐标并使用 PyBullet 和 OpenCV 在框架上画一条线？
我们想这样做是因为 PyBullet 本机 addUserDebugLine() 函数在 DIRECT 模式下不可用。
import pybullet as p
import numpy as np
import time
import pybullet_data
import cv2
VIDEO_RESOLUTION = (1280, 720)
MY_COLORS = [(255,0,0), (0,255,0), (0,0,255)]
def capture_frame(base_pos=[0,0,0], _cam_dist=3, _cam_yaw=45, _cam_pitch=-45):
_render_width, _render_height = VIDEO_RESOLUTION
view_matrix = p.computeViewMatrixFromYawPitchRoll(
cameraTargetPosition=base_pos,
distance=_cam_dist,
yaw=_cam_yaw,
pitch=_cam_pitch,
roll=0,
upAxisIndex=2)
proj_matrix = p.computeProjectionMatrixFOV(
fov=90, aspect=float(_render_width) / _render_height,
nearVal=0.01, farVal=100.0)
(_, _, px, _, _) = p.getCameraImage(
width=_render_width, height=_render_height, viewMatrix=view_matrix,
projectionMatrix=proj_matrix, renderer=p.ER_TINY_RENDERER) # ER_BULLET_HARDWARE_OPENGL)
rgb_array = np.array(px, dtype=np.uint8)
rgb_array = np.reshape(rgb_array, (_render_height, _render_width, 4))
rgb_array = rgb_array[:, :, :3]
return rgb_array, view_matrix, proj_matrix
def render():
frame, vmat, pmat = capture_frame()
p1, cubeOrn = p.getBasePositionAndOrientation(1)
p2, cubeOrn = p.getBasePositionAndOrientation(2)
frame, view_matrix, proj_matrix = capture_frame()
frame = cv2.resize(frame, VIDEO_RESOLUTION)
points = {}
# reshape matrices
my_order = 'C'
pmat = np.array(proj_matrix).reshape((4,4), order=my_order)
vmat = np.array(view_matrix).reshape((4,4), order=my_order)
fmat = vmat.T @ pmat.T
# compute origin from origin point in simulation
origin = np.array([0,0,0,1])
frame_origin = (fmat @ origin)[:3]*np.array([1280, 640, 0]) + np.array([640, 360, 0])
# define unit vectors
unit_vectors = [ np.array([1,0,0,1]),
np.array([0,1,0,1]),
np.array([0,0,1,1]) ]
for col_id, unit_vector in enumerate(unit_vectors):
cur_point = (fmat @ unit_vector)[:3]*np.array([1280, 640, 0]) + np.array([640, 360, 0])
cv2.line(frame, (640,360), (int(cur_point[0]),int(cur_point[1])), color=MY_COLORS[col_id], thickness=2)
cv2.imwrite("my_rendering.jpg", frame)
print(p1,p2)
if __name__ == '__main__':
physicsClient = p.connect(p.DIRECT)#or p.DIRECT for non-graphical version
p.setAdditionalSearchPath(pybullet_data.getDataPath()) #optionally
p.setGravity(0,0,-10)
planeId = p.loadURDF("plane.urdf")
startPos = [1,0,0.2]
startOrientation = p.getQuaternionFromEuler([0,0,0])
boxId = p.loadURDF("r2d2.urdf",startPos, startOrientation)
startPos = [0,2,0.2]
boxId = p.loadURDF("r2d2.urdf",startPos, startOrientation)
#set the center of mass frame (loadURDF sets base link frame) startPos/Ornp.resetBasePositionAndOrientation(boxId, startPos, startOrientation)
for i in range (2400):
if i == 2399:
render()
p.stepSimulation()
p.disconnect()
预期的输出将是以下帧，但原点坐标帧绘制正确。例如。 X、Y 和 Z 轴分别为红色、蓝色和绿色。
由于两台R2D2机器人分别位于[1,0,0]和[0,1,0]，可以看出坐标系是关闭的。 （见下图）
我们尝试了以下方法：
- 转置矩阵
- 不转置矩阵
- 改变我们计算 fmat 的顺序，例如pmat @vmat 而不是 vmat @pmat 等
感谢任何帮助。
折腾了很久，终于找到了解决办法。
玩了一会儿，我发现除了偏航角给定的轴旋转外，它看起来几乎没问题。因此，我第二次调用 computeViewMatrixFromYawPitchRoll 但使用相反的偏航来计算轴的变换。
不幸的是，我不确定为什么会这样……但它确实有效！
注意：base_pos、_cam_dist、_cam_yaw 和 _cam_pitch 已被替换为 render() 另请注意：向上方向也已反转（不要问为什么.. . :-) ) 一个相当混乱的解释，我必须承认...
import pybullet as p
import numpy as np
import time
import pybullet_data
import cv2
import os
VIDEO_RESOLUTION = (1280, 720)
MY_COLORS = [(255,0,0), (0,255,0), (0,0,255)]
K=np.array([[1280,0,0],[0,720,0],[0,0,1]])
def capture_frame(base_pos, _cam_dist, _cam_yaw, _cam_pitch):
_render_width, _render_height = VIDEO_RESOLUTION
view_matrix = p.computeViewMatrixFromYawPitchRoll(
cameraTargetPosition=base_pos,
distance=_cam_dist,
yaw=_cam_yaw,
pitch=_cam_pitch,
roll=0,
upAxisIndex=2)
proj_matrix = p.computeProjectionMatrixFOV(
fov=90, aspect=float(_render_width) / _render_height,
nearVal=0.01, farVal=100.0)
(_, _, px, _, _) = p.getCameraImage(
width=_render_width, height=_render_height, viewMatrix=view_matrix,
projectionMatrix=proj_matrix, renderer=p.ER_TINY_RENDERER) # ER_BULLET_HARDWARE_OPENGL)
rgb_array = np.array(px, dtype=np.uint8)
rgb_array = np.reshape(rgb_array, (_render_height, _render_width, 4))
rgb_array = rgb_array[:, :, :3]
return rgb_array, view_matrix, proj_matrix
def render():
p1, cubeOrn = p.getBasePositionAndOrientation(1)
p2, cubeOrn = p.getBasePositionAndOrientation(2)
base_pos=[0,0,0]
_cam_dist=3
_cam_yaw=45
_cam_pitch=-30
frame, view_matrix, proj_matrix = capture_frame(base_pos, _cam_dist, _cam_yaw, _cam_pitch)
frame = cv2.resize(frame, VIDEO_RESOLUTION)
points = {}
# inverse transform
view_matrix = p.computeViewMatrixFromYawPitchRoll(
cameraTargetPosition=base_pos,
distance=_cam_dist,
yaw=-_cam_yaw,
pitch=_cam_pitch,
roll=0,
upAxisIndex=2)
my_order = 'C'
pmat = np.array(proj_matrix).reshape((4,4), order=my_order)
vmat = np.array(view_matrix).reshape((4,4), order=my_order)
fmat = pmat @ vmat.T
# compute origin from origin point in simulation
origin = np.array([0,0,0,1])
frame_origin = (fmat @ origin)[:3]*np.array([1280, 720, 0]) + np.array([640, 360, 0])
# define unit vectors
unit_vectors = [ np.array([1,0,0,1]),
np.array([0,1,0,1]),
np.array([0,0,-1,1]) ]
for col_id, unit_vector in enumerate(unit_vectors):
cur_point = (fmat @ unit_vector)[:3]*np.array([1280, 720, 0]) + np.array([640, 360, 0])
cv2.line(frame, (640,360), (int(cur_point[0]),int(cur_point[1])), color=MY_COLORS[col_id], thickness=2)
cv2.imwrite("my_rendering.jpg", frame)
print(p1,p2)
if __name__ == '__main__':
physicsClient = p.connect(p.DIRECT)#or p.DIRECT for non-graphical version
#physicsClient = p.connect(p.GUI)#or p.DIRECT for non-graphical version
p.setAdditionalSearchPath(pybullet_data.getDataPath()) #optionally
p.setGravity(0,0,-10)
planeId = p.loadURDF("plane.urdf")
#arrows = p.loadURDF("arrows.urdf")
startPos = [1,0,0.2]
startOrientation = p.getQuaternionFromEuler([0,0,0])
boxId = p.loadURDF("r2d2.urdf",startPos, startOrientation)
startPos = [0,2,0.2]
boxId = p.loadURDF("r2d2.urdf",startPos, startOrientation)
#set the center of mass frame (loadURDF sets base link frame) startPos/Ornp.resetBasePositionAndOrientation(boxId, startPos, startOrientation)
for i in range (2400):
if i == 2399:
render()
p.stepSimulation()
p.disconnect()
结果如下：
最好的祝福。
如何将 PyBullet 中的对象位置转换为像素坐标并使用 PyBullet 和 OpenCV 在框架上画一条线？
我们想这样做是因为 PyBullet 本机 addUserDebugLine() 函数在 DIRECT 模式下不可用。
import pybullet as p
import numpy as np
import time
import pybullet_data
import cv2
VIDEO_RESOLUTION = (1280, 720)
MY_COLORS = [(255,0,0), (0,255,0), (0,0,255)]
def capture_frame(base_pos=[0,0,0], _cam_dist=3, _cam_yaw=45, _cam_pitch=-45):
_render_width, _render_height = VIDEO_RESOLUTION
view_matrix = p.computeViewMatrixFromYawPitchRoll(
cameraTargetPosition=base_pos,
distance=_cam_dist,
yaw=_cam_yaw,
pitch=_cam_pitch,
roll=0,
upAxisIndex=2)
proj_matrix = p.computeProjectionMatrixFOV(
fov=90, aspect=float(_render_width) / _render_height,
nearVal=0.01, farVal=100.0)
(_, _, px, _, _) = p.getCameraImage(
width=_render_width, height=_render_height, viewMatrix=view_matrix,
projectionMatrix=proj_matrix, renderer=p.ER_TINY_RENDERER) # ER_BULLET_HARDWARE_OPENGL)
rgb_array = np.array(px, dtype=np.uint8)
rgb_array = np.reshape(rgb_array, (_render_height, _render_width, 4))
rgb_array = rgb_array[:, :, :3]
return rgb_array, view_matrix, proj_matrix
def render():
frame, vmat, pmat = capture_frame()
p1, cubeOrn = p.getBasePositionAndOrientation(1)
p2, cubeOrn = p.getBasePositionAndOrientation(2)
frame, view_matrix, proj_matrix = capture_frame()
frame = cv2.resize(frame, VIDEO_RESOLUTION)
points = {}
# reshape matrices
my_order = 'C'
pmat = np.array(proj_matrix).reshape((4,4), order=my_order)
vmat = np.array(view_matrix).reshape((4,4), order=my_order)
fmat = vmat.T @ pmat.T
# compute origin from origin point in simulation
origin = np.array([0,0,0,1])
frame_origin = (fmat @ origin)[:3]*np.array([1280, 640, 0]) + np.array([640, 360, 0])
# define unit vectors
unit_vectors = [ np.array([1,0,0,1]),
np.array([0,1,0,1]),
np.array([0,0,1,1]) ]
for col_id, unit_vector in enumerate(unit_vectors):
cur_point = (fmat @ unit_vector)[:3]*np.array([1280, 640, 0]) + np.array([640, 360, 0])
cv2.line(frame, (640,360), (int(cur_point[0]),int(cur_point[1])), color=MY_COLORS[col_id], thickness=2)
cv2.imwrite("my_rendering.jpg", frame)
print(p1,p2)
if __name__ == '__main__':
physicsClient = p.connect(p.DIRECT)#or p.DIRECT for non-graphical version
p.setAdditionalSearchPath(pybullet_data.getDataPath()) #optionally
p.setGravity(0,0,-10)
planeId = p.loadURDF("plane.urdf")
startPos = [1,0,0.2]
startOrientation = p.getQuaternionFromEuler([0,0,0])
boxId = p.loadURDF("r2d2.urdf",startPos, startOrientation)
startPos = [0,2,0.2]
boxId = p.loadURDF("r2d2.urdf",startPos, startOrientation)
#set the center of mass frame (loadURDF sets base link frame) startPos/Ornp.resetBasePositionAndOrientation(boxId, startPos, startOrientation)
for i in range (2400):
if i == 2399:
render()
p.stepSimulation()
p.disconnect()
预期的输出将是以下帧，但原点坐标帧绘制正确。例如。 X、Y 和 Z 轴分别为红色、蓝色和绿色。
由于两台R2D2机器人分别位于[1,0,0]和[0,1,0]，可以看出坐标系是关闭的。 （见下图）
我们尝试了以下方法：
- 转置矩阵
- 不转置矩阵
- 改变我们计算 fmat 的顺序，例如pmat @vmat 而不是 vmat @pmat 等
感谢任何帮助。
折腾了很久，终于找到了解决办法。 玩了一会儿，我发现除了偏航角给定的轴旋转外，它看起来几乎没问题。因此，我第二次调用 computeViewMatrixFromYawPitchRoll 但使用相反的偏航来计算轴的变换。 不幸的是，我不确定为什么会这样……但它确实有效！ 注意：base_pos、_cam_dist、_cam_yaw 和 _cam_pitch 已被替换为 render() 另请注意：向上方向也已反转（不要问为什么.. . :-) ) 一个相当混乱的解释，我必须承认...
import pybullet as p
import numpy as np
import time
import pybullet_data
import cv2
import os
VIDEO_RESOLUTION = (1280, 720)
MY_COLORS = [(255,0,0), (0,255,0), (0,0,255)]
K=np.array([[1280,0,0],[0,720,0],[0,0,1]])
def capture_frame(base_pos, _cam_dist, _cam_yaw, _cam_pitch):
_render_width, _render_height = VIDEO_RESOLUTION
view_matrix = p.computeViewMatrixFromYawPitchRoll(
cameraTargetPosition=base_pos,
distance=_cam_dist,
yaw=_cam_yaw,
pitch=_cam_pitch,
roll=0,
upAxisIndex=2)
proj_matrix = p.computeProjectionMatrixFOV(
fov=90, aspect=float(_render_width) / _render_height,
nearVal=0.01, farVal=100.0)
(_, _, px, _, _) = p.getCameraImage(
width=_render_width, height=_render_height, viewMatrix=view_matrix,
projectionMatrix=proj_matrix, renderer=p.ER_TINY_RENDERER) # ER_BULLET_HARDWARE_OPENGL)
rgb_array = np.array(px, dtype=np.uint8)
rgb_array = np.reshape(rgb_array, (_render_height, _render_width, 4))
rgb_array = rgb_array[:, :, :3]
return rgb_array, view_matrix, proj_matrix
def render():
p1, cubeOrn = p.getBasePositionAndOrientation(1)
p2, cubeOrn = p.getBasePositionAndOrientation(2)
base_pos=[0,0,0]
_cam_dist=3
_cam_yaw=45
_cam_pitch=-30
frame, view_matrix, proj_matrix = capture_frame(base_pos, _cam_dist, _cam_yaw, _cam_pitch)
frame = cv2.resize(frame, VIDEO_RESOLUTION)
points = {}
# inverse transform
view_matrix = p.computeViewMatrixFromYawPitchRoll(
cameraTargetPosition=base_pos,
distance=_cam_dist,
yaw=-_cam_yaw,
pitch=_cam_pitch,
roll=0,
upAxisIndex=2)
my_order = 'C'
pmat = np.array(proj_matrix).reshape((4,4), order=my_order)
vmat = np.array(view_matrix).reshape((4,4), order=my_order)
fmat = pmat @ vmat.T
# compute origin from origin point in simulation
origin = np.array([0,0,0,1])
frame_origin = (fmat @ origin)[:3]*np.array([1280, 720, 0]) + np.array([640, 360, 0])
# define unit vectors
unit_vectors = [ np.array([1,0,0,1]),
np.array([0,1,0,1]),
np.array([0,0,-1,1]) ]
for col_id, unit_vector in enumerate(unit_vectors):
cur_point = (fmat @ unit_vector)[:3]*np.array([1280, 720, 0]) + np.array([640, 360, 0])
cv2.line(frame, (640,360), (int(cur_point[0]),int(cur_point[1])), color=MY_COLORS[col_id], thickness=2)
cv2.imwrite("my_rendering.jpg", frame)
print(p1,p2)
if __name__ == '__main__':
physicsClient = p.connect(p.DIRECT)#or p.DIRECT for non-graphical version
#physicsClient = p.connect(p.GUI)#or p.DIRECT for non-graphical version
p.setAdditionalSearchPath(pybullet_data.getDataPath()) #optionally
p.setGravity(0,0,-10)
planeId = p.loadURDF("plane.urdf")
#arrows = p.loadURDF("arrows.urdf")
startPos = [1,0,0.2]
startOrientation = p.getQuaternionFromEuler([0,0,0])
boxId = p.loadURDF("r2d2.urdf",startPos, startOrientation)
startPos = [0,2,0.2]
boxId = p.loadURDF("r2d2.urdf",startPos, startOrientation)
#set the center of mass frame (loadURDF sets base link frame) startPos/Ornp.resetBasePositionAndOrientation(boxId, startPos, startOrientation)
for i in range (2400):
if i == 2399:
render()
p.stepSimulation()
p.disconnect()
结果如下：
最好的祝福。