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CamDown.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""'used for manage and generate cam data with set ground-image.
it is a virtual camera
By xiaobo
Contact [email protected]
Created on 十一月 21 20:29 2019
"""
# Copyright (C)
#
# This file is part of quadrotorfly
#
# GWpy is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# GWpy is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with GWpy. If not, see <http://www.gnu.org/licenses/>.
import numpy as np
import CommonFunctions as Cf
import cv2
from enum import Enum
import enum
from numba import jit
"""
********************************************************************************************************
**-------------------------------------------------------------------------------------------------------
** Compiler : python 3.6
** Module Name: CamDown
** Module Date: 2019/11/21
** Module Auth: xiaobo
** Version : V0.1
** Description: a virtual camera looking down
**-------------------------------------------------------------------------------------------------------
** Reversion :
** Modified By:
** Date :
** Content :
** Notes :
********************************************************************************************************/
"""
class CamDownPara(Enum):
Render_Mode_Mem = enum.auto()
Render_Mode_Cpu = enum.auto()
Render_Mode_Gpu = enum.auto()
class CamDown(object):
def __init__(self, img_horizon=400, img_vertical=400, img_depth=3,
sensor_horizon=4., sensor_vertical=4., cam_focal=2.36,
ground_img_path='./Data/groundImgWood.jpg',
small_ground_img_path='./Data/groundImgSmall.jpg',
small_land_img_path='./Data/landingMark.jpg',
render_mode=CamDownPara.Render_Mode_Mem):
"""
****************** horizon ****************
*
v
e
r
t
i
c
a
l
********************************************
:param img_horizon: the num of vertical pixes of the image which is generated by sensor
:param img_vertical: the num of horizon pixes of the image which is generated by sensor
:param img_depth: the num of chanel the image, i.e. rgb is 3
:param sensor_horizon: mm, the height of the active area of the sensor
:param sensor_vertical: mm, the width of the active area of the sensor
:param cam_focal: mm, the focal of the lens of the camera
"""
self.imgHorizon = img_horizon
self.imgVertical = img_vertical
self.imgDepth = img_depth
self.skx = sensor_horizon * 1. / img_horizon # skx is sensor_k_x
self.sky = sensor_vertical * 1. / img_vertical # skx is sensor_k_y
self.sx0 = sensor_horizon * 0.5
self.sy0 = sensor_vertical * 0.5
self.camFocal = cam_focal
self.axCamImgArr = np.zeros([self.imgVertical * self.imgHorizon, 3])
self.pixCamImg = np.zeros([self.imgVertical, self.imgHorizon, self.imgDepth], dtype=np.uint8)
self.groundImgPath = ground_img_path
self.groundImg = None
# small image
self.smallGroundImgPath = small_ground_img_path
self.smallLandingImgPath = small_land_img_path
self.smallGroundImg = None
self.smallLandingImg = None
self.smallImgHorizon = 7854
self.smallImgVertical = 3490
self.smallLandingImgHos = 315
self.smallLandingImgVet = 315
self.renderMode = render_mode
# init the array
for ii in range(self.imgVertical):
for j in range(self.imgHorizon):
self.axCamImgArr[ii * self.imgHorizon + j, :] = [ii, j, 1]
def load_ground_img(self):
if self.renderMode == CamDownPara.Render_Mode_Mem:
if self.groundImg is not None:
del self.groundImg
else:
self.groundImg = cv2.imread(self.groundImgPath)
elif self.renderMode == CamDownPara.Render_Mode_Cpu:
if self.smallGroundImg is not None:
del self.smallGroundImg
else:
self.smallGroundImg = cv2.imread(self.smallGroundImgPath)
# if read success, get size of image
if self.smallGroundImg is not None:
self.smallImgVertical, self.smallImgHorizon = self.smallGroundImg.shape
elif self.renderMode == CamDownPara.Render_Mode_Gpu:
if self.smallGroundImg is not None:
del self.smallGroundImg
else:
self.smallGroundImg = cv2.imread(self.smallGroundImgPath)
self.smallLandingImg = cv2.imread(self.smallLandingImgPath)
# if read success, get size of image
if self.smallGroundImg is not None:
self.smallImgVertical, self.smallImgHorizon, _ = self.smallGroundImg.shape
if self.smallLandingImg is not None:
self.smallLandingImgVet, self.smallLandingImgHos, _ = self.smallLandingImg.shape
def get_img_by_state(self, pos, att):
m_img2sensor = np.array([[self.skx, 0, self.sx0],
[0, -self.sky, -self.sy0],
[0, 0, 1]])
m_sensor2cam = np.array([[pos[2] / self.camFocal, 0, self.imgVertical / 2],
[0, pos[2] / self.camFocal, -self.imgHorizon / 2],
[0, 0, 1]])
m_cam2world = Cf.get_rotation_matrix(att)
m_cam2world[0:2, 2] = pos[0:2]
m_cam2world[2, :] = np.array([0, 0, 1])
m_trans = m_cam2world.dot(m_sensor2cam.dot(m_img2sensor))
if self.renderMode == CamDownPara.Render_Mode_Mem:
ax_real = m_trans.dot(self.axCamImgArr.transpose()).transpose()
for ii in range(self.imgVertical):
for j in range(self.imgHorizon):
self.pixCamImg[ii, j, :] = self.groundImg[int(ax_real[ii * self.imgHorizon + j, 0]),
int(ax_real[ii * self.imgHorizon + j, 1] + 10000), :]
elif self.renderMode == CamDownPara.Render_Mode_Cpu:
ax_real = m_trans.dot(self.axCamImgArr.transpose()).transpose()
for ii in range(self.imgVertical):
for j in range(self.imgHorizon):
ax_vertical = int(ax_real[ii * self.imgHorizon + j, 0]) % self.smallImgVertical
ax_horizon = int(ax_real[ii * self.imgHorizon + j, 1] + 10000) % self.smallImgHorizon
self.pixCamImg[ii, j, :] = self.smallGroundImg[ax_vertical, ax_horizon, :]
elif self.renderMode == CamDownPara.Render_Mode_Gpu:
ax_real = m_trans.dot(self.axCamImgArr.transpose()).transpose()
accelerate_img_mapping_gpu(ax_real, self.smallGroundImg, self.smallLandingImg, self.pixCamImg,
self.imgVertical, self.imgHorizon, self.smallImgHorizon, self.smallImgVertical,
self.smallLandingImgHos, self.smallLandingImgVet)
return self.pixCamImg
@jit(nopython=True)
def accelerate_img_mapping_gpu(m_ax_real, m_img_small, m_img_landing, m_img_result,
img_vertical, img_horizon, small_horizon, small_vertical, land_horizon, land_vertical):
"""
# 用来加速映射计算的函数
:param m_ax_real: 映射后的座标
:param m_img_small: 贴图，小图片
:param m_img_result: 目标图像
:param m_img_landing
:param img_vertical: 目标图像高度
:param img_horizon: 目标图像宽度
:param small_horizon: 贴图宽度
:param small_vertical: 贴图高度
:param land_horizon:
:param land_vertical
:return:
"""
land_hos_max = 5000 + land_horizon
land_vet_min = 5000 - land_vertical
for ii in range(img_vertical):
for j in range(img_horizon):
ax_vertical = int(m_ax_real[ii * img_horizon + j, 0])
ax_horizon = int(m_ax_real[ii * img_horizon + j, 1] + 10000)
if (ax_horizon > 5000) and (ax_horizon < land_hos_max) and (ax_vertical > land_vet_min) \
and (ax_vertical < 5000):
ax_horizon = ax_horizon - 5000
ax_vertical = ax_vertical - land_vet_min
m_img_result[ii, j, :] = m_img_landing[ax_vertical, ax_horizon, :]
else:
ax_vertical = ax_vertical % small_vertical
ax_horizon = ax_horizon % small_horizon
m_img_result[ii, j, :] = m_img_small[ax_vertical, ax_horizon, :]
return m_img_result
if __name__ == '__main__':
" used for testing this module"
testFlag = 3
if testFlag == 1:
cam1 = CamDown()
print('init completed!')
cam1.load_ground_img()
print('Load img completed!')
pos_0 = np.array([4251.97508977, -5843.00458236, 227.35483937])
att_0 = np.array([-0.13647458, -0.1990263, 0.27836947])
img1 = cam1.get_img_by_state(pos_0, att_0)
import matplotlib.pyplot as plt
plt.imshow(cam1.pixCamImg / 255)
cv2.imwrite('Data/test.jpg', img1)
elif testFlag == 2:
import matplotlib.pyplot as plt
# import matplotlib as mpl
from QuadrotorFlyModel import QuadModel, QuadSimOpt, QuadParas, StructureType, SimInitType
import MemoryStore
D2R = np.pi / 180
print("PID controller test: ")
uavPara = QuadParas(structure_type=StructureType.quad_x)
simPara = QuadSimOpt(init_mode=SimInitType.fixed, enable_sensor_sys=False,
init_att=np.array([10., -10., 30]), init_pos=np.array([5, -5, 0]))
quad1 = QuadModel(uavPara, simPara)
record = MemoryStore.DataRecord()
record.clear()
step_cnt = 0
# init the camera
cam1 = CamDown()
cam1.load_ground_img()
print('Load img completed!')
fourcc = cv2.VideoWriter_fourcc(*'MJPG')
out1 = cv2.VideoWriter('Data/img/test.avi', fourcc, 1 / quad1.uavPara.ts, (cam1.imgVertical, cam1.imgHorizon))
for i in range(1000):
ref = np.array([0., 0., 1., 0.])
stateTemp = quad1.observe()
# get image
pos_0 = quad1.position * 1000
att_0 = quad1.attitude
img1 = cam1.get_img_by_state(pos_0, att_0)
# file_name = 'Data/img/test_' + str(i) + '.jpg'
# cv2.imwrite(file_name, img1)
out1.write(img1)
action2, oil = quad1.get_controller_pid(stateTemp, ref)
print('action: ', action2)
action2 = np.clip(action2, 0.1, 0.9)
quad1.step(action2)
record.buffer_append((stateTemp, action2))
step_cnt = step_cnt + 1
record.episode_append()
out1.release()
print('Quadrotor structure type', quad1.uavPara.structureType)
# quad1.reset_states()
print('Quadrotor get reward:', quad1.get_reward())
data = record.get_episode_buffer()
bs = data[0]
ba = data[1]
t = range(0, record.count)
# mpl.style.use('seaborn')
fig1 = plt.figure(1)
plt.clf()
plt.subplot(3, 1, 1)
plt.plot(t, bs[t, 6] / D2R, label='roll')
plt.plot(t, bs[t, 7] / D2R, label='pitch')
plt.plot(t, bs[t, 8] / D2R, label='yaw')
plt.ylabel('Attitude $(\circ)$', fontsize=15)
plt.legend(fontsize=15, bbox_to_anchor=(1, 1.05))
plt.subplot(3, 1, 2)
plt.plot(t, bs[t, 0], label='x')
plt.plot(t, bs[t, 1], label='y')
plt.ylabel('Position (m)', fontsize=15)
plt.legend(fontsize=15, bbox_to_anchor=(1, 1.05))
plt.subplot(3, 1, 3)
plt.plot(t, bs[t, 2], label='z')
plt.ylabel('Altitude (m)', fontsize=15)
plt.legend(fontsize=15, bbox_to_anchor=(1, 1.05))
plt.show()
# performance test
elif testFlag == 3:
import matplotlib.pyplot as plt
# import matplotlib as mpl
from QuadrotorFlyModel import QuadModel, QuadSimOpt, QuadParas, StructureType, SimInitType
import MemoryStore
import time
D2R = np.pi / 180
video_write_flag = True
print("PID controller test: ")
uavPara = QuadParas(structure_type=StructureType.quad_x)
simPara = QuadSimOpt(init_mode=SimInitType.fixed, enable_sensor_sys=False,
init_att=np.array([0., 0., 0]), init_pos=np.array([0, -0, 0]))
quad1 = QuadModel(uavPara, simPara)
record = MemoryStore.DataRecord()
record.clear()
step_cnt = 0
# init the camera
cam1 = CamDown(render_mode=CamDownPara.Render_Mode_Gpu)
cam1.load_ground_img()
print('Load img completed!')
if video_write_flag:
v_format = cv2.VideoWriter_fourcc(*'MJPG')
out1 = cv2.VideoWriter('Data/img/test.avi', v_format, 1 / quad1.uavPara.ts, (cam1.imgVertical, cam1.imgHorizon))
for i in range(1000):
if i == 0:
time_start = time.time()
ref = np.array([0., 0., 3., 0.])
stateTemp = quad1.observe()
# get image
pos_0 = quad1.position * 1000
att_0 = quad1.attitude
img1 = cam1.get_img_by_state(pos_0, att_0)
# file_name = 'Data/img/test_' + str(i) + '.jpg'
# cv2.imwrite(file_name, img1)
if video_write_flag:
out1.write(img1)
action2, oil = quad1.get_controller_pid(stateTemp, ref)
print('action: ', action2)
action2 = np.clip(action2, 0.1, 0.9)
quad1.step(action2)
record.buffer_append((stateTemp, action2))
step_cnt = step_cnt + 1
time_end = time.time()
print('time cost:', str(time_end - time_start))
record.episode_append()
if video_write_flag:
out1.release()
print('Quadrotor structure type', quad1.uavPara.structureType)
# quad1.reset_states()
print('Quadrotor get reward:', quad1.get_reward())
data = record.get_episode_buffer()
bs = data[0]
ba = data[1]
t = range(0, record.count)
# mpl.style.use('seaborn')
fig1 = plt.figure(1)
plt.clf()
plt.subplot(3, 1, 1)
plt.plot(t, bs[t, 6] / D2R, label='roll')
plt.plot(t, bs[t, 7] / D2R, label='pitch')
plt.plot(t, bs[t, 8] / D2R, label='yaw')
plt.ylabel('Attitude $(\circ)$', fontsize=15)
plt.legend(fontsize=15, bbox_to_anchor=(1, 1.05))
plt.subplot(3, 1, 2)
plt.plot(t, bs[t, 0], label='x')
plt.plot(t, bs[t, 1], label='y')
plt.ylabel('Position (m)', fontsize=15)
plt.legend(fontsize=15, bbox_to_anchor=(1, 1.05))
plt.subplot(3, 1, 3)
plt.plot(t, bs[t, 2], label='z')
plt.ylabel('Altitude (m)', fontsize=15)
plt.legend(fontsize=15, bbox_to_anchor=(1, 1.05))
plt.show()