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Getting rid of OpenCV2

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kyberszittya
2019-06-03 00:02:18 +02:00
parent 5d6927a7d9
commit a5aad31271
2 changed files with 169 additions and 53 deletions
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102
Mapping/lidar_to_grid_map/lidar_to_grid_map.py
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@@ -8,11 +8,12 @@ author: Erno Horvath, Csaba Hajdu based on Atsushi Sakai's scripts (@Atsushi_twi
import math
import numpy as np
import cv2
import matplotlib.pyplot as plt
from collections import deque
EXTEND_AREA = 1.0
def file_read(f):
"""
Reading LIDAR laser beams (angles and corresponding distance data)
@@ -27,6 +28,7 @@ def file_read(f):
distances = np.array(distances)
return angles, distances
def bresenham(start, end):
"""
Implementation of Bresenham's line drawing algorithm
@@ -70,6 +72,7 @@ def bresenham(start, end):
points = np.array(points)
return points
def calc_grid_map_config(ox, oy, xyreso):
"""
Calculates the size, and the maximum distances according to the the measurement center
@@ -83,13 +86,72 @@ def calc_grid_map_config(ox, oy, xyreso):
print("The grid map is ", xw, "x", yw, ".")
return minx, miny, maxx, maxy, xw, yw
def atan_zero_to_twopi(y, x):
angle = math.atan2(y, x)
if angle < 0.0:
angle += math.pi * 2.0
return angle
def generate_ray_casting_grid_map(ox, oy, xyreso, yawreso, breshen = True):
def init_floodfill(cpoint, opoints, xypoints, mincoord, xyreso):
"""
cpoint: center point
opoints: detected obstacles points (x,y)
xypoints: (x,y) point pairs
"""
centix, centiy = cpoint
prev_ix, prev_iy = centix - 1, centiy
ox, oy = opoints
xw, yw = xypoints
minx, miny = mincoord
pmap = (np.ones((xw, yw))) * 0.5
for (x, y) in zip(ox, oy):
ix = int(round((x - minx) / xyreso)) # x coordinate of the the occupied area
iy = int(round((y - miny) / xyreso)) # y coordinate of the the occupied area
free_area = bresenham((prev_ix, prev_iy), (ix, iy))
for fa in free_area:
pmap[fa[0]][fa[1]] = 0 # free area 0.0
prev_ix = ix
prev_iy = iy
return pmap
def flood_fill(cpoint, pmap):
"""
cpoint: starting point (x,y) of fill
pmap: occupancy map generated from Bresenham ray-tracing
"""
# Fill empty areas with queue method
sx, sy = pmap.shape
fringe = deque()
fringe.appendleft(cpoint)
while len(fringe)>0:
n = fringe.pop()
nx, ny = n
# West
if nx > 0:
if pmap[nx - 1, ny] == 0.5:
pmap[nx - 1, ny] = 0.0
fringe.appendleft((nx - 1, ny))
# East
if nx < sx - 1:
if pmap[nx + 1, ny] == 0.5:
pmap[nx + 1, ny] = 0.0
fringe.appendleft((nx + 1, ny))
# North
if ny > 0:
if pmap[nx, ny - 1] == 0.5:
pmap[nx, ny - 1] = 0.0
fringe.appendleft((nx, ny - 1))
# South
if ny < sy - 1:
if pmap[nx, ny + 1] == 0.5:
pmap[nx, ny + 1] = 0.0
fringe.appendleft((nx, ny + 1))
def generate_ray_casting_grid_map(ox, oy, xyreso, breshen=True):
"""
The breshen boolean tells if it's computed with bresenham ray casting (True) or with flood fill (False)
"""
@@ -97,14 +159,11 @@ def generate_ray_casting_grid_map(ox, oy, xyreso, yawreso, breshen = True):
pmap = np.ones((xw, yw))/2 # default 0.5 -- [[0.5 for i in range(yw)] for i in range(xw)]
centix = int(round(-minx / xyreso)) # center x coordinate of the grid map
centiy = int(round(-miny / xyreso)) # center y coordinate of the grid map
#print(centix, centiy)
prev_ix, prev_iy = centix - 1, centiy
# occupancy grid computed with bresenham ray casting
if breshen:
for (x, y) in zip(ox, oy):
angle = atan_zero_to_twopi(y, x)
ix = int(round((x - minx) / xyreso)) # x coordinte of the the occupied area
iy = int(round((y - miny) / xyreso)) # y coordinte of the the occupied area
ix = int(round((x - minx) / xyreso)) # x coordinate of the the occupied area
iy = int(round((y - miny) / xyreso)) # y coordinate of the the occupied area
laser_beams = bresenham((centix, centiy), (ix, iy)) # line form the lidar to the cooupied point
for laser_beam in laser_beams:
pmap[laser_beam[0]][laser_beam[1]] = 0.0 # free area 0.0
@@ -114,19 +173,10 @@ def generate_ray_casting_grid_map(ox, oy, xyreso, yawreso, breshen = True):
pmap[ix+1][iy+1] = 1.0 # extend the occupied area
# occupancy grid computed with with flood fill
else:
pmap = (np.ones((xw, yw), dtype=np.uint8)) * 5 # food fill does not work with float numbers such as 0.5; so 5 is the default and later it is divided by 10
for (x, y) in zip(ox, oy):
ix = int(round((x - minx) / xyreso)) # x coordinte of the the occupied area
iy = int(round((y - miny) / xyreso)) # y coordinte of the the occupied area
free_area = bresenham((prev_ix, prev_iy), (ix, iy))
for fa in free_area:
pmap[fa[0]][fa[1]] = 0 # free area 0.0
prev_ix = ix
prev_iy = iy
cv2.floodFill(pmap, None, (centix, centiy), 0) # filling the free spaces with 0, stating from the center
pmap = init_floodfill((centix, centiy), (ox, oy), (xw, yw), (minx, miny), xyreso)
flood_fill((centix, centiy), pmap)
pmap = np.array(pmap, dtype=np.float)
pmap /= 10
for (x, y) in zip(ox, oy):
for (x, y) in zip(ox, oy):
ix = int(round((x - minx) / xyreso))
iy = int(round((y - miny) / xyreso))
pmap[ix][iy] = 1.0 # occupied area 1.0
@@ -135,25 +185,25 @@ def generate_ray_casting_grid_map(ox, oy, xyreso, yawreso, breshen = True):
pmap[ix+1][iy+1] = 1.0 # extend the occupied area
return pmap, minx, maxx, miny, maxy, xyreso
def main():
"""
Example usage
"""
print(__file__, "start")
xyreso = 0.02 # x-y grid resolution
yawreso = math.radians(3.1) # yaw angle resolution [rad]
ang, dist = file_read("lidar01.csv")
ox = np.sin(ang) * dist
oy = np.cos(ang) * dist
pmap, minx, maxx, miny, maxy, xyreso = generate_ray_casting_grid_map(ox, oy, xyreso, yawreso, True)
pmap, minx, maxx, miny, maxy, xyreso = generate_ray_casting_grid_map(ox, oy, xyreso, True)
xyres = np.array(pmap).shape
plt.figure(1, figsize=(10,4))
plt.subplot(122)
plt.imshow(pmap, cmap = "PiYG_r") # cmap = "binary" "PiYG_r" "PiYG_r" "bone" "bone_r" "RdYlGn_r"
plt.imshow(pmap, cmap="PiYG_r") # cmap = "binary" "PiYG_r" "PiYG_r" "bone" "bone_r" "RdYlGn_r"
plt.clim(-0.4, 1.4)
plt.gca().set_xticks(np.arange(-.5, xyres[1], 1), minor = True)
plt.gca().set_yticks(np.arange(-.5, xyres[0], 1), minor = True)
plt.grid(True, which="minor", color="w", linewidth = .6, alpha = 0.5)
plt.gca().set_xticks(np.arange(-.5, xyres[1], 1), minor=True)
plt.gca().set_yticks(np.arange(-.5, xyres[0], 1), minor=True)
plt.grid(True, which="minor", color="w", linewidth=0.6, alpha=0.5)
plt.colorbar()
plt.subplot(121)
plt.plot([oy, np.zeros(np.size(oy))], [ox, np.zeros(np.size(oy))], "ro-")
@@ -164,7 +214,7 @@ def main():
plt.ylim((top, bottom)) # rescale y axis, to match the grid orientation
plt.grid(True)
plt.show()
if __name__ == '__main__':
main()