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aPf.py
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aPf.py
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#Prerequisite import
from geopy.point import Point
from geopy import distance
import numpy as np
from scipy import ndimage
import cv2
import math
import time
def geofencedata(Geofence_file):
fence = open(Geofence_file,"r")
flist = []
for i in fence.readlines():
thisline=i.split()
fseq=[]
fseq.append(float(thisline[0]))
fseq.append(float(thisline[1]))
flist.append(fseq)
fence.close()
return flist
#GEO-FENCE IMAGE BOUNDARY
def rows_and_cols(flist):
latlim=[]
lonlim=[]
alist=np.asarray(flist)
latlim.append(float(min(alist[:,0])-0.001))
latlim.append(float(max(alist[:,0])+0.001))
lonlim.append(float(min(alist[:,1])-0.001))
lonlim.append(float(max(alist[:,1])+0.001))
p1 = Point(latlim[0],lonlim[0])
p2 = Point(latlim[0],lonlim[1])
p3 = Point(latlim[1],lonlim[1])
p4 = Point(latlim[1],lonlim[0])
d1=(distance.distance(p1,p2).meters)
d2=(distance.distance(p3,p4).meters)
londist=max(d1,d2)
latdist=(distance.distance(p3,p2).meters)
row_s=int(latdist/scale_factor)
col_s=int(londist/scale_factor)
if (row_s%scale_factor != 0):
row_s+=1
if (col_s%scale_factor != 0):
col_s+=1
return latdist,londist,latlim,lonlim,row_s,col_s
def gps2grid(lat,lon):
row=row_s-(row_s*((lat-latlim[0])/(latlim[1]-latlim[0])))
col=(col_s*((lon-lonlim[0])/(lonlim[1]-lonlim[0])))
return [int(col),int(row)]
def grid2gps(row,col):
lon=((col*(lonlim[1]-lonlim[0]))/col_s)+lonlim[0]
lat=(((row_s-row)*(latlim[1]-latlim[0]))/row_s)+latlim[0]
return (lat,lon)
def array2image(row_s,col_s,flist):
img = np.zeros((col_s,row_s), dtype=np.uint8)
polyarray=[]
for j in range(0,len(flist)):
polyarray.append(gps2grid(float(flist[j][0]),float(flist[j][1])))
pts = np.array(polyarray, np.int32)
cv2.polylines(img, [pts], True, (255),thickness=1)
cv2.fillPoly(img,[pts],(255))
return img,polyarray
def ft2me(x):
return(x*0.3048)
def so_obstacle(so_file):
so = open(so_file,"r")
olist=list()
lines = so.readlines()
for i in lines:
thisline = i.split()
col,row=gps2grid(float(thisline[0]),float(thisline[1]))
l3=list()
l3.append(col)
l3.append(row)
radius=ft2me(float(thisline[2]))
if radius<=scale_factor:
img[col][row]=0
else:
radius=int(radius/scale_factor)
if (radius%scale_factor != 0):
radius+=1
l3.append(radius)
cv2.circle(img,(col,row), int(radius), (0,0,0), -1)
olist.append(l3)
so.close()
return(olist)
def waypoint(wp_file):
wp_i = open(wp_file,"r")
y=list()
j=0
lines=wp_i.readlines()
wparray=[]
for i in lines:
thisline = i.split()
if j>=2:
l=list()
x=list()
x.append(float(thisline[8]))
x.append(float(thisline[9]))
l=gps2grid(float(thisline[8]),float(thisline[9]))
wparray.append(l)
y.append(x)
j+=1
return wparray,y
def yc(Y):
return(row_s-Y)
def fn(cn):
fn1=f[cn[0]][cn[1]]
return fn1
def neighbour_min(sn,dn):
min=fn([sn[0]-1],[sn[1]-1])
mn=list(sn)
m=0
n=0
dn=list()
for i in range(-1,2):
for j in range (-1,2):
if (i==0 and j==0):
continue
mn[0]=sn[0]+i
mn[1]=sn[1]+j
f=fn(mn)
if(f<=min):
min=f
m=i
n=j
sn[0]=sn[0]+m
sn[1]=sn[1]+n
return(sn)
def mark_wo(wo):
imgwo= np.ones((col_s,row_s), dtype=np.uint8)
imgwo[wo[0]][wo[1]]=0
edt=ndimage.morphology.distance_transform_edt(imgwo)
#edt=edt.astype(int)
return edt
scale_factor=int(raw_input("Enter scaling factor"))
flist=geofencedata("suas_geo.txt")
latdist,londist,latlim,lonlim,row_s,col_s=rows_and_cols(flist)
img,polyarray=array2image(row_s,col_s,flist)
cv2.imshow("img",img)
cv2.waitKey(0)
ol2=so_obstacle("so_suas.txt")
wpary2,wlist=waypoint("wp_suas.waypoints")
print (wpary2)
cv2.imshow("img",img)
cv2.waitKey(0)
Pathlist=list()
#conversion to numPy array of 0 and 1
img2=np.array(img,dtype=np.int8)
img2=img/255
#print img2
#cv2.imshow("img2",img2)
#cv2.waitKey(0)
# gives nearest obstacle and its distance
node=wpary2[0]
dest_node=wpary2[1]
edts=ndimage.morphology.distance_transform_edt(img2)
edts=edts.astype("uint8")
cv2.imshow("i",edts)
edts=np.where(edts>20,0,edts)
#edts=(edts/np.amax(edts))*255
cv2.circle(edts,(node[0],node[1]),5, (100,100,100), -1)
cv2.imshow("img2",edts)
#cv2.waitKey(0) to int array
#print edts
print ("edts formed")
#towards destination wayoint
edtwo=np.zeros((col_s,row_s), dtype=np.uint8)
edtwo=mark_wo(dest_node)
edtwo=255-((edtwo/np.amax(edtwo))*255)
#print edtwo
att_re=(edtwo+edts)
att_re=att_re*img2
att_re=(att_re/np.amax(att_re))*255
att_re=att_re.astype("uint8")
print (att_re)
cv2.imshow("att",att_re)
cv2.circle(att_re,(dest_node[0],dest_node[1]),10, (100), -1)
cv2.imshow("att",att_re)
cv2.waitKey(0)
i=0
while (i<(len(wpary2)-1)):
node=wpary2[i]
dest_node=wpary2[i+1]
print ("startnode",node)
print ("destination node", dest_node)
edtwo=mark_wo(dest_node)
f=edtwo+(edts.transpose())
f=ndimage.morphology.distance_transform_edt(f)
while (node!=dest_node):
node=neighbour_min(node,dest_node)
print ("returned",node)
cv2.circle(img,(node[0],node[1]), 0, (100,100,100), -1)
cv2.imshow("img",img)
cv2.waitKey(0)
Pathlist.append(node)
i=i+1
"""e=[[0 for i in range (0,row_s)] for j in range (0,col_s)]
for i in range(row_s):
for j in range(col_s):
e[i][j]=int(edts[i][j])
for i in range(len(wpary2)):
cv2.circle(img,(wpary2[i][0],row_s-int(wpary2[i][1])), 2, (100,100,100), -1)
cv2.imshow("img",img)
cv2.waitKey(0)
for i in range(len(wpary2)-1):
sn=list(wpary2[i])
sn[1]=row_s-sn[1]
dn=list(wpary2[i+1])
dn[1]=row_s-dn[1]
print sn, dn
cn=sn
while(cn!=dn):
Pathlist.append(cn)
cn=neighbour_min(cn,dn)
cv2.circle(img,(cn[0],cn[1]), 0, (100,100,100), -1)
cv2.imshow("img",img)
cv2.waitKey(0)
print "reached --------------- --------------- ------------- ----------"
Pathlist.append(dn)
"""
print ("yeah yeah")
for i in range(len(Pathlist)):
img[Pathlist[i][0]][Pathlist[i][1]]==100
cv2.imshow("im2",img)
cv2.waitKey(0)