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mapgenerator.py
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mapgenerator.py
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from tkinter import *
import random
import math
import time
from matplotlib.colors import hsv_to_rgb
import numpy as np
import os
DYNAMIC_TESTING=True
GOALS=True
output_path="environments"
model_path="model_primal"
dirDict = {0:(0,0),1:(0,1),2:(1,0),3:(0,-1),4:(-1,0),5:(1,1),6:(1,-1),7:(-1,-1),8:(-1,1)}
if DYNAMIC_TESTING:
import tensorflow as tf
from ACNet import ACNet
def init(data):
data.size=10
data.state=np.zeros((data.size,data.size)).astype(int)
data.goals=np.zeros((data.size,data.size)).astype(int)
data.mode="obstacle"
data.agent_counter=1
data.primed_goal=0
data.ID=0
data.paused=True
data.blocking_confidences=[]
data.agent_goals=[]
data.agent_positions=[]
if not os.path.exists(output_path):
os.makedirs(output_path)
if os.path.exists(output_path):
for (_,_,files) in os.walk(output_path):
for f in files:
if ".npy" in f:
try:
ID=int(f[:f.find(".npy")])
except Exception:
continue
if ID>data.ID:
data.ID=ID
data.ID+=1
if DYNAMIC_TESTING:
data.rnn_states=[]
data.sess=tf.Session()
data.network=ACNet("global",5,None,False,10,"global")
#load the weights from the checkpoint (only the global ones!)
ckpt = tf.train.get_checkpoint_state(model_path)
saver = tf.train.Saver()
saver.restore(data.sess,ckpt.model_checkpoint_path)
def getDir(action):
return dirDict[action]
def mousePressed(event, data):
r=int((event.y/data.height)*data.state.shape[0])
c=int((event.x/data.width)*data.state.shape[1])
if data.mode=="obstacle":
if data.state[r,c]<=0 and data.goals[r,c]==0:
data.state[r,c]=-((data.state[r,c]+1)%2)
elif data.mode=="agent":
if data.state[r,c]==0:
data.state[r,c]=data.agent_counter
data.goals[r,c]=data.agent_counter
data.agent_positions.append((r,c))
data.blocking_confidences.append(0)
data.rnn_states.append(data.network.state_init)
data.agent_goals.append((r,c))
data.agent_counter+=1
elif data.mode=="goal":
if data.state[r,c]>0 and data.primed_goal==0:
data.primed_goal=data.state[r,c]
elif data.state[r,c]!=-1 and data.primed_goal>0 and data.goals[r,c]==0:
removeGoal(data,data.primed_goal)
data.agent_goals[data.primed_goal-1]=(r,c)
data.goals[r,c]=data.primed_goal
data.primed_goal=0
def removeGoal(data,agent):
for i in range(data.state.shape[0]):
for j in range(data.state.shape[1]):
if data.goals[i,j]==agent:
data.goals[i,j]=0
def keyPressed(event, data):
if event.keysym=='r':
data.state=np.zeros((data.size,data.size)).astype(int)
data.goals=np.zeros((data.size,data.size)).astype(int)
data.agent_goals=[]
data.rnn_states=[]
data.agent_positions=[]
data.blocking_confidences=[]
data.primed_goal=0
data.agent_counter=1
elif event.keysym=="c":
data.agent_counter=1
data.primed_goal=0
data.rnn_states=[]
data.blocking_confidences=[]
data.agent_goals=[]
data.agent_positions=[]
data.goals=np.zeros((data.size,data.size))
data.state=-(data.state==-1).astype(int)
elif event.keysym=="p":
data.paused=not data.paused
elif event.keysym=="o":
data.mode="obstacle"
elif event.keysym=="g":
data.mode="goal"
elif event.keysym=="a":
data.mode="agent"
elif event.keysym=='Up':
data.size+=1
data.state=np.zeros((data.size,data.size)).astype(int)
data.goals=np.zeros((data.size,data.size)).astype(int)
elif event.keysym=='Down':
data.size-=1;
if data.size<1:
data.size==1
data.state=np.zeros((data.size,data.size)).astype(int)
data.goals=np.zeros((data.size,data.size)).astype(int)
elif event.keysym=="s":
savedata=np.array([data.state,data.goals,data.agent_counter-1])
np.save(output_path+"/%d"%data.ID,savedata)
data.ID+=1
def observe(data,agent_id,goals):
assert(agent_id>0)
top_left=(data.agent_positions[agent_id-1][0]-10//2,data.agent_positions[agent_id-1][1]-10//2)
bottom_right=(top_left[0]+10,top_left[1]+10)
obs_shape=(10,10)
goal_map = np.zeros(obs_shape)
poss_map = np.zeros(obs_shape)
obs_map = np.zeros(obs_shape)
goals_map = np.zeros(obs_shape)
visible_agents=[]
for i in range(top_left[0],top_left[0]+10):
for j in range(top_left[1],top_left[1]+10):
if i>=data.state.shape[0] or i<0 or j>=data.state.shape[1] or j<0:
#out of bounds, just treat as an obstacle
obs_map[i-top_left[0],j-top_left[1]]=1
continue
if data.state[i,j]==-1:
#obstacles
obs_map[i-top_left[0],j-top_left[1]]=1
if data.state[i,j]==agent_id:
#agent's position
# pos_map[i-top_left[0],j-top_left[1]]=1
poss_map[i-top_left[0],j-top_left[1]]=1
elif data.goals[i,j]==agent_id:
#agent's goal
goal_map[i-top_left[0],j-top_left[1]]=1
if data.state[i,j]>0 and data.state[i,j]!=agent_id:
#other agents' positions
poss_map[i-top_left[0],j-top_left[1]]=1
visible_agents.append(data.state[i,j])
dx=data.agent_goals[agent_id-1][0]-data.agent_positions[agent_id-1][0]
dy=data.agent_goals[agent_id-1][1]-data.agent_positions[agent_id-1][1]
mag=(dx**2+dy**2)**.5
if mag!=0:
dx=dx/mag
dy=dy/mag
if goals:
distance=lambda x1,y1,x2,y2:((x2-x1)**2+(y2-y1)**2)**.5
for agent in visible_agents:
x,y=data.agent_goals[agent-1]
if x<top_left[0] or x>=bottom_right[0] or y>=bottom_right[1] or y<top_left[1]:
#out of observation
min_node=(-1,-1)
min_dist=1000
for i in range(top_left[0],top_left[0]+10):
for j in range(top_left[1],top_left[1]+10):
d=distance(i,j,x,y)
if d<min_dist:
min_node=(i,j)
min_dist=d
goals_map[min_node[0]-top_left[0],min_node[1]-top_left[1]]=1
else:
goals_map[x-top_left[0],y-top_left[1]]=1
return ([poss_map,goal_map,goals_map,obs_map],[dx,dy,mag])
else:
return ([poss_map,goal_map,obs_map],[dx,dy,mag])
def timerFired(data):
if DYNAMIC_TESTING and not data.paused:
for (x,y) in data.agent_positions:
ID=data.state[x,y]
observation=observe(data,ID,GOALS)
rnn_state=data.rnn_states[ID-1]#yes minus 1 is correct
a_dist,v,rnn_state,blocking = data.sess.run([data.network.policy,data.network.value,data.network.state_out,data.network.blocking],
feed_dict={data.network.inputs:[observation[0]],
data.network.goal_pos:[observation[1]],
data.network.state_in[0]:rnn_state[0],
data.network.state_in[1]:rnn_state[1]})
data.rnn_states[ID-1]=rnn_state
data.blocking_confidences[ID-1]=np.ravel(blocking)[0]
action=np.argmax(a_dist)
dx,dy =getDir(action)
ax,ay =data.agent_positions[ID-1]
if(ax+dx>=data.state.shape[0] or ax+dx<0 or ay+dy>=data.state.shape[1] or ay+dy<0):#out of bounds
continue
if(data.state[ax+dx,ay+dy]<0):#collide with static obstacle
continue
if(data.state[ax+dx,ay+dy]>0):#collide with robot
continue
# No collision: we can carry out the action
data.state[ax,ay] = 0
data.state[ax+dx,ay+dy] = ID
data.agent_positions[ID-1] = (ax+dx,ay+dy)
def redrawAll(canvas, data):
for r in range(data.state.shape[0]):
y=(data.height/data.state.shape[0])*r
color_depth=30
for c in range(data.state.shape[1]):
x=(data.height/data.state.shape[0])*c
if data.state[r,c]==-1:
canvas.create_rectangle(x, y, x+data.width/data.state.shape[0], y+data.height/data.state.shape[1],
fill='grey', width=0)
elif data.state[r,c]>0:
color=hsv_to_rgb(np.array([(data.state[r,c]%color_depth)/float(color_depth),1,1]))
color*=255
color=color.astype(int)
mycolor = '#%02x%02x%02x' % (color[0], color[1], color[2])
canvas.create_rectangle(x, y, x+data.width/data.state.shape[0], y+data.height/data.state.shape[1],
fill=mycolor, width=0)
confidence=data.blocking_confidences[data.state[r,c]-1]
confidence="%.0001f"%confidence
canvas.create_text(x+data.width/data.state.shape[0]/2, y+data.height/data.state.shape[1]/2,
fill='black', anchor="s",text=confidence,font="Arial 30 bold")
if data.goals[r,c]>0:
color=hsv_to_rgb(np.array([(data.goals[r,c]%color_depth)/float(color_depth),1,1]))
color*=255
color=color.astype(int)
mycolor = '#%02x%02x%02x' % (color[0], color[1], color[2])
if data.state[r,c]==data.goals[r,c]:
canvas.create_text(x+data.width/data.state.shape[0]/2, y+data.height/data.state.shape[1]/2,
fill="black", anchor="center",text="+",font="Arial 50 bold")
else:
canvas.create_text(x+data.width/data.state.shape[0]/2, y+data.height/data.state.shape[1]/2,
fill=mycolor, anchor="center",text="+",font="Arial 50 bold")
for r in range(data.state.shape[0]):
y=(data.height/data.state.shape[0])*r
canvas.create_line(0,y,data.width,y,fill="black")
for c in range(data.state.shape[1]):
x=(data.height/data.state.shape[0])*c
canvas.create_line(x,0,x,data.height,fill="black")
canvas.create_text(data.width/2, 20,
fill="black", text=data.mode,font="Arial 20",anchor="center")
txt="Paused" if data.paused else "Running"
canvas.create_text(data.width-100, 20,
fill="black", text=txt,font="Arial 20",anchor="center")
def run(width=300, height=300):
def redrawAllWrapper(canvas, data):
canvas.delete(ALL)
canvas.create_rectangle(0, 0, data.width, data.height,
fill='white', width=0)
redrawAll(canvas, data)
canvas.update()
def mousePressedWrapper(event, canvas, data):
mousePressed(event, data)
redrawAllWrapper(canvas, data)
def keyPressedWrapper(event, canvas, data):
keyPressed(event, data)
redrawAllWrapper(canvas, data)
def timerFiredWrapper(canvas, data):
timerFired(data)
redrawAllWrapper(canvas, data)
# pause, then call timerFired again
canvas.after(data.timerDelay, timerFiredWrapper, canvas, data)
# Set up data and call init
class Struct(object): pass
data = Struct()
data.width = width
data.height = height
data.timerDelay = 200 # milliseconds
init(data)
# create the root and the canvas
root = Tk()
canvas = Canvas(root, width=data.width, height=data.height)
canvas.pack()
# set up events
root.bind("<Button-1>", lambda event:
mousePressedWrapper(event, canvas, data))
root.bind("<Key>", lambda event:
keyPressedWrapper(event, canvas, data))
timerFiredWrapper(canvas, data)
# and launch the app
root.mainloop() # blocks until window is closed
print("bye!")
def main():
run(900,900)
if __name__=='__main__':
main()