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from Map import MapIn,MapOut
from Axis import AxisFinder
import cv2
import config
import time
from ast import literal_eval as make_tuple
def run_axis_finder(total_execution_time):
maps_list = []
lines_list = []
axis_division_cond = True
maps_processing_queue = []
map_id = 0
iteration = 0
# axis finding process (1.1)
config.log_axis_finding_settings()
config.log(f"------Axis Finder------")
start_time = time.time()
while axis_division_cond:
config.log(f"----Step {iteration}----")
if (map_id == 0):
# read map and make masks
mymap = MapIn(config.MAIN_MAP_ADDR,config.MAIN_MAP_FILLED_BLOCK_MASK,config.MAIN_MAP_FILLED_F_F_MASK,
config.PARCELS_COUNT,config.ARCH,map_id=map_id)
# set random values for carbon
# mymap.correct_input()
else:
mymap = maps_processing_queue.pop(0)
# makes axis_finder object to split
myaxis = AxisFinder(mymap)
# Arch Selection on start division is the same
if mymap.arch_choice == config.ArchStyles.Customized:
# axis_center = myaxis.get_center(mymap.block_mask)
# mymap.set_map_axis_center(axis_center)
cv2.imshow(f'Map{mymap.map_id}', mymap.frame)
cv2.setMouseCallback(f'Map{mymap.map_id}', AxisFinder.click_callback)
cv2.waitKey(0)
cv2.destroyAllWindows()
p_f = AxisFinder.clicked_points.pop(0)
p_s = AxisFinder.clicked_points.pop(0)
points=[]
points.append((1,p_f,p_s,p_f,p_s))
elif map_id == 0 and mymap.arch_choice == config.ArchStyles.Human_Centered_AI:
p_f = ()
if config.ARCH_FIRST_INPUT == None:
cv2.imshow(f'Map{mymap.map_id}', mymap.frame)
cv2.setMouseCallback(f'Map{mymap.map_id}', AxisFinder.click_callback)
cv2.waitKey(0)
cv2.destroyAllWindows()
p_f = AxisFinder.clicked_points.pop(0)
else:
p_f = config.ARCH_FIRST_INPUT
points = myaxis.iterate_throughall(mymap,p_f)
elif map_id == 0:
points = myaxis.iterate_throughall(mymap)
else:
points = myaxis.iterate_old_boundries_new_york()
# dump axis if hit fixed_facility
if points[-1][0] == -1:
if not maps_processing_queue:
axis_division_cond = False
continue
# draw the found line carbon_fitness
config.log(f"Map div best score:{points[-1][0]} map_id:{mymap.map_id}")
config.log(f"Map div best access split fitness:{points[-1][5][0]}")
config.log(f"Map div best area split fitness:{points[-1][5][1]}")
config.log(f"Map div best fixed facilities fitness:{points[-1][5][2]}")
config.log(f"Map div best carbon fitness:{points[-1][5][3]}")
lines_list.append((points[-1][3:5],mymap.map_id))
# make map for split two parts (add line as access)
split_mask_u,split_mask_d = mymap.line_split_mask_maker(points[-1][1],points[-1][2])
line_mask = mymap.line_mask_maker(points[-1][1],points[-1][2])
up_map = MapIn(split_mask_u,mymap,line_mask,map_id+1,0,points[-1][1:3])
down_map = MapIn(split_mask_d,mymap,line_mask,map_id+2,1,points[-1][1:3])
parcels = AxisFinder.cal_split_parcels(up_map,down_map,mymap.parcel_cnt)
up_map.parcel_cnt,down_map.parcel_cnt = parcels
config.log(f"Map:{map_id+1} Parcels:{up_map.parcel_cnt}")
config.log(f"Map:{map_id+2} Parcels:{down_map.parcel_cnt}")
# check finishing condition
up_feasibility, down_feasibility = (up_map.isfeasible(), down_map.isfeasible())
# add new maps to processing queue
if up_feasibility:
config.log(f"Map:{map_id+1} Added!")
up_map.set_line_point(points[-1][1:])
maps_processing_queue.append(up_map)
# was the last axis so add axis to final answer
else:
config.log(f"Map:{map_id+1} Added As Answer")
up_map.set_line_point(points[-1][1:])
maps_list.append(up_map)
if down_feasibility:
config.log(f"Map:{map_id+2} Added!")
down_map.set_line_point(points[-1][1:])
maps_processing_queue.append(down_map)
else:
config.log(f"Map:{map_id+2} Added As Answer")
down_map.set_line_point(points[-1][1:])
maps_list.append(down_map)
if not maps_processing_queue:
axis_division_cond = False
map_id += 2
iteration+=1
config.log('-'*8)
# sort maps by size
maps_list.sort(key=lambda x: x.curr_size,reverse=True)
cv2.destroyAllWindows()
# export split result
config.log(f"------Axis Result------")
export_map = MapOut(config.MAIN_MAP_ADDR,lines_list)
export_map.draw_axis()
export_map.draw_collision()
export_map.report()
config.log("--- Axis Finder Finished In %s seconds ---" % (time.time() - start_time))
total_execution_time += time.time() - start_time
return total_execution_time
def gradio_inference(access_ratio,start_point,carbon_weight):
config.ACCESS_RATIO = float(access_ratio)
config.ARCH_FIRST_INPUT = make_tuple(start_point)
config.A_CARBON_WEIGHT = int(carbon_weight)
run_axis_finder(0)
image = cv2.imread(f'outputs/collision_map.bmp')
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
return image
if __name__ == "__main__":
run_axis_finder(0) |