Traktor/source/main.py

228 lines
7.3 KiB
Python

import pygame
import time
import random
import pandas as pd
import joblib
from area.constants import WIDTH, HEIGHT, TILE_SIZE
from area.field import drawWindow
from area.tractor import Tractor, do_actions, display_work_results
from area.field import tiles, fieldX, fieldY
from area.field import get_tile_coordinates, get_tile_index
from ground import Dirt
from plant import Plant
from bfs import graphsearch, Istate, succ_astar, succ
from astar import a_star
from NN.neural_network import load_model, load_image, guess_image, display_image, display_result, clear_text_area
from PIL import Image
from genetic import genetic_algorithm
from area.field import createTiles
pygame.init()
WIN_WIDTH = WIDTH + 300
WIN = pygame.display.set_mode((WIN_WIDTH, HEIGHT))
pygame.display.set_caption('Intelligent tractor')
def main():
run = True
window = drawWindow(WIN)
pygame.display.update()
#Tractor initialization:
tractor = Tractor(0*TILE_SIZE, 0*TILE_SIZE, 2, None, None)
tractor.rect.x += fieldX
tractor.rect.y += fieldY
tractor.tractor_start = ((170, 100))
istate = Istate(170, 100, 2) #initial state
#main loop:
while run:
for event in pygame.event.get():
if event.type == pygame.QUIT:
run = False
time.sleep(1)
#getting coordinates of our "goal tile":
tile_index = get_tile_index()
tile_x, tile_y = get_tile_coordinates(tile_index)
if tile_x is not None and tile_y is not None:
print(f"Coordinates of tile {tile_index} are: ({tile_x}, {tile_y})")
else: print("Such tile does not exist")
#mark the goal tile:
tiles[tile_index].image = "resources/images/sampling_goal.png"
image = pygame.image.load(tiles[tile_index].image).convert()
image = pygame.transform.scale(image, (TILE_SIZE, TILE_SIZE))
WIN.blit(image, (tiles[tile_index].x, tiles[tile_index].y))
pygame.display.flip()
tractor.tractor_end = ((tile_x, tile_y))
goaltest = [] #final state (consists of x and y because direction doesnt matter)
goaltest.append(tile_x)
goaltest.append(tile_y)
goaltest[0] = tile_x
goaltest[1]=tile_y
#moves = (graphsearch(istate, succ, goaltest, tractor)) #<-------BFS
moves = (a_star(istate, succ_astar, goaltest))
print(moves)
# movement based on route-planning:
tractor.draw_tractor(WIN)
time.sleep(1)
if moves != False:
do_actions(tractor, WIN, moves)
#guessing the image under the tile:
goalTile = tiles[tile_index]
image_path = goalTile.photo
display_image(WIN, goalTile.photo, (WIDTH-20 , 300)) #displays photo next to the field
pygame.display.update()
image_tensor = load_image(image_path)
prediction = guess_image(load_model(), image_tensor)
clear_text_area(WIN, WIDTH - 50, 600, 400, 50)
display_result(WIN, (WIDTH - 50 , 600), prediction) #display text under the photo
pygame.display.update()
print(f"The predicted image is: {prediction}")
p1 = Plant('wheat', 'cereal', random.randint(1,100), random.randint(1,100), random.randint(1,100))
goalTile.plant = p1
d1 = Dirt(random.randint(1, 100), random.randint(1,100))
d1.pests_and_weeds()
goalTile.ground=d1
#getting the name and type of the recognized plant:
p1.update_name(prediction)
#decission tree test:
if d1.pest:
pe = 1
else:
pe = 0
if d1.weed:
we = 1
else:
we = 0
if p1.plant_type == 'cereal':
t1 = True
t2 = False
t3 = False
t4 = False
else:
t1 = False
if p1.plant_type == 'fruit':
t2 = True
t3 = False
t4 = False
else:
t2 = False
if p1.plant_type == 'vegetable':
t4 = True
t3 = False
else:
t3 = True
t4 = False
weather_n = random.randint(1, 4)
if weather_n == 1:
h1 = True
h2 = False
h3 = False
h4 = False
else:
h1 = False
if weather_n == 2:
h2 = True
h3 = False
h4 = False
else:
h2 = False
if weather_n == 3:
h3 = True
h4 = False
else:
h3 = False
h4 = True
season_n = random.randint(1,4)
if season_n == 1:
s1 = True
s2 = False
s3 = False
s4 = False
temp_n = random.randint(0,22)
else:
s1 = False
if season_n == 2:
s2 = True
s3 = False
s4 = False
temp_n = random.randint(0,22)
else:
s2 = False
if season_n == 3:
s3 = True
s4 = False
temp_n = random.randint(20,39)
else:
s3 = False
s4 = True
temp_n = random.randint(-20, 10)
anomaly_n = random.randint(1, 10)
if anomaly_n == 1:
a1 = True
else:
a1 = False
dane = {
'anomalies': [a1],
'temp': [temp_n],
'water': [d1.water_level],
'nutri': [d1.nutrients_level],
'pests': [pe],
'weeds': [we],
'ripeness': [p1.growth_level],
'season_autumn': [s1], 'season_spring': [s2], 'season_summer': [s3], 'season_winter': [s4],
'weather_heavyCloudy': [h1], 'weather_partCloudy': [h2], 'weather_precipitation': [h3],
'weather_sunny': [h4],
'type_cereal': [t1], 'type_fruit': [t2], 'type_none': [t3], 'type_vegetable': [t4]
}
df = pd.DataFrame(dane)
df.to_csv('model_data.csv', index=False)
model = joblib.load('model.pkl')
nowe_dane = pd.read_csv('model_data.csv')
predykcje = model.predict(nowe_dane)
print(predykcje)
#work on field:
if predykcje == 'work':
tractor.work_on_field(WIN, goalTile, d1, p1)
#update the initial state for the next target:
istate = Istate(tile_x, tile_y, tractor.direction)
#old goalTile is displayed with a black border - to show that it was an old target:
tiles[tile_index].image = "resources/images/sampling_old_goal.png"
image = pygame.image.load(tiles[tile_index].image).convert()
image = pygame.transform.scale(image, (TILE_SIZE, TILE_SIZE))
WIN.blit(image, (tiles[tile_index].x, tiles[tile_index].y))
pygame.display.flip()
tractor.draw_tractor(WIN)
time.sleep(2)
print("\n")
main()