Zaktualizuj 'Traktorek/ran.py'
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Traktorek/ran.py
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Traktorek/ran.py
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import pygame
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import sys
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import random
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import NataliaWisniewskaDrzewoDecyzyjne
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from Tractor import Tractor
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import pygame, sys
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from traktor import Traktor
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import matplotlib.pyplot as plt
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from tensorflow.keras.preprocessing import image
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from tensorflow.keras.models import load_model
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from tensorflow.keras.applications import MobileNetV2
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from tensorflow.keras.applications.mobilenet import preprocess_input, decode_predictions
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import numpy as np
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import os, random
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from algorytm_genetyczny import Gen
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import drzewo_decyzyjne_n as drzewko
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from drzewo_decyzyjne_o import Tree
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os.environ['KMP_DUPLICATE_LIB_OK'] = 'True'
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class Game(object):
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def __init__(self):
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# Config
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self.max_tps = 2.0
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self.res = (720, 720)
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self.gen = Gen(self)
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# nat
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self.nawadnianie = []
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# ola
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self.stan = []
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self.fields = []
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self.randomize_field()
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self.nawadnianie = []
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# Initialization
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self.neighbours()
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# planszę przedstawiam za pomocą punktów 25 pól (współrzędne środka)
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self.punkty_pola = [[22, 22], [22, 166], [22, 310], [22, 454], [22, 598], # pierwsza kolumna
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[166, 22], [166, 166], [166, 310], [166, 454], [166, 598], # druga kolumna
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[310, 22], [310, 166], [310, 310], [310, 454], [310, 598], # trzecia kolumna
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[454, 22], [454, 166], [454, 310], [454, 454], [454, 598], # czwarta kolumna
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[598, 22], [598, 166], [598, 310], [598, 454], [598, 598]] # 5 kolumna
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# tworzę listę etykiet warzyw, które mogą pojawić się na polu
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self.warzywa_etykiety = []
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self.warzywa_etykiety_sciezka = './warzywa_etykiety'
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# losowo przypisuję do każdego pola etykietę
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for _ in self.punkty_pola:
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self.warzywa_etykiety.append(
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'./warzywa_etykiety/' + random.choice(os.listdir(self.warzywa_etykiety_sciezka)))
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# ładuję model sieci neutronowej
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self.model = load_model('neural_model.h5')
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pygame.init()
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self.res = (720, 720)
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self.screen = pygame.display.set_mode(self.res)
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pygame.display.set_caption('Traktorek')
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self.clock = pygame.time.Clock()
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self.dt = 0.0
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my_tree = drzewoDecyzyjne.build_tree(drzewoDecyzyjne.training_data)
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self.player = Tractor(self)
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self.player = Traktor(self)
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self.rozpoznawanie_planszy()
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self.randomize_field()
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# gen
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# sadzonki do zasadzenia
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self.sadzonka = self.gen.algorytm()
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# nat
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drzewko.build_tree(drzewko.training_data)
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# ola
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self.tree = Tree()
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self.tree.Algorithm()
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while True:
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# Handle events
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pole = int(self.player.y // 144 * 5 + self.player.x // 144)
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for event in pygame.event.get():
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if event.type == pygame.QUIT:
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sys.exit(0)
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elif event.type == pygame.K_ESCAPE:
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pygame.quit()
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sys.exit(0)
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# Ticking
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self.dt += self.clock.tick() / 1000.0
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while self.dt > 1 / self.max_tps:
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self.tick()
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self.dt -= 1 / self.max_tps
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if event.type == pygame.KEYDOWN:
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if event.key == pygame.K_UP:
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self.player.y -= 144
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if self.player.y < 0:
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self.player.y = 0
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elif event.key == pygame.K_DOWN:
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self.player.y += 144
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print(pole)
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if self.player.y > 720:
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self.player.y = 598
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elif event.key == pygame.K_RIGHT:
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self.player.x += 144
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if self.player.x > 720:
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self.player.x = 598
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elif event.key == pygame.K_LEFT:
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self.player.x -= 144
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if self.player.x < 0:
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self.player.x = 0
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elif event.key == pygame.K_SPACE:
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# sieci neuronowe
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# dla obecnego położenia klienta rozpoznaję jakie rośnie tam warzywo
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obecne_polozenie_agenta = [self.player.x, self.player.y]
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self.player.obecne_pole = self.punkty_pola.index(obecne_polozenie_agenta)
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temp = self.player.obecne_pole
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img_path = self.warzywa_etykiety[temp]
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img = image.load_img(img_path, target_size=(224, 224))
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x = image.img_to_array(img)
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x = np.expand_dims(x, axis=0)
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x = preprocess_input(x)
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plt.imshow(img)
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preds = self.model.predict(x)
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preds = np.asarray(preds)
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plt.show()
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elif event.key == pygame.K_s:
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# algorytm genetyczny
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# dla każdego pustego pola sadzę warzywo, które najlepiej się przyjmie względem sąsiadujących
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if pole in self.gen.index_gen:
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self.fields[pole] = self.sadzonka[self.gen.index_gen.index(pole)]
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print('zasadzono', self.sadzonka[self.gen.index_gen.index(pole)])
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self.gen.index_gen.remove(pole)
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elif event.key == pygame.K_p:
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# drzewo decyzyjne
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# dla każdego pola decyduje czy należy je podlać
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wynik = drzewko.finalAnswer(self.nawadnianie[pole], drzewko.my_tree)
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if (wynik == 's'):
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print('należy podlać pole')
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else:
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print('nie podlewać pola ')
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elif event.key == pygame.K_g:
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# drzewo decyzyjne
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# dla danego pola sprawdza stan gleby
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s = self.stan[pole]
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print(self.tree.Solution(s))
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pygame.display.update()
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# Rendering
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self.screen.fill((0, 0, 0))
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self.draw()
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pygame.display.flip()
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def tick(self):
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self.player.tick()
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# plansza
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def draw(self):
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self.screen.fill((0, 0, 0))
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self.screen.fill((108, 142, 191))
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self.draw_field()
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self.draw_net()
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self.player.draw()
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pygame.display.update()
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# krata
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def draw_net(self):
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color = (255, 255, 255)
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for i in range(1, 5):
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@ -62,89 +161,116 @@ class Game(object):
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# linia pionowa
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pygame.draw.line(self.screen, color, (krat, 0), (krat, 720), 1)
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def draw_field(self):
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for x in range(25):
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self.screen.fill((255, 234, 234), (144 * (x % 5), 144 * (x // 5), 144 * (x % 5 + 1), 144 * (x // 5 + 1)))
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#sąsiedzi
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def neighbours(self):
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self.neighbours = list(range(25))
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self.neighbours[0] = [1, 5]
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self.neighbours[4] = [3, 9]
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self.neighbours[20] = [15, 21]
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self.neighbours[24] = [19, 23]
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for x in range(1, 4):
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self.neighbours[x] = [x - 1, x + 5, x + 1]
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for x in range(5, 16, 5):
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self.neighbours[x] = [x - 5, x + 1, x + 5]
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for x in range(9, 20, 5):
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self.neighbours[x] = [x - 5, x - 1, x + 5]
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for x in range(21, 24):
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self.neighbours[x] = [x - 1, x - 5, x + 1]
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for x in [6, 7, 8, 11, 12, 13, 16, 17, 18]:
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self.neighbours[x] = [x - 5, x - 1, x + 1, x + 5]
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# rozpoznawanie warzyw na każdym polu
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def rozpoznawanie_planszy(self):
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for _ in range(25):
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temp = _
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img_path = self.warzywa_etykiety[temp]
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img = image.load_img(img_path, target_size=(224, 224))
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x = image.img_to_array(img)
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x = np.expand_dims(x, axis=0)
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x = preprocess_input(x)
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preds = self.model.predict(x)
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preds = np.asarray(preds)
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szacunek = preds.max()
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ind = np.where(preds == szacunek)
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if ind == 0:
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self.fields.append('rzodkiewa')
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if ind == 1:
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self.fields.append('papryka')
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if ind == 2:
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self.fields.append('pomidor')
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if ind == 3:
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self.fields.append('marchew')
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if ind == 4:
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self.fields.append('salata')
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if ind == 5:
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self.fields.append('pietrucha')
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if ind == 6:
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self.fields.append('puste')
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# generowanie dodatkowych własności dla każdego pola w oparciu o rosnącą tam roślinę
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def randomize_field(self):
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chwasty_list = list(range(1, 11))
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waga_ch = [0.3, 0.2, 0.15, 0.1, 0.05, 0.05, 0.05, 0.04, 0.03, 0.03]
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podlanie_list = list(range(1, 11))
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waga_po = [0.02, 0.05, 0.05, 0.05, 0.05, 0.08, 0.1, 0.15, 0.15, 0.3]
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ph_list = list(range(1, 11))
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waga_ph = [0.01, 0.01, 0.02, 0.03, 0.07, 0.37, 0.4, 0.05, 0.03, 0.01]
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for x in range(25):
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temp = []
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# nasiona
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temp.append(random.choice(["żyto", "jęczmień", "owies", "marchew", "rzodkiew", "pietruszka", "puste"]))
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# gleba
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temp.append(random.choice([True, False]))
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# woda
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temp.append(random.choice(['s', 'n']))
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temp1 = []
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temp1.append(random.choices(chwasty_list, waga_ch)[0])
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woda = random.choices(podlanie_list, waga_po)[0]
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temp1.append(woda)
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temp1.append(random.choices(ph_list, waga_ph)[0])
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self.stan.append(temp1)
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# ile dni temu pole bylo podlewane
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temp.append(random.randrange(7))
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# czy ma padac
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pada = random.choice(['t', 'n'])
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temp.append(pada)
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# kiedy padalo
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kiedyPada = random.randrange(9)
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temp.append(kiedyPada)
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ind = 2
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# nawoz
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temp.append(random.choice([True, False]))
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# # growth rate
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# temp.append(random)
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# # cost + co ile dni nalezy podlewac dana uprawe
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if temp[0] == "żyto":
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temp.append(10)
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temp.append(ind)
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#co ile dni nalezy podlewac dana uprawe
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if self.fields[x] == "rzodkiewa":
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temp.append(4)
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elif temp[0] == "jęczmień":
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temp.append(12)
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elif self.fields[x] == "papryka":
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temp.append(3)
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elif temp[0] == "owies":
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temp.append(8)
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elif self.fields[x] == "pomidor":
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temp.append(2)
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elif temp[0] == "marchew":
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temp.append(14)
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elif self.fields[x] == "marchew":
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temp.append(5)
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elif temp[0] == "rzodkiew":
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temp.append(7)
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elif self.fields[x] == "sałata":
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temp.append(5)
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elif temp[0] == "pietruszka":
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temp.append(6)
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elif self.fields[x] == "pietruszka":
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temp.append(1)
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elif temp[0] == "puste":
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temp.append(2)
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elif self.fields[x] == "puste":
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temp.append(6)
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else:
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temp.append(0)
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self.fields.append(temp)
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# czy ma padac
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pada = random.choice(['t', 'n'])
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temp.append(pada)
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self.nawadnianie.append([temp[3], temp[8], temp[4], temp[5], temp[2]])
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i=0
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print('\nPODLEWANIE: \n')
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# kiedy padalo
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kiedyPada = random.randrange(9)
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temp.append(kiedyPada)
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while i<25:
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wynik = drzewoDecyzyjne.finalAnswer(self.nawadnianie[i], drzewoDecyzyjne.my_tree)
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#print(self.nawadnianie[i])
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#print(wynik)
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if (wynik == 's'):
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print('należy podlać pole ' + str(i))
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# woda
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if woda <= 5:
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temp.append('s')
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else:
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print('nie podlewać pola ' + str(i))
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i=i+1
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def draw_field(self):
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for x in range(25):
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self.screen.fill(self.color(x), (144 * (x % 5), 144 * (x // 5), 144 * (x % 5 + 1), 144 * (x // 5 + 1)))
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def color(self, z):
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if self.fields[z][0] == 'owies':
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return (255, 200, 55)
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elif self.fields[z][0] == 'jęczmień':
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return (170, 150, 40)
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elif self.fields[z][0] == 'żyto':
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return (100, 215, 80)
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elif self.fields[z][0] == 'marchew':
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return (224, 60, 14)
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elif self.fields[z][0] == 'rzodkiew':
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return (142, 24, 104)
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elif self.fields[z][0] == 'pietruszka':
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return (254, 247, 246)
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else:
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return (0,0,0)
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temp.append('n')
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self.nawadnianie.append(temp)
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if __name__ == "__main__":
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