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37 changed files with 93 additions and 1277 deletions

1
.gitignore vendored
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@ -150,4 +150,3 @@ cython_debug/
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
.idea/
/algorithms/neural_network/data/

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{}

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{}

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@ -10,39 +10,23 @@ from common.constants import DEVICE, BATCH_SIZE, NUM_EPOCHS, LEARNING_RATE, SETU
class NeuralNetwork(pl.LightningModule):
def __init__(self, numChannels=3, batch_size=BATCH_SIZE, learning_rate=LEARNING_RATE, num_classes=4):
super(NeuralNetwork, self).__init__()
self.conv1 = nn.Conv2d(numChannels, 24, (3, 3), padding=1)
self.relu1 = nn.ReLU()
self.maxpool1 = nn.MaxPool2d((2, 2), stride=2)
self.conv2 = nn.Conv2d(24, 48, (3, 3), padding=1)
self.relu2 = nn.ReLU()
self.fc1 = nn.Linear(48*18*18, 800)
self.relu3 = nn.ReLU()
self.fc2 = nn.Linear(800, 400)
self.relu4 = nn.ReLU()
self.fc3 = nn.Linear(400, 4)
self.logSoftmax = nn.LogSoftmax(dim=1)
super().__init__()
self.layer = nn.Sequential(
nn.Linear(36*36*3, 300),
nn.ReLU(),
nn.Linear(300, 4),
nn.LogSoftmax(dim=-1)
)
self.batch_size = batch_size
self.learning_rate = learning_rate
def forward(self, x):
x = self.conv1(x)
x = self.relu1(x)
x = self.maxpool1(x)
x = self.conv2(x)
x = self.relu2(x)
x = x.reshape(x.shape[0], -1)
x = self.fc1(x)
x = self.relu3(x)
x = self.fc2(x)
x = self.relu4(x)
x = self.fc3(x)
x = self.logSoftmax(x)
x = self.layer(x)
return x
def configure_optimizers(self):
optimizer = Adam(self.parameters(), lr=self.learning_rate)
optimizer = SGD(self.parameters(), lr=self.learning_rate)
return optimizer
def training_step(self, batch, batch_idx):

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@ -10,8 +10,44 @@ from torch.optim import Adam
import matplotlib.pyplot as plt
import pytorch_lightning as pl
from pytorch_lightning.callbacks import EarlyStopping
import torchvision.transforms.functional as F
from PIL import Image
def train(model):
model = model.to(DEVICE)
model.train()
trainset = WaterSandTreeGrass('./data/train_csv_file.csv', transform=SETUP_PHOTOS)
testset = WaterSandTreeGrass('./data/test_csv_file.csv', transform=SETUP_PHOTOS)
train_loader = DataLoader(trainset, batch_size=BATCH_SIZE, shuffle=True)
test_loader = DataLoader(testset, batch_size=BATCH_SIZE, shuffle=True)
criterion = nn.CrossEntropyLoss()
optimizer = Adam(model.parameters(), lr=LEARNING_RATE)
for epoch in range(NUM_EPOCHS):
for batch_idx, (data, targets) in enumerate(train_loader):
data = data.to(device=DEVICE)
targets = targets.to(device=DEVICE)
scores = model(data)
loss = criterion(scores, targets)
optimizer.zero_grad()
loss.backward()
optimizer.step()
if batch_idx % 4 == 0:
print("epoch: %d loss: %.4f" % (epoch, loss.item()))
print("FINISHED TRAINING!")
torch.save(model.state_dict(), "./learnednetwork.pth")
print("Checking accuracy for the train set.")
check_accuracy(train_loader)
print("Checking accuracy for the test set.")
check_accuracy(test_loader)
print("Checking accuracy for the tiles.")
check_accuracy_tiles()
def check_accuracy_tiles():
@ -59,13 +95,12 @@ def check_accuracy_tiles():
def what_is_it(img_path, show_img=False):
image = Image.open(img_path).convert('RGB')
image = read_image(img_path, mode=ImageReadMode.RGB)
if show_img:
plt.imshow(image)
plt.imshow(plt.imread(img_path))
plt.show()
image = SETUP_PHOTOS(image).unsqueeze(0)
model = NeuralNetwork.load_from_checkpoint('./lightning_logs/version_20/checkpoints/epoch=3-step=324.ckpt')
model = NeuralNetwork.load_from_checkpoint('./lightning_logs/version_3/checkpoints/epoch=8-step=810.ckpt')
with torch.no_grad():
model.eval()
@ -73,53 +108,18 @@ def what_is_it(img_path, show_img=False):
return ID_TO_CLASS[idx]
def check_accuracy(tset):
model = NeuralNetwork.load_from_checkpoint('./lightning_logs/version_23/checkpoints/epoch=3-step=324.ckpt')
num_correct = 0
num_samples = 0
model = model.to(DEVICE)
model.eval()
with torch.no_grad():
for photo, label in tset:
photo = photo.to(DEVICE)
label = label.to(DEVICE)
scores = model(photo)
predictions = scores.argmax(dim=1)
num_correct += (predictions == label).sum()
num_samples += predictions.size(0)
print(f'Got {num_correct} / {num_samples} with accuracy {float(num_correct)/float(num_samples)*100:.2f}%')
CNN = NeuralNetwork()
def check_accuracy_data():
trainset = WaterSandTreeGrass('./data/train_csv_file.csv', transform=SETUP_PHOTOS)
testset = WaterSandTreeGrass('./data/test_csv_file.csv', transform=SETUP_PHOTOS)
train_loader = DataLoader(trainset, batch_size=BATCH_SIZE, shuffle=True)
test_loader = DataLoader(testset, batch_size=BATCH_SIZE)
print("Accuracy of train_set:")
check_accuracy(train_loader)
print("Accuracy of test_set:")
check_accuracy(test_loader)
#CNN = NeuralNetwork()
#common.helpers.createCSV()
#trainer = pl.Trainer(accelerator='gpu', callbacks=EarlyStopping('val_loss'), devices=1, max_epochs=NUM_EPOCHS)
trainer = pl.Trainer(accelerator='gpu', devices=1, auto_scale_batch_size=True, callbacks=[EarlyStopping('val_loss')], max_epochs=NUM_EPOCHS)
#trainer = pl.Trainer(accelerator='gpu', devices=1, auto_lr_find=True, max_epochs=NUM_EPOCHS)
#trainset = WaterSandTreeGrass('./data/train_csv_file.csv', transform=SETUP_PHOTOS)
#testset = WaterSandTreeGrass('./data/test_csv_file.csv', transform=SETUP_PHOTOS)
#train_loader = DataLoader(trainset, batch_size=BATCH_SIZE, shuffle=True)
#test_loader = DataLoader(testset, batch_size=BATCH_SIZE)
trainset = WaterSandTreeGrass('./data/train_csv_file.csv', transform=SETUP_PHOTOS)
testset = WaterSandTreeGrass('./data/test_csv_file.csv', transform=SETUP_PHOTOS)
train_loader = DataLoader(trainset, batch_size=BATCH_SIZE, shuffle=True)
test_loader = DataLoader(testset, batch_size=BATCH_SIZE)
#trainer.fit(CNN, train_loader, test_loader)
#trainer.tune(CNN, train_loader, test_loader)
#print(what_is_it('../../resources/textures/grass2.png', True))
#check_accuracy_data()
#check_accuracy_tiles()
check_accuracy_tiles()
print(what_is_it('../../resources/textures/sand.png', True))

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@ -3,7 +3,6 @@ from torch.utils.data import Dataset
import pandas as pd
from torchvision.io import read_image, ImageReadMode
from common.helpers import createCSV
from PIL import Image
class WaterSandTreeGrass(Dataset):
@ -16,8 +15,7 @@ class WaterSandTreeGrass(Dataset):
return len(self.img_labels)
def __getitem__(self, idx):
image = Image.open(self.img_labels.iloc[idx, 0]).convert('RGB')
image = read_image(self.img_labels.iloc[idx, 0], mode=ImageReadMode.RGB)
label = torch.tensor(int(self.img_labels.iloc[idx, 1]))
if self.transform:

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@ -6,7 +6,7 @@ GAME_TITLE = 'WMICraft'
WINDOW_HEIGHT = 800
WINDOW_WIDTH = 1360
FPS_COUNT = 60
TURN_INTERVAL = 200
TURN_INTERVAL = 500
GRID_CELL_PADDING = 5
GRID_CELL_SIZE = 36
@ -77,17 +77,19 @@ BAR_HEIGHT_MULTIPLIER = 0.1
#NEURAL_NETWORK
LEARNING_RATE = 0.000630957344480193
LEARNING_RATE = 0.13182567385564073
BATCH_SIZE = 64
NUM_EPOCHS = 9
NUM_EPOCHS = 50
DEVICE = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
print("Using ", DEVICE)
CLASSES = ['grass', 'sand', 'tree', 'water']
SETUP_PHOTOS = transforms.Compose([
transforms.Resize(36),
transforms.CenterCrop(36),
transforms.ToPILImage(),
transforms.ToTensor(),
transforms.Resize((36, 36)),
transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])
])

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@ -26,7 +26,7 @@ def parse_idx_of_opp_or_monster(s: str) -> int:
class DecisionTree:
def __init__(self) -> None:
data_frame = pd.read_csv('learning/dataset_tree_1000.csv', delimiter=';')
data_frame = pd.read_csv('learning/dataset_tree.csv', delimiter=';')
unlabeled_goals = data_frame['goal']
self.goals_label_encoder = LabelEncoder()
self.goals = self.goals_label_encoder.fit_transform(unlabeled_goals)

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@ -45,7 +45,6 @@ class Game:
# create level
level.create_map()
stats = Stats(self.screen, level.list_knights_blue, level.list_knights_red)
level.setup_stats(stats)
print_numbers_flag = False
running = True

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@ -10,7 +10,7 @@ class KnightsQueue:
def dequeue_knight(self):
if self.both_teams_alive():
knight = self.queues[self.team_idx_turn].popleft()
if knight.health_bar.current_hp <= 0:
if knight.max_hp <= 0:
return self.dequeue_knight()
else:
self.queues[self.team_idx_turn].append(knight)

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@ -31,15 +31,6 @@ class Level:
self.knights_queue = None
self.stats = None
def setup_stats(self, stats):
self.stats = stats
def add_points(self, team, points_to_add):
if self.stats is not None:
self.stats.add_points(team, points_to_add)
def create_map(self):
self.map = import_random_map()
self.setup_base_tiles()
@ -101,119 +92,11 @@ class Level:
self.map[row_index][col_index] = castle
self.list_castles.append(castle)
#def attack_knight(self, knights_list, positions, current_knight):
# op_pos_1 = current_knight.position[0] - 1, current_knight.position[1]
# positions.append(op_pos_1)
# op_pos_2 = current_knight.position[0], current_knight.position[1] - 1
# positions.append(op_pos_2)
# op_pos_3 = current_knight.position[0] + 1, current_knight.position[1]
# positions.append(op_pos_3)
# op_pos_4 = current_knight.position[0], current_knight.position[1] + 1
# positions.append(op_pos_4)
# for some_knight in knights_list:
# for some_position in positions:
# if (some_knight.position == some_position and some_knight.team != current_knight.team):
# some_knight.health_bar.take_dmg(current_knight.attack)
# if some_knight.health_bar.current_hp == 0:
# some_knight.kill()
# positions.clear()
def attack_knight_left(self, knights_list, current_knight):
position_left = current_knight.position[0] - 1, current_knight.position[1]
for some_knight in knights_list:
if (some_knight.position == position_left and some_knight.team != current_knight.team):
some_knight.health_bar.take_dmg(current_knight.attack)
if some_knight.health_bar.current_hp <= 0:
some_knight.kill()
self.add_points(current_knight.team, 5)
for monster in self.list_monsters:
if monster.position == position_left:
monster.health_bar.take_dmg(current_knight.attack)
if monster.health_bar.current_hp <= 0:
monster.kill()
self.add_points(current_knight.team, monster.points)
else:
current_knight.health_bar.take_dmg(monster.attack)
if current_knight.health_bar.current_hp <= 0:
current_knight.kill()
for castle in self.list_castles:
if castle.position == position_left:
castle.health_bar.take_dmg(current_knight.attack)
def attack_knight_right(self, knights_list, current_knight):
position_right = current_knight.position[0] + 1, current_knight.position[1]
for some_knight in knights_list:
if (some_knight.position == position_right and some_knight.team != current_knight.team):
some_knight.health_bar.take_dmg(current_knight.attack)
if some_knight.health_bar.current_hp == 0:
some_knight.kill()
self.add_points(current_knight.team, 5)
for monster in self.list_monsters:
if monster.position == position_right:
monster.health_bar.take_dmg(current_knight.attack)
if monster.health_bar.current_hp <= 0:
monster.kill()
self.add_points(current_knight.team, monster.points)
else:
current_knight.health_bar.take_dmg(monster.attack)
if current_knight.health_bar.current_hp <= 0:
current_knight.kill()
for castle in self.list_castles:
if castle.position == position_right:
castle.health_bar.take_dmg(current_knight.attack)
def attack_knight_up(self, knights_list, current_knight):
position_up = current_knight.position[0], current_knight.position[1] - 1
for some_knight in knights_list:
if (some_knight.position == position_up and some_knight.team != current_knight.team):
some_knight.health_bar.take_dmg(current_knight.attack)
if some_knight.health_bar.current_hp == 0:
some_knight.kill()
self.add_points(current_knight.team, 5)
for monster in self.list_monsters:
if monster.position == position_up:
monster.health_bar.take_dmg(current_knight.attack)
if monster.health_bar.current_hp <= 0:
monster.kill()
self.add_points(current_knight.team, monster.points)
else:
current_knight.health_bar.take_dmg(monster.attack)
if current_knight.health_bar.current_hp <= 0:
current_knight.kill()
for castle in self.list_castles:
if castle.position == position_up:
castle.health_bar.take_dmg(current_knight.attack)
def attack_knight_down(self, knights_list, current_knight):
position_down = current_knight.position[0], current_knight.position[1] + 1
for some_knight in knights_list:
if (some_knight.position == position_down and some_knight.team != current_knight.team):
some_knight.health_bar.take_dmg(current_knight.attack)
if some_knight.health_bar.current_hp == 0:
some_knight.kill()
self.add_points(current_knight.team, 5)
for monster in self.list_monsters:
if monster.position == position_down:
monster.health_bar.take_dmg(current_knight.attack)
if monster.health_bar.current_hp <= 0:
monster.kill()
self.add_points(current_knight.team, monster.points)
else:
current_knight.health_bar.take_dmg(monster.attack)
if current_knight.health_bar.current_hp <= 0:
current_knight.kill()
for castle in self.list_castles:
if castle.position == position_down:
castle.health_bar.take_dmg(current_knight.attack)
def handle_turn(self):
current_knight = self.knights_queue.dequeue_knight()
knights_list = self.list_knights_red + self.list_knights_blue
print("next turn " + current_knight.team)
knight_pos_x = current_knight.position[0]
knight_pos_y = current_knight.position[1]
positions = []
goal_list = self.decision_tree.predict_move(grid=self.map, current_knight=current_knight,
monsters=self.list_monsters,
@ -221,9 +104,6 @@ class Level:
if current_knight.team_alias() == 'k_r' else self.list_knights_red,
castle=self.list_castles[0])
if (len(self.list_knights_blue) == 0 or len(self.list_knights_red) == 0):
pygame.quit()
if len(goal_list) == 0:
return
@ -236,19 +116,6 @@ class Level:
return
next_action = action_list.pop(0)
#if current_knight.health_bar.current_hp != 0:
#self.attack_knight(knights_list, positions, current_knight)
if current_knight.direction.name == UP:
self.attack_knight_up(knights_list, current_knight)
elif current_knight.direction.name == DOWN:
self.attack_knight_down(knights_list, current_knight)
elif current_knight.direction.name == RIGHT:
self.attack_knight_right(knights_list, current_knight)
elif current_knight.direction.name == LEFT:
self.attack_knight_left(knights_list, current_knight)
if next_action == TURN_LEFT:
self.logs.enqueue_log(f'AI {current_knight.team}: Obrót w lewo.')
current_knight.rotate_left()
@ -259,7 +126,7 @@ class Level:
current_knight.step_forward()
self.map[knight_pos_y][knight_pos_x] = MAP_ALIASES.get("GRASS")
# update knight on map
# update knight on map
if current_knight.direction.name == UP:
self.logs.enqueue_log(f'AI {current_knight.team}: Ruch do góry.')
self.map[knight_pos_y - 1][knight_pos_x] = current_knight.team_alias()
@ -281,6 +148,3 @@ class Level:
# update and draw the game
self.sprites.draw(self.screen)
self.sprites.update()

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@ -16,7 +16,8 @@ class Castle(pygame.sprite.Sprite):
position_in_px = (parse_cord(position[0]), parse_cord(position[1]))
self.rect = self.image.get_rect(center=position_in_px)
self.max_hp = 80
self.health_bar = HealthBar(screen, self.rect, current_hp=self.max_hp, max_hp=self.max_hp, calculate_xy=True, calculate_size=True)
self.current_hp = random.randint(1, self.max_hp)
self.health_bar = HealthBar(screen, self.rect, current_hp=self.current_hp, max_hp=self.max_hp, calculate_xy=True, calculate_size=True)
def update(self):
self.health_bar.update()

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@ -7,11 +7,8 @@ from common.helpers import parse_cord
from logic.health_bar import HealthBar
def load_knight_textures(team):
if team == "blue":
random_index = 3
else:
random_index = 4
def load_knight_textures():
random_index = random.randint(1, 4)
states = [
pygame.image.load(f'resources/textures/knight_{random_index}_up.png').convert_alpha(), # up = 0
pygame.image.load(f'resources/textures/knight_{random_index}_right.png').convert_alpha(), # right = 1
@ -27,7 +24,7 @@ class Knight(pygame.sprite.Sprite):
super().__init__(group)
self.direction = Direction.DOWN
self.states = load_knight_textures(team)
self.states = load_knight_textures()
self.image = self.states[self.direction.value]
self.position = position
@ -36,11 +33,11 @@ class Knight(pygame.sprite.Sprite):
self.rect = self.image.get_rect(topleft=position_in_px)
self.team = team
self.max_hp = random.randint(9, 13)
self.attack = random.randint(2, 4)
self.max_hp = random.randint(7, 12)
self.attack = random.randint(4, 7)
self.defense = random.randint(1, 4)
self.points = 1
self.health_bar = HealthBar(screen, self.rect, current_hp=self.max_hp, max_hp=self.max_hp, calculate_xy=True, calculate_size=True)
self.health_bar = HealthBar(screen, self.rect, current_hp=random.randint(1, self.max_hp), max_hp=self.max_hp, calculate_xy=True, calculate_size=True)
def rotate_left(self):
self.direction = self.direction.left()

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@ -22,13 +22,14 @@ class Monster(pygame.sprite.Sprite):
position_in_px = (parse_cord(position[0]), parse_cord(position[1]))
self.rect = self.image.get_rect(topleft=position_in_px)
self.position = position
self.max_hp = random.randrange(15, 20)
self.health_bar = HealthBar(screen, self.rect, current_hp=self.max_hp, max_hp=self.max_hp,
self.max_hp = random.randrange(15, 25)
self.current_hp = random.randint(1, self.max_hp)
self.health_bar = HealthBar(screen, self.rect, current_hp=self.current_hp, max_hp=self.max_hp,
calculate_xy=True, calculate_size=True)
self.attack = random.randrange(4, 6)
self.attack = random.randrange(2, 10)
if self.image == monster_images[0]:
self.max_hp = 20
self.attack = 6
self.attack = 9
self.points = 10
elif self.image == monster_images[1]:
self.max_hp = 15

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@ -1,31 +1,6 @@
import pygame
from ui.screens.screen import Screen
from common.colors import BLACK
from common.helpers import draw_text
class Credits(Screen):
def __init__(self, screen, clock):
super().__init__('credits', screen, clock)
def display_screen(self):
running = True
while running:
self.screen.fill((252, 164, 12))
draw_text('Twórcy :', BLACK, self.screen, 520, 150)
draw_text('Angelika Iskra', BLACK, self.screen, 520, 250)
draw_text('Dawid Korzępa', BLACK, self.screen, 520, 300)
draw_text('Juliusz Sadowski', BLACK, self.screen, 520, 350)
draw_text('Aleksandra Muczyńska', BLACK, self.screen, 520, 400)
draw_text('Jerzy Tomaszewski', BLACK, self.screen, 520, 450)
draw_text('Mateusz Konofał', BLACK, self.screen, 520, 500)
for event in pygame.event.get():
if event.type == pygame.QUIT:
running = False
if event.type == pygame.KEYDOWN:
if event.key == pygame.K_ESCAPE:
running = False
pygame.display.update()
self.clock.tick(60)

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@ -23,8 +23,6 @@ class Stats:
pygame.Rect(self.x + 210, self.y + 210, 100, 15),
current_hp=sum([knight.get_current_hp() for knight in self.list_knights_red]),
max_hp=sum([knight.get_max_hp() for knight in self.list_knights_red]))
self.blue_team_points = 0
self.red_team_points = 0
def update(self):
@ -52,16 +50,12 @@ class Stats:
# texts
draw_text('Rycerze: ' + str(len(self.list_knights_blue)), FONT_DARK, self.screen, self.x + 35, self.y + 240, 18) # blue
draw_text('Fortece: ' + str(len(self.list_knights_red)), FONT_DARK, self.screen, self.x + 35, self.y + 270, 18) # red
draw_text('Rycerze: ' + str(len(self.list_knights_red)), FONT_DARK, self.screen, self.x + 215, self.y + 240, 18)
draw_text('Rycerze: 4', FONT_DARK, self.screen, self.x + 215, self.y + 240, 18)
draw_text('Fortece: 0', FONT_DARK, self.screen, self.x + 215, self.y + 270, 18)
# points
pygame.draw.rect(self.screen, ORANGE, pygame.Rect(self.x, self.y + 390, 340, 3))
draw_text('PUNKTY: ' + str(self.blue_team_points), FONT_DARK, self.screen, self.x + 35, self.y + 408, 18, True)
draw_text('PUNKTY: ' + str(self.red_team_points), FONT_DARK, self.screen, self.x + 215, self.y + 408, 18, True)
def add_points(self, team, points):
if team == "blue":
self.blue_team_points += points
else:
self.red_team_points += points
draw_text('PUNKTY: 10', FONT_DARK, self.screen, self.x + 35, self.y + 408, 18, True)
draw_text('PUNKTY: 10', FONT_DARK, self.screen, self.x + 215, self.y + 408, 18, True)