92 lines
1.7 KiB
Python
92 lines
1.7 KiB
Python
from enum import Enum
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import torchvision.transforms as transforms
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import torch
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GAME_TITLE = 'WMICraft'
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WINDOW_HEIGHT = 800
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WINDOW_WIDTH = 1360
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FPS_COUNT = 60
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TURN_INTERVAL = 300
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GRID_CELL_PADDING = 5
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GRID_CELL_SIZE = 36
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ROWS = 19
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COLUMNS = 24
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BORDER_WIDTH = 10
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BORDER_RADIUS = 5
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KNIGHTS_SPAWN_WIDTH = 4
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KNIGHTS_SPAWN_HEIGHT = 7
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LEFT_KNIGHTS_SPAWN_FIRST_ROW = 6
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LEFT_KNIGHTS_SPAWN_FIRST_COL = 0
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RIGHT_KNIGHTS_SPAWN_FIRST_ROW = 6
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RIGHT_KNIGHTS_SPAWN_FIRST_COL = 20
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CASTLE_SPAWN_WIDTH = 6
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CASTLE_SPAWN_HEIGHT = 5
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CASTLE_SPAWN_FIRST_ROW = 7
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CASTLE_SPAWN_FIRST_COL = 9
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NBR_OF_WATER = 16
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NBR_OF_TREES = 20
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NBR_OF_MONSTERS = 2
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NBR_OF_SANDS = 35
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TILES = [
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'grass1.png',
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'grass2.png',
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'grass3.png',
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'grass4.png',
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'sand.png',
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'water.png',
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'grass_with_tree.jpg',
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]
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class Direction(Enum):
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UP = 0
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RIGHT = 1
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DOWN = 2
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LEFT = 3
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def right(self):
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v = (self.value + 1) % 4
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return Direction(v)
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def left(self):
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v = (self.value - 1) % 4
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return Direction(v)
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ACTION = {
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"rotate_left": -1,
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"rotate_right": 1,
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"go": 0,
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}
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# HEALTH_BAR
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BAR_ANIMATION_SPEED = 1
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BAR_WIDTH_MULTIPLIER = 0.9 # (0;1>
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BAR_HEIGHT_MULTIPLIER = 0.1
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#NEURAL_NETWORK
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learning_rate = 0.001
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batch_size = 7
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num_epochs = 10
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device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
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classes = ['grass', 'sand', 'tree', 'water']
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setup_photos = transforms.Compose([
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transforms.Resize(36),
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transforms.CenterCrop(36),
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transforms.ToPILImage(),
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transforms.ToTensor(),
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transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])
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])
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id_to_class = {i: j for i, j in enumerate(classes)}
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class_to_id = {value: key for key, value in id_to_class.items()}
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