def addToDataset(self, path, label=None, dataFile='', labelFile=''):
"""
adds a set of image matches to train_data based on a log file of labelled matches
:param path: the path to the matches log
:param label: an integer np_array representing the label. When not given defaults to the labels given in the log file
:param dataFile: the path to optionally save the data object to
:param labelFile: the path to optionally save the label object to
:return: None
"""
imLoader = ImageLoader(path, image_size=self.img_dims)
if (self.data.shape[0] == 0):
self.data = imLoader.train_set
if (label != None):
entries = self.data.shape[0]
self.labels = np.vstack([label] * entries)
else:
self.labels = imLoader.label_set
else:
self.data = np.concatenate((self.data, imLoader.train_set), 0)
entries = imLoader.train_set.shape[0]
if (label != None):
self.labels = np.concatenate(
(self.labels, np.vstack([label] * entries)), 0)
else:
self.labels = np.concatenate((self.labels, imLoader.label_set),
0)
imLoader.closeFile()
if dataFile != '' and labelFile != '':
np.save(open(dataFile, 'wb'), self.data)
np.save(open(labelFile, 'wb'), self.labels)
def load_batch(self,path):
'''
Loading a image batch
'''
batch_loader = ImageLoader()
return batch_loader.load_image(path)
def epilepsy_mode(self):
root = Tkinter.Tk()
root.geometry('+%d+%d' % (100,100))
old_label_image = None
loader = ImageLoader("../testImages")
loader.start()
while True:
try:
image1 = loader.get()
root.geometry('%dx%d' % (image1.size[0],image1.size[1]))
tkpi = ImageTk.PhotoImage(image1)
root.geometry('%dx%d' % (image1.size[0],image1.size[1]))
label_image = Tkinter.Label(root, image=tkpi)
label_image.place(x=0,y=0,width=image1.size[0],height=image1.size[1])
if old_label_image is not None:
old_label_image.destroy()
old_label_image = label_image
root.update()
# time.sleep(1)
except Exception, e:
print "Something got f****d up:", e
pass
def test_images_are_resized(self):
loader = ImageLoader()
loader.load_from(imageLocation, 1)
images = loader.get_images()
for image in images:
self.assertEqual('(30, 30, 3)', str(image.shape))
def openFile(self):
filename = tk.filedialog.askopenfilename()
imageLoader = ImageLoader()
image = imageLoader.get_image(filename)
model = RoadSignModel()
model.load('./models/fullset-10epochs.h5')
category = model.predict_class(image)
print('Category =', self.sign_name(category - 1))
self.category.set(category)
def xtest_TrainModel(self):
imageLoader = ImageLoader()
imageLoader.load_from('./test-images', 1)
model = RoadSignModel(imageLoader)
self.assertEqual(False, model.is_trained())
model.train()
self.assertEqual(True, model.is_trained())
def test_SaveModel(self):
imageLoader = ImageLoader()
imageLoader.load_from('./test-images', 1)
model = RoadSignModel(imageLoader)
os.remove('model.h5')
model.train()
model.save()
self.assertEqual(True, os.path.exists('model.h5'))
def loadAssets(self):
"""Game class method to load all assets.
"""
#loading assets (images, sounds)
self.imageLoader = ImageLoader(self)
self.soundLoader = snd.Sound()
try:
self.imageLoader.load_assets()
self.soundLoader.load()
except Exception:
traceback.print_exc()
self.running = False
def recycle(self, image: ImageInfo):
existing_image = self.db.get_by_hash(image.hash)
if existing_image:
prune_hash = ImageLoader.hash_file(image.path.as_posix())
existing_hash = ImageLoader.hash_file(
existing_image.path.as_posix())
if prune_hash == existing_hash:
self.logger.info(f"Deleting {image}")
self.logger.info(f" Matches {existing_image}")
os.remove(image.path)
time.sleep(0.1)
return
self.logger.debug(f"Recycling {image}")
self.sort_to(self.recycle_dir, image, False)
def find_better(cls, image1: ImageInfo, image2: ImageInfo):
pixels1 = image1.width * image1.height
pixels2 = image2.width * image2.height
is_hdr1 = ImageLoader.is_hdr(image1.exif)
is_hdr2 = ImageLoader.is_hdr(image2.exif)
if pixels1 == pixels2 and (is_hdr1 or is_hdr2):
if is_hdr1:
return image1
else:
return image2
elif pixels1 >= pixels2:
return image1
else:
return image2
def __init__(self, filename_image, viewportSize_imageScaled,
matrix=QtGui.QMatrix()):
# These variables are needed later to handle rescaling.
self.rescale_info = PreFetcher.RescaleInfo()
if isinstance(filename_image, QtGui.QPixmap) \
and isinstance(viewportSize_imageScaled, QtGui.QPixmap):
self.image = filename_image
self.image_scaled = viewportSize_imageScaled
self.from_loader = False
self.to_rescale = False
elif (isinstance(filename_image, QtCore.QString) or \
isinstance(filename_image, str)) \
and isinstance(viewportSize_imageScaled, QtCore.QSize):
self.loader = ImageLoader(filename_image, viewportSize_imageScaled,
matrix)
self.loader.start()
self.from_loader = True
self.to_rescale = False
else:
msg = 'Incorrect PreFetcher contructor: ' + \
str(type(filename_image)) + ', ' + \
str(type(viewportSize_imageScaled))
raise InternalException(msg)
def main():
image_loader = ImageLoader(3)
images = image_loader.get_next_image_batch()
print (len(images))
print (images[0].get_label())
print (images[-1].get_label())
pink = []
tiel = []
for i in images:
if (i.get_label() == "cockatiel"):
tiel.append(i)
elif (i.get_label() == "pink_cockatoo"):
pink.append(i)
print (len(pink))
print (len(tiel))
def startLoading_(self, sender):
self.startLoadingButton.setEnabled_(False)
loader = ImageLoader(self.selectedPath,
self.setNameTextField.stringValue(),
self.groupByColorCheckbox.state() == NSOnState,
self)
self.worker = ImageLoaderWorker(loader)
self.worker.daemon = True
self.worker.start()
def __init__(self, input_PIL_img, lib_Lab_vectors, photoLog, cellLog, subimage, progress=0): # Set instance variables self.input = input_PIL_img self.photoLog = photoLog # The photoLog, cellLog, and progress should probably be in it's own information expert self.cellLog = cellLog self.progress = int(progress) self.ImgAnalyzer = ImageAnalyzer() self.ImgFinder = ImageFinder(lib_Lab_vectors) self.ImgLoader = ImageLoader() self.subimage = subimage
def __init__(self):
pygame.init()
self.window = pygame.display.set_mode(WINDOWDIMS)
pygame.display.set_caption("BLOODHELL")
self.font = pygame.font.SysFont('Comic Sans MS', 48)
self.pauseText = self.font.render("Game Paused", False, WHITE)
self.clock = pygame.time.Clock()
self.states = {'titleScreen': True, 'controlScreen': False, 'gameRunning': False, 'pause': False, 'gameOver': False}
self.running = True
self.titleScreenImage = pygame.transform.scale(pygame.image.load("assets//title_screen.png").convert(), WINDOWDIMS)
self.controlScreenImage = pygame.transform.scale(pygame.image.load("assets//control_screen.png").convert(), WINDOWDIMS)
self.endScreenImage = pygame.transform.scale(pygame.image.load("assets//end_screen.png").convert(), WINDOWDIMS)
self.input = {'closeGame': False}
ImageLoader.loadImages()
return
def sort_file(self, path: Path):
self.logger.info(f"Processing FILE {path}")
path = self.cleanup_filename(path)
incoming_image = ImageLoader.load(path)
existing_image = self.find_existing(incoming_image.hash)
if not existing_image:
self.move_to_sorted(incoming_image)
else:
self.logger.info(
f"Found match for incoming image {incoming_image}")
self.logger.info(f" With existing image {existing_image}")
self.keep_better(existing_image, incoming_image)
def get(self, userId, photoId):
# Get Access Token and Photo URL from header
access_token = self.request.headers["access-token"]
photo_url = self.request.headers["photo-url"]
# Load PIL image from facebook url
im = ImageLoader().load_url_image(photo_url)
# Crop image to a square
cols, rows = im.size
# Landscape Layout (or Square)
if cols >= rows:
target_cols = rows
left = (cols-target_cols)/2
right = left+target_cols
im = im.crop( (left, 0, right, rows) )
# Portrait Layout
else:
target_rows = cols
upper = (rows-target_rows)/2
lower = upper+target_rows
im = im.crop( (0, upper, cols, lower) )
# Analyze image
imgAnalyzer = ImageAnalyzer()
cols, rows = im.size
labVec = imgAnalyzer.getLABVector(im, 0, 0, cols, rows)
# Store the Lab Vector into the Google Datastore
ImageDatastore().set_Lab_vector(userId, photoId, labVec)
# Prepare JSON response
json_response = json.dumps( {"success": True, "photoId": photoId}, indent=4)
# Write JSON response
self.response.headers['Content-Type'] = 'application/json'
self.response.write(json_response)
def reload(self, path: Path):
self.logger.info(f"Reloading {path}")
reloaded = ImageLoader.load(path)
existing = self.db.get_by_hash(reloaded.hash)
if existing and existing.path != path:
self.logger.warning(f"Reloaded image: {reloaded}")
self.logger.warning(f" Matches existing: {existing}")
better = self.find_better(reloaded, existing)
if better == reloaded:
self.db.remove(existing)
self.recycle(existing)
else:
self.db.remove(reloaded)
self.recycle(reloaded)
self.db.add(reloaded)
def run_model(self,
writer,
set_path,
preload_epoch,
epoch,
training=False,
shuffle=False,
pretrain=False):
if not training:
print('VALIDATION')
image_loader = ImageLoader(batch_size=2, image_dir=set_path)
if shuffle:
image_loader.shuffle_data()
batch_gen = image_loader.getImages()
for i, (batch_x, batch_y) in enumerate(batch_gen):
subbatch = 100
feed = {
'tf_x:0': batch_x,
'tf_y:0': batch_y,
'tf_training:0': training
}
if (i % subbatch == 0):
print('batch ' + str(i) + '/' + str(image_loader.batch_count))
loss = self.sess.run(self.merged, feed_dict=feed)
writer.add_summary(loss)
if (training and i % 1000 == 0):
self.save(epoch=preload_epoch + epoch)
if (not pretrain):
_ = self.sess.run('train_op_disc', feed_dict=feed)
_ = self.sess.run('train_op', feed_dict=feed)
else:
loss, _ = self.sess.run([self.mse_loss_summ, 'train_mse_op'],
feed_dict=feed)
writer.add_summary(loss)
def accuracy(self,
net,
path,
epoch,
phase,
device,
log_path,
batch_size=64,
do_logwrite=False):
try:
os.makedirs(log_path)
except OSError:
pass
category = path.split('/')[-1] + "_" + phase
with torch.no_grad():
transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.5, ), (0.5, )) # Normalize [-1, 1]
])
dataset = ImageLoader(path, phase, transforms=transform)
data_loader = torch.utils.data.DataLoader(dataset,
batch_size=batch_size,
shuffle=False)
correct = 0
for idx, (images, labels) in enumerate(data_loader):
images = images.to(device)
labels = labels.to(device)
outputs = net(images)
_, pred_y = torch.max(outputs.data, 1)
correct += (pred_y == labels).sum().item()
accuracy = (correct / len(dataset)) * 100
print('phase:%s --- correct [%d/%d] acc: %.2f%%' %
(category, correct, len(dataset), accuracy))
if do_logwrite:
f = open('%s/%s_log.txt' % (log_path, category), 'a')
f.write('epoch:%d, phase:%s --- correct [%d/%d] %.4f%%\n' %
(epoch, phase, correct, len(dataset), accuracy))
f.close()
return accuracy
def keep_incoming(self, existing_image: ImageInfo,
incoming_image: ImageInfo):
self.logger.info(f"Deleting existing: {existing_image}")
self.logger.info(f" Keeping incoming: {incoming_image}")
if existing_image.path.name.lower().endswith(
".jpg"
) and existing_image.ts > OLD_TS and existing_image.ts < incoming_image.ts:
self.logger.info(
f" But preserving existing's exif: {existing_image}")
try:
piexif.transplant(existing_image.path.as_posix(),
incoming_image.path.as_posix())
except ValueError as e:
self.logger.warning(f"Failed to transplant exif: {e}")
incoming_image = ImageLoader.load(incoming_image.path)
self.db.remove(existing_image)
self.recycle(existing_image)
self.move_to_sorted(incoming_image)
def __InitUI(self):
ImageLoader.LoaderInit()
Navigation.NavigationInit()
self.__buttons = []
self.__ids = []
self.__menubar = wx.MenuBar()
self.__fileMenu = wx.Menu()
self.__fileItemQ = self.__fileMenu.Append(wx.ID_EXIT, 'Quit',
'Quit application')
self.__fileItemL = self.__fileMenu.Append(wx.ID_OPEN, 'Load',
'Load application')
self.__menubar.Append(self.__fileMenu, '&File')
self.__frame.SetMenuBar(self.__menubar)
self.__frame.Bind(wx.EVT_MENU, self.OnQuit, self.__fileItemQ)
self.__frame.Bind(wx.EVT_MENU, self.__world.Load, self.__fileItemL)
self.__panel = wx.Panel(self.__frame)
self.__panel.SetBackgroundColour("white")
self.__vbox = wx.BoxSizer(wx.VERTICAL)
self.__hbox = wx.BoxSizer(wx.HORIZONTAL)
self.__st1 = wx.StaticText(self.__panel, label='Set border dimensions')
self.__tc = wx.TextCtrl(self.__panel)
self.__hbox.Add(self.__st1, flag=wx.RIGHT, border=8)
self.__hbox.Add(self.__tc, proportion=1)
self.__vbox.Add(self.__hbox,
flag=wx.EXPAND | wx.LEFT | wx.RIGHT | wx.TOP,
border=10)
self.__btn = wx.Button(self.__panel, wx.ID_STOP, 'Done', (70, 30))
self.__vbox.Add(self.__btn, flag=wx.ALIGN_CENTRE | wx.TOP, border=30)
self.__frame.Bind(wx.EVT_BUTTON, self.__Done, id=wx.ID_STOP)
self.__panel.SetSizer(self.__vbox)
def __init__(self):
t = ImageGrab.grab().convert("RGB")
self.screen = cv2.cvtColor(numpy.array(t), cv2.COLOR_RGB2BGR)
self.ultLoader = ImageLoader('image/ult/')
if self.have('topleft'):
tl = self._imageLoader.get('topleft')
res = cv2.matchTemplate(self.screen, tl, cv2.TM_CCOEFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
x1, y1 = max_loc
rd = self._imageLoader.get('rightdown')
res = cv2.matchTemplate(self.screen, rd, cv2.TM_CCOEFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
x2, y2 = max_loc
# default 989
GameStatus().y = y2 - y1
GameStatus().use_Droid4X = True
def FRR(self,
net,
path,
device,
log_path,
batch_size=64,
do_logwrite=False):
try:
os.makedirs(log_path)
except OSError:
pass
with torch.no_grad():
transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.5, ), (0.5, )) # Normalize [-1, 1]
])
dataset = ImageLoader(path, "Real", transforms=transform)
data_loader = torch.utils.data.DataLoader(dataset,
batch_size=batch_size,
shuffle=False)
wrong = 0
for idx, (images, labels) in enumerate(data_loader):
images = images.to(device)
labels = labels.to(device)
outputs = net(images)
_, pred_y = torch.max(outputs.data, 1)
wrong += (pred_y != labels).sum().item()
metric = (wrong / len(dataset)) * 100
print_log = '%s --- pos(real) -> neg(fake) Wrong [%d/%d] FRR: %.2f%%' % (
"FRR", wrong, len(dataset), metric)
print(print_log)
if do_logwrite:
f = open('%s/%s_log.txt' % (log_path, "test_"), 'a')
f.write(print_log)
f.close()
return metric
def test_load_images_from_two_categories(self):
numberOfImages = 60
loader = ImageLoader()
loader.load_from(imageLocation, 2)
images = loader.get_images()
labels = loader.get_labels()
self.assertEqual(numberOfImages, len(images))
self.assertIs(np.ndarray, type(images))
self.assertIs(np.ndarray, type(images[0]))
np.testing.assert_array_equal(np.zeros(30), labels[:30])
np.testing.assert_array_equal(np.ones(30), labels[30:numberOfImages])
self.assertIs(np.ndarray, type(labels))
def test_load_images_from_one_category(self):
numberOfImages = 30
loader = ImageLoader()
loader.load_from(imageLocation, 1)
images = loader.get_images()
labels = loader.get_labels()
self.assertEqual(numberOfImages, len(images))
self.assertIs(np.ndarray, type(images))
self.assertIs(np.ndarray, type(images[0]))
np.testing.assert_array_equal(np.zeros(numberOfImages), labels)
self.assertIs(np.ndarray, type(labels))
def __init__(self):
self.currentProgram = 'menu' # Current main loop
WIDTH, HEIGHT = 720,406 # Output video quality
self.clock = pygame.time.Clock()
self.timerController = TimerController()
self.renderer = Renderer(WIDTH, HEIGHT)
self.imageLoader = ImageLoader()
self.soundController = SoundController('bgMusic.ogg',[('cutSpell',0.1),('lightingSpell',0.1),('explosionSpell',0.1)],0.05)
self.mouseController = MouseController()
self.menu = Menu(self.imageLoader.imageStorage['menu'],self)
self.player = Player((WIDTH, HEIGHT),self.imageLoader.imageStorage["player"],[(0,2),(2,5),(5,8),(8,11),(11,14),(14,22),(22,37)])
self.spellController = SpellController(self.mouseController,self.imageLoader.imageStorage,self.renderer, self.player,self.soundController)
self.amountBars = AmountBars(self.player, None, self.imageLoader.imageStorage['bars'],(WIDTH//2,HEIGHT//2))
self.boss = None
self.level = None
self.playerMovement = None
def main():
"main function"
# optional command line args
parser = argparse.ArgumentParser()
parser.add_argument('--train', help='train the NN', action='store_true')
parser.add_argument('--validate',
help='validate the NN',
action='store_true')
args = parser.parse_args()
# train or validate on IAM dataset
if args.train or args.validate:
# load training data, create TF model
loader = ImageLoader(FilePaths.fnTrain, Model.batchSize, Model.imgSize,
Model.maxTextLen)
# save characters of model for inference mode
open(FilePaths.fnCharList, 'w').write(str().join(loader.charList))
# save words contained in dataset into file
open(FilePaths.fnCorpus, 'w').write(
str(' ').join(loader.trainWords + loader.validationWords))
# execute training or validation
if args.train:
model = Model(loader.charList)
train(model, loader)
elif args.validate:
model = Model(loader.charList, mustRestore=True)
validate(model, loader)
# infer text on test image
else:
print(open(FilePaths.fnAccuracy).read())
model = Model(open(FilePaths.fnCharList).read(), mustRestore=True)
derive(model, FilePaths.fnDerive, contrast=False)
class PreFetcher():
class RescaleInfo:
def __init__(self):
self.rescale_path = None
self.rescale_viewport_size = None
self.rescale_matrix = None
def __init__(self, filename_image, viewportSize_imageScaled,
matrix=QtGui.QMatrix()):
# These variables are needed later to handle rescaling.
self.rescale_info = PreFetcher.RescaleInfo()
if isinstance(filename_image, QtGui.QPixmap) \
and isinstance(viewportSize_imageScaled, QtGui.QPixmap):
self.image = filename_image
self.image_scaled = viewportSize_imageScaled
self.from_loader = False
self.to_rescale = False
elif (isinstance(filename_image, QtCore.QString) or \
isinstance(filename_image, str)) \
and isinstance(viewportSize_imageScaled, QtCore.QSize):
self.loader = ImageLoader(filename_image, viewportSize_imageScaled,
matrix)
self.loader.start()
self.from_loader = True
self.to_rescale = False
else:
msg = 'Incorrect PreFetcher contructor: ' + \
str(type(filename_image)) + ', ' + \
str(type(viewportSize_imageScaled))
raise InternalException(msg)
def get_images(self):
if self.from_loader:
self.loader.join()
self.image = QtGui.QPixmap.fromImage(self.loader.image)
self.image_scaled = QtGui.QPixmap.fromImage(self.loader.image_scaled)
self.from_loader = False
if self.to_rescale:
self.image_scaled = scale_and_rotate_image(
self.image,
self.rescale_info.rescale_path,
self.rescale_info.rescale_viewport_size,
self.rescale_info.rescale_matrix)
self.to_rescale = False
return (self.image, self.image_scaled)
def get_rotated_image(self, path, matrix=QtGui.QMatrix()):
(image, _) = self.get_images()
return rotate_image(image, path, matrix)
def rescale(self, path, viewport_size, matrix=QtGui.QMatrix()):
self.to_rescale = True
self.rescale_info.rescale_path = path
self.rescale_info.rescale_viewport_size = viewport_size
self.rescale_info.rescale_matrix = matrix
def set_image(self, new_image):
if not self.from_loader:
self.image = new_image
def set_scaled_image(self, new_image):
if not self.from_loader:
self.image_scaled = new_image
import sys
from ImageLoader import ImageLoader
from ClusteringHandler import ClusteringHandler
from HTMLCreator import HTMLCreator
from ClustersPrinter import ClustersPrinter
import constants as c
if len(sys.argv) < 2:
print("Please pass a path to a file containing image paths list")
else:
paths_file = sys.argv[1]
images = ImageLoader.load_images(paths_file)
clustered_images = ClusteringHandler.cluster(images)
HTMLCreator.create_html(c.HTML_TEMPLATE,
c.HTML_OUTPUT,
clustered_images=clustered_images,
clusters_count=len(clustered_images))
ClustersPrinter.print_clusters_to_file(clustered_images, c.FILE_OUTPUT)
def __init__(self, parent=None):
super(MinesweeperGUI, self).__init__(parent)
self.benchmarking = False
self.setCentralWidget(QWidget(self))
self.setWindowTitle(" Unreal Minesweeper ")
#Menu
menubar = self.menuBar()
benchMenu = menubar.addMenu(" Benchmark ")
newGameMenu = menubar.addMenu(" Game ")
helperMenu = menubar.addMenu(" Helper ")
solverMenu = menubar.addMenu(" Solver ")
debugMenu = menubar.addMenu(" Debug ")
'''
Benchmark menu
'''
benchmarkProbasV1 = QAction(" Benchmark probabilistic algorithm v1",
self)
benchmarkProbasV1.triggered.connect(self.runBenchmarkProbasV1)
benchMenu.addAction(benchmarkProbasV1)
'''
Game menu
'''
newGameEasy = QAction(" Easy (8x8 + 10 mines) ", self)
newGameIntermediate = QAction(" Intermediate (16x16 + 40 mines) ",
self)
newGameHard = QAction(" Expert (30x16 + 99 mines) ", self)
newGameEasy.triggered.connect(lambda: self.newGame(8, 8, 10))
newGameIntermediate.triggered.connect(lambda: self.newGame(16, 16, 40))
newGameHard.triggered.connect(lambda: self.newGame(30, 16, 99))
newGameMenu.addAction(newGameEasy)
newGameMenu.addAction(newGameIntermediate)
newGameMenu.addAction(newGameHard)
'''layout.addWidget(QPushButton(" Probabilistic solver : next step"))
layout.addWidget(QPushButton(" Probabilistic solver : auto-solve"))
layout.addWidget(QPushButton(" CSP Solver : next step "))
layout.addWidget(QPushButton(" CSP Solver : auto-solve "))'''
'''
Helper menu
'''
helpers = QActionGroup(self, exclusive=True)
self.helperNone = helpers.addAction(
QAction(" No help !", self, checkable=True, checked=True))
self.helperNone.triggered.connect(self.setHelper)
helperMenu.addAction(self.helperNone)
self.helperProba = helpers.addAction(
QAction(" Probabilistic approach ", self, checkable=True))
self.helperProba.triggered.connect(self.setHelper)
helperMenu.addAction(self.helperProba)
self.helperCSP = helpers.addAction(
QAction(" CSP approach ", self, checkable=True))
self.helperCSP.triggered.connect(self.setHelper)
helperMenu.addAction(self.helperCSP)
'''
Helper menu
'''
self.verboseDisplay = QAction(" Verbose display ",
self,
checkable=True)
self.verboseDisplay.triggered.connect(self.setDebug)
debugMenu.addAction(self.verboseDisplay)
''' Solver menu '''
solverOneStep = QAction(" Solve next step ", self)
solverOneStep.triggered.connect(self.solveNextStep)
solverAllStep = QAction(" Solve all game ", self)
solverAllStep.triggered.connect(self.solveAllStep)
solverMenu.addAction(solverOneStep)
solverMenu.addAction(solverAllStep)
ImageLoader.init()
self.mainLayout = None
self.setStatus(" Ready to play ! ")
class Photomosaic:
# Variables
total_rows = 0
total_cols = 0
progress = 0
photoLog = []
cellLog = []
photos = {}
subimage = {}
# Convenience objects
ImgAnalyzer = None
ImgFinder = None
ImgLoader = None
# The input image to analyze
input = None
input_grid_width = 0
input_grid_height = 0
input_cell_width = 0
input_cell_height = 0
# The output photomosiac based on the input image
output = None
output_mag = 1
output_grid_width = 0
output_grid_height = 0
output_cell_width = 0
output_cell_height = 0
# Constructor
def __init__(self, input_PIL_img, lib_Lab_vectors, photoLog, cellLog, subimage, progress=0):
# Set instance variables
self.input = input_PIL_img
self.photoLog = photoLog # The photoLog, cellLog, and progress should probably be in it's own information expert
self.cellLog = cellLog
self.progress = int(progress)
self.ImgAnalyzer = ImageAnalyzer()
self.ImgFinder = ImageFinder(lib_Lab_vectors)
self.ImgLoader = ImageLoader()
self.subimage = subimage
# Calculate all of the closests photos in the photomosaic
def calculate_photomosaic(self, rows, cols):
# Initialize input image
self._input_dims(int(rows), int(cols))
# Find the initial coordinates
row = int(len(self.cellLog) / self.total_cols)
col = int(len(self.cellLog) % self.total_cols)
x0 = col*self.input_cell_width
y0 = row*self.input_cell_height
# Traverse the cells, and call "_process_cell" for each one of them
self._traverse_cells(self._process_cell, x0, y0)
# Create the photomosiac - currently only works with a square (rows=cols)
def create_photomosaic(self, rows, cols, mag):
# Initialize input and output images
self._input_dims(int(rows), int(cols))
self._output_dims(float(mag))
# Find the initial coordinates to start pasting cells
row = int(self.progress / self.total_cols)
col = int(self.progress % self.total_cols)
x0 = col*self.input_cell_width
y0 = row*self.input_cell_height
# Traverse the cells, and call "_paste_cell" for each one of them
self._traverse_cells(self._paste_cell, x0, y0)
# Return the ouput image as a base64 encoded string
return self.base64()
# Return the output image as a base64 encoded string
def base64(self):
file = StringIO()
self.output.save(file, "png")
return b64encode(file.getvalue())
# Traverse the cells
def _traverse_cells(self, fnc_process_cell, x0=0, y0=0):
for y in range(y0, self.input_grid_height, self.input_cell_height):
if y != y0: x0 = 0 # Only start in the middle of the grid on the first iteration
for x in range(x0, self.input_grid_width, self.input_cell_width):
fnc_process_cell(x, y)
self.progress += 1
# Analyze the input cell, find the best match, and add it to the cell log
def _process_cell(self, x0, y0):
labVec = self.ImgAnalyzer.getLABVector(self.input, x0, y0, self.input_cell_width, self.input_cell_height)
closest_photoId = self.ImgFinder.closest_match(labVec)
self.cellLog.append(closest_photoId)
# Download the image and paste it into the output image
def _paste_cell(self, x0, y0):
# Translate the x and y coordinates into a cellLog index and find the photoId
row = int(y0/self.input_cell_height)
col = int(x0/self.input_cell_width)
cellLogIndex = row*self.total_cols + col
photoId = self.cellLog[cellLogIndex]
# Get the image associated with the photo
if photoId in self.photos:
# We already have the image, so grab it from the dictionary
closest_img = self.photos[photoId]
else:
# We haven't previously downloaded the image, so get it from Facebook
closest_img = self.ImgLoader.load_url_image(self._get_url(photoId))
# Crop the image and resize it into a square
closest_img = self._crop_resize_square(closest_img)
# Add the image to the photos dictionary
self.photos[photoId] = closest_img
# Now that the image has been found, paste it into the corresponding output cell
self.output.paste( closest_img, (col*self.output_cell_width, row*self.output_cell_height) )
# Returns the URL associated with the photoId
def _get_url(self, photoId):
for log in self.photoLog:
if log["photoId"] == photoId:
return log["url"]
else: return None
# Crop the image into a square and resize it to the output cell size
def _crop_resize_square(self, im):
cols, rows = im.size
# Landscape Layout (or Square)
if cols >= rows:
target_cols = rows
left = (cols-target_cols)/2
right = left+target_cols
return im.transform( (self.output_cell_width, self.output_cell_height), Image.EXTENT, (left, 0, right, rows) )
# Portrait Layout
else:
target_rows = cols
upper = (rows-target_rows)/2
lower = upper+target_rows
return im.transform( (self.output_cell_width, self.output_cell_height), Image.EXTENT, (0, upper, cols, lower) )
# Defines input dimensions
def _input_dims(self, rows, cols):
# Since number of columns is the width and number of rows is height
self.input_grid_width = self.subimage["w"]
self.input_grid_height = self.subimage["h"]
self.total_rows = int(rows)
self.total_cols = int(cols)
self.input_grid_width -= self.input_grid_width % self.total_cols
self.input_grid_height -= self.input_grid_height % self.total_rows
self.input_cell_width = self.input_grid_width / self.total_cols
self.input_cell_height = self.input_grid_height / self.total_rows
# Crop Image
self.input = self.input.crop( (self.subimage["x"], self.subimage["y"], self.subimage["x"]+self.input_cell_width*self.total_cols, self.subimage["y"]+self.input_cell_height*self.total_rows) )
# Defines output dimensions and creates output image
def _output_dims(self, mag):
# Set dimensions
self.output_mag = float(mag)
self.output_grid_width = int(self.input_grid_width * self.output_mag)
self.output_grid_height = int(self.input_grid_height * self.output_mag)
self.output_grid_width -= self.output_grid_width % self.total_cols
self.output_grid_height -= self.output_grid_height % self.total_rows
self.output_cell_width = self.output_grid_width / self.total_cols
self.output_cell_height = self.output_grid_height / self.total_rows
# Create output image
self.output = Image.new("RGB", (self.output_grid_width, self.output_grid_height), "red")
class Screen(metaclass=Singleton):
_delay = 0.3
_imageLoader = ImageLoader('image/')
_skills = ImageLoader('image/skills/')
target = ImageLoader('./', need_scale=False)
@staticmethod
def log(text):
GameStatus().window.add_text(text)
def __init__(self):
t = ImageGrab.grab().convert("RGB")
self.screen = cv2.cvtColor(numpy.array(t), cv2.COLOR_RGB2BGR)
self.ultLoader = ImageLoader('image/ult/')
if self.have('topleft'):
tl = self._imageLoader.get('topleft')
res = cv2.matchTemplate(self.screen, tl, cv2.TM_CCOEFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
x1, y1 = max_loc
rd = self._imageLoader.get('rightdown')
res = cv2.matchTemplate(self.screen, rd, cv2.TM_CCOEFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
x2, y2 = max_loc
# default 989
GameStatus().y = y2 - y1
GameStatus().use_Droid4X = True
def get_cards(self):
self.capture()
GameStatus().cards = []
GameStatus().cards += self.find_list('buster')
GameStatus().cards += self.find_list('art')
GameStatus().cards += self.find_list('quick')
def get_current_level(self):
c33 = self.chances_of('3_3')
c23 = self.chances_of('2_3')
c31 = self.chances_of('1_3')
if c33 > max(c23, c31):
self.log('3-3')
return 3
elif c23 > max(c33, c31):
self.log('2-3')
return 2
else:
self.log('1-3')
return 1
def find_list(self, name):
cards = []
res = cv2.matchTemplate(self.screen, self._imageLoader.get(name),
cv2.TM_CCOEFF_NORMED)
threshold = 0.8
loc = numpy.where(res >= threshold)
x = 0
t = sorted(zip(*loc[::-1]))
for pt in t:
if abs(x - pt[0]) > 100 or x == 0:
x = pt[0]
cards.append((pt[0], pt[1]))
else:
continue
self.log(name + ': ' + str(len(cards)))
return cards
def set_delay(self, delay):
self._delay = delay
def capture(self):
t = ImageGrab.grab().convert("RGB")
self.screen = cv2.cvtColor(numpy.array(t), cv2.COLOR_RGB2BGR)
@staticmethod
def _click(x, y):
handle = win32gui.GetForegroundWindow()
x_old, y_old = win32api.GetCursorPos()
# see https://github.com/asweigart/pyautogui/issues/23
try:
pyautogui.click(x, y, 1)
except FileNotFoundError:
pass
win32api.SetCursorPos((x_old, y_old))
win32gui.SetForegroundWindow(handle)
def click_on(self, name, repeat=False, loader=_imageLoader):
if GameStatus().game_stage == GameStage.Stopped:
return
self.log('try click ' + name)
p = loader.get(name)
max_val = 0
x, y = 0, 0
while max_val < 0.8:
if GameStatus().game_stage == GameStage.Stopped:
return
self.capture()
res = cv2.matchTemplate(self.screen, p, cv2.TM_CCOEFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
self.log(name + ' ' + str(max_val))
x, y = max_loc
time.sleep(self._delay)
m, n, q = p.shape
x += n / 2
y += m / 2
self._click(x, y)
max_val = 1 if repeat else 0
while max_val > 0.8:
if GameStatus().game_stage == GameStage.Stopped:
return
time.sleep(1)
self.capture()
res = cv2.matchTemplate(self.screen, p, cv2.TM_CCOEFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
if max_val > 0.8:
self._click(x, y)
def have(self, name, loader=_imageLoader):
return self.chances_of(name, loader) > 0.8
def chances_of(self, name, loader=_imageLoader):
self.capture()
p = loader.get(name)
res = cv2.matchTemplate(self.screen, p, cv2.TM_CCOEFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
self.log('chances of ' + name + ': ' + str(max_val))
return max_val
T_B_GRAPH_PATH = './graph/' + args.save_model + NOWTIME
BATCH_SIZE = args.batchsize
LEARNING_RATE = 0.0001
NUM_EPOCHS = args.maxepoch
is_write_sub_log = False
transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.5, ), (0.5, )) # Normalize [-1, 1]
])
# train data set: image 1 x 57 x 116
train_dataset = ImageLoader(TRAIN_DATASET_PATH, transforms=transform)
# data loader: batch_size x 1 x 57 x 116
train_loader = torch.utils.data.DataLoader(train_dataset,
batch_size=BATCH_SIZE,
shuffle=True)
# data set: image 1 x 57 x 116
test_dataset = ImageLoader(TEST_DATASET_PATH, transforms=transform)
# data loader: batch_size x 1 x 57 x 116
test_loader = torch.utils.data.DataLoader(test_dataset,
batch_size=BATCH_SIZE,
shuffle=False)
# Network
if args.model == "Ann":
net = Ann(node=args.node, num_classes=2).to(device) # Real or Fake
class Game:
"""This class is main Game class.
"""
def __init__(self):
"""__init__ method for Game class.
"""
# initialise game window, settings etc.
pygame.mixer.pre_init(44100, -16, 2, 2048)
pygame.mixer.init()
pygame.init()
pygame.mouse.set_visible(False)
pygame.key.set_repeat(10, cfg.KEY_DELAY)
self.actual_screen = pygame.display.set_mode(
(cfg.S_WIDTH, cfg.S_HEIGHT))
#self.actual_screen = pygame.display.set_mode((cfg.S_WIDTH, cfg.S_HEIGHT), pygame.FULLSCREEN)
self.screen = pygame.Surface((cfg.WIDTH, cfg.HEIGHT))
self.clock = pygame.time.Clock()
self.running = True
self.loaded = False
self.dircheck = None
# booleans for drawing the hit rects and other debug stuff
self.debug = False
self.draw_vectors = False
self.show_player_stats = False
self.caption = ''
self.key_down = None
self.state = 'GAME'
self.in_transition = False
self.loadAssets()
self.clearcount = 0
self.check = True
self.timer = 0
self.levelcleared = 1
self.pistolpick = True
self.machinegunpick = False
self.lastweapon = 'MachineGun'
self.spritecheck = []
def keyDown(self, events, game):
"""Game class method for checking keys presses.
Args:
events (<Event>): key press events.
game (Integrate.Game): Integrate.Game class object.
"""
for event in events:
if event.type == pygame.KEYUP:
if event.key == cfg.KEY_RIGHT:
game.player.RightCheck = False
if event.key == cfg.KEY_UP:
game.player.UpCheck = False
if event.key == cfg.KEY_LEFT:
game.player.LeftCheck = False
if event.key == cfg.KEY_DOWN:
game.player.DownCheck = False
def transitRoom(self, game, dungeon, offset=pygame.math.Vector2(0, 0)):
"""Game class method for room transition.
Args:
game (Integrate.Game): Integrate.Game class object.
dungeon (Dungeon.Dungeon): Dungeon.Dungeon object
"""
# get the index of the next and the previous room
index_next = dungeon.current_room_index
index_prev = game.prev_room
# select the rooms based on the indices
room_prev = dungeon.room_matrix[index_prev[0]][index_prev[1]]
room_next = dungeon.room_matrix[index_next[0]][index_next[1]]
# remove all sprite from the previous room
room_prev.object_data = []
for sprite in game.all_sprites:
if sprite != game.player and sprite not in game.item_drops:
if hasattr(sprite, 'data'):
room_prev.object_data.append(sprite.data)
sprite.kill()
if room_next.visited == False:
# if room not visited, get the object data from the initial layout
data = room_next.layout
for d in data:
try:
if offset == (0, 0):
self.create(game, d)
else:
self.create(game, d, offset)
except Exception:
traceback.print_exc()
pass
room_next.visited = True
else:
# if room already visited, get the objects from the stored data
data = room_next.object_data
for d in data:
try:
if offset == (0, 0):
self.create(game, d)
else:
self.create(game, d, offset)
except Exception:
traceback.print_exc()
pass
# set the dungeon's current room based on room index
dungeon.room_current = dungeon.room_matrix[
dungeon.current_room_index[0]][dungeon.current_room_index[1]]
def create(self, game, data, offset=pygame.math.Vector2(0,
cfg.GUI_HEIGHT)):
"""Game class method for room transition.
Args:
game (Integrate.Game): Integrate.Game class object.
data (dict{'id', 'name', 'x', 'y', 'width', 'height'}): objects data
"""
# takes a dictionary of sprite properties
name = data['name']
# capitalizing first letter
name_1 = name[0].capitalize()
name_2 = name[1:]
name = name_1 + name_2
#instantiate the sprite
spr = module_dict[name](game,
(data['x'] + offset.x, data['y'] + offset.y),
(data['width'], data['height']))
for key, value in data.items():
try:
setattr(spr, key, value)
except:
print('cant set value of {0} for {1}'.format(key, spr))
if hasattr(spr, 'on_create'):
# do initialisation stuff after ___init__()
spr.on_create()
spr.data = data
def loadAssets(self):
"""Game class method to load all assets.
"""
#loading assets (images, sounds)
self.imageLoader = ImageLoader(self)
self.soundLoader = snd.Sound()
try:
self.imageLoader.load_assets()
self.soundLoader.load()
except Exception:
traceback.print_exc()
self.running = False
def new(self):
"""Game class method to start a new game.
"""
# start a new game
# initialise sprite groups
self.all_sprites = pygame.sprite.LayeredUpdates()
self.walls = pygame.sprite.LayeredUpdates()
self.gui = pygame.sprite.LayeredUpdates()
self.enemies = pygame.sprite.LayeredUpdates()
self.item_drops = pygame.sprite.LayeredUpdates()
# instantiate dungeon
self.dungeon = Dungeon(self, cfg.DUNGEON_SIZE)
if self.loaded:
self.dungeon.tileset = self.saveGame.data['tileset']
else:
self.dungeon.create()
self.WSign = self.imageLoader.WarnSign
self.WSign2 = self.imageLoader.WarnSign2
self.inventory = Inventory(self)
# spawn the player in the middle of the room
self.player = Player(self, (cfg.WIDTH // 2, cfg.TILESIZE * 12))
self.currentpistol = Pistol(self, self.player)
self.currentmachine = MachineGun(self, self.player)
if self.pistolpick == True:
self.player.itemA = self.currentpistol
elif self.machinegunpick == True:
self.player.itemA = self.currentmachine
# load settings
if self.loaded:
self.loadSavefile()
# spawn the new objects (invisible)
self.prev_room = self.dungeon.current_room_index
self.transitRoom(self, self.dungeon)
# create a background image from the tileset for the current room
self.background = self.tileRoom(self, self.imageLoader.tileset,
self.dungeon.current_room_index)
self.run()
def checkFight(self, game):
"""Game class method to check distance from door and closes the doors
and opens them when player defeats all enemies in the room
"""
room = game.dungeon.room_current
if len(game.enemies) > 0:
room.cleared = False
else:
if not room.is_doors_shut:
room.cleared = True
return
# check if the room's doors are closed
if room.is_doors_shut == False:
# check player's position
margin_x = 5 * cfg.TILESIZE_SMALL
margin_y = 5.5 * cfg.TILESIZE_SMALL + cfg.GUI_HEIGHT
rect = pygame.Rect((margin_x, margin_y),
(cfg.WIDTH - 2 * margin_x,
cfg.HEIGHT - cfg.GUI_HEIGHT - margin_y))
if rect.colliderect(game.player.hit_rect):
# player is far enough in the room to shut the doors
room.shut_doors()
game.soundLoader.get['roomLocked'].play()
else:
if len(game.enemies) == 0:
# if all enemies are defeated, open the doors
room.open_doors()
game.soundLoader.get['roomCleared'].play()
room.cleared = True
def get_inputs(self, game):
"""Game class method to load all assets store keyboard inputs in a key map
"""
game.keys = {
'A': False,
'B': False,
'X': False,
'Y': False,
'L': False,
'BACK': False,
'START': False,
'STICK_L_PRESSED': False,
'STICK_R_PRESSED': False,
'STICK_R': pygame.math.Vector2(0, 0),
'STICK_L': pygame.math.Vector2(0, 0),
'DPAD': pygame.math.Vector2(0, 0),
'DPAD_MENU': pygame.math.Vector2(0, 0)
}
key = game.keys
# get keyboard keys
get_keys = pygame.key.get_pressed()
if get_keys[cfg.KEY_RIGHT]:
game.player.RightCheck = True
elif get_keys[cfg.KEY_LEFT]:
game.player.LeftCheck = True
if get_keys[cfg.KEY_DOWN]:
game.player.DownCheck = True
elif get_keys[cfg.KEY_UP]:
game.player.UpCheck = True
get_mkeys = pygame.mouse.get_pressed()
key['A'] = get_mkeys == cfg.KEY_A or key['A']
key['B'] = game.key_down == cfg.KEY_B or key['B']
key['X'] = game.key_down == cfg.KEY_ENTER or key['X']
key['START'] = get_keys[cfg.KEY_MENU]
def run(self):
"""Game class method to start running infinite loop until quit.
"""
# game loop
self.playing = True
while self.playing:
#reset game screen
self.screen = pygame.Surface((cfg.WIDTH, cfg.HEIGHT))
self.dt = self.clock.tick(cfg.FPS) / 1000
self.events()
self.get_inputs(self)
self.update()
self.draw()
def events(self):
"""Game class method to loop game events.
"""
# game loop events
self.event_list = pygame.event.get()
for event in self.event_list:
if event.type == pygame.QUIT:
if self.playing:
self.playing = False
self.running = False
pygame.quit()
quit()
if event.type == pygame.KEYDOWN:
# Key events
if event.key == pygame.K_r and self.debug:
self.loaded = False
self.new()
if event.key == pygame.K_h:
self.debug = not self.debug
if event.key == pygame.K_k and self.debug:
# kill all enemies
for e in self.enemies:
e.hp = 0
def screenWrap(self, player, dungeon):
"""Game class method to check if the player goes outside the screen
if they do, set their new position based on where they went
"""
index = list(dungeon.current_room_index)
direction = ''
new_pos = pygame.math.Vector2(player.hit_rect.center)
if player.hit_rect.left < cfg.TILESIZE:
direction = (-1, 0)
player.vel = pygame.math.Vector2(0, 0)
new_pos.x = cfg.WIDTH - player.hit_rect.width - cfg.TILESIZE
index[1] -= 1
elif player.hit_rect.right > cfg.WIDTH - cfg.TILESIZE:
player.vel = pygame.math.Vector2(0, 0)
direction = (1, 0)
new_pos.x = player.hit_rect.width + cfg.TILESIZE
index[1] += 1
elif player.hit_rect.top < cfg.GUI_HEIGHT + cfg.TILESIZE:
player.vel = pygame.math.Vector2(0, 0)
direction = (0, -1)
new_pos.y = cfg.HEIGHT - player.hit_rect.height - cfg.TILESIZE
index[0] -= 1
elif player.hit_rect.bottom > cfg.HEIGHT - cfg.TILESIZE:
player.vel = pygame.math.Vector2(0, 0)
direction = (0, 1)
new_pos.y = player.hit_rect.height + cfg.GUI_HEIGHT + cfg.TILESIZE
index[0] += 1
try:
return direction, index, new_pos
except Exception:
traceback.print_exc()
def update(self):
"""Game class method update game situation.
"""
if self.pistolpick == True:
self.player.itemA = self.currentpistol
elif self.machinegunpick == True:
self.player.itemA = self.currentmachine
if self.debug:
self.caption = (str(round(self.clock.get_fps(), 2)))
else:
self.caption = cfg.TITLE
pygame.display.set_caption(self.caption)
# check for key presses
self.key_down = self.keyDown(self.event_list, self)
if self.state == 'GAME':
pygame.mouse.set_visible(False)
self.all_sprites.update()
self.inventory.update()
# check for room transitions on screen exit (every frame)
self.direction, self.new_room, self.new_pos = self.screenWrap(
self.player, self.dungeon)
if self.direction == UP:
self.dircheck = UP
elif self.direction == DOWN:
self.dircheck = DOWN
elif self.direction == LEFT:
self.dircheck = LEFT
elif self.direction == RIGHT:
self.dircheck = RIGHT
if self.new_room != self.dungeon.current_room_index:
self.prev_room = self.dungeon.current_room_index
self.dungeon.current_room_index = self.new_room
self.state = 'TRANSITION'
# When in a fight, shut the doors:
if not self.dungeon.room_current.cleared:
self.checkFight(self)
if self.check:
if self.dungeon.room_current.cleared:
a = self.clearcount
self.clearcount = self.clearcount + 1
self.spritecheck = []
if a + 1 == self.clearcount:
self.check = False
elif self.state == 'MENU' or self.state == 'MENU_TRANSITION':
pygame.mouse.set_visible(True)
self.inventory.update()
elif self.state == 'TRANSITION':
#self.RoomTransition(self.new_pos, self.direction)
# ^this went into draw()
pass
elif self.state == 'CUTSCENE':
self.walls.update()
def WinSit(self):
"""Game class method to check if player won then show next screen.
"""
global Dx, Dy
if self.dungeon.room_current.type == "endboss" and self.dungeon.room_current.cleared:
pygame.mouse.set_visible(True)
self.state = 'WIN'
self.actual_screen.blit(self.imageLoader.WinImg, (0, 0))
self.Quitbtn = Button(400, 450, 150, 50, 'Quit', (200, 20, 20, 0),
(180, 0, 0, 0), self.imageLoader.font1,
self.imageLoader.font2)
self.Nextbtn = Button(200, 450, 150, 50, 'Next', (200, 20, 20, 0),
(180, 0, 0, 0), self.imageLoader.font1,
self.imageLoader.font2)
self.Quitbtn.show(self.imageLoader.WinImg)
self.Nextbtn.show(self.imageLoader.WinImg)
if self.Quitbtn.is_mouse_clicked():
pygame.quit()
quit()
if self.Nextbtn.is_mouse_clicked():
self.levelcleared += 1
self.clearcount = 0
self.check = True
cfg.DUNGEON_SIZE = (Dx, Dy)
self.state = 'GAME'
self.new()
Dx = Dx + 1
Dy = Dy + 1
def GameOverr(self):
"""Game class method to check if player is dead and game is over.
"""
global Dx, Dy
if self.player.Dead == True:
self.state = 'GAME OVER'
pygame.mouse.set_visible(True)
self.actual_screen.blit(self.imageLoader.GameOverImg, (0, 0))
self.Quitbtn = Button(400, 450, 150, 50, 'Quit', (200, 20, 20, 0),
(180, 0, 0, 0), self.imageLoader.font1,
self.imageLoader.font2)
self.Nextbtn = Button(200, 450, 150, 50, 'Restart',
(200, 20, 20, 0), (180, 0, 0, 0),
self.imageLoader.font1,
self.imageLoader.font2)
self.Quitbtn.show(self.imageLoader.GameOverImg)
self.Nextbtn.show(self.imageLoader.GameOverImg)
if self.Quitbtn.is_mouse_clicked():
pygame.quit()
quit()
if self.Nextbtn.is_mouse_clicked():
self.levelcleared = 1
self.clearcount = 0
Dx = 5
Dy = 5
self.pistolpick = True
self.machinegunpick = False
self.check = True
cfg.DUNGEON_SIZE = (Dx, Dy)
self.state = 'GAME'
self.new()
def draw(self):
"""Game class method to draw
"""
if self.state != 'TRANSITION':
# draw the background (tilemap)
self.screen.blit(self.background, (0, cfg.GUI_HEIGHT))
# call additional draw methods (before drawing)
for sprite in self.all_sprites:
if hasattr(sprite, 'draw_before'):
sprite.draw_before()
# draw the sprites
self.all_sprites.draw(self.screen)
for sprite in self.all_sprites:
if hasattr(sprite, 'draw_after'):
sprite.draw_after()
# for machine gun with player
if self.machinegunpick and self.player.itemA == self.currentmachine:
if self.player.itemA.check and self.player.mana < 9.8:
self.WSignRect = self.WSign.get_rect()
self.WSignRect.center = pygame.mouse.get_pos(
) - pygame.math.Vector2(0, 30)
self.screen.blit(self.WSign, self.WSignRect)
if self.player.itemA.check and self.player.mana > 9.8:
self.WSignRect = self.WSign2.get_rect()
self.WSignRect.center = pygame.mouse.get_pos(
) - pygame.math.Vector2(0, 30)
self.screen.blit(self.WSign2, self.WSignRect)
if self.player.mana < 0.2:
self.cursor = self.imageLoader.CursorMain1
elif self.player.mana < 1.4:
self.cursor = self.imageLoader.cursor[0]
elif self.player.mana < 2.8:
self.cursor = self.imageLoader.cursor[1]
elif self.player.mana < 4.2:
self.cursor = self.imageLoader.cursor[2]
elif self.player.mana < 5.6:
self.cursor = self.imageLoader.cursor[3]
elif self.player.mana < 7:
self.cursor = self.imageLoader.cursor[4]
elif self.player.mana < 8.4:
self.cursor = self.imageLoader.cursor[5]
elif self.player.mana < 9.8:
self.cursor = self.imageLoader.cursor[6]
elif self.player.mana < 11.4:
self.cursor = self.imageLoader.cursor[7]
self.cursorrect = self.cursor.get_rect()
self.cursorrect.center = pygame.mouse.get_pos()
self.screen.blit(self.cursor, self.cursorrect)
else:
self.cursor = self.imageLoader.CursorMain1
self.cursorrect = self.cursor.get_rect()
self.cursorrect.center = pygame.mouse.get_pos()
self.screen.blit(self.cursor, self.cursorrect)
else:
self.RoomTransition(self.new_pos, self.direction)
if not self.dungeon.room_current.cleared:
self.check = True
# ----- DEBUG STUFF ----- #
# draw hitboxes in debug mode
if self.debug:
for sprite in self.all_sprites:
if hasattr(sprite, 'hit_rect'):
pygame.draw.rect(self.screen, cfg.CYAN, sprite.hit_rect, 1)
if hasattr(sprite, 'interact_rect'):
pygame.draw.rect(self.screen, cfg.GREEN,
sprite.interact_rect, 1)
# draw the inventory
self.drawGUI()
self.screen = pygame.transform.scale(self.screen,
(cfg.S_WIDTH, cfg.S_HEIGHT))
self.actual_screen.blit(self.screen, (0, 0))
self.WinSit()
self.GameOverr()
pygame.display.update()
def drawGUI(self):
"""Game class method draw inventory with map.
"""
self.inventory.map_img = self.dungeon.render_rooms_map()
self.inventory.draw()
def tileRoom(self, game, tileset, index):
"""Game class method render room tiles.
"""
image = pygame.Surface((cfg.WIDTH, cfg.HEIGHT - cfg.GUI_HEIGHT))
data = game.dungeon.room_matrix[index[0]][index[1]].tiles
for i in range(len(data)):
for j in range(len(data[i])):
x = j * cfg.TILESIZE
y = i * cfg.TILESIZE
try:
image.blit(tileset[data[i][j]], (x, y))
except Exception:
traceback.print_exc()
return
return image
def RoomTransition(self, new_pos, direction):
"""Game class method for room transition.
Args:
new_pos (tuple): tuple with x,y corrdinates for the new room for player
direction (Up, DOWN, LEFT OR RIGHT): direction of start in new room
"""
if not self.in_transition:
# store the old background image temporarily
self.old_background = self.background
# blit the background and sprites to prevent flickering
self.screen.blit(self.old_background, (0, cfg.GUI_HEIGHT))
self.all_sprites.draw(self.screen)
# build the new room
self.background = self.tileRoom(self, self.imageLoader.tileset,
self.dungeon.current_room_index)
# scroll the new and old background
# start positions for the new bg are based on the direction the
# player is moving
start_positions = {
UP: pygame.math.Vector2(0, -(cfg.HEIGHT - cfg.GUI_HEIGHT * 2)),
DOWN: pygame.math.Vector2(0, cfg.HEIGHT),
LEFT: pygame.math.Vector2(-cfg.WIDTH, cfg.GUI_HEIGHT),
RIGHT: pygame.math.Vector2(cfg.WIDTH, cfg.GUI_HEIGHT)
}
self.bg_pos1 = start_positions[direction]
# pos2 is the old bg's position that gets pushed out of the screen
self.bg_pos2 = pygame.math.Vector2(0, cfg.GUI_HEIGHT)
self.in_transition = True
self.transitRoom(self, self.dungeon, self.bg_pos1)
else:
if self.bg_pos1 != (0, cfg.GUI_HEIGHT):
# moves the 2 room backrounds until the new background is at (0,0)
# PROBLEM: Only works with certain scroll speeds!
# calculate the move vector based on the direction
move = (pygame.math.Vector2(0, 0) -
direction) * cfg.SCROLLSPEED
# move the background surfaces
self.bg_pos1 += move
self.bg_pos2 += move
if direction == UP:
self.bg_pos1.y = min(cfg.GUI_HEIGHT, self.bg_pos1.y)
elif direction == DOWN:
self.bg_pos1.y = max(cfg.GUI_HEIGHT, self.bg_pos1.y)
elif direction == LEFT:
self.bg_pos1.x = min(0, self.bg_pos1.x)
elif direction == RIGHT:
self.bg_pos1.x = max(0, self.bg_pos1.x)
# move the sprites during transition
for sprite in self.all_sprites:
sprite.rect.topleft += move
sprite.hit_rect.topleft += move
sprite.pos += move
self.screen.blit(self.old_background, self.bg_pos2)
self.screen.blit(self.background, self.bg_pos1)
self.all_sprites.draw(self.screen)
else:
# update the player's position
self.player.pos = pygame.math.Vector2(new_pos)
self.player.hit_rect.center = pygame.math.Vector2(new_pos)
self.player.spawn_pos = pygame.math.Vector2(new_pos)
self.player.rect.bottom = self.player.hit_rect.bottom
# end transtition
self.in_transition = False
self.state = 'GAME'
# blit the background and sprites to prevent flickering
self.screen.blit(self.background, (0, cfg.GUI_HEIGHT))
self.all_sprites.draw(self.screen)
def write_to_file(self, filename):
""" Salva os dados em um arquivo usando o loader strategy designado """
loader = ImageLoader()
loader.write(self, filename)
