image = numpy.expand_dims(image, axis=0)
image = image.astype('float32')
image /= 255
return image
finalImageSize = (1024, 768) # Size of the final image generated by the demo
categoricalInitialPosition = 260 # Initial position for adding the categorical graph in the final image
faceSize = (64, 64) # Input size for both models: categorical and dimensional
faceDetectionMaximumFrequency = 20 # Frequency that a face will be detected: every X frames.
modelDimensional = modelLoader.modelLoader(
"/home/pablo/Documents/Workspace/EmotionsWithMasks/trainedModels/FaceChannel_Dimensional.h5"
)
saveNetwork = "/home/pablo/Documents/Workspace/EmotionsWithMasks/trainedModels/"
trainDataSet = "/home/pablo/Documents/Datasets/AffectNet_Mask/Training" #AffectNet-Mask
# trainDataSet = "/home/pablo/Documents/Datasets/AffectNet/AffectNetProcessed_Training" #AffectNet
images = []
amount = 0
labels = []
arousals = []
valences = []
print("Loading Images")
def __init__(self):
base.disableMouse()
base.camLens.setFar(100)
self.parserClass = Parser.Parser() # Making the required instances
self.mapLoaderClass = mapLoader.mapLoader(self)
self.gameObjects = {}
self.gameObjectID = 0
self.mapX = self.mapLoaderClass.mapConfigParser.getint(
"map", "width") - 1 # Name says it all really
self.mapY = self.mapLoaderClass.mapConfigParser.getint(
"map", "height") - 1
self.modelLoaderClass = modelLoader.modelLoader(self)
self.cameraClass = stratCam.CameraHandler(self)
self.mouseClass = stratCam.mouseHandler(self)
self.GUI = stratCam.GUI(self)
# self.GUI = stratCam.GUI(self)
self.priorities = priorities.priorities()
base.setFrameRateMeter(True)
###############
base.cTrav2 = CollisionTraverser('world2')
# base.cTrav2.showCollisions(render)
self.heightRay = CollisionRay(
) # A collision ray, used for getting the height of the terrain
self.heightRay.setOrigin(0, 0, 100)
self.heightRay.setDirection(0, 0, -1)
self.heightCol = CollisionNode('unit Ray')
self.heightCol.addSolid(self.heightRay)
self.heightCol.setTag('units', 'ray1')
self.heightCol.setFromCollideMask(BitMask32.bit(0))
# self.heightCol.setIntoCollideMask(BitMask32.allOff())
self.heightColNp = render.attachNewNode(self.heightCol)
self.heightColNp.setPos(2, 2, 0)
self.heightHandler = CollisionHandlerQueue()
base.cTrav2.addCollider(self.heightColNp, self.heightHandler)
###############
# myFrame = DirectFrame(frameColor=(0, 0, 0, 1),
# frameSize=(-0.25, 0.25, -1, 1),
# pos=(1.08, 0, 0))
# button = DirectButton(text = ("button"), scale = 0.1)
# button.reparentTo(myFrame)
# button.setPos(0, 0, 0.9)
self.grids = astar.grid(self)
self.unitHandler = unitHandler.world(self)
# self.unitHandler.addUnit(0, (10,10,5), self)
# self.unitHandler.addUnit(1, (6,10,5), self)
# self.unitHandler.moveTo(self, (6, 34), 0)
# self.unitHandler.moveTo(self, (34, 30), 1)
self.buildingHandler = buildingHandler.buildingHandler(self)
self.tileSelected = (0, 0)
taskMgr.add(self.tskCheckWalls, "Wall checking")
taskMgr.add(self.priorities.jobTask, "Jobs", extraArgs=[self])
self.loadLight()
self.accept("escape", sys.exit)
self.accept("1", self.unitHandler.addUnit2, extraArgs=[0, self])
self.accept("2", self.unitHandler.addUnit2, extraArgs=[1, self])
self.accept("3", self.unitHandler.addUnit2, extraArgs=[2, self])
self.accept("enter",
self.buildingHandler.addBuilding2,
extraArgs=[self, 0])
self.accept("p", self.priorities.addJob)
print 'END OF GAMEMAIN.PY!'
import numpy
import cv2
import modelLoader
import modelDictionary
import imageProcessingUtil
import GUIController
import numpy
import sys
finalImageSize = (1024, 768) # Size of the final image generated by the demo
categoricalInitialPosition = 260 # Initial position for adding the categorical graph in the final image
faceSize = (64, 64) # Input size for both models: categorical and dimensional
faceDetectionMaximumFrequency = 10 # Frequency that a face will be detected: every X frames.
modelCategorical = modelLoader.modelLoader(modelDictionary.CategoricaModel)
modelDimensional = modelLoader.modelLoader(modelDictionary.DimensionalModel)
imageProcessing = imageProcessingUtil.imageProcessingUtil(
faceDetectionMaximumFrequency)
GUIController = GUIController.GUIController()
cv2.namedWindow("Visual Emotion Recognition")
cap = cv2.VideoCapture(0)
#cap.open(0)
if cap.isOpened(): # try to get the first frame
rval, f = cap.read()
# rval2, f2 = vc2.read()
import Parser
import mapLoader
import modelLoader
import gameMain
import stratCam
import fpsTest
#import something4
parserClass = Parser.Parser()
mapLoaderClass = mapLoader.mapLoader(parserClass)
modelLoaderClass = modelLoader.modelLoader(parserClass, mapLoaderClass)#, mapLoaderClass.mapConfigParser.get("map", "width"))
gameMain = gameMain.world(parserClass, mapLoaderClass, modelLoaderClass)
stratCam.CameraHandler(parserClass, mapLoaderClass, modelLoaderClass, gameMain,
modelLoaderClass.mapX, modelLoaderClass.mapY,
parserClass.userConfig.getfloat("control", "scrollborder"),
parserClass.userConfig.getfloat("control", "zoominspeed"),
parserClass.userConfig.getfloat("control", "zoomoutspeed"),
parserClass.userConfig.getfloat("control", "zoommax"),
parserClass.userConfig.getfloat("control", "zoommin"))
#f = fpsTest.thirdPerson(parserClass, gameMain, mapLoaderClass, modelLoaderClass)
#s = something4.grid(mapLoaderClass)
#s1 = something4.aStar(s.landMesh, mapLoaderClass)
#s1.moveTo((14,30))
run()
image = numpy.expand_dims(image, axis=0)
image = image.astype('float32')
image /= 255
return image
finalImageSize = (1024,768) # Size of the final image generated by the demo
categoricalInitialPosition = 260 # Initial position for adding the categorical graph in the final image
faceSize = (64,64) # Input size for both models: categorical and dimensional
faceDetectionMaximumFrequency = 20 # Frequency that a face will be detected: every X frames.
modelDimensional = modelLoader.modelLoader("/home/pablo/Documents/Workspace/EmotionsWithMasks/trainedModels/FaceChannelMask_250k_scratch.h5") #MASK 10k
saveOriginal = "/home/pablo/Documents/Datasets/AffectNet_Mask/originalExample"
# validationDataSet = "/home/pablo/Documents/Datasets/AffectNet/AffectNetProcessed_Validation" #AffectNet
validationDataSet = "/home/pablo/Documents/Datasets/AffectNet_Mask/Validation" #AffectNet-Mask
images = []
amount = 0
labels = []
arousals = []
valences = []
print ("Loading Images")
for imgFile in os.listdir(validationDataSet):
img = preProcess(cv2.imread(validationDataSet+"/"+imgFile))
def __init__(self):
base.disableMouse()
base.camLens.setFar(100)
self.parserClass = Parser.Parser() # Making the required instances
self.mapLoaderClass = mapLoader.mapLoader(self)
self.gameObjects = {}
self.gameObjectID = 0
self.mapX = self.mapLoaderClass.mapConfigParser.getint("map", "width") - 1 # Name says it all really
self.mapY = self.mapLoaderClass.mapConfigParser.getint("map", "height") - 1
self.modelLoaderClass = modelLoader.modelLoader(self)
self.cameraClass = stratCam.CameraHandler(self)
self.mouseClass = stratCam.mouseHandler(self)
self.GUI = stratCam.GUI(self)
# self.GUI = stratCam.GUI(self)
self.priorities = priorities.priorities()
base.setFrameRateMeter(True)
###############
base.cTrav2 = CollisionTraverser('world2')
# base.cTrav2.showCollisions(render)
self.heightRay = CollisionRay() # A collision ray, used for getting the height of the terrain
self.heightRay.setOrigin(0,0,100)
self.heightRay.setDirection(0,0,-1)
self.heightCol = CollisionNode('unit Ray')
self.heightCol.addSolid(self.heightRay)
self.heightCol.setTag('units','ray1')
self.heightCol.setFromCollideMask(BitMask32.bit(0))
# self.heightCol.setIntoCollideMask(BitMask32.allOff())
self.heightColNp = render.attachNewNode(self.heightCol)
self.heightColNp.setPos(2,2,0)
self.heightHandler = CollisionHandlerQueue()
base.cTrav2.addCollider(self.heightColNp, self.heightHandler)
###############
# myFrame = DirectFrame(frameColor=(0, 0, 0, 1),
# frameSize=(-0.25, 0.25, -1, 1),
# pos=(1.08, 0, 0))
# button = DirectButton(text = ("button"), scale = 0.1)
# button.reparentTo(myFrame)
# button.setPos(0, 0, 0.9)
self.grids = astar.grid(self)
self.unitHandler = unitHandler.world(self)
# self.unitHandler.addUnit(0, (10,10,5), self)
# self.unitHandler.addUnit(1, (6,10,5), self)
# self.unitHandler.moveTo(self, (6, 34), 0)
# self.unitHandler.moveTo(self, (34, 30), 1)
self.buildingHandler = buildingHandler.buildingHandler(self)
self.tileSelected = (0,0)
taskMgr.add(self.tskCheckWalls, "Wall checking")
taskMgr.add(self.priorities.jobTask, "Jobs", extraArgs = [self])
self.loadLight()
self.accept("escape", sys.exit)
self.accept("1", self.unitHandler.addUnit2, extraArgs = [0, self])
self.accept("2", self.unitHandler.addUnit2, extraArgs = [1, self])
self.accept("3", self.unitHandler.addUnit2, extraArgs = [2, self])
self.accept("enter", self.buildingHandler.addBuilding2, extraArgs = [self, 0])
self.accept("p", self.priorities.addJob)
print 'END OF GAMEMAIN.PY!'
