def get_true_values(self):
true_values = []
in_front = peak.isWallInFront(self.state['x'], self.state['y'],
self.state['yaw'], self.grid_world)
true_values.append([in_front])
on_left = peak.isWallOnLeft(self.state['x'], self.state['y'],
self.state['yaw'], self.grid_world)
on_right = peak.isWallOnRight(self.state['x'], self.state['y'],
self.state['yaw'], self.grid_world)
true_values.append([on_left, on_right])
return true_values
def get_true_values(self):
true_values = []
in_front = peak.isWallInFront(self.state['x'], self.state['y'],
self.state['yaw'], self.grid_world)
true_values.append([in_front])
on_left = peak.isWallOnLeft(self.state['x'], self.state['y'],
self.state['yaw'], self.grid_world)
on_right = peak.isWallOnRight(self.state['x'], self.state['y'],
self.state['yaw'], self.grid_world)
true_values.append([on_left, on_right])
is_behind = peak.isWallBehind(self.state['x'], self.state['y'],
self.state['yaw'], self.grid_world)
wall_adjacent = peak.isWallAdjacent(self.state['x'], self.state['y'],
self.state['yaw'], self.grid_world)
distance_to_adjacent = peak.distanceToAdjacent(self.state['x'],
self.state['y'],
self.state['yaw'],
self.grid_world)
distance_left = peak.distanceLeftToAdjacent(self.state['x'],
self.state['y'],
self.state['yaw'],
self.grid_world)
distance_right = peak.distanceRightToAdjacent(self.state['x'],
self.state['y'],
self.state['yaw'],
self.grid_world)
distance_back = peak.distanceBehindToAdjacent(self.state['x'],
self.state['y'],
self.state['yaw'],
self.grid_world)
wall_left_forward = peak.wallLeftForward(self.state['x'],
self.state['y'],
self.state['yaw'],
self.grid_world)
return true_values
def update_ui(self, action):
"""Re-draws the UI
Args:
action (int): the action taken this time-step.
"""
# Create a voronoi image
if self.state:
frame = self.state['visionData']
if self.show_display:
voronoi = voronoi_from_pixels(
pixels=frame,
dimensions=(WIDTH, HEIGHT),
pixelsOfInterest=self.network.layers[0].
function_approximation.pointsOfInterest)
# cv2.imshow('My Image', voronoi)
# cv2.waitKey(0)
if self.state is False: # todo: should be None for first val, not bool.
did_touch = False
else:
did_touch = self.state['touchData']
# find the ground truth of the predictions.
in_front = peak.isWallInFront(self.state['x'], self.state['y'],
self.state['yaw'], self.grid_world)
on_left = peak.isWallOnLeft(self.state['x'], self.state['y'],
self.state['yaw'], self.grid_world)
on_right = peak.isWallOnRight(self.state['x'], self.state['y'],
self.state['yaw'], self.grid_world)
is_behind = peak.isWallBehind(self.state['x'], self.state['y'],
self.state['yaw'], self.grid_world)
wall_adjacent = peak.isWallAdjacent(self.state['x'],
self.state['y'],
self.state['yaw'],
self.grid_world)
distance_to_adjacent = peak.distanceToAdjacent(
self.state['x'], self.state['y'], self.state['yaw'],
self.grid_world)
distance_left = peak.distanceLeftToAdjacent(
self.state['x'], self.state['y'], self.state['yaw'],
self.grid_world)
distance_right = peak.distanceRightToAdjacent(
self.state['x'], self.state['y'], self.state['yaw'],
self.grid_world)
distance_back = peak.distanceBehindToAdjacent(
self.state['x'], self.state['y'], self.state['yaw'],
self.grid_world)
wall_left_forward = peak.wallLeftForward(self.state['x'],
self.state['y'],
self.state['yaw'],
self.grid_world)
# get the most recent predictions
touch_prediction = self.network.layers[0].last_prediction[0]
turn_left_and_touch_prediction = self.network.layers[
1].last_prediction[0]
# turn_left_and_touch_prediction = 0
turn_right_and_touch_prediction = self.network.layers[
1].last_prediction[1]
# turn_right_and_touch_prediction = 0
# unimplemented, so zero...
touch_behind_prediction = 0
is_wall_adjacent_prediction = 0
distance_to_adjacent_prediction = 0
distance_left_prediction = 0
distance_right_prediction = 0
distance_back_prediction = 0
wall_left_forward_prediction = 0
game_image = Image.frombytes('RGB', (WIDTH, HEIGHT), bytes(frame))
if self.show_display:
if self.action_count > self.steps_before_updating_display:
self.display.update(
voronoiImage=voronoi,
gameImage=game_image,
numberOfSteps=self.action_count,
currentTouchPrediction=touch_prediction,
wallInFront=in_front,
didTouch=did_touch,
turnLeftAndTouchPrediction=
turn_left_and_touch_prediction,
wallOnLeft=on_left,
turnRightAndTouchPrediction=
turn_right_and_touch_prediction,
touchBehindPrediction=touch_behind_prediction,
wallBehind=is_behind,
touchAdjacentPrediction=is_wall_adjacent_prediction,
wallAdjacent=wall_adjacent,
wallOnRight=on_right,
distanceToAdjacent=distance_to_adjacent,
distanceToAdjacentPrediction=
distance_to_adjacent_prediction,
distanceToLeft=distance_left,
distanceToLeftPrediction=distance_left_prediction,
distanceToRight=distance_right,
distanceToRightPrediction=distance_right_prediction,
distanceBack=distance_back,
distanceBackPrediction=distance_back_prediction,
wallLeftForward=wall_left_forward,
wallLeftForwardPrediction=wall_left_forward_prediction,
action=action)
def updateUI(self):
# Create a voronoi image
frameError = False
try:
frame = self.state['visionData']
except:
frameError = True
print("Error gettnig frame")
if not frameError:
# rgb = self.s
if self.showDisplay:
voronoi = voronoi_from_pixels(pixels=frame, dimensions=(WIDTH, HEIGHT),
pixelsOfInterest=self.stateRepresentation.pointsOfInterest)
# cv2.imshow('My Image', voronoi)
# cv2.waitKey(0)
if self.state == False:
didTouch = False
else:
didTouch = self.state['touchData']
inFront = peak.isWallInFront(self.state['x'], self.state['y'], self.state['yaw'], self.gridWorld)
touchPrediction = self.gvfs['T'].prediction(self.phi)
gameImage = Image.frombytes('RGB', (WIDTH, HEIGHT), bytes(frame))
'''
#For debugging
previousInFront = peak.isWallInFront(self.oldState['x'], self.oldState['y'], self.oldState['yaw'], self.gridWorld)
previousTouchPrediction = self.gvfs['T'].prediction(self.oldPhi)
if not previousInFront and previousTouchPrediction > 0.0:
print("Bad first learning. ")
print("Last action: " + self.action)
msg = self.oldState.observations[0].text
observations = json.loads(msg) # and parse the JSON
yaw = observations.get(u'Yaw', 0)
x = observations.get(u'XPos', 0)
z = observations.get(u'ZPos', 0)
print("From: " + str(yaw) + ", " + str(x) + ", " + str(z))
msg = self.state.observations[0].text
observations = json.loads(msg) # and parse the JSON
yaw = observations.get(u'Yaw', 0)
x = observations.get(u'XPos', 0)
z = observations.get(u'ZPos', 0)
print("To: " + str(yaw) + ", " + str(x) + ", " + str(z))
ph = self.stateRepresentation.getPhi(previousPhi = self.oldPhi, state=self.state, previousAction=self.action, simplePhi = USE_SIMPLE_PHI)
idx = np.nonzero(ph)[0][0]
numNonZeros = len(np.nonzero(ph)[0])
print("idx: " + str(idx) + ", nonZeros: " + str(numNonZeros))
print("Observations since last:" + str(self.state.number_of_observations_since_last_state))
print("")
'''
onLeft = peak.isWallOnLeft(self.state['x'], self.state['y'], self.state['yaw'], self.gridWorld)
turnLeftAndTouchPrediction = self.gvfs['TL'].prediction(self.phi)
onRight = peak.isWallOnRight(self.state['x'], self.state['y'], self.state['yaw'], self.gridWorld)
turnRightAndtouchPrediction = self.gvfs['TR'].prediction(self.phi)
isBehind = peak.isWallBehind(self.state['x'], self.state['y'], self.state['yaw'], self.gridWorld)
touchBehindPrediction = self.gvfs['TB'].prediction(self.phi)
wallAdjacent = peak.isWallAdjacent(self.state['x'], self.state['y'], self.state['yaw'], self.gridWorld)
isWallAdjacentPrediction = self.gvfs['TA'].prediction(self.phi)
distanceToAdjacent = peak.distanceToAdjacent(self.state['x'], self.state['y'], self.state['yaw'], self.gridWorld)
distanceToAdjacentPrediction = self.gvfs['DTA'].prediction(self.phi)
distanceLeft = peak.distanceLeftToAdjacent(self.state['x'], self.state['y'], self.state['yaw'], self.gridWorld)
distanceLeftPrediction = self.gvfs['DTL'].prediction(self.phi)
distanceRight = peak.distanceRightToAdjacent(self.state['x'], self.state['y'], self.state['yaw'], self.gridWorld)
distanceRightPrediction = self.gvfs['DTR'].prediction(self.phi)
distanceBack = peak.distanceBehindToAdjacent(self.state['x'], self.state['y'], self.state['yaw'], self.gridWorld)
distanceBackPrediction = self.gvfs['DTB'].prediction(self.phi)
wallLeftForward =peak.wallLeftForward(self.state['x'], self.state['y'], self.state['yaw'], self.gridWorld)
wallLeftForwardPrediction = self.gvfs['WLF'].prediction(self.phi)
if self.showDisplay:
if self.actionCount > self.stepsBeforeUpdatingDisplay:
self.display.update(voronoiImage=voronoi,
gameImage = gameImage,
numberOfSteps=self.actionCount,
currentTouchPrediction=touchPrediction,
wallInFront=inFront,
didTouch=didTouch,
turnLeftAndTouchPrediction=turnLeftAndTouchPrediction,
wallOnLeft=onLeft,
turnRightAndTouchPrediction=turnRightAndtouchPrediction,
touchBehindPrediction = touchBehindPrediction,
wallBehind = isBehind,
touchAdjacentPrediction=isWallAdjacentPrediction,
wallAdjacent=wallAdjacent,
wallOnRight=onRight,
distanceToAdjacent = distanceToAdjacent,
distanceToAdjacentPrediction = distanceToAdjacentPrediction,
distanceToLeft = distanceLeft,
distanceToLeftPrediction = distanceLeftPrediction,
distanceToRight = distanceRight,
distanceToRightPrediction = distanceRightPrediction,
distanceBack = distanceBack,
distanceBackPrediction = distanceBackPrediction,
wallLeftForward = wallLeftForward,
wallLeftForwardPrediction = wallLeftForwardPrediction
)