def __init__(self, text_to_speech, speech_to_text):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
self.speech_to_text = speech_to_text
self.neural_network = None
self.background_image = np.array([])
self.iris_slide = np.array([])
def stop(self):
Feature.stop(self)
self.background_image = np.array([])
if self.video_capture.isOpened():
self.video_capture.release()
def stop(self):
Feature.stop(self)
self.background_image = np.array([])
if self.video_capture.isOpened():
self.video_capture.release()
def set_attrs(self,
target=None,
features=None,
metrics=None,
model=None,
column_subset=None,
prediction=None,
predictions_name=None,
actual=None,
reporters=None):
if prediction is not None:
if predictions_name is None:
raise ValueError(
"If you provide a prediction feature, you "
"must also specify a _unique_ 'predictions_name'")
self.target = target if isinstance(
target, BaseFeature) or target is None else Feature(target)
self.prediction = prediction if isinstance(
prediction,
BaseFeature) or prediction is None else Feature(prediction)
self.predictions_name = predictions_name
if actual is None:
actual = self.target
self.actual = actual if isinstance(actual,
BaseFeature) else Feature(actual)
self.features = [
f if isinstance(f, BaseFeature) else Feature(f) for f in features
] if features else None
self.metrics = metrics or []
self.model = model
self.column_subset = column_subset
self.reporters = reporters or []
for r in self.reporters:
r.set_config(self)
def __init__(self, text_to_speech):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
self.is_pyramid = False
self.is_cube = False
self.rotation = 0
self.background_image = np.array([])
self.speech_thread = None
def __init__(self, text_to_speech):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
self.is_pyramid = False
self.is_cube = False
self.rotation = 0
self.background_image = np.array([])
self.speech_thread = None
def start(self, args=None):
Feature.start(self, args)
# draw rotating pyramid or cube
self.rotation += 1
if self.is_pyramid:
draw_pyramid(self.rotation)
elif self.is_cube:
draw_cube(self.rotation)
def __init__(self, text_to_speech):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
self.background_image = np.array([])
self.slides = []
self.blurbs = []
self.current_item = 0
self.current_slide = np.array([])
self.blurb_thread = None
self._get_slides_and_blurbs()
def start(self, args=None):
Feature.start(self, args)
# draw rotating pyramid or cube
self.rotation += 1
if self.is_pyramid:
draw_pyramid(self.rotation)
elif self.is_cube:
draw_cube(self.rotation)
def __init__(self, text_to_speech):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
self.background_image = np.array([])
self.slides = []
self.blurbs = []
self.current_item = 0
self.current_slide = np.array([])
self.blurb_thread = None
self._get_slides_and_blurbs()
def start(self, args=None):
image = args
Feature.start(self, args)
# if slide, add to background image
if self.iris_slide.size > 0:
slide_offset_and_height = self.SLIDE_OFFSET + self.iris_slide.shape[0]
slide_offset_and_width = self.SLIDE_OFFSET + self.iris_slide.shape[1]
image[self.SLIDE_OFFSET:slide_offset_and_height, self.SLIDE_OFFSET:slide_offset_and_width] = self.iris_slide
self.background_image = image
else:
self.background_image = np.array([])
def start(self, args=None):
Feature.start(self, args)
# enable fog if cloudy
if self.is_cloudy:
glFogi(GL_FOG_MODE, GL_LINEAR)
glFogfv(GL_FOG_COLOR, (0.5, 0.5, 0.5, 1.0))
glFogf(GL_FOG_DENSITY, 0.35)
glHint(GL_FOG_HINT, GL_NICEST)
glFogf(GL_FOG_START, 1.0)
glFogf(GL_FOG_END, 5.0)
glEnable(GL_FOG)
else:
glDisable(GL_FOG)
def start(self, args=None):
Feature.start(self, args)
# enable fog if cloudy
if self.is_cloudy:
glFogi(GL_FOG_MODE, GL_LINEAR)
glFogfv(GL_FOG_COLOR, (0.5, 0.5, 0.5, 1.0))
glFogf(GL_FOG_DENSITY, 0.35)
glHint(GL_FOG_HINT, GL_NICEST)
glFogf(GL_FOG_START, 1.0)
glFogf(GL_FOG_END, 5.0)
glEnable(GL_FOG)
else:
glDisable(GL_FOG)
def __init__(self, text_to_speech, speech_to_text):
Feature.__init__(self)
# setup AV Table
self.av_table = GameTable(13, 2)
if (self.av_table.loadParameters() == False):
self.av_table.initialize(0.)
# setup a Q-Learning agent
learner = Q(0.5, 0.0)
learner._setExplorer(EpsilonGreedyExplorer(0.0))
self.agent = LearningAgent(self.av_table, learner)
# setup game interaction
self.game_interaction = GameInteraction(text_to_speech, speech_to_text)
# setup environment
environment = GameEnvironment(self.game_interaction)
# setup task
task = GameTask(environment, self.game_interaction)
# setup experiment
self.experiment = Experiment(task, self.agent)
def __init__(self, text_to_speech, speech_to_text):
Feature.__init__(self)
# setup AV Table
self.av_table = GameTable(13, 2)
if(self.av_table.loadParameters() == False):
self.av_table.initialize(0.)
# setup a Q-Learning agent
learner = Q(0.5, 0.0)
learner._setExplorer(EpsilonGreedyExplorer(0.0))
self.agent = LearningAgent(self.av_table, learner)
# setup game interaction
self.game_interaction = GameInteraction(text_to_speech, speech_to_text)
# setup environment
environment = GameEnvironment(self.game_interaction)
# setup task
task = GameTask(environment, self.game_interaction)
# setup experiment
self.experiment = Experiment(task, self.agent)
def stop(self):
Feature.stop(self)
self.background_image = np.array([])
def __init__(self, text_to_speech, speech_to_text):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
self.speech_to_text = speech_to_text
self.is_cloudy = False
def __init__(self, text_to_speech):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
def __init__(self):
Feature.__init__(self)
self.background_image = np.array([])
self.video_capture = cv2.VideoCapture()
def stop(self):
Feature.stop(self)
self.background_image = np.array([])
def __init__(self, speech_to_text):
Feature.__init__(self)
self.is_speaking = False
self.speech_to_text = speech_to_text
self.phrases = self._load_config()
pygame.mixer.init()
def mark_tags(weights):
"""标注全部目标选框"""
new_image = image.copy()
drawer = ImageDraw.Draw(new_image)
print('\n标注目标选框：')
final_weight = lambda xy: reduce(
lambda l, r: l + weights[r] * features[r].weight(xy),
range(len(features)), 0)
cap = weights[6] if len(weights) > 6 else 0.5
is_tag = lambda xy: final_weight(xy) > cap
visited = {}
def mark_tag(xy):
"""标注目标选框"""
x0, y0, x1, y1 = xy[0], xy[1], xy[0], xy[1]
count = 0
stack = [xy]
while len(stack):
xy = stack.pop()
visited[xy] = True
if xy[0] < x0:
x0 = xy[0]
elif xy[0] > x1:
x1 = xy[0]
if xy[1] < y0:
y0 = xy[1]
elif xy[1] > y1:
y1 = xy[1]
# 向附近延展
for x in range(max(0, xy[0] - 10), min(width, xy[0] + 10)):
for y in range(max(0, xy[1] - 10), min(height,
xy[1] + 10)):
if (x, y) not in visited and is_tag((x, y)):
count += 1
stack.append((x, y))
visited[(x, y)] = True
x0, y0, x1, y1 = (
max(0, x0 - 10),
max(0, y0 - 10),
min(width, x1 + 10),
min(height, y1 + 10),
)
for x in range(x0, x1):
for y in range(y0, y1):
visited[(x, y)] = True
# 去噪点
if (x0 - x1) * (y0 - y1) < 1600 or count < 120:
return
# print(x0, y0, x1, y1)
for ex in range(3):
drawer.rectangle((x0 + ex, y0 + ex, x1 - ex, y1 - ex),
outline='#f00')
final_feature = Feature(width, height)
def each_pix(xy, rgb):
"""每个像素点处理"""
weight = final_weight(xy)
if weight > cap and xy not in visited:
final_feature.point(xy, 255)
mark_tag(xy)
else:
final_feature.point(xy, 255 * weight)
# if is_tag(xy) and xy not in visited:
# mark_tag(xy)
pix_iter(each_pix)
print_progress('OK')
# Thread(target=new_image.show, name=path).start()
new_image.save(main.outdir + 'result-marked.jpg')
# final_feature.show()
final_feature.weight_image.save(main.outdir + 'result-weight.jpg')
def __init__(self, text_to_speech):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
self.neural_network = None
def stop(self):
Feature.stop(self)
# disable fog
glDisable(GL_FOG)
self.is_cloudy = False
def __init__(self, text_to_speech):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
def __init__(self):
Feature.__init__(self)
self.background_image = np.array([])
self.video_capture = cv2.VideoCapture()
def __init__(self, text_to_speech, speech_to_text):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
self.speech_to_text = speech_to_text
self.is_cloudy = False
def __init__(self, text_to_speech, speech_to_text):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
self.speech_to_text = speech_to_text
self.recognizer = sr.Recognizer()
pygame.mixer.init(frequency=8000)
def __init__(self, speech_to_text):
Feature.__init__(self)
self.is_speaking = False
self.speech_to_text = speech_to_text
self.phrases = self._load_config()
pygame.mixer.init()
def __init__(self, text_to_speech, speech_to_text):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
self.speech_to_text = speech_to_text
self.recognizer = sr.Recognizer()
pygame.mixer.init(frequency=8000)
def stop(self):
Feature.stop(self)
# disable fog
glDisable(GL_FOG)
self.is_cloudy = False
def __init__(self, text_to_speech):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
self.neural_network = None
