本文整理汇总了Python中NeuralNetwork.NeuralNetwork.classifyImage方法的典型用法代码示例。如果您正苦于以下问题：Python NeuralNetwork.classifyImage方法的具体用法？Python NeuralNetwork.classifyImage怎么用？Python NeuralNetwork.classifyImage使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类NeuralNetwork.NeuralNetwork的用法示例。
在下文中一共展示了NeuralNetwork.classifyImage方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
# 需要导入模块: from NeuralNetwork import NeuralNetwork [as 别名]
# 或者: from NeuralNetwork.NeuralNetwork import classifyImage [as 别名]
class Classifier:
def __init__(self):
self.alias = "[CLASSIFIER]>> "
print self.alias , "Iniciando Clasificador..."
self.netHandler = NeuralNetworksHandler()
self.imageProcesor = ImagePreprocesor(wideSegment=150, highSegment=150, horizontalStride=50, verticalStride=50, withResizeImgOut=250, highResizeImgOut=250)
networkModel, netMean, prototype, classes = self.netHandler.getNetworkByIndex(0)
self.neuralNetwork = NeuralNetwork(networkModel, prototype, netMean, classes)
self.speaker = AudioPlayer()
self.eventListener()
def eventListener(self):
tickTime = pygame.time.Clock()
holdTime = 0
pygame.init()
DISPLAYSURF = pygame.display.set_mode((900, 900))
DISPLAYSURF.fill((255, 255, 255, 255))
while True:
for event in pygame.event.get():
if event.type == pygame.MOUSEBUTTONDOWN:
holdTime = tickTime.tick(60)
print self.alias, "DOWN: ", holdTime
if event.type == pygame.MOUSEBUTTONUP:
if holdTime < 3000:
print "----------------------------"
print self.alias, "CLASSIFYING... "
print "----------------------------"
pygame.mixer.music.load("perro.wav")
self.takePicture()
#Para pruebas de reproducción --- (En mi compu no furula)
self.play("perro")
self.play("gato")
self.play("desconocido")
# -------------------------------
self.startClasification()
print self.alias, "UP: ", holdTime
holdTime = 0
else:
print self.alias, ": ", holdTime, " miliSegundos"
networkModel, netMean, prototype, classes = self.netHandler.getNextNet()
self.neuralNetwork = NeuralNetwork(networkModel, netMean, prototype, classes)
holdTime = 0
if event.type == pygame.QUIT:
sys.exit(0)
def takePicture(self):
print self.alias , "Adquiriendo imagen"
os.system("bash AdquisidorImagenes.sh")
def startClasification(self):
print self.alias, "Clasificando objetos en imágen"
#numImages = self.imageProcesor.runSegmentation("img/photo.jpg")
numImages = self.segment_entry_image("img/photo.jpg", 'img/segments/')
for imageIndex in range(numImages):
self.neuralNetwork.classifyImage('img/segments/cutout'+str(imageIndex)+'.jpg' , imageIndex)
def segment_entry_image(self, url_image, url_output):
img = open(url_image)
width_image, height_image = img.size
trajectory = get_circular_trajectory(width_image, height_image)
segmenter = get_rectangular_segmenter(img, trajectory)
i = 0
image = segmenter.get_current_segment()
image.pil_image.save(url_output+'cutout' + str(i) + '.jpg')
i += 1
while (segmenter.has_next_segment()):
image = segmenter.get_next_segment()
image.pil_image.save(url_output+'cutout' + str(i) + '.jpg')
i += 1
return i
def play(self, audio):
#pygame.init()
print self.alias, "Reproduciendo sonido para clase ", audio
pygame.mixer.music.load(self.audioPath + audio + self.audioFormat)
pygame.mixer.music.play(0)
clock = pygame.time.Clock()
clock.tick(10)
while pygame.mixer.music.get_busy():
pygame.event.poll()
clock.tick(10)