def __init__( self, image_size, learning_rate=2e-5, batch_size=1, classes_size=2, ngf=64, ): """ Args: input_size:list [H, W, C] batch_size: integer, batch size learning_rate: float, initial learning rate for Adam ngf: number of gen filters in first conv layer """ self.learning_rate = learning_rate self.input_shape = [ int(batch_size / 4), image_size[0], image_size[1], image_size[2] ] self.tenaor_name = {} self.classes_size = classes_size self.G_X = Unet('G_X', ngf=ngf, output_channl=image_size[2], keep_prob=0.97) self.D_X = Discriminator('D_X', ngf=ngf, keep_prob=0.9) self.G_L_X = Detector('G_L_X', ngf, classes_size=classes_size, keep_prob=0.99, input_channl=image_size[2])
def __init__(self): # params self.count = 1 self.clear_str = '0:0: ' self.is_configuring = False self.is_self_driving = False self.is_time_configuring = False self.first_load = True self.engine = None self.video_recorder = None self.path = rospack.get_path('team107') + '/scripts/' self.bt1_status = False self.bt2_status = False self.bt3_status = False self.bt4_status = False self.ss_status = False self.model = Model(self.path) self.sign_model = Detector(self.path) # ros subscribers and publishers # hal self.sub_bt1 = rospy.Subscriber('/bt1_status', Bool, self.bt1_callback, queue_size=1) self.sub_bt2 = rospy.Subscriber('/bt2_status', Bool, self.bt2_callback, queue_size=1) self.sub_bt3 = rospy.Subscriber('/bt3_status', Bool, self.bt3_callback, queue_size=1) self.sub_bt4 = rospy.Subscriber('/bt4_status', Bool, self.bt4_callback, queue_size=1) self.sub_ss = rospy.Subscriber('/ss_status', Bool, self.ss_callback, queue_size=1) self.pub_lcd = rospy.Publisher('/lcd_print', String, queue_size='5') # car controller self.sub_img = None rospy.init_node('team107') print 'Finish initializing'
def __init__(self): self.detector = Detector()
@route('/object', method='POST') def object(): try: image = request.files.get('file') image = io.imread(StringIO(image.file.read())) objs = detector(image.astype(np.float32) / 255.) return json.dumps(objs) except Exception as e: print str(type(e)), e @route('/style', method='POST') def style(): try: image = request.files.get('file') image = io.imread(StringIO(image.file.read())) result_image = style(image) s = StringIO() np.save(s, result_image) return s.getvalue() except Exception as e: print str(type(e)), e if __name__ == '__main__': detector = Detector() style = Style() run(host='0.0.0.0', port=8080, debug=True, reloader=True)