class NeuralControl:
def __init__(self):
rospy.init_node('BMW_controller')
self.rate = rospy.Rate(10)
self.ic = ImageConverter()
self.image_process = ImageProcess()
self.drive = DriveRun(sys.argv[1])
rospy.Subscriber('/image_topic_2', Image, self.controller_cb)
rospy.Subscriber('/usb_cam/image_raw', Image, self.recorder1)
self.image = None
self.image_processed = False
def recorder1(self, image):
cam_img = self.ic.imgmsg_to_opencv(image)
cropImg = cam_img[yMin:yMax, xMin:xMax]
global newimg
newimg = cv2.resize(cropImg, (160, 50))
def controller_cb(self, image):
img = self.ic.imgmsg_to_opencv(image)
img_resize = cv2.resize(img, (160, 50))
stacked_img = np.concatenate((img_resize, newimg), axis=0)
self.image = self.image_process.process(stacked_img)
self.image_processed = True
class NeuralControl:
def __init__(self):
rospy.init_node('controller')
self.ic = ImageConverter()
self.image_process = ImageProcess()
self.rate = rospy.Rate(30)
self.drive = DriveRun(sys.argv[1])
rospy.Subscriber('/bolt/front_camera/image_raw', Image,
self.controller_cb)
self.image = None
self.image_processed = False
self.config = Config()
def controller_cb(self, image):
img = self.ic.imgmsg_to_opencv(image)
cropImg = img[self.config.capture_area[1]:self.config.capture_area[3],
self.config.capture_area[0]:self.config.capture_area[2]]
#cropImg = img[yMin:yMax,xMin:xMax]
img = cv2.resize(
cropImg, (self.config.image_size[0], self.config.image_size[1]))
self.image = self.image_process.process(img)
if self.config.typeofModel == 4 or self.config.typeofModel == 5:
self.image = np.array(self.image).reshape(
1, self.config.image_size[1], self.config.image_size[0],
self.config.image_size[2])
self.image_processed = True
class camera:
def __init__(self):
self.ic = ImageConverter()
self.image_process = ImageProcess()
self.driveC = DriveRun(sys.argv[2])
rospy.Subscriber('/usb_cam/image_raw', Image, self.recorder1)
self.imageC = None
self.camera_processed = False
def recorder1(self, image):
cam_img = self.ic.imgmsg_to_opencv(image)
cropImg = cam_img[yMin:yMax, xMin:xMax]
self.imageC = cv2.resize(cropImg, (160, 70))
self.camera_processed = True
class NeuralControl:
def __init__(self):
rospy.init_node('BMW_controller')
self.ic = ImageConverter()
self.image_process = ImageProcess()
self.rate = rospy.Rate(10)
self.drive= DriveRun(sys.argv[1])
rospy.Subscriber('/image_topic_2', Image, self.controller_cb)
self.image = None
self.image_processed = False
def controller_cb(self, image):
img = self.ic.imgmsg_to_opencv(image)
img = cv2.resize(img,(160,70))
self.image = self.image_process.process(img)
self.image_processed = True
class NeuralControl:
def __init__(self):
rospy.init_node('controller')
self.ic = ImageConverter()
self.image_process = ImageProcess()
self.rate = rospy.Rate(10)
self.drive= DriveRun(sys.argv[1])
rospy.Subscriber('/bulldogbolt/camera_left/image_raw_left', Image, self.controller_cb)
self.image = None
self.image_processed = False
def controller_cb(self, image):
img = self.ic.imgmsg_to_opencv(image)
cropImg = img[yMin:yMax,xMin:xMax]
img = cv2.resize(cropImg,(160,70))
self.image = self.image_process.process(img)
self.image_processed = True
class NeuralControl:
def __init__(self, weight_file_name):
rospy.init_node('run_neural')
self.ic = ImageConverter()
self.image_process = ImageProcess()
self.rate = rospy.Rate(30)
self.drive = DriveRun(weight_file_name)
rospy.Subscriber(Config.data_collection['camera_image_topic'], Image,
self._controller_cb)
self.image = None
self.image_processed = False
#self.config = Config()
self.braking = False
def _controller_cb(self, image):
img = self.ic.imgmsg_to_opencv(image)
cropped = img[Config.data_collection['image_crop_y1']:Config.
data_collection['image_crop_y2'],
Config.data_collection['image_crop_x1']:Config.
data_collection['image_crop_x2']]
img = cv2.resize(
cropped,
(config['input_image_width'], config['input_image_height']))
self.image = self.image_process.process(img)
## this is for CNN-LSTM net models
if config['lstm'] is True:
self.image = np.array(self.image).reshape(
1, config['input_image_height'], config['input_image_width'],
config['input_image_depth'])
self.image_processed = True
def _timer_cb(self):
self.braking = False
def apply_brake(self):
self.braking = True
timer = threading.Timer(Config.run_neural['brake_apply_sec'],
self._timer_cb)
timer.start()