drive.py 文件源码

def telemetry(sid, data):
    if data:
        # The current steering angle of the car
        steering_angle = float(data["steering_angle"])
        # The current throttle of the car, how hard to push peddle
        throttle = float(data["throttle"])
        # The current speed of the car
        speed = float(data["speed"])
        # The current image from the center camera of the car
        image = Image.open(BytesIO(base64.b64decode(data["image"])))
        try:
            image = np.asarray(image)       # from PIL image to numpy array
            image = utils.preprocess(image) # apply the preprocessing
            image = np.array([image])       # the model expects 4D array

            # predict the steering angle for the image
            steering_angle = float(model.predict(image, batch_size=1))
            # lower the throttle as the speed increases
            # if the speed is above the current speed limit, we are on a downhill.
            # make sure we slow down first and then go back to the original max speed.
            global speed_limit
            if speed > speed_limit:
                speed_limit = MIN_SPEED  # slow down
            else:
                speed_limit = MAX_SPEED
            throttle = 1.0 - steering_angle**2 - (speed/speed_limit)**2

            print('{} {} {}'.format(steering_angle, throttle, speed))
            send_control(steering_angle, throttle)
        except Exception as e:
            print(e)

        # save frame
        if args.image_folder != '':
            timestamp = datetime.utcnow().strftime('%Y_%m_%d_%H_%M_%S_%f')[:-3]
            image_filename = os.path.join(args.image_folder, timestamp)
            image.save('{}.jpg'.format(image_filename))
    else:

        sio.emit('manual', data={}, skip_sid=True)