Standard Donkeycar Config

standard-config.py

#VEHICLE
DRIVE_LOOP_HZ = 50      # the vehicle loop will pause if faster than this speed.
MAX_LOOPS = None        # the vehicle loop can abort after this many iterations, when given a positive integer.
 
# #CAMERA
CAMERA_TYPE = "LEOPARD" # (PICAM|WEBCAM|CVCAM|CSIC|V4L|MOCK|LEOPARD)
IMAGE_W = 224
IMAGE_H = 224
IMAGE_DEPTH = 3         # default RGB=3, make 1 for mono
CAMERA_FRAMERATE = DRIVE_LOOP_HZ
 
#9865, over rides only if needed, ie. TX2..
PCA9685_I2C_ADDR = 0x40     # I2C address, use i2cdetect to validate this number
PCA9685_I2C_BUSNUM = 0      # None will auto detect, which is fine on the pi. But other platforms should specify the bus num.
 
#SSD1306_128_32
USE_SSD1306_128_32 = True     # Enable the SSD_1306 OLED Display
SSD1306_128_32_I2C_BUSNUM = 1 # I2C bus number
 
#SERVO_HBRIDGE_PWM use ServoBlaster to output pwm control from the PiZero directly to control steering, and HBridge for a drive motor.
DRIVE_TRAIN_TYPE = "SERVO_ESC" # SERVO_ESC|DC_STEER_THROTTLE|DC_TWO_WHEEL|SERVO_HBRIDGE_PWM
 
# #STEERING
STEERING_CHANNEL = 1
STEERING_LEFT_PWM = 410
STEERING_RIGHT_PWM = 310
 
# #THROTTLE
THROTTLE_CHANNEL = 0
THROTTLE_FORWARD_PWM = 400
THROTTLE_STOPPED_PWM = 310
THROTTLE_REVERSE_PWM = 280
 
# 
# #TRAINING
DEFAULT_MODEL_TYPE = 'linear'   #(linear|categorical|rnn|imu|behavior|3d|localizer|latent|transfer|inferred)
BATCH_SIZE = 128                #how many records to use when doing one pass of gradient decent. Use a smaller number if your gpu is running out of memory.
TRAIN_TEST_SPLIT = 0.8          #what percent of records to use for training. the remaining used for validation.
MAX_EPOCHS = 100                #how many times to visit all records of your data
SHOW_PLOT = True                #would you like to see a pop up display of final loss?
VERBOSE_TRAIN = True             #would you like to see a progress bar with text during training?
USE_EARLY_STOP = True           #would you like to stop the training if we see it's not improving fit?
EARLY_STOP_PATIENCE = 5         #how many epochs to wait before no improvement
MIN_DELTA = .0005               #early stop will want this much loss change before calling it improved.
PRINT_MODEL_SUMMARY = True      #print layers and weights to stdout
CACHE_IMAGES = False            #keep images in memory. will speed succesive epochs, but crater if not enough mem.

# #JOYSTICK
USE_JOYSTICK_AS_DEFAULT = True      #when starting the manage.py, when True, will not require a --js option to use the joystick
JOYSTICK_MAX_THROTTLE = 0.85        #this scalar is multiplied with the -1 to 1 throttle value to limit the maximum throttle. This can help if you drop the controller or just don't need the full speed available.
JOYSTICK_STEERING_SCALE = 1.0       #some people want a steering that is less sensitve. This scalar is multiplied with the steering -1 to 1. It can be negative to reverse dir.
AUTO_RECORD_ON_THROTTLE = True      #if true, we will record whenever throttle is not zero. if false, you must manually toggle recording with some other trigger. Usually circle button on joystick.
CONTROLLER_TYPE = 'xbox'            #(ps3|ps4|xbox|nimbus|wiiu|F710|rc3)
JOYSTICK_DEADZONE = 0.01            # when non zero, this is the smallest throttle before recording triggered.
JOYSTICK_THROTTLE_DIR = 1.0         # use -1.0 to flip forward/backward, use 1.0 to use joystick's natural forward/backward

# #When racing, to give the ai a boost, configure these values.
# AI_LAUNCH_DURATION = 0.0            # the ai will output throttle for this many seconds
# AI_LAUNCH_THROTTLE = 0.0            # the ai will output this throttle value
# AI_LAUNCH_ENABLE_BUTTON = 'R2'      # this keypress will enable this boost. It must be enabled before each use to prevent accidental trigger.
# AI_LAUNCH_KEEP_ENABLED = False      # when False ( default) you will need to hit the AI_LAUNCH_ENABLE_BUTTON for each use. This is safest. When this True, is active on each trip into "local" ai mode.
# 
# #Scale the output of the throttle of the ai pilot for all model types.
AI_THROTTLE_MULT = 1.0                # this multiplier will scale every throttle value for all output from NN models