Description:

aicoedonkeycar 4.3.0.post1

donkeycar: a python self driving library




Donkeycar is minimalist and modular self driving library for Python. It is
developed for hobbyists and students with a focus on allowing fast experimentation and easy
community contributions.
NOTE: this package is a non-official build by the AICoE. Please check the upstream project links for official information.
Quick Links

Donkeycar Updates & Examples
Build instructions and Software documentation
Discord / Chat

Use Donkey if you want to:

Make an RC car drive its self.
Compete in self driving races like DIY Robocars
Experiment with autopilots, mapping computer vision and neural networks.
Log sensor data. (images, user inputs, sensor readings)
Drive your car via a web or game controller.
Leverage community contributed driving data.
Use existing CAD models for design upgrades.

Get driving.
After building a Donkey2 you can turn on your car and go to http://localhost:8887 to drive.
Modify your cars behavior.
The donkey car is controlled by running a sequence of events
#Define a vehicle to take and record pictures 10 times per second.

import time
from donkeycar import Vehicle
from donkeycar.parts.cv import CvCam
from donkeycar.parts.tub_v2 import TubWriter
V = Vehicle()

IMAGE_W = 160
IMAGE_H = 120
IMAGE_DEPTH = 3

#Add a camera part
cam = CvCam(image_w=IMAGE_W, image_h=IMAGE_H, image_d=IMAGE_DEPTH)
V.add(cam, outputs=['image'], threaded=True)

#warmup camera
while cam.run() is None:
time.sleep(1)

#add tub part to record images
tub = TubWriter(path='./dat', inputs=['image'], types=['image_array'])
V.add(tub, inputs=['image'], outputs=['num_records'])

#start the drive loop at 10 Hz
V.start(rate_hz=10)

See home page, docs
or join the Discord server to learn more.

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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