Camera Parts

Camera parts for image capture in Donkeycar

Camera parts capture images from various camera hardware. All cameras inherit from BaseCamera and provide a consistent interface for the vehicle.

Available Cameras

PiCamera (Raspberry Pi Camera Module)

The standard camera for Raspberry Pi using the Picamera2 library (Bullseye/Bookworm).

Location: donkeycar/parts/camera.py:23

from donkeycar.parts.camera import PiCamera

cam = PiCamera(
    image_w=160,      # Image width
    image_h=120,      # Image height
    image_d=3,        # Image depth (3=RGB, 1=grayscale)
    vflip=False,      # Vertical flip
    hflip=False       # Horizontal flip
)

Parameters:

• image_w: Image width in pixels (default: 160)
• image_h: Image height in pixels (default: 120)
• image_d: Color depth - 3 for RGB, 1 for grayscale (default: 3)
• vflip: Vertical flip boolean (default: False)
• hflip: Horizontal flip boolean (default: False)

Hardware Setup:

• Connect camera ribbon cable to CSI port on Raspberry Pi
• Enable camera interface: sudo raspi-config → Interface Options → Camera
• Requires: picamera2 library (pre-installed on recent Raspberry Pi OS)

Webcam

USB webcam support using pygame.

Location: donkeycar/parts/camera.py:85

from donkeycar.parts.camera import Webcam

cam = Webcam(
    image_w=160,
    image_h=120,
    image_d=3,
    framerate=20,
    camera_index=0    # Index if multiple cameras
)

Parameters:

• image_w, image_h, image_d: Image dimensions
• framerate: Target frames per second (default: 20)
• camera_index: Camera index when multiple USB cameras (default: 0)

Installation:

sudo apt-get install libsdl2-mixer-2.0-0 libsdl2-image-2.0-0 libsdl2-2.0-0
pip install pygame

CSI Camera (NVIDIA Jetson)

For Jetson Nano IMX219 camera modules using GStreamer.

Location: donkeycar/parts/camera.py:194

from donkeycar.parts.camera import CSICamera

cam = CSICamera(
    image_w=224,
    image_h=224,
    image_d=3,
    capture_width=3280,
    capture_height=2464,
    framerate=60,
    gstreamer_flip=0  # 0=none, 1=rotate CCW 90, 2=flip vert, 3=rotate CW 90
)

Parameters:

• capture_width, capture_height: Native camera resolution
• image_w, image_h: Output resolution (will be scaled)
• framerate: Target FPS (default: 60)
• gstreamer_flip: Image rotation/flip method

V4L Camera (Video4Linux)

Direct V4L2 access for low-level camera control.

Location: donkeycar/parts/camera.py:273

from donkeycar.parts.camera import V4LCamera

cam = V4LCamera(
    image_w=160,
    image_h=120,
    image_d=3,
    framerate=20,
    dev_fn="/dev/video0",
    fourcc='MJPG'
)

Installation:

sudo apt-get install libv4l-dev
pip install v4l2capture

Advanced Cameras

OAK-D (Luxonis)

Intel Movidius-based depth camera with onboard AI processing.

Location: donkeycar/parts/oak_d.py:34

from donkeycar.parts.oak_d import OakD

cam = OakD(
    width=640,
    height=480,
    enable_rgb=True,
    enable_depth=True,
    device_id=None  # Or specific device serial number
)

Features:

• RGB color camera
• Stereo depth sensing
• Onboard neural network inference
• 4K video capability

Installation:

pip install depthai
# Add udev rules:
echo 'SUBSYSTEM=="usb", ATTRS{idVendor}=="03e7", MODE="0666"' | sudo tee /etc/udev/rules.d/80-movidius.rules
sudo udevadm control --reload-rules && sudo udevadm trigger

Usage:

V.add(cam, outputs=['cam/image_array', 'cam/depth_array'], threaded=True)

RealSense T265 (Intel)

Tracking camera with visual-inertial odometry.

Location: donkeycar/parts/realsense2.py:13

from donkeycar.parts.realsense2 import RS_T265

cam = RS_T265(
    image_output=False,      # Enable fisheye image output
    calib_filename=None      # Wheel odometry calibration file
)

Outputs:

• Position (x, y, z) in meters
• Velocity (vx, vy, vz) in m/s
• Acceleration (ax, ay, az) in m/s²
• Optional fisheye camera images

Installation:

pip install pyrealsense2

Usage:

V.add(cam, 
      inputs=['enc/velocity'],
      outputs=['pos', 'vel', 'acc', 'img'], 
      threaded=True)

Leopard Imaging Camera

High-performance camera for NVIDIA Jetson with built-in fast stretch.

Location: donkeycar/parts/leopard_imaging.py:7

from donkeycar.parts.leopard_imaging import LICamera

cam = LICamera(
    width=224,
    height=224,
    capture_width=1280,
    capture_height=720,
    fps=60
)

Features:

• Hardware-accelerated image processing
• High frame rates (up to 60 FPS)
• Optimized for Jetson platform

Testing Cameras

Use the camera test script:

donkey makemovie

Or test in Python:

from donkeycar.parts.camera import PiCamera
import time

cam = PiCamera()
time.sleep(2)  # Warm up

for i in range(10):
    img = cam.run()
    print(f"Frame {i}: shape={img.shape}")
    time.sleep(0.1)

cam.shutdown()

Mock Cameras for Testing

MockCamera

Returns a static image for testing without hardware.

Location: donkeycar/parts/camera.py:333

from donkeycar.parts.camera import MockCamera
import numpy as np

# Use with default blank image
cam = MockCamera(image_w=160, image_h=120)

# Or provide a specific image
test_image = np.random.randint(0, 255, (120, 160, 3), dtype=np.uint8)
cam = MockCamera(image=test_image)

ImageListCamera

Replays images from a tub for testing.

Location: donkeycar/parts/camera.py:350

from donkeycar.parts.camera import ImageListCamera

cam = ImageListCamera(path_mask='~/mycar/data/**/images/*.jpg')

Camera Configuration

In myconfig.py:

# Camera type
CAMERA_TYPE = "PICAM"  # Options: PICAM, WEBCAM, CVCAM, CSIC, MOCK

# Image dimensions
IMAGE_W = 160
IMAGE_H = 120
IMAGE_DEPTH = 3  # 1 for grayscale, 3 for RGB

# Camera-specific settings
CAMERA_FRAMERATE = 20
CAMERA_VFLIP = False
CAMERA_HFLIP = False

Common Issues

Camera Not Detected

Raspberry Pi:

# Check if camera is detected
vcgencmd get_camera
# Should show: supported=1 detected=1

# Enable camera interface
sudo raspi-config
# Navigate to Interface Options → Camera → Enable

Jetson:

# Check for video devices
ls /dev/video*

# Test GStreamer pipeline
gst-launch-1.0 nvarguscamerasrc ! nvoverlaysink

Low Frame Rate

• Reduce image resolution
• Disable unnecessary image processing
• Use hardware acceleration when available
• Check USB bandwidth (for USB cameras)

Image Quality Issues

• Adjust lighting conditions
• Clean camera lens
• Check focus (if adjustable)
• Verify correct image orientation (use flip settings)

Next Steps

• Controllers - Add user input
• Models - Process camera images with AI
• Data Stores - Record camera data