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Use for camera and video capture nodes in dora. Triggers on: opencv-video-capture, dora-pyrealsense, dora-pyorbbecksdk, realsense, orbbeck, camera, webcam, video capture, RGB, depth camera, image capture, 摄像头, 视频捕获, 深度相机, 图像采集
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Use for dora CLI command questions. Triggers on: dora run, dora build, dora start, dora stop, dora new, dora up, dora destroy, dora list, dora ps, dora logs, dora check, dora graph, dora daemon, dora coordinator, CLI命令, 命令行, 运行数据流, 构建, 启动, 停止
Use for data recording and replay questions with dora. Triggers on: recording, replay, lerobot, data collection, dataset, rosbag, record data, play back, training data, HDF5, parquet, 数据记录, 数据回放, 数据收集, 训练数据
Use for dora-rs dataflow YAML configuration questions. Triggers on: dataflow.yml, dataflow.yaml, nodes:, inputs:, outputs:, timer, dora/timer, queue_size, env:, build:, path:, git:, branch:, tag:, restart_policy, send_stdout_as, operator:, operators:, YAML配置, 数据流配置, 节点配置, 输入输出, 定时器
Use for audio processing pipeline questions with dora. Triggers on: speech, TTS, STT, voice, audio, Whisper, Kokoro, text-to-speech, speech-to-text, voice activity, VAD, microphone, 语音, 音频, 文本转语音, 语音转文本, 语音识别
Use for robot control pipeline questions with dora. Triggers on: robot, arm, chassis, actuator, servo, motor, gripper, kinematics, FK, IK, URDF, joint, position control, velocity control, serial port, 机器人, 机械臂, 底盘, 执行器, 舵机, 电机, 运动学
Use for ML/Vision pipeline questions with dora. Triggers on: YOLO, detection, object detection, segmentation, tracking, VLM, SAM, camera, webcam, image processing, bbox, bounding box, rerun, visualization, 视觉, 目标检测, 分割, 跟踪, 摄像头, 图像处理
| name | hub-camera |
| description | Use for camera and video capture nodes in dora. Triggers on: opencv-video-capture, dora-pyrealsense, dora-pyorbbecksdk, realsense, orbbeck, camera, webcam, video capture, RGB, depth camera, image capture, 摄像头, 视频捕获, 深度相机, 图像采集 |
| globs | ["**/dataflow.yml","**/dataflow.yaml"] |
| source | https://github.com/dora-rs/dora-hub |
Capture video frames from cameras and depth sensors
| Node | Install | Description | Platform |
|---|---|---|---|
| opencv-video-capture | pip install opencv-video-capture | OpenCV camera/video | All |
| dora-pyrealsense | pip install dora-pyrealsense | Intel RealSense depth | Linux |
| dora-pyorbbecksdk | pip install dora-pyorbbecksdk | Orbbeck depth camera | All |
OpenCV-based video capture from webcam or video file.
- id: camera
build: pip install opencv-video-capture
path: opencv-video-capture
inputs:
tick: dora/timer/millis/16 # ~60fps
outputs:
- image
env:
PATH: "0" # Camera index (0, 1, ...) or video file path
IMAGE_WIDTH: 640 # Optional: output width
IMAGE_HEIGHT: 480 # Optional: output height
image - UInt8Array with metadata:
metadata = {
"width": 640,
"height": 480,
"encoding": "bgr8", # or "rgb8"
"primitive": "image" # for dora-rerun
}
storage = event["value"]
metadata = event["metadata"]
width = metadata["width"]
height = metadata["height"]
encoding = metadata["encoding"]
channels = 3
frame = storage.to_numpy().astype(np.uint8).reshape((height, width, channels))
# Convert BGR to RGB if needed
if encoding == "bgr8":
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
Intel RealSense camera with RGB and depth streams.
- id: realsense
build: pip install dora-pyrealsense
path: dora-pyrealsense
inputs:
tick: dora/timer/millis/33 # ~30fps
outputs:
- image # RGB image
- depth # Depth image
env:
IMAGE_WIDTH: 640
IMAGE_HEIGHT: 480
image - RGB UInt8Array
metadata = {"width": 640, "height": 480, "encoding": "rgb8"}
depth - Float32Array depth values (meters)
metadata = {"width": 640, "height": 480}
Orbbeck depth camera support.
- id: orbbeck
build: pip install dora-pyorbbecksdk
path: dora-pyorbbecksdk
inputs:
tick: dora/timer/millis/33
outputs:
- image
- depth
All camera nodes output images in Apache Arrow format:
import pyarrow as pa
import numpy as np
# Encoding image
image_data = pa.array(frame.ravel()) # UInt8Array
# Sending
node.send_output("image", image_data, {
"width": 640,
"height": 480,
"encoding": "bgr8",
"primitive": "image" # for dora-rerun visualization
})
nodes:
- id: camera
build: pip install opencv-video-capture
path: opencv-video-capture
inputs:
tick: dora/timer/millis/33
outputs:
- image
env:
IMAGE_WIDTH: 640
IMAGE_HEIGHT: 480
- id: yolo
build: pip install dora-yolo
path: dora-yolo
inputs:
image: camera/image
outputs:
- bbox
- id: rerun
build: pip install dora-rerun
path: dora-rerun
inputs:
image: camera/image
detections: yolo/bbox
nodes:
- id: camera_left
build: pip install opencv-video-capture
path: opencv-video-capture
inputs:
tick: dora/timer/millis/33
outputs:
- image
env:
PATH: "0"
- id: camera_right
build: pip install opencv-video-capture
path: opencv-video-capture
inputs:
tick: dora/timer/millis/33
outputs:
- image
env:
PATH: "1"
nodes:
- id: realsense
build: pip install dora-pyrealsense
path: dora-pyrealsense
inputs:
tick: dora/timer/millis/33
outputs:
- image
- depth
- id: rerun
build: pip install dora-rerun
path: dora-rerun
inputs:
rgb_camera:
source: realsense/image
metadata:
primitive: "image"
depth_sensor:
source: realsense/depth
metadata:
primitive: "depth"
focal: [600, 600]
camera_position: [0, 0, 0]
# List available cameras
v4l2-ctl --list-devices # Linux
# Add user to video group (Linux)
sudo usermod -a -G video $USER