semvec/pypi-packages huggingface dataset:
dora-kit-car 0.4.1
Dora Node for dora kit car
License: MIT
Requires Python: >=3.8

# dora-kit-car control

## Introduce

Dora Kit Car is a DORA node for controlling a differential-drive mobile robot to move forward/backward and turn left/right. Developed in Rust with Python API support.

## Highlights

- Compatible with the ROS geometry_msgs/Twist.msg format, utilizing only:
- linear.x (positive: forward movement, negative: backward movement)
- angular.z (positive: left turn, negative: right turn)

## Raw Message Definition

Accepts an array of six f64's

- six f64 array [x, y, z, rx, ry, rz] only used x, rz

see [https://docs.ros.org/en/noetic/api/geometry_msgs/html/msg/Twist.html](https://docs.ros.org/en/noetic/api/geometry_msgs/html/msg/Twist.html)

## Environment

Adds an environment variable `SERIAL_PORT` to specify the serial port for the car device, with `/dev/ttyUSB0` as the default value

## Demo Video

[![Dora Kit Car Video](https://yt3.ggpht.com/92FGXQL59VsiXim13EJQek4IB7CRI-9SjmW3LhH8PFY16oBXqKUvkKhg5UdzLiGCOmoSuTvdpQxIuw=s640-rw-nd-v1)](https://youtu.be/B7zGHtRUZSo)

## Getting Started

```yaml
nodes:
  - id: keyboard-listener # Run on car
    build: pip install dora-keyboard
    path: dora-keyboard
    inputs:
      tick: dora/timer/millis/10
    outputs:
      - twist # for example [2.0,0.0,0.0,0.0,0.0,1.0]

  - id: car
    build: pip install dora-kit-car
    path: dora-kit-car
    inputs:
      keyboard: keyboard-listener/twist
    env:
      SERIAL_PORT: /dev/ttyUSB0

```

## License

The MIT License (MIT)

Copyright (c) 2024-present, Leon
dora-ugv 0.4.1
Dora Node for using Agilex UGV
License: MIT
Requires Python: >=3.8

# Dora Node (Experimental) to communicate with Agilex UGV

This node is used to communicate with Agilex UGV.

Make sure to follow both the setup script and installation script from https://github.com/westonrobot/ugv_sdk/tree/main?tab=readme-ov-file#build-the-package-as-a-python-package
dora-piper 0.4.1
Dora Node for using Agilex piper
License: MIT
Requires Python: >=3.8

# Dora Node (Experimental) to communicate with Agilex Piper SDK

This node is used to communicate with piper.

Make sure to follow both the setup script and installation script from https://github.com/agilexrobotics/piper_sdk

# To setup the arm

Make sure that the can bus is activated for both arm and leader arms are not connected.
dora-sam2 0.4.1
dora-sam2
License: MIT
Requires Python: >=3.10

# dora-sam2

> [!WARNING]  
> SAM2 requires Nvidia GPU to be able to run.

## Getting started

- Install it with pip:

```bash
pip install -e .
```

## Contribution Guide

- Format with [ruff](https://docs.astral.sh/ruff/):

```bash
ruff check . --fix
```

- Lint with ruff:

```bash
ruff check .
```

- Test with [pytest](https://github.com/pytest-dev/pytest)

```bash
pytest . # Test
```

## YAML Specification

## Examples

## License

dora-sam2's code are released under the MIT License
pyarrow-assert 0.4.1
Dora Node for plotting text and bbox on image with OpenCV
License: MIT
Requires Python: >=3.8

# Dora Node for asserting arrow data.

This node assert that the DATA that is specified within the environment variable or from `--data` argument is the same as the data received.

Check example at [examples/pyarrow-test](examples/pyarrow-test)
dora-kokoro-tts 0.4.1
dora-kokoro-tts
License: MIT
Requires Python: >=3.10

# dora-kokoro-tts

## Getting started

- Install it with pip:

```bash
uv venv -p 3.11 --seed
uv pip install -e .
```

## Contribution Guide

- Format with [ruff](https://docs.astral.sh/ruff/):

```bash
uv run ruff check . --fix
```

- Lint with ruff:

```bash
uv run ruff check .
```

- Test with [pytest](https://github.com/pytest-dev/pytest)

```bash
uv run pytest . # Test
```

## YAML Specification

## Examples

## License

dora-kokoro-tts's code are released under the MIT License
dora-pyaudio 0.4.1
dora-pyaudio
License: MIT
Requires Python: >=3.8

# dora-pyaudio

## Getting started

- (MacOS) Install `portaudio`

```bash
brew install portaudio
```

- (Linux) Install `portaudio`

```bash
sudo apt-get install portaudio19-dev python-all-dev
```

- Install it with pip:

```bash
pip install -e .
```

## Contribution Guide

- Format with [ruff](https://docs.astral.sh/ruff/):

```bash
ruff check . --fix
```

- Lint with ruff:

```bash
ruff check .
```

- Test with [pytest](https://github.com/pytest-dev/pytest)

```bash
pytest . # Test
```

## YAML Specification

## Examples

## License

dora-pyaudio's code are released under the MIT License
mujoco-client 0.4.1
Dora Node client for mujoco simulated robots.
License: MIT
Requires Python: >=3.9

## Mujoco Client

This node is a client for a Mujoco simulation.

## YAML Configuration

````YAML
nodes:
  - id: mujoco_client
    path: client.py # modify this to the relative path from the graph file to the client script
    inputs:
      pull_position: dora/timer/millis/10 # pull the present position every 10ms

      # write_goal_position: some goal position from other node
      # end: some end signal from other node
    outputs:
      - position # regarding 'pull_position' input, it will output the position every 10ms
      - end # end signal that can be sent to other nodes (sent when the simulation ends)

    env:
      SCENE: scene.xml # the scene file to be used in the simulation modify this to the relative path from the graph file to the scene file
      CONFIG: config.json # the configuration file for the simulated arm (only retrieve joints names)
````

## Inputs

## Outputs

## License

This library is licensed under the [Apache License 2.0](../../LICENSE).
dora-distil-whisper 0.4.1
Dora dora-distil-whisper
License: MIT
Requires Python: >=3.9

# Dora Whisper Node for transforming speech to text

## YAML Specification

This node is supposed to be used as follows:

```yaml
- id: dora-distil-whisper
  build: pip install dora-distil-whisper
  path: dora-distil-whisper
  inputs:
    input: dora-vad/audio
  outputs:
    - text
  env:
    TARGET_LANGUAGE: english
```

## Examples

- speech to text
  - github: https://github.com/dora-rs/dora-hub/blob/main/examples/speech-to-text
- vision language model
  - github: https://github.com/dora-rs/dora-hub/blob/main/examples/vlm

## License

Dora-whisper's code and model weights are released under the MIT License
dora-pytorch-kinematics 0.4.1
dora-pytorch-kinematics
License: MIT
Requires Python: >=3.10

# dora-pytorch-kinematics

## Getting started

- Install it with uv:

```bash
uv venv -p 3.11 --seed
uv pip install -e .
```

## Contribution Guide

- Format with [ruff](https://docs.astral.sh/ruff/):

```bash
uv pip install ruff
uv run ruff check . --fix
```

- Lint with ruff:

```bash
uv run ruff check .
```

- Test with [pytest](https://github.com/pytest-dev/pytest)

```bash
uv pip install pytest
uv run pytest . # Test
```

## YAML Specification

## Examples

## License

dora-pytorch-kinematics's code are released under the MIT License
video-encoder 0.4.1
Dora Node for video encoding (LeRobot compatible).
License: MIT
Requires Python: >=3.9

## Camera Node for OpenCV compatible cameras

Simple Camera node that uses OpenCV to capture images from a camera. The node can be configured to use a specific camera
id, width and height.
It then sends the images to the dataflow.

## YAML Configuration

````YAML
nodes:
  - id: video_encoder
    path: encoder.py # modify this to the relative path from the graph file to the client script
    inputs:
    # image: some image from other node
    # episode_index: some episode index from other node
    outputs:
      - image

    env:
      VIDEO_NAME: cam_up
      VIDEO_WIDTH: 640
      VIDEO_HEIGHT: 480
      FPS: 30
````

## License

This library is licensed under the [Apache License 2.0](../../LICENSE).
dora-yolo 0.4.1
Dora Node for object detection with dora YOLOv8
License: MIT
Requires Python: >=3.8

# Dora Node for detecting objects in images using YOLOv8

This node is used to detect objects in images using YOLOv8.

# YAML

```yaml
- id: object_detection
  build: pip install ../../dora-yolo
  path: dora-yolo
  inputs:
    image: webcam/image

  outputs:
    - bbox
  env:
    MODEL: yolov5n.pt
```

# Inputs

- `image`: Arrow array containing the base image

```python
## Image data
image_data: UInt8Array # Example: pa.array(img.ravel())
metadata = {
  "width": 640,
  "height": 480,
  "encoding": str, # bgr8, rgb8
}

## Example
node.send_output(
  image_data, {"width": 640, "height": 480, "encoding": "bgr8"}
  )

## Decoding
storage = event["value"]

metadata = event["metadata"]
encoding = metadata["encoding"]
width = metadata["width"]
height = metadata["height"]

if encoding == "bgr8":
    channels = 3
    storage_type = np.uint8

frame = (
    storage.to_numpy()
    .astype(storage_type)
    .reshape((height, width, channels))
)

```

# Outputs

- `bbox`: an arrow array containing the bounding boxes, confidence scores, and class names of the detected objects

```Python

bbox: {
    "bbox": np.array,  # flattened array of bounding boxes
    "conf": np.array,  # flat array of confidence scores
    "labels": np.array,  # flat array of class names
}

encoded_bbox = pa.array([bbox], {"format": "xyxy"})

decoded_bbox = {
    "bbox": encoded_bbox[0]["bbox"].values.to_numpy().reshape(-1, 4),
    "conf": encoded_bbox[0]["conf"].values.to_numpy(),
    "labels": encoded_bbox[0]["labels"].values.to_numpy(zero_copy_only=False),
}
```

## Example

Check example at [examples/python-dataflow](examples/python-dataflow)

## License

This project is licensed under Apache-2.0. Check out [NOTICE.md](../../NOTICE.md) for more information.
dora-outtetts 0.4.1
dora-outtetts
License: MIT
Requires Python: >=3.10

# dora-outtetts

> dora-outtetts is no longer maintained in favor of dora-kokorotts

## Getting started

- Install it with pip:

```bash
pip install -e .
```

## Contribution Guide

- Format with [ruff](https://docs.astral.sh/ruff/):

```bash
ruff check . --fix
```

- Lint with ruff:

```bash
ruff check .
```

- Test with [pytest](https://github.com/pytest-dev/pytest)

```bash
pytest . # Test
```

## YAML Specification

## Examples

## License

dora-outtetts's code are released under the MIT License