haixuantao
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Delete v0.0.1
Browse files- v0.0.1/README.md +0 -1
- v0.0.1/aloha-client/Cargo.toml +0 -14
- v0.0.1/aloha-client/src/main.rs +0 -59
- v0.0.1/aloha-teleop/Cargo.toml +0 -15
- v0.0.1/aloha-teleop/src/main.rs +0 -126
- v0.0.1/compress_image.py +0 -28
- v0.0.1/data/episode_1.parquet +0 -3
- v0.0.1/data/episode_2.parquet +0 -3
- v0.0.1/data/episode_3.parquet +0 -3
- v0.0.1/data/episode_4.parquet +0 -3
- v0.0.1/keyboard_node.py +0 -28
- v0.0.1/lerobot_webcam_saver.py +0 -74
- v0.0.1/llm_op.py +0 -234
- v0.0.1/plot_node.py +0 -53
- v0.0.1/policy.py +0 -17
- v0.0.1/realsense_node.py +0 -26
- v0.0.1/record_2arms_teleop.yml +0 -125
- v0.0.1/replay.py +0 -27
- v0.0.1/videos/cam_bottom_episode_1.mp4 +0 -3
- v0.0.1/videos/cam_bottom_episode_2.mp4 +0 -3
- v0.0.1/videos/cam_bottom_episode_3.mp4 +0 -3
- v0.0.1/videos/cam_bottom_episode_4.mp4 +0 -3
- v0.0.1/videos/cam_left_wrist_episode_1.mp4 +0 -3
- v0.0.1/videos/cam_left_wrist_episode_2.mp4 +0 -3
- v0.0.1/videos/cam_left_wrist_episode_3.mp4 +0 -0
- v0.0.1/videos/cam_left_wrist_episode_4.mp4 +0 -3
- v0.0.1/videos/cam_right_wrist_episode_1.mp4 +0 -3
- v0.0.1/videos/cam_right_wrist_episode_2.mp4 +0 -3
- v0.0.1/videos/cam_right_wrist_episode_3.mp4 +0 -3
- v0.0.1/videos/cam_right_wrist_episode_4.mp4 +0 -3
- v0.0.1/videos/cam_up_episode_1.mp4 +0 -3
- v0.0.1/videos/cam_up_episode_2.mp4 +0 -3
- v0.0.1/videos/cam_up_episode_3.mp4 +0 -3
- v0.0.1/videos/cam_up_episode_4.mp4 +0 -3
- v0.0.1/webcam.py +0 -45
- v0.0.1/whisper_node.py +0 -59
v0.0.1/README.md
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First Draft of a dataset using dora-arms
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v0.0.1/aloha-client/Cargo.toml
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[package]
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name = "aloha-client"
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version = "0.1.0"
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edition = "2021"
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# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
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[dependencies]
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serialport = "4.2.0"
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rustypot = { git = "https://github.com/haixuanTao/rustypot" }
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tokio = { version = "1.37.0", features = ["full"] }
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eyre = "0.6.12"
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dora-node-api = "0.3.3"
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v0.0.1/aloha-client/src/main.rs
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use dora_node_api::{
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arrow::array::UInt32Array, dora_core::config::DataId, DoraNode, Event, IntoArrow,
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};
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use eyre::Result;
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use rustypot::{device::xm, DynamixelSerialIO};
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use std::time::Duration;
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fn main() -> Result<()> {
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let (mut node, mut events) = DoraNode::init_from_env()?;
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let mut puppet_serial_port = serialport::new("/dev/ttyDXL_puppet_right", 1_000_000)
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.timeout(Duration::from_millis(20))
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.open()
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.expect("Failed to open port");
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let io = DynamixelSerialIO::v2();
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xm::sync_write_torque_enable(
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&io,
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puppet_serial_port.as_mut(),
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&[1, 2, 3, 4, 5, 6, 7, 8, 9],
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&[1; 9],
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)
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.expect("Communication error");
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while let Some(Event::Input {
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id,
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metadata: _,
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data,
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}) = events.recv()
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{
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match id.as_str() {
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"puppet_goal_position" => {
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let buffer: UInt32Array = data.to_data().into();
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let target: &[u32] = buffer.values();
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xm::sync_write_goal_position(
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&io,
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puppet_serial_port.as_mut(),
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&[1, 2, 3, 4, 5, 6, 7, 8, 9],
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&target,
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)
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.expect("Communication error");
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}
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"tick" => {
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let pos = xm::sync_read_present_position(
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&io,
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puppet_serial_port.as_mut(),
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&[1, 2, 3, 4, 5, 6, 7, 8, 9],
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)
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.expect("Communication error");
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node.send_output(
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DataId::from("puppet_position".to_owned()),
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Default::default(),
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pos.into_arrow(),
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)?;
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}
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_ => todo!(),
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};
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}
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Ok(())
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}
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v0.0.1/aloha-teleop/Cargo.toml
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[package]
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name = "aloha-teleop"
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version = "0.1.0"
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edition = "2021"
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# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
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[dependencies]
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serialport = "4.2.0"
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rustypot = { git = "https://github.com/haixuanTao/rustypot" }
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tokio = { version = "1.37.0", features = ["full"] }
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eyre = "0.6.12"
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clap = { version = "4.5.4", features = ["derive"] }
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dora-node-api = "0.3.3"
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v0.0.1/aloha-teleop/src/main.rs
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use dora_node_api::{dora_core::config::DataId, DoraNode, IntoArrow, MetadataParameters};
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use eyre::{Context, Result};
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use rustypot::{device::xm, DynamixelSerialIO};
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use serialport::SerialPort;
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use std::{
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sync::mpsc,
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time::{Duration, Instant},
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};
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static MAX_MASTER_GRIPER: u32 = 2554;
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static MAX_PUPPET_GRIPER: u32 = 3145;
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static MIN_MASTER_GRIPER: u32 = 1965;
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static MIN_PUPPET_GRIPER: u32 = 2500;
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use clap::Parser;
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/// Simple aloha teleop program for recording data
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#[derive(Parser, Debug)]
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#[command(version, about, long_about = None)]
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struct Args {
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#[arg(short, long, default_value = "/dev/ttyDXL_master_right")]
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master_path: String,
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#[arg(short, long, default_value = "/dev/ttyDXL_puppet_right")]
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puppet_path: String,
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#[arg(long, default_value = "1000000")]
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master_baudrate: u32,
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#[arg(long, default_value = "1000000")]
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puppet_baudrate: u32,
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}
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enum State {
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Position(Vec<u32>),
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GoalPosition(Vec<u32>),
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}
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fn main_multithreaded(
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io: DynamixelSerialIO,
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mut master_serial_port: Box<dyn SerialPort>,
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mut puppet_serial_port: Box<dyn SerialPort>,
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) -> Result<()> {
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let (tx, rx) = mpsc::channel();
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let (tx_dora, rx_dora) = mpsc::channel();
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let tx_dora_read = tx_dora.clone();
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std::thread::spawn(move || loop {
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let now = Instant::now();
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let pos = xm::sync_read_present_position(
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&io,
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master_serial_port.as_mut(),
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&[1, 2, 3, 4, 5, 6, 7, 8, 9],
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)
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.expect("Read Communication error");
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tx.send((now, pos.clone())).unwrap();
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tx_dora_read.send(State::Position(pos)).unwrap();
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});
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let io = DynamixelSerialIO::v2();
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let join = std::thread::spawn(move || {
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while let Ok((_now, pos)) = rx.recv() {
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// Compute linear interpolation for gripper as input and output range missmatch
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let gripper = (pos[8] - MIN_MASTER_GRIPER) * (MAX_PUPPET_GRIPER - MIN_PUPPET_GRIPER)
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/ (MAX_MASTER_GRIPER - MIN_MASTER_GRIPER)
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+ MIN_PUPPET_GRIPER;
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let mut target = pos;
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target[8] = gripper;
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xm::sync_write_goal_position(
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&io,
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puppet_serial_port.as_mut(),
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&[1, 2, 3, 4, 5, 6, 7, 8, 9],
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&target,
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)
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.expect("Write Communication error");
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// println!("elapsed time: {:?}", now.elapsed());
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tx_dora.send(State::GoalPosition(target)).unwrap();
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}
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});
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if std::env::var("DORA_NODE_CONFIG").is_ok() {
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let (mut node, mut events) = DoraNode::init_from_env()?;
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while let Ok(target) = rx_dora.recv() {
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let parameters = MetadataParameters::default();
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match target {
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State::Position(pos) => {
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let output = DataId::from("puppet_goal_position".to_owned());
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node.send_output(output.clone(), parameters, pos.into_arrow())?;
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}
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State::GoalPosition(pos) => {
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let output = DataId::from("puppet_state".to_owned());
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node.send_output(output.clone(), parameters, pos.into_arrow())?;
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}
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}
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if events.recv_timeout(Duration::from_nanos(100)).is_none() {
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println!("Events channel finished");
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break;
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}
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}
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} else {
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join.join().unwrap();
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};
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Ok(())
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}
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fn main() -> Result<()> {
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let args = Args::parse();
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let master_serial_port = serialport::new(args.master_path, args.master_baudrate)
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.timeout(Duration::from_millis(2))
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.open()
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.context("Failed to open port")?;
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let mut puppet_serial_port = serialport::new(args.puppet_path, args.puppet_baudrate)
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.timeout(Duration::from_millis(2))
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.open()
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.context("Failed to open port")?;
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let io = DynamixelSerialIO::v2();
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xm::sync_write_torque_enable(
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&io,
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puppet_serial_port.as_mut(),
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&[1, 2, 3, 4, 5, 6, 7, 8, 9],
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&[1; 9],
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)
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.expect("Communication error");
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main_multithreaded(io, master_serial_port, puppet_serial_port)?;
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Ok(())
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}
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v0.0.1/compress_image.py
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from dora import Node
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import shutil
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FPS = 50
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frame_id = 0
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node = Node()
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for event in node:
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if event["TYPE"] != "INPUT":
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break
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result = {"path": f"videos/{fname}", "timestamp": frame_id / FPS}
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frame_id += 1
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tmp_imgs_dir = out_dir / "tmp_images"
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save_images_concurrently(imgs_array, tmp_imgs_dir)
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# encode images to a mp4 video
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fname = f"{img_key}_episode_{ep_idx:06d}.mp4"
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video_path = "out" / "videos" / fname
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encode_video_frames(tmp_imgs_dir, video_path, FPS)
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# clean temporary images directory
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shutil.rmtree(tmp_imgs_dir)
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v0.0.1/data/episode_1.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:fb0cb717b54bda0a3460241096e9b5e974e9da44a89722959693c5a347af69d2
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size 42285
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v0.0.1/data/episode_2.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:0350bb61ff20b4c9d4b67e1293b1c45ec82942fadbefaf51a8d29b3998cdbe66
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size 36604
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v0.0.1/data/episode_3.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:7c37d6ac89906fd6f313641ad371923c0f9044e45463deeb274b9003ad46eab5
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size 33102
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v0.0.1/data/episode_4.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:61ce815a1d8a9907f6b0935884f25a8c1359835669e8598424f50610433884e4
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size 70380
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v0.0.1/keyboard_node.py
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@@ -1,28 +0,0 @@
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from pynput import keyboard
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from pynput.keyboard import Key, Events
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import pyarrow as pa
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from dora import Node
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node = Node()
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buffer_text = ""
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space = False
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submitted_text = []
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cursor = 1
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with keyboard.Events() as events:
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while True:
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14 |
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event = events.get(0.1)
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15 |
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if event is not None and isinstance(event, Events.Press):
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16 |
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if event.key == Key.space and space == False:
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node.send_output("space", pa.array([cursor]))
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18 |
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space = True
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-
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20 |
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elif event is not None and isinstance(event, Events.Release):
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21 |
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if event.key == Key.space:
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node.send_output("space", pa.array([0]))
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cursor += 1
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space = False
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if node.next(0.001) is None:
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break
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# 1
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v0.0.1/lerobot_webcam_saver.py
DELETED
@@ -1,74 +0,0 @@
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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import os
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import time
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import numpy as np
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import cv2
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import pyarrow as pa
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from pathlib import Path
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from dora import Node
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import subprocess
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node = Node()
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14 |
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CAMERA_NAME = os.getenv("CAMERA_NAME", "camera" )
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16 |
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CAMERA_WIDTH = 640
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CAMERA_HEIGHT = 480
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18 |
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FPS = 50
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19 |
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20 |
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i = 0
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21 |
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episode = 0
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out_dir = "videos" / Path(f"cam_{CAMERA_NAME}_episode_{episode}")
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23 |
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24 |
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for event in node:
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event_type = event["type"]
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if event_type == "INPUT":
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27 |
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if event["id"] == "record_episode":
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record_episode = event["value"].to_numpy()[0]
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print(f"Recording episode {record_episode}", flush=True)
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# Save Episode Video
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31 |
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if episode != 0 and record_episode == 0:
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out_dir = "videos" / Path(f"{CAMERA_NAME}_episode_{episode}")
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33 |
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fname = f"{CAMERA_NAME}_episode_{episode}.mp4"
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34 |
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video_path = Path("videos") / fname
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35 |
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# Save video
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36 |
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ffmpeg_cmd = (
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37 |
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f"ffmpeg -r {FPS} "
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38 |
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"-f image2 "
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"-loglevel error "
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f"-i {str(out_dir / 'frame_%06d.png')} "
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"-vcodec libx264 "
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"-g 2 "
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"-pix_fmt yuv444p "
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f"{str(video_path)}"
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)
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print(ffmpeg_cmd, flush=True)
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47 |
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subprocess.Popen(ffmpeg_cmd.split(" "), start_new_session=True)
|
48 |
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episode = record_episode
|
49 |
-
|
50 |
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# Make new directory and start saving images
|
51 |
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elif episode == 0 and record_episode != 0:
|
52 |
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episode = record_episode
|
53 |
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out_dir = "videos" / Path(f"{CAMERA_NAME}_episode_{episode}")
|
54 |
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out_dir.mkdir(parents=True, exist_ok=True)
|
55 |
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i = 0
|
56 |
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else:
|
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continue
|
58 |
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|
59 |
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elif event["id"] == "image":
|
60 |
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# Only record image when in episode.
|
61 |
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# Episode 0 is for not recording periods.
|
62 |
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if episode == 0:
|
63 |
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continue
|
64 |
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|
65 |
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fname = f"{CAMERA_NAME}_episode_{episode}.mp4"
|
66 |
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node.send_output(
|
67 |
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"saved_image",
|
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pa.array([{"path": f"videos/{fname}", "timestamp": i / FPS}]),
|
69 |
-
event["metadata"],
|
70 |
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)
|
71 |
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image = event["value"].to_numpy().reshape((CAMERA_HEIGHT, CAMERA_WIDTH, 3))
|
72 |
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path = str(out_dir / f"frame_{i:06d}.png")
|
73 |
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cv2.imwrite(path, image)
|
74 |
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i += 1
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v0.0.1/llm_op.py
DELETED
@@ -1,234 +0,0 @@
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1 |
-
from dora import DoraStatus
|
2 |
-
import pylcs
|
3 |
-
import os
|
4 |
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import pyarrow as pa
|
5 |
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from transformers import AutoModelForCausalLM, AutoTokenizer
|
6 |
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import torch
|
7 |
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|
8 |
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import gc # garbage collect library
|
9 |
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import re
|
10 |
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import time
|
11 |
-
|
12 |
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CHATGPT = False
|
13 |
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MODEL_NAME_OR_PATH = "TheBloke/deepseek-coder-6.7B-instruct-GPTQ"
|
14 |
-
|
15 |
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CODE_MODIFIER_TEMPLATE = """
|
16 |
-
### Instruction
|
17 |
-
Respond with one block of modified code only in ```python block. No explaination.
|
18 |
-
|
19 |
-
```python
|
20 |
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{code}
|
21 |
-
```
|
22 |
-
|
23 |
-
{user_message}
|
24 |
-
|
25 |
-
### Response:
|
26 |
-
"""
|
27 |
-
|
28 |
-
|
29 |
-
model = AutoModelForCausalLM.from_pretrained(
|
30 |
-
MODEL_NAME_OR_PATH,
|
31 |
-
device_map="auto",
|
32 |
-
trust_remote_code=True,
|
33 |
-
revision="main",
|
34 |
-
max_length=1024,
|
35 |
-
).to("cuda:0")
|
36 |
-
|
37 |
-
|
38 |
-
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME_OR_PATH, use_fast=True)
|
39 |
-
|
40 |
-
|
41 |
-
def extract_python_code_blocks(text):
|
42 |
-
"""
|
43 |
-
Extracts Python code blocks from the given text that are enclosed in triple backticks with a python language identifier.
|
44 |
-
|
45 |
-
Parameters:
|
46 |
-
- text: A string that may contain one or more Python code blocks.
|
47 |
-
|
48 |
-
Returns:
|
49 |
-
- A list of strings, where each string is a block of Python code extracted from the text.
|
50 |
-
"""
|
51 |
-
pattern = r"```python\n(.*?)\n```"
|
52 |
-
matches = re.findall(pattern, text, re.DOTALL)
|
53 |
-
if len(matches) == 0:
|
54 |
-
pattern = r"```python\n(.*?)(?:\n```|$)"
|
55 |
-
matches = re.findall(pattern, text, re.DOTALL)
|
56 |
-
if len(matches) == 0:
|
57 |
-
return [text]
|
58 |
-
else:
|
59 |
-
matches = [remove_last_line(matches[0])]
|
60 |
-
|
61 |
-
return matches
|
62 |
-
|
63 |
-
|
64 |
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def remove_last_line(python_code):
|
65 |
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"""
|
66 |
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Removes the last line from a given string of Python code.
|
67 |
-
|
68 |
-
Parameters:
|
69 |
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- python_code: A string representing Python source code.
|
70 |
-
|
71 |
-
Returns:
|
72 |
-
- A string with the last line removed.
|
73 |
-
"""
|
74 |
-
lines = python_code.split("\n") # Split the string into lines
|
75 |
-
if lines: # Check if there are any lines to remove
|
76 |
-
lines.pop() # Remove the last line
|
77 |
-
return "\n".join(lines) # Join the remaining lines back into a string
|
78 |
-
|
79 |
-
|
80 |
-
def calculate_similarity(source, target):
|
81 |
-
"""
|
82 |
-
Calculate a similarity score between the source and target strings.
|
83 |
-
This uses the edit distance relative to the length of the strings.
|
84 |
-
"""
|
85 |
-
edit_distance = pylcs.edit_distance(source, target)
|
86 |
-
max_length = max(len(source), len(target))
|
87 |
-
# Normalize the score by the maximum possible edit distance (the length of the longer string)
|
88 |
-
similarity = 1 - (edit_distance / max_length)
|
89 |
-
return similarity
|
90 |
-
|
91 |
-
|
92 |
-
def find_best_match_location(source_code, target_block):
|
93 |
-
"""
|
94 |
-
Find the best match for the target_block within the source_code by searching line by line,
|
95 |
-
considering blocks of varying lengths.
|
96 |
-
"""
|
97 |
-
source_lines = source_code.split("\n")
|
98 |
-
target_lines = target_block.split("\n")
|
99 |
-
|
100 |
-
best_similarity = 0
|
101 |
-
best_start_index = 0
|
102 |
-
best_end_index = -1
|
103 |
-
|
104 |
-
# Iterate over the source lines to find the best matching range for all lines in target_block
|
105 |
-
for start_index in range(len(source_lines) - len(target_lines) + 1):
|
106 |
-
for end_index in range(start_index + len(target_lines), len(source_lines) + 1):
|
107 |
-
current_window = "\n".join(source_lines[start_index:end_index])
|
108 |
-
current_similarity = calculate_similarity(current_window, target_block)
|
109 |
-
if current_similarity > best_similarity:
|
110 |
-
best_similarity = current_similarity
|
111 |
-
best_start_index = start_index
|
112 |
-
best_end_index = end_index
|
113 |
-
|
114 |
-
# Convert line indices back to character indices for replacement
|
115 |
-
char_start_index = len("\n".join(source_lines[:best_start_index])) + (
|
116 |
-
1 if best_start_index > 0 else 0
|
117 |
-
)
|
118 |
-
char_end_index = len("\n".join(source_lines[:best_end_index]))
|
119 |
-
|
120 |
-
return char_start_index, char_end_index
|
121 |
-
|
122 |
-
|
123 |
-
def replace_code_in_source(source_code, replacement_block: str):
|
124 |
-
"""
|
125 |
-
Replace the best matching block in the source_code with the replacement_block, considering variable block lengths.
|
126 |
-
"""
|
127 |
-
replacement_block = extract_python_code_blocks(replacement_block)[0]
|
128 |
-
start_index, end_index = find_best_match_location(source_code, replacement_block)
|
129 |
-
if start_index != -1 and end_index != -1:
|
130 |
-
# Replace the best matching part with the replacement block
|
131 |
-
new_source = (
|
132 |
-
source_code[:start_index] + replacement_block + source_code[end_index:]
|
133 |
-
)
|
134 |
-
return new_source
|
135 |
-
else:
|
136 |
-
return source_code
|
137 |
-
|
138 |
-
|
139 |
-
class Operator:
|
140 |
-
def __init__(self) -> None:
|
141 |
-
self.policy_init = False
|
142 |
-
|
143 |
-
def on_event(
|
144 |
-
self,
|
145 |
-
dora_event,
|
146 |
-
send_output,
|
147 |
-
) -> DoraStatus:
|
148 |
-
global model, tokenizer
|
149 |
-
if dora_event["type"] == "INPUT" and dora_event["id"] == "text":
|
150 |
-
input = dora_event["value"][0].as_py()
|
151 |
-
# Path to the current file
|
152 |
-
current_file_path = __file__
|
153 |
-
|
154 |
-
# Directory of the current file
|
155 |
-
current_directory = os.path.dirname(current_file_path)
|
156 |
-
path = current_directory + "/policy.py"
|
157 |
-
|
158 |
-
with open(path, "r", encoding="utf8") as f:
|
159 |
-
code = f.read()
|
160 |
-
|
161 |
-
user_message = input
|
162 |
-
start_llm = time.time()
|
163 |
-
|
164 |
-
output = self.ask_llm(
|
165 |
-
CODE_MODIFIER_TEMPLATE.format(code=code, user_message=user_message)
|
166 |
-
)
|
167 |
-
|
168 |
-
source_code = replace_code_in_source(code, output)
|
169 |
-
print("response time:", time.time() - start_llm, flush=True)
|
170 |
-
|
171 |
-
print("response: ", output, flush=True)
|
172 |
-
with open(path, "w") as file:
|
173 |
-
file.write(source_code)
|
174 |
-
|
175 |
-
gc.collect()
|
176 |
-
torch.cuda.empty_cache()
|
177 |
-
|
178 |
-
return DoraStatus.CONTINUE
|
179 |
-
|
180 |
-
def ask_llm(self, prompt):
|
181 |
-
|
182 |
-
# Generate output
|
183 |
-
# prompt = PROMPT_TEMPLATE.format(system_message=system_message, prompt=prompt))
|
184 |
-
input = tokenizer(prompt, return_tensors="pt")
|
185 |
-
input_ids = input.input_ids.cuda()
|
186 |
-
|
187 |
-
# add attention mask here
|
188 |
-
attention_mask = input.attention_mask.cuda()
|
189 |
-
|
190 |
-
output = model.generate(
|
191 |
-
inputs=input_ids,
|
192 |
-
temperature=0.7,
|
193 |
-
do_sample=True,
|
194 |
-
top_p=0.95,
|
195 |
-
top_k=40,
|
196 |
-
max_new_tokens=512,
|
197 |
-
attention_mask=attention_mask,
|
198 |
-
eos_token_id=tokenizer.eos_token_id,
|
199 |
-
)
|
200 |
-
# Get the tokens from the output, decode them, print them
|
201 |
-
|
202 |
-
# Get text between im_start and im_end
|
203 |
-
return tokenizer.decode(output[0], skip_special_tokens=True)[len(prompt) :]
|
204 |
-
|
205 |
-
|
206 |
-
if __name__ == "__main__":
|
207 |
-
op = Operator()
|
208 |
-
|
209 |
-
# Path to the current file
|
210 |
-
current_file_path = __file__
|
211 |
-
|
212 |
-
# Directory of the current file
|
213 |
-
current_directory = os.path.dirname(current_file_path)
|
214 |
-
|
215 |
-
path = current_directory + "/policy.py"
|
216 |
-
with open(path, "r", encoding="utf8") as f:
|
217 |
-
raw = f.read()
|
218 |
-
|
219 |
-
op.on_event(
|
220 |
-
{
|
221 |
-
"type": "INPUT",
|
222 |
-
"id": "text",
|
223 |
-
"value": pa.array(
|
224 |
-
[
|
225 |
-
{
|
226 |
-
"path": path,
|
227 |
-
"user_message": "When I say suit up, get the hat and the get the food.",
|
228 |
-
},
|
229 |
-
]
|
230 |
-
),
|
231 |
-
"metadata": [],
|
232 |
-
},
|
233 |
-
print,
|
234 |
-
)
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v0.0.1/plot_node.py
DELETED
@@ -1,53 +0,0 @@
|
|
1 |
-
import os
|
2 |
-
import cv2
|
3 |
-
from dora import Node
|
4 |
-
|
5 |
-
|
6 |
-
IMAGE_WIDTH = int(os.getenv("IMAGE_WIDTH", "1280"))
|
7 |
-
IMAGE_HEIGHT = int(os.getenv("IMAGE_HEIGHT", "720"))
|
8 |
-
FONT = cv2.FONT_HERSHEY_SIMPLEX
|
9 |
-
|
10 |
-
|
11 |
-
node = Node()
|
12 |
-
|
13 |
-
joint = None
|
14 |
-
text = None
|
15 |
-
|
16 |
-
for event in node:
|
17 |
-
if event["type"] == "INPUT":
|
18 |
-
dora_id = event["id"]
|
19 |
-
|
20 |
-
if dora_id == "position":
|
21 |
-
joint = event["value"].to_numpy()
|
22 |
-
if "text" in dora_id:
|
23 |
-
text = event["value"][0].as_py()
|
24 |
-
|
25 |
-
if dora_id == "image":
|
26 |
-
image = (
|
27 |
-
event["value"].to_numpy().reshape((IMAGE_HEIGHT, IMAGE_WIDTH, 3)).copy()
|
28 |
-
)
|
29 |
-
if text is not None:
|
30 |
-
cv2.putText(
|
31 |
-
image,
|
32 |
-
f"Speech: {text}",
|
33 |
-
(20, 40),
|
34 |
-
FONT,
|
35 |
-
0.5,
|
36 |
-
(190, 250, 0),
|
37 |
-
2,
|
38 |
-
)
|
39 |
-
|
40 |
-
if joint is not None:
|
41 |
-
cv2.putText(
|
42 |
-
image,
|
43 |
-
f"pos: {joint}",
|
44 |
-
(20, 20),
|
45 |
-
FONT,
|
46 |
-
0.5,
|
47 |
-
(190, 250, 100),
|
48 |
-
2,
|
49 |
-
)
|
50 |
-
|
51 |
-
cv2.imshow("frame", image)
|
52 |
-
if cv2.waitKey(1) & 0xFF == ord("q"):
|
53 |
-
break
|
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v0.0.1/policy.py
DELETED
@@ -1,17 +0,0 @@
|
|
1 |
-
import pyarrow as pa
|
2 |
-
from dora import DoraStatus
|
3 |
-
|
4 |
-
|
5 |
-
class Operator:
|
6 |
-
def __init__(self):
|
7 |
-
self.actions = ["get_food", "get_hat"]
|
8 |
-
|
9 |
-
def on_event(self, event: dict, send_output) -> DoraStatus:
|
10 |
-
if event["type"] == "INPUT":
|
11 |
-
id = event["id"]
|
12 |
-
# On initialization
|
13 |
-
if id == "speech":
|
14 |
-
text: str = event["value"][0].as_py().lower()
|
15 |
-
# send_output("action", pa.array([""]))
|
16 |
-
|
17 |
-
return DoraStatus.CONTINUE
|
|
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|
v0.0.1/realsense_node.py
DELETED
@@ -1,26 +0,0 @@
|
|
1 |
-
import pyrealsense2 as rs
|
2 |
-
import numpy as np
|
3 |
-
from dora import Node
|
4 |
-
import pyarrow as pa
|
5 |
-
import os
|
6 |
-
import cv2
|
7 |
-
|
8 |
-
IMAGE_WIDTH = int(os.getenv("IMAGE_WIDTH", "1280"))
|
9 |
-
IMAGE_HEIGHT = int(os.getenv("IMAGE_HEIGHT", "720"))
|
10 |
-
CAMERA_ID = os.getenv("CAMERA_ID")
|
11 |
-
pipe = rs.pipeline()
|
12 |
-
config = rs.config()
|
13 |
-
config.enable_device(CAMERA_ID)
|
14 |
-
config.enable_stream(rs.stream.color, IMAGE_WIDTH, IMAGE_HEIGHT, rs.format.bgr8, 15)
|
15 |
-
profile = pipe.start(config)
|
16 |
-
|
17 |
-
node = Node()
|
18 |
-
|
19 |
-
for event in node:
|
20 |
-
frames = pipe.wait_for_frames()
|
21 |
-
color_frame = frames.get_color_frame()
|
22 |
-
color_images = np.asanyarray(color_frame.get_data())
|
23 |
-
node.send_output("image", pa.array(color_images.ravel()))
|
24 |
-
cv2.imshow(CAMERA_ID, color_images)
|
25 |
-
if cv2.waitKey(1) & 0xFF == ord("q"):
|
26 |
-
break
|
|
|
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|
v0.0.1/record_2arms_teleop.yml
DELETED
@@ -1,125 +0,0 @@
|
|
1 |
-
nodes:
|
2 |
-
# - id: teleop_left
|
3 |
-
# custom:
|
4 |
-
# source: cargo
|
5 |
-
# args: run --release -p aloha-teleop -- --master-path /dev/ttyDXL_master_left --puppet-path /dev/ttyDXL_puppet_left
|
6 |
-
# outputs:
|
7 |
-
# - puppet_goal_position
|
8 |
-
# - puppet_state
|
9 |
-
|
10 |
-
- id: teleop_right
|
11 |
-
custom:
|
12 |
-
source: cargo
|
13 |
-
args: run --release -p aloha-teleop -- --master-path /dev/ttyDXL_master_right --puppet-path /dev/ttyDXL_puppet_right
|
14 |
-
inputs:
|
15 |
-
heartbeat: dora/timer/millis/20
|
16 |
-
outputs:
|
17 |
-
- puppet_goal_position
|
18 |
-
- puppet_state
|
19 |
-
|
20 |
-
- id: dora-record
|
21 |
-
custom:
|
22 |
-
build: cargo install --git https://github.com/dora-rs/dora dora-record
|
23 |
-
source: dora-record
|
24 |
-
inputs:
|
25 |
-
# puppet_left_goal_position: teleop_left/puppet_goal_position
|
26 |
-
action: teleop_right/puppet_goal_position
|
27 |
-
# puppet_left_state: teleop_left/puppet_state
|
28 |
-
state: teleop_right/puppet_state
|
29 |
-
record_episode: keyboard/space
|
30 |
-
cam_left_wrist: cam_saver_left_wrist/saved_image
|
31 |
-
cam_right_wrist: cam_saver_right_wrist/saved_image
|
32 |
-
cam_bottom: cam_saver_bottom/saved_image
|
33 |
-
cam_high: cam_saver_high/saved_image
|
34 |
-
|
35 |
-
- id: cam_left_wrist
|
36 |
-
custom:
|
37 |
-
source: ../nodes/webcam.py
|
38 |
-
inputs:
|
39 |
-
tick: dora/timer/millis/20
|
40 |
-
outputs:
|
41 |
-
- image
|
42 |
-
envs:
|
43 |
-
CAMERA_INDEX: 2
|
44 |
-
|
45 |
-
- id: cam_right_wrist
|
46 |
-
custom:
|
47 |
-
source: ../nodes/webcam.py
|
48 |
-
inputs:
|
49 |
-
tick: dora/timer/millis/20
|
50 |
-
outputs:
|
51 |
-
- image
|
52 |
-
envs:
|
53 |
-
CAMERA_INDEX: 22
|
54 |
-
|
55 |
-
- id: cam_bottom
|
56 |
-
custom:
|
57 |
-
source: ../nodes/webcam.py
|
58 |
-
inputs:
|
59 |
-
tick: dora/timer/millis/20
|
60 |
-
outputs:
|
61 |
-
- image
|
62 |
-
envs:
|
63 |
-
CAMERA_INDEX: 8
|
64 |
-
|
65 |
-
- id: cam_high
|
66 |
-
custom:
|
67 |
-
source: ../nodes/webcam.py
|
68 |
-
inputs:
|
69 |
-
tick: dora/timer/millis/20
|
70 |
-
outputs:
|
71 |
-
- image
|
72 |
-
envs:
|
73 |
-
CAMERA_INDEX: 14
|
74 |
-
|
75 |
-
- id: keyboard
|
76 |
-
custom:
|
77 |
-
source: ../nodes/keyboard_node.py
|
78 |
-
inputs:
|
79 |
-
heartbeat: dora/timer/millis/20
|
80 |
-
outputs:
|
81 |
-
- space
|
82 |
-
|
83 |
-
- id: cam_saver_left_wrist
|
84 |
-
custom:
|
85 |
-
source: ../nodes/lerobot_webcam_saver.py
|
86 |
-
inputs:
|
87 |
-
image: cam_left_wrist/image
|
88 |
-
record_episode: keyboard/space
|
89 |
-
outputs:
|
90 |
-
- saved_image
|
91 |
-
envs:
|
92 |
-
CAMERA_NAME: cam_left_wrist
|
93 |
-
|
94 |
-
- id: cam_saver_right_wrist
|
95 |
-
custom:
|
96 |
-
source: ../nodes/lerobot_webcam_saver.py
|
97 |
-
inputs:
|
98 |
-
image: cam_right_wrist/image
|
99 |
-
record_episode: keyboard/space
|
100 |
-
outputs:
|
101 |
-
- saved_image
|
102 |
-
envs:
|
103 |
-
CAMERA_NAME: cam_right_wrist
|
104 |
-
|
105 |
-
- id: cam_saver_bottom
|
106 |
-
custom:
|
107 |
-
source: ../nodes/lerobot_webcam_saver.py
|
108 |
-
inputs:
|
109 |
-
image: cam_bottom/image
|
110 |
-
record_episode: keyboard/space
|
111 |
-
outputs:
|
112 |
-
- saved_image
|
113 |
-
envs:
|
114 |
-
CAMERA_NAME: cam_bottom
|
115 |
-
|
116 |
-
- id: cam_saver_high
|
117 |
-
custom:
|
118 |
-
source: ../nodes/lerobot_webcam_saver.py
|
119 |
-
inputs:
|
120 |
-
image: cam_up/image
|
121 |
-
record_episode: keyboard/space
|
122 |
-
outputs:
|
123 |
-
- saved_image
|
124 |
-
envs:
|
125 |
-
CAMERA_NAME: cam_high
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
v0.0.1/replay.py
DELETED
@@ -1,27 +0,0 @@
|
|
1 |
-
from dora import Node
|
2 |
-
import pandas as pd
|
3 |
-
import pyarrow as pa
|
4 |
-
import time
|
5 |
-
|
6 |
-
|
7 |
-
TOPIC = "puppet_goal_position"
|
8 |
-
|
9 |
-
|
10 |
-
if __name__ == "__main__":
|
11 |
-
node = Node()
|
12 |
-
|
13 |
-
for event in node:
|
14 |
-
if event["type"] == "INPUT":
|
15 |
-
for action in event["value"]:
|
16 |
-
print(action, flush=True)
|
17 |
-
action = action.as_py()
|
18 |
-
|
19 |
-
df = pd.read_parquet(action + ".parquet")
|
20 |
-
|
21 |
-
initial_time = df["timestamp_utc"].iloc[0]
|
22 |
-
current_time = initial_time
|
23 |
-
for index, row in df.iterrows():
|
24 |
-
delta_time = (row["timestamp_utc"] - current_time).microseconds
|
25 |
-
current_time = row["timestamp_utc"]
|
26 |
-
time.sleep(delta_time / 1_000_000)
|
27 |
-
node.send_output(TOPIC, pa.array(row[TOPIC], type=pa.uint32()))
|
|
|
|
|
|
|
|
|
|
|
|
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|
v0.0.1/videos/cam_bottom_episode_1.mp4
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:6e4f0bcfd515557c5f2bab4c3ab9017259e0bee53472219707a226007194cf30
|
3 |
-
size 3158732
|
|
|
|
|
|
|
|
v0.0.1/videos/cam_bottom_episode_2.mp4
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:e10c84b3ef013fbff8e9c57ab11f0a70caf32be719aacc7c1cd5cf9968b79521
|
3 |
-
size 2678292
|
|
|
|
|
|
|
|
v0.0.1/videos/cam_bottom_episode_3.mp4
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:be545dfb0cc4e44e3b0ff1d5332afb55dc7db71331f0a7feac289ab2802af877
|
3 |
-
size 2198902
|
|
|
|
|
|
|
|
v0.0.1/videos/cam_bottom_episode_4.mp4
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:cf203cf3af951a0750c000dcacfe5e5e9b60df0d35bc9c3a08e97ccfd42051ab
|
3 |
-
size 6130834
|
|
|
|
|
|
|
|
v0.0.1/videos/cam_left_wrist_episode_1.mp4
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:fc61cb434dd1e11ce5e9a4c620d847c1d15a02119ec358731989193ce2d180f6
|
3 |
-
size 2300015
|
|
|
|
|
|
|
|
v0.0.1/videos/cam_left_wrist_episode_2.mp4
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:e804bc3ae0802ff2e6bc8664f595e39cb7f14806fde7a0e81ea7fc1d0752cb29
|
3 |
-
size 1133727
|
|
|
|
|
|
|
|
v0.0.1/videos/cam_left_wrist_episode_3.mp4
DELETED
Binary file (922 kB)
|
|
v0.0.1/videos/cam_left_wrist_episode_4.mp4
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:d4cb5314c5cf9ba0c99d44fb23d0dc7703eb153962c94666fb797f9806940199
|
3 |
-
size 2517780
|
|
|
|
|
|
|
|
v0.0.1/videos/cam_right_wrist_episode_1.mp4
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:44f7a972481d14c291425d06edb6adcd58604a3f06aa7adeb0e1d48881b04a04
|
3 |
-
size 3803200
|
|
|
|
|
|
|
|
v0.0.1/videos/cam_right_wrist_episode_2.mp4
DELETED
@@ -1,3 +0,0 @@
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version https://git-lfs.github.com/spec/v1
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size 2467078
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v0.0.1/videos/cam_right_wrist_episode_3.mp4
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version https://git-lfs.github.com/spec/v1
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size 2297313
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v0.0.1/videos/cam_right_wrist_episode_4.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:33d95fb5203acc5a4b65896717db822c0836510998fa3f81d6fce72b491a081b
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size 4973378
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v0.0.1/videos/cam_up_episode_1.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:5ea20f9e369f5f26380403504d1701e3b2f1fface1ce8af88b7b8e950e4985be
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size 3389350
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v0.0.1/videos/cam_up_episode_2.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:d2807059c207e75704445a58f70a22278f6398d6fd1b7ef2f59455cff531f57f
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size 2830621
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v0.0.1/videos/cam_up_episode_3.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:3b8e2672570044735cf32a28e9ad786701dca327118062002f7021290e3f32a5
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size 2379028
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v0.0.1/videos/cam_up_episode_4.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:bf09eaee125f7c244fdbd3a238d27e608ab5d87133186c3ab07876080460361b
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size 6435591
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v0.0.1/webcam.py
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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import os
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import time
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import numpy as np
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import cv2
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import pyarrow as pa
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from dora import Node
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node = Node()
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CAMERA_INDEX = int(os.getenv("CAMERA_INDEX", 0))
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CAMERA_WIDTH = 640
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-
CAMERA_HEIGHT = 480
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video_capture = cv2.VideoCapture(CAMERA_INDEX)
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-
font = cv2.FONT_HERSHEY_SIMPLEX
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-
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-
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for event in node:
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event_type = event["type"]
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if event_type == "INPUT":
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-
ret, frame = video_capture.read()
|
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if not ret:
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-
frame = np.zeros((CAMERA_HEIGHT, CAMERA_WIDTH, 3), dtype=np.uint8)
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-
cv2.putText(
|
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frame,
|
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"No Webcam was found at index %d" % (CAMERA_INDEX),
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(int(30), int(30)),
|
31 |
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font,
|
32 |
-
0.75,
|
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(255, 255, 255),
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2,
|
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-
1,
|
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-
)
|
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-
node.send_output(
|
38 |
-
"image",
|
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-
pa.array(frame.ravel()),
|
40 |
-
event["metadata"],
|
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-
)
|
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-
cv2.imshow(str(CAMERA_INDEX), frame)
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-
if cv2.waitKey(1) & 0xFF == ord("q"):
|
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-
break
|
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-
video_capture.release()
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v0.0.1/whisper_node.py
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-
import pyarrow as pa
|
2 |
-
import whisper
|
3 |
-
from pynput import keyboard
|
4 |
-
from pynput.keyboard import Key, Events
|
5 |
-
from dora import Node
|
6 |
-
|
7 |
-
import torch
|
8 |
-
import numpy as np
|
9 |
-
import pyarrow as pa
|
10 |
-
import sounddevice as sd
|
11 |
-
import gc # garbage collect library
|
12 |
-
|
13 |
-
model = whisper.load_model("base")
|
14 |
-
|
15 |
-
SAMPLE_RATE = 16000
|
16 |
-
|
17 |
-
node = Node()
|
18 |
-
|
19 |
-
|
20 |
-
def get_text(duration) -> str:
|
21 |
-
|
22 |
-
## Microphone
|
23 |
-
audio_data = sd.rec(
|
24 |
-
int(SAMPLE_RATE * duration),
|
25 |
-
samplerate=SAMPLE_RATE,
|
26 |
-
channels=1,
|
27 |
-
dtype=np.int16,
|
28 |
-
blocking=True,
|
29 |
-
)
|
30 |
-
|
31 |
-
audio = audio_data.ravel().astype(np.float32) / 32768.0
|
32 |
-
|
33 |
-
## Speech to text
|
34 |
-
audio = whisper.pad_or_trim(audio)
|
35 |
-
return model.transcribe(audio, language="en")
|
36 |
-
|
37 |
-
|
38 |
-
## Check for keyboard event
|
39 |
-
with keyboard.Events() as events:
|
40 |
-
for dora_event in node:
|
41 |
-
if dora_event["type"] == "INPUT":
|
42 |
-
event = events.get(0.1)
|
43 |
-
if (
|
44 |
-
event is not None
|
45 |
-
and (event.key == Key.alt_r or event.key == Key.ctrl_r)
|
46 |
-
and isinstance(event, Events.Press)
|
47 |
-
):
|
48 |
-
if event.key == Key.alt_r:
|
49 |
-
result = get_text(5)
|
50 |
-
node.send_output(
|
51 |
-
"text_llm", pa.array([result["text"]]), dora_event["metadata"]
|
52 |
-
)
|
53 |
-
elif event.key == Key.ctrl_r:
|
54 |
-
result = get_text(3)
|
55 |
-
node.send_output(
|
56 |
-
"text_policy",
|
57 |
-
pa.array([result["text"]]),
|
58 |
-
dora_event["metadata"],
|
59 |
-
)
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