jhurliman

# syntax=docker/dockerfile:1

ARG PYTHON_VERSION=3.11

FROM python:${PYTHON_VERSION}-slim

ARG PYTORCH_INSTALL_ARGS=""
ARG EXTRA_ARGS=""
ARG USERNAME=comfyui
ARG USER_UID=1000

jhurliman

{
  "last_node_id": 797,
  "last_link_id": 1712,
  "nodes": [
    {
      "id": 79,
      "type": "ADE_ApplyAnimateDiffModelSimple",
      "pos": [
        -0.0234637416563368,
        -326.12276996452505

jhurliman

function get_L4T_major_version_only {
  # Will return the L4T <release>.<major> version (ex: "32.6" or "32.4")
  local RELEASE=$(cat /etc/nv_tegra_release | grep -oP "R\d{2}" | grep -oP "\d{2}")
  local MAJOR_VERSION=$(cat /etc/nv_tegra_release | grep -oP "REVISION: \d{1}\.\d{1}" | grep -oP "\d{1}.\d{1}" | grep -oP "\d{1}". | grep -oP "\d{1}")
  echo "${RELEASE}.${MAJOR_VERSION}"
}

jhurliman

#include <cxxabi.h>
#include <typeinfo>

CATCH_TRANSLATE_EXCEPTION(const std::exception& e) {
  std::string s;
  int status;

  const char* name = typeid(e).name();
  char* realname = abi::__cxa_demangle(name, 0, 0, &status);
  if (realname) {

jhurliman

docker run -it --rm --privileged -v /:/host ubuntu chroot /host bash

jhurliman

#!/usr/bin/env python3

"""Publish ground truth or inference COCO JSON labels to Aquarium."""

import argparse
import os
import typing as tp
from pathlib import Path

import aquariumlearning as al

jhurliman

"""
Convert a tab-separated text file list of timestamped body marker positions
from <https://accad.osu.edu/research/motion-lab/mocap-system-and-data> into an
MCAP file.
"""

import argparse
import csv
import json
import typing as tp

jhurliman

from scipy.ndimage import center_of_mass
from typing import List

Vec2 = Tuple[float, float]


def sample_near_center_of_mass(
    mask: NDArray[np.uint8], num_samples: int = 10, distance: float = 5
) -> List[Vec2]:
    """

jhurliman

#!/usr/bin/env bash

docker run --init \
  -d \
  --restart unless-stopped \
  --hostname jupiter.martian.ag \
  --log-opt max-size=50m \
  -p 6006:6006 \
  -e DOCKER_USER=$(id -un) \
  -e DOCKER_USER_ID=$(id -u) \

jhurliman

alias killgpu='nvidia-smi --query-compute-apps=pid --format=csv,noheader | xargs --no-run-if-empty sudo kill'