Sairahcaz

# SETUP #
DOMAIN=example.com
PROJECT_REPO="[email protected]:example.com/app.git"
AMOUNT_KEEP_RELEASES=5

RELEASE_NAME=$(date +%s--%Y_%m_%d--%H_%M_%S)
RELEASES_DIRECTORY=~/$DOMAIN/releases
DEPLOYMENT_DIRECTORY=$RELEASES_DIRECTORY/$RELEASE_NAME

# stop script on error signal (-e) and undefined variables (-u)

dhh

# THIS LINUX SETUP SCRIPT HAS MORPHED INTO A WHOLE PROJECT: HTTPS://OMAKUB.ORG
# PLEASE CHECKOUT THAT PROJECT INSTEAD OF THIS OUTDATED SETUP SCRIPT.
#
#

# Libraries and infrastructure
sudo apt update -y
sudo apt install -y \
	docker.io docker-buildx \
	build-essential pkg-config autoconf bison rustc cargo clang \

Maxiviper117

// Import the Sass math module for division and other mathematical operations
@use "sass:math";

// Function to generate a series of color shades from a base color
@function generate-shades($base-color) {
    // Initialize an empty map to store the shades
    $shades: ();
    // Define the scale for the shades
    $scale: (50, 100, 200, 300, 400, 500, 600, 700, 800, 900, 950);
    

jo-chemla

# py kapture-cropper.py -i dataset-kapture\ --border_px 0 --scale_factor 1 -v

import kapture
import kapture.io.csv as csv
from PIL import Image
from kapture.io.csv import kapture_to_dir
import os, logging, argparse
import kapture.utils.logging

logger = logging.getLogger("kapture-cropper")

hwchase17

from langchain.chat_models import ChatOpenAI
from pydantic import BaseModel, Field
from langchain.document_loaders import UnstructuredURLLoader
from langchain.chains.openai_functions import create_extraction_chain_pydantic

class LLMItem(BaseModel):
    title: str = Field(description="The simple and concise title of the product")
    description: str = Field(description="The description of the product")

def main():

chunibyo-wly

import json, os, shutil
from os.path import join, basename
from tqdm import tqdm
import numpy as np

MESHROOM = r"E:\workspace\dataset\01_DTU\cache\20\meshroom\MeshroomCache\ConvertSfMFormat\4b9ced4a64f3f996f7650f3d5ed9e27c4774a7c9\sfm.json"
COLMAP = r"E:\workspace\dataset\01_DTU\cache\20\colmap"


def make_dir(folder):

aradalvand

*This Dockerfile is intended for SvelteKit applications that use adapter-node. So, the Dockerfile below assumes that you have already installed and configured the adapter.

Dockerfile:

FROM node:18-alpine AS builder
WORKDIR /app
COPY package*.json .
RUN npm ci
COPY . .
RUN npm run build

href

from collections import namedtuple
def convert(dictionary):
    return namedtuple('GenericDict', dictionary.keys())(**dictionary)

"""
>>> d = dictionary(a=1, b='b', c=[3])
>>> named = convert(d)
>>> named.a == d.a
True
>>> named.b == d.b