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Blenderで動画作った際の副産物置き場。

• EC2向けのネットワークレンダ用サービススクリプト
• Blenderマクロ（Python）
• OpenEXR連番から動画作成

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@echo off
echo Start
call "C:\dow\MyDowUpdate.bat"
call "C:\dow\MyLaunchServer.bat"
echo end

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global_config {
  default_context {
    array_class: "CudaCachedArray"
    device_id: "0"
    backends: "cudnn:float"
    backends: "cuda:float"
    backends: "cpu:float"
  }
}
training_config {

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#!/bin/bash
#
# rotate_desktop.sh
#
# Rotates modern Linux desktop screen and input devices to match. Handy for
# convertible notebooks. Call this script from panel launchers, keyboard
# shortcuts, or touch gesture bindings (xSwipe, touchegg, etc.).
#
# Using transformation matrix bits taken from:
#   https://wiki.ubuntu.com/X/InputCoordinateTransformation

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# Tezos Account Addres ("tz...") -> Get account OBJKT list
#     -> Get IPFS addresses -> IPFS Pinning
#
# Requirements
# ------------
#
# - IPFS Desktop (https://docs.ipfs.io/install/ipfs-desktop/) or CLI tool
#
# - python package
#

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glslViewer.exe .\square_2_alter.frag -w 1920 -h 1920 --nocursor --headless -E sequence,0,11,60
ffmpeg -framerate 60 -start_number 1 -i %05d.png -c:v libx264 -preset placebo -crf 16 -pix_fmt yuv420p _output.mp4

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<?xml version="1.0" encoding="utf-8" ?>
<CodeSnippets  xmlns="http://schemas.microsoft.com/VisualStudio/2005/CodeSnippet">
    <CodeSnippet Format="1.0.0">
        <Header>
            <Title>Define a DependencyProperty</Title>
            <Shortcut>propdpng</Shortcut>
            <Description>Code snippet for a property using DependencyProperty as the backing store</Description>
            <Author>Microsoft Corporation</Author>
            <SnippetTypes>
                <SnippetType>Expansion</SnippetType>

ugai

import os
import shutil
from argparse import ArgumentParser, Namespace

import numpy as np
from loguru import logger


def print_args(args: Namespace):
    for arg in vars(args):

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"""
Conversation Retrieval Chain
https://python.langchain.com/docs/get_started/quickstart#conversation-retrieval-chain
"""

from langchain.chains import create_history_aware_retriever, create_retrieval_chain
from langchain.chains.combine_documents import create_stuff_documents_chain
from langchain_community.document_loaders import WebBaseLoader
from langchain_community.vectorstores import FAISS
from langchain_core.messages import AIMessage, HumanMessage