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oiehot /
Created Oct 1, 2017
Building Photoshop layers with Python
import os
import comtypes.client
app = comtypes.client.CreateObject('Photoshop.Application.60') # CS6
# maya config
project_path = 'd:/project/alice/maya'
log_path = project_path + '/log'
images_path = project_path + '/images'
layers = ['master', 'prop_matte', 'shadow', 'wall_matte']
passes = ['beauty', 'N']
oiehot /
Created Nov 4, 2017
Naver cafe crawler (wip)
from selenium import webdriver
class Article():
def __init__(self, id, title, author, date, view_count=0, like_count=0, contents=''): = id
self.title = title = author = date
self.view_count = view_count
self.like_count = like_count
oiehot /
Created Nov 10, 2017
Tensorflow Custom Estimator
import numpy as np
import tensorflow as tf
# 커스텀 Estimator 모델(func)
def model_fn(features, labels, mode):
W = tf.get_variable('W', [1], dtype=tf.float64) # tf.get_variable(): Gets an existing variable with parameter or create a new one.
b = tf.get_variable('b', [1], dtype=tf.float64)
y = W * features['x'] + b
# loss(오차) 서브 그래프
# $ mosquitto_pub -t "house/main-light" -m "message from mosquitto_pub client" -u "oiehot" -P "*******"
import time
import paho.mqtt.client as mqtt
ID = 'oiehot'
oiehot /
Created Dec 16, 2018

마야 언리얼 ART


  1. 마켓플레이스에서 ARTv1을 구입하고 다운로드 한다.

  2. C:/Program Files/Epic Games/UE_4.20/Engine/Plugins/Marketplace/ARTv1/MayaTools

  3. ARTv1/MayaTools를 다른 곳으로 카피한다.] 예) D:/ARTv1/MayaTools

View AAPawn.cpp
#include "ABPawn.h"
PrimaryActorTick.bCanEverTick = true;
Capsule = CreateDefaultSubobject<UCapsuleComponent>(TEXT("CAPSULE"));
Mesh = CreateDefaultSubobject<USkeletalMeshComponent>(TEXT("MESH"));
Movement = CreateDefaultSubobject<UFloatingPawnMovement>(TEXT("MOVEMENT"));
SpringArm = CreateDefaultSubobject<USpringArmComponent>(TEXT("SPRINGARM"));
import os
import sys
import re
from PIL import Image, ImageDraw, ImageFont
from PyQt5.QtWidgets import *
from PyQt5.QtCore import pyqtSignal
from PyQt5.QtCore import QEvent
from datetime import datetime
from os.path import getmtime
import io
import requests
import pandas as pd
import json
apikey = 'API_KEY_HERE'
oiehot /
Created Nov 11, 2017
Tensorflow 심층신경망(DNN)을 이용하여 꽃 분류하기
Tensorflow 심층신경망(DNN)을 이용하여 꽃 분류하기 (Classification)
1. CSV로 부터 Iris 훈련/시험 데이터를 읽는다.
2. 분류하는 신경망을 만든다.
3. 데이터를 통한 훈련.
4. 새로운 샘플을 통해 판별하기.
SL SW PL PW species
import numpy as np
import tensorflow as tf
x = tf.feature_column.numeric_column('x', shape=[1]) # 랭크 1 텐서, 1차원 배열
feature_columns = [x]
# LinearRegressor < tf.estimator.Estimator
estimator = tf.estimator.LinearRegressor(feature_columns=feature_columns)
# 데이터 세트
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