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import numpy as np | |
from sklearn.svm import SVR | |
import matplotlib.pyplot as plt | |
# Generate sample data | |
X = np.sort(5 * np.random.rand(40, 1), axis=0) | |
y = np.sin(X).ravel() | |
# Add noise to targets | |
y[::5] += 3 * (0.5 - np.random.rand(8)) |
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// VREX_WIN Client | |
// 1. 변수선언 | |
private IntPtr client; | |
// x,y coord; | |
static float x_coord; | |
static float y_coord; | |
// UI Text Content | |
private static String logContent = ""; |
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// 1. PiPeClientTest.dll 파일 추가 | |
#pragma comment(lib,"VREX_WIN.lib") | |
// 2. 헤더 파일 추가 | |
#include "VREX.h" | |
using namespace std; | |
// 3. Gaze Point를 받는 콜백함수 작성 | |
void getGazePt(float x, float y) { | |
_tprintf(_T("getGazePt %f %f \n"),x,y); |
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from __future__ import print_function | |
import keras | |
import os | |
from keras.datasets import mnist | |
from keras.models import Sequential | |
from keras.layers import Dense, Dropout, Flatten | |
from keras.layers import Conv2D, MaxPooling2D | |
from keras import backend as K | |
from keras.models import load_model |
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def conv2d_bn(x, filters, kernel_size, strides=1, padding='same', activation='relu', use_bias=False, name=None): | |
x = Conv2D(filters, kernel_size, strides=strides, padding=padding, use_bias=use_bias, kernel_initializer='he_normal', name=name)(x) | |
if not use_bias: | |
bn_axis = 1 if K.image_data_format() == 'channels_first' else 3 | |
bn_name = None if name is None else name + '_bn' | |
x = BatchNormalization(axis=bn_axis, scale=False, name=bn_name)(x) | |
return x | |
def mfm(x): | |
shape = K.int_shape(x) |
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const http = require('http'); | |
const url = require('url'); | |
const fs = require('fs'); | |
const path = require('path'); | |
const port = process.argv[2] || 9000; | |
http.createServer(function (req, res) { | |
console.log(`${req.method} ${req.url}`); | |
// parse URL |
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from dynamikontrol import Module | |
module = Module() | |
module.motor.angle(45) |
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from dynamikontrol import Module | |
module = Module() | |
module.motor.speed(1000) |
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//Reference: https://github.com/hnasr/javascript_playground/tree/master/chatgpt-twochats | |
//go to chat.openai.com | |
//paste the following code in the console | |
document.body.removeChild(document.body.firstChild) | |
document.body.innerHTML = `<table> | |
<tr> | |
<td><iframe style = 'width:600px;height:1200px' id = 'cf1' src = 'https://chat.openai.com/chat/36327d80-e9a4-4cd2-a4e7-4323cf4f05c8'></iframe></td> | |
<td><iframe style = 'width:600px;height:1200px' id = 'cf2' src = 'https://chat.openai.com/chat/1aa8ab10-2e0a-4856-8d83-7b77a4471567'></iframe></td> |