플러터 다트(dart) Toast (2022.04.28)

import 'package:flutter/material.dart'; import 'package:fluttertoast/fluttertoast.dart'; void main() => runApp(MyApp()); class MyApp extends StatelessWidget { MyApp({Key? key}) : super(key: key); @override Widget build(BuildContext context) { return MaterialApp( title: 'Appbar', theme: ThemeData(primarySwatch: Colors.red), home: MyPage()); } } class MyPage extends StatelessWidget { const MyPage(..

플러터 다트(dart) 빌더(Builder widget)위젯 없이 스낵바(Snack bar)(2022.04.28)

import 'package:flutter/material.dart'; void main() => runApp(MyApp()); class MyApp extends StatelessWidget { MyApp({Key? key}) : super(key: key); @override Widget build(BuildContext context) { return MaterialApp( title: 'Appbar', theme: ThemeData(primarySwatch: Colors.red), home: MyPage()); } } class MyPage extends StatelessWidget { const MyPage({Key? key}) : super(key: key); @override Widget b..

(NLP) Prompt Learning 발표 (2022-04-27)

Attention Is All You Need https://arxiv.org/pdf/1706.03762.pdf BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding https://arxiv.org/pdf/1810.04805.pdf ALBERT: A Lite BERT for Self-supervised Learning of Language Representations https://arxiv.org/pdf/1909.11942.pdf Improving language understanding by generative pre-training https://s3-us-west-2.amazonaws.com/openai-a..

플러터 다트(dart) 메뉴아이콘(2022.04.25)

import 'package:flutter/material.dart'; void main() => runApp(MyApp()); class MyApp extends StatelessWidget { const MyApp({Key? key}) : super(key: key); @override Widget build(BuildContext context) { return MaterialApp( debugShowCheckedModeBanner: false, title: 'Appbar', theme: ThemeData( primarySwatch: Colors.red // ThemeData를 통해서 전체적인 Theme을 설정할 수 있습니다. ), home: MyPage(), ); } } class MyPage e..

플러터 다트(dart) 핵심정리(2022.04.25)

// ignore_for_file: prefer_const_constructors, prefer_const_literals_to_create_immutables import 'package:flutter/material.dart'; void main() => runApp(MyApp()); class MyApp extends StatelessWidget { const MyApp({Key? key}) : super(key: key); @override Widget build(BuildContext context) { return MaterialApp( debugShowCheckedModeBanner: false, title: 'BBANTO', home: Grade(), ); } } class Grade ex..

(NLP 연구) prompt based learning 04.18

논문 리스트 정리 Attention Is All You Need https://arxiv.org/pdf/1706.03762.pdf BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding https://arxiv.org/pdf/1810.04805.pdf ALBERT: A Lite BERT for Self-supervised Learning of Language Representations https://arxiv.org/pdf/1909.11942.pdf Improving language understanding by generative pre-training https://s3-us-west-2.amazonaws.co..

(NIA 데이터셋 과제준비) Oxford-IIIT Pet Dataset

# Images: https://www.robots.ox.ac.uk/~vgg/data/pets/data/images.tar.gz # Annotations: https://www.robots.ox.ac.uk/~vgg/data/pets/data/annotations.tar.gz from IPython.display import Image, display from tensorflow.keras.preprocessing.image import load_img import PIL from PIL import ImageOps import os from tensorflow.keras import layers input_dir = "/root/yj/yj/Kaggle/data/images" target_dir = "/r..

Brain MRI Images for Brain Tumor Detection

def load_data(dir_list, image_size): # load all images in a directory X = [] y = [] image_width, image_height = image_size for directory in dir_list: for filename in listdir(directory): image = cv2.imread(directory+'/'+filename) image = crop_brain_contour(image, plot=False) image = cv2.resize(image, dsize=(image_width, image_height), interpolation=cv2.INTER_CUBIC) # normalize values image = imag..

2022_Ukraine Russia War visualization

import numpy as np import pandas as pd import plotly import plotly.graph_objs as go import plotly.express as px from plotly.subplots import make_subplots import seaborn as sns ru_losses_per = pd.read_csv('/root/yj/yj/Kaggle/data/Ukraine_war/russia_losses_personnel.csv') ru_losses_eq = pd.read_csv('/root/yj/yj/Kaggle/data/Ukraine_war/russia_losses_equipment.csv') x, y = ru_losses_per['date'], ru_..

Age, Gender & Ethnicity Prediction

import numpy as np import pandas as pd import tensorflow as tf import tensorflow.keras.layers as L import matplotlib.pyplot as plt import plotly.graph_objects as go import plotly.express as px from sklearn.model_selection import train_test_split Loading Dataset data = pd.read_csv("/root/yj/yj/Kaggle/data/age_gender/age_gender.csv") data['pixels'] = data['pixels'].apply(lambda x : np.array(x.spli..

(NLP 연구) The Long-Document Transformer 04.06 발표

(NLP 연구) The Long-Document Transformer 04.01 (데이터셋 LSH 코딩)

import glob import os import io import string import re import random import spacy import torchtext from torchtext.vocab import Vectors import re import numpy as np import itertools from random import shuffle import time from tqdm import tqdm from numba import jit def get_split(text: str): text = text.replace('\t', " ") text = text.replace('\\', "") text = text.replace('--', "") text = re.sub(' ..