ffmpeg官網,這是一款用指令達成的影片工具
# ubuntu
sudo apt-get install ffmpeg
1.116.136.219 | |
1.117.174.124 | |
1.14.109.65 | |
1.14.44.105 | |
1.15.247.236 | |
1.164.105.71 | |
1.164.108.115 | |
1.164.115.116 | |
1.164.120.129 | |
1.164.120.61 |
""" | |
Author: owo | |
Date: 2023/09/09 | |
Post: https://blog.o-w-o.cc/archives/streamlit-chatelements | |
License: CC BY-NC-SA 4.0 | |
""" | |
import streamlit as st | |
import numpy as np | |
MODE = st.sidebar.selectbox("選擇展示模式", ['chat_input用法', 'chat_message用法', '組合', '組合(含紀錄)']) |
# -*- coding: utf-8 -*- | |
"""DAC HW1_劉弘祥 | |
Automatically generated by Colaboratory. | |
Original file is located at | |
https://colab.research.google.com/drive/1dwcMqxWb29IuwAxoX_6xn-ct64VHOLFD | |
# DAC-Python HW1 | |
+ 時間:2023/03/01 |
{ | |
"model": "text-davinci-003", | |
"prompt": "{{1.events[].message.text}}", | |
"max_tokens": 100 | |
} |
#%% 讀取資料 | |
import pandas as pd | |
orders_df = pd.read_excel('Order1.xlsx') | |
orders_df.columns | |
#%% 合併訂單產品ID | |
orders_df["TradeProductID"] = orders_df["TradesID"] + orders_df["ProductID"] | |
#%% 篩選return |
import sys | |
print(sys.executable) # 顯示目前python解釋器的路徑 | |
print(help("modules")) # 顯示所有目前的模組 |
# %% | |
from opencc import OpenCC | |
mode_config = { | |
"簡體->繁體":"s2t", | |
"簡體->繁體台灣":"s2tw", | |
"簡體->繁體台灣(含慣用詞)": "s2twp" | |
} | |
MODE = "簡體->繁體台灣(含慣用詞)" | |
FILE_INPUT = "data/input.txt" |
ffmpeg官網,這是一款用指令達成的影片工具
# ubuntu
sudo apt-get install ffmpeg
from sklearn.ensemble import RandomForestClassifier | |
import matplotlib.pyplot as plt | |
feature_labels = list(train_X.columns) # 欄位名稱存下來等下顯示用 | |
forest = RandomForestClassifier().fit(train_X, train_Y) # 送進模型fit | |
# 用`.feature_importances_`取得重要性 | |
importances = forest.feature_importances_ | |
# 取得對應的index,等下顯示用 | |
indices = np.argsort(importances)[::-1] |
# 統計敘述(個別) | |
df.max() | |
df.mean() | |
df.count() # 回傳非nan數量 | |
# 統計敘述(統合) | |
df.describe() | |
# 唯一值 | |
df.apply(lambda x:x.unique(),axis=0) # uniques by columns |