Minimal example: transcode from MP3 to WMA:
ffmpeg -i input.mp3 output.wma
You can get the list of supported formats with:
ffmpeg -formats
Convert WAV to MP3, mix down to mono (use 1 audio channel), set bit rate to 64 kbps and sample rate to 22050 Hz:
| import sounddevice as sd | |
| duration = 5 # seconds | |
| import wave | |
| from scipy.io import wavfile | |
| def writeWavFile(frames,width=2L,fileName="test.wav"): | |
| #writing the wave file | |
| wf = wave.open(fileName, 'wb') | |
| wf.setnchannels(1) | |
| wf.setsampwidth(2L) |
| import sys | |
| import time | |
| def spinning_cursor(): | |
| while True: | |
| for cursor in '|/-\\': | |
| yield cursor | |
| spinner = spinning_cursor() | |
| for _ in range(50): |
| from pydispatch import dispatcher | |
| SIGNAL = 'my-first-signal' | |
| def handle_event( **kwargs ): | |
| """Simple event handler""" | |
| print 'Signal was sent by', kwargs['message'] | |
| dispatcher.connect( handle_event, signal=SIGNAL, sender=dispatcher.Any ) | |
| first_sender = "sender" | |
| second_sender = "sender" |
| import re | |
| from datetime import datetime, timedelta | |
| datas=["01:48PM","Yesterday 06:31PM", "04/08 05:25PM","11/07/2018 05:12PM"] | |
| def date_parse(data): | |
| pattern1 = "(\d{2}):(\d{2})([AaPp][Mm])" |
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <meta charset="utf-8"/> | |
| <meta http-equiv="X-UA-Compatible" content="IE=edge"/> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <title>Navin - My Portifolo | Developer </title> | |
| </head> | |
| <style> | |
| #web, #tablet, #mobile { display: none;} |
| ================================================================================================================================================================================================================ | |
| _ ____ ___ ____ _ _ ____ ____ _ ____ _____ _ _ ____ _____ | |
| / \ / ___|_ _/ ___| | / \ | __ ) / ___| / \ | _ \| ____| \ | |/ ___| ____| | |
| / _ \ \___ \| | | | | / _ \ | _ \ _____| | / _ \ | | | | _| | \| | | | _| | |
| / ___ \ ___) | | |___| |___ / ___ \| |_) |_____| |___ / ___ \| |_| | |___| |\ | |___| |___ | |
| /_/ \_\____/___\____|_____/_/ \_\____/ \____/_/ \_\____/|_____|_| \_|\____|_____| | |
| =================================================================================================================================================================================================================== | |
| Snippet by Navin TheNapster |
https://medium.com/@medasuryatej/install-tensorflow-gpu-2-0-f4e215438199
I have encountered this problem before. When you use CUDA 8.0,the file cupti64_80.dll lies in C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\extras\CUPTI\libx64. I just fixed the problem by copying the dll into C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin, and the file cupti.lib in the same location into C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\lib\x64.
On Nvidia Control Panel, there is a Developer-Manage GPU Performance Counters section. Default toggle is to limit access to GPU preformance counters to admin users only. But you must select 'Allow acces to the GPU prformance counters to all users'. Once toggled, access permissions to the cupti dll are resolved.
| # Windows | |
| netsh wlan show profiles | |
| netsh wlan show profile name=<wifi_name_ssid> key=clear | |
| https://www.online-tech-tips.com/computer-tips/view-saved-wifi-passwords-windows/ | |
| #ubuntu | |
| sudo cat /etc/NetworkManager/system-connections/<wiFi_name_ssid>.nmconnection | |
| https://itsfoss.com/how-to-find-saved-wireless-wifi-passwords-ubuntu/ |
| # to read data | |
| df_data=pd.read_csv("csvfile.csv") | |
| #replace value in columns | |
| df_data = df_data.replace({ | |
| 'colname': { | |
| 'value': 'new_value' | |
| } | |
| }) |
