A list of useful commands for the FFmpeg command line tool.
Download FFmpeg: https://www.ffmpeg.org/download.html
Full documentation: https://www.ffmpeg.org/ffmpeg.html
| I was drawn to programming, science, technology and science fiction | |
| ever since I was a little kid. I can't say it's because I wanted to | |
| make the world a better place. Not really. I was simply drawn to it | |
| because I was drawn to it. Writing programs was fun. Figuring out how | |
| nature works was fascinating. Science fiction felt like a grand | |
| adventure. | |
| Then I started a software company and poured every ounce of energy | |
| into it. It failed. That hurt, but that part is ok. I made a lot of | |
| mistakes and learned from them. This experience made me much, much |
A list of useful commands for the FFmpeg command line tool.
Download FFmpeg: https://www.ffmpeg.org/download.html
Full documentation: https://www.ffmpeg.org/ffmpeg.html
I’m currently working (I’m just at the beginning, and I’m quite slow) on a personal project that will use Keepass files (kdb and kdbx).
I tried to find some documentation about .kdb and .kdbx format, but I didn’t find anything, even in the Keepass official website. I you want to know how these file formats are structured, you must read Keepass’s source code. So I wrote this article that explains how Keepass file format are structured, maybe it will help someone.
Probably one of the easiest things you'll ever do with gpg
Install Keybase: https://keybase.io/download and Ensure the keybase cli is in your PATH
First get the public key
keybase pgp export | gpg --import
Next get the private key
I'm going to walk you through the steps for setting up a AWS Lambda to talk to the internet and a VPC. Let's dive in.
So it might be really unintuitive at first but lambda functions have three states.
Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.
The short answer: No. While Cloud Vision provides bounding polygon coordinates in its output, it doesn't provide it at the word or region level, which would be needed to then calculate the data delimiters.
On the other hand, the OCR quality is pretty good, if you just need to identify text anywhere in an image, without regards to its physical coordinates. I've included two examples:
####### 1. A low-resolution photo of road signs
| var expect = require('chai').expect; | |
| // store | |
| const createStore = (reducer) => { | |
| let listeners = []; | |
| let state; | |
| const getState = () => state; | |
| const subscribe = (listener) => { |
| # The following produces DetachedInstanceError | |
| app = Flask(__name__) | |
| db = SQLAlchemy(app) | |
| class Foo(db.Model): | |
| id = db.Column(db.Integer, primary_key=True) | |
| foo = Foo() | |
| db.session.add(foo) |
| ''' | |
| A minimal example of how to use Paste and WebOb to build a custom | |
| WSGI app and serve it. | |
| Depends on: | |
| * paste - http://pypi.python.org/pypi/Paste | |
| * webob - http://pypi.python.org/pypi/WebOb/1.1.1 | |
| * routes - http://pypi.python.org/pypi/Routes/1.12.3 | |
| I (marmida) still think this is less appropriate than using CouchDB; you'll need |