#105 Colorizing and Restoring Old Images with Deep Learning
Published November 23, 2018
|
24 min
    Download
    Add to queue
    Copy URL
    Show notes

    Sponsored by DigitalOcean: pythonbytes.fm/digitalocean

    Brian #1: Colorizing and Restoring Old Images with Deep Learning

    • Text interview by Charlie Harrington of Jason Antic, developer of DeOldify
    • A whole bunch of machine learning buzzwords that I don’t understand in the slightest combine to make a really cool to to make B&W photos look freaking amazing.
    • “This is a deep learning based model. More specifically, what I've done is combined the following approaches:
      • Self-Attention Generative Adversarial Network
      • Training structure inspired by (but not the same as) Progressive Growing of GANs.
      • Two Time-Scale Update Rule.
      • Generator Loss is two parts: One is a basic Perceptual Loss (or Feature Loss) based on VGG16. The second is the loss score from the critic.”
    Michael #2: PlatformIO IDE for VSCode

    • via Jason Pecor
    • PlatformIO is an open source ecosystem for IoT development
    • Cross-platform IDE and unified debugger. Remote unit testing and firmware updates
    • Built on Visual Studio Code which has a nice extension for Python
    • PlatformIO, combined with the features of VSCode provides some great improvements for project development over the standard Arduino IDE for Arduino-compatible microcontroller based solutions.
    • Some of these features are paid, but it’s a reasonable price
    • With Python becoming more popular for microcontroller design, as well, this might be a very nice option for designers.
    • And for Jason’s, specifically, it provides a single environment that can eventually be configured to handle doing the embedded code design, associated Python supporting tools mods, and HDL development.
    • The PlatformIO Core written in Python. Python 2.7 (hiss…)
    • Jason’s test drive video from Tuesday: Test Driving PlatformIO IDE for VSCode
    Brian #3: Python Data Visualization 2018: Why So Many Libraries?

    • Nice overview of visualization landscape, by Anaconda team
    • Differentiating factors, API types, and emerging trends
    • Related: Drawing Data with Flask and matplotlib
      • Finally! A really simple example app in Flask that shows how to both generate and display matplotlib plots.
      • I was looking for something like this about a year ago and didn’t find it.
    Michael #4: coder.com - VS Code in the cloud

    • Full Visual Studio Code, but in your browser
    • Code in the browser
    • Access up to 96 cores
    • VS Code + extensions, so all the languages and features
    • Collaborate in real time, think google docs
    • Access linux from any OS
    • Note: They sponsored an episode of Talk Python To Me, but this is not an ad here...
    Brian #5: By Welcoming Women, Python’s Founder Overcomes Closed Minds In Open Source

    • Forbes’s article about Guido and the Python community actively working to get more women involved in core development as well as speaking at conferences.
    • Good lessons for other projects, and work teams, about how you cannot just passively “let people join”, you need to work to make it happen.
    Michael #6: Machine Learning Basics

    Extras:

      15
      15
        0:00:00 / 0:00:00