| // Don't forget to add to the project: | |
| // 1. DeepLabV3 - https://developer.apple.com/machine-learning/models/ | |
| // 2. CoreMLHelpers - https://github.com/hollance/CoreMLHelpers | |
| enum RemoveBackroundResult { | |
| case background | |
| case finalImage | |
| } | |
| extension UIImage { |
I'm writing this gist for my own records but it might help someone else too.
Support for Catalina has improved a lot since the update was first rolled out.
Note: See the NixOS manual for discussion of the --darwin-use-unencrypted-nix-store-volume option.
| // Image+Trim.swift | |
| // | |
| // Copyright © 2020 Christopher Zielinski. | |
| // https://gist.github.com/chriszielinski/aec9a2f2ba54745dc715dd55f5718177 | |
| // | |
| // Permission is hereby granted, free of charge, to any person obtaining a copy | |
| // of this software and associated documentation files (the "Software"), to deal | |
| // in the Software without restriction, including without limitation the rights | |
| // to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
| // copies of the Software, and to permit persons to whom the Software is |
| #!/bin/bash | |
| echo "Restarting bluetooth service..." | |
| blueutil -p 0 && sleep 1 && blueutil -p 1 | |
| echo "Waiting bluetooth service to be restored..." | |
| until blueutil -p | grep "1" >/dev/null; do sleep 1; done | |
| echo "Searching for devices not connected..." | |
| devices=($(blueutil --paired | grep "not connected" | awk -F '[ ,]' '{print $2}')) |
GNU parallel is a command line tool for running jobs in parallel.
parallel is awesome and belongs in the toolbox of every programmer. But I found the docs a bit overwhelming at first. Fortunately, you can start being useful with parallel with just a few basic commands.
Let's compare sequential and parallel execution of the same compute-intensive task.
Imagine you have a folder of .wav audio files to convert to .flac:
The libdispatch is one of the most misused API due to the way it was presented to us when it was introduced and for many years after that, and due to the confusing documentation and API. This page is a compilation of important things to know if you're going to use this library. Many references are available at the end of this document pointing to comments from Apple's very own libdispatch maintainer (Pierre Habouzit).
My take-aways are:
You should create very few, long-lived, well-defined queues. These queues should be seen as execution contexts in your program (gui, background work, ...) that benefit from executing in parallel. An important thing to note is that if these queues are all active at once, you will get as many threads running. In most apps, you probably do not need to create more than 3 or 4 queues.
Go serial first, and as you find performance bottle necks, measure why, and if concurrency helps, apply with care, always validating under system pressure. Reuse
A string identifying the build system action being performed.
The locations of any sparse SDKs that should be layered on top of the one specified by Base SDK (SDKROOT). If more than one SDK is listed, the first one has highest precedence. Every SDK specified in this setting should be a "sparse" SDK, for example, not an SDK for an entire macOS release.
| /// RepeatingTimer mimics the API of DispatchSourceTimer but in a way that prevents | |
| /// crashes that occur from calling resume multiple times on a timer that is | |
| /// already resumed (noted by https://github.com/SiftScience/sift-ios/issues/52 | |
| class RepeatingTimer { | |
| let timeInterval: TimeInterval | |
| init(timeInterval: TimeInterval) { | |
| self.timeInterval = timeInterval | |
| } |
Author: Chris Lattner