t-mat

// Win32 : Minimal VST 2.x Synth host in C++11.
//
// This is a simplified version of the following project by hotwatermorning :
//      A sample VST Host Application for C++ Advent Calendar 2013 5th day.
//      https://github.com/hotwatermorning/VstHostDemo
//
// Usage :
//      1. Compile & Run this program.
//      2. Select your VST Synth DLL.
//      3. Press QWERTY, ZXCV, etc.

bkaradzic

Orthodox C++

What is Orthodox C++?

Orthodox C++ (sometimes referred as C+) is minimal subset of C++ that improves C, but avoids all unnecessary things from so called Modern C++. It's exactly opposite of what Modern C++ suppose to be.

Why not Modern C++?

hillin

FASTBuild is an open-source distributed build system, which could be a free alternative to Incredibuild. Unreal Engine 4 (UE4) does not support FASTBuild natively, however it's not hard to integrate it manually.

Integrate FASTBuild with UE4

Install FASTBuild

We assume you already have the full UE4 source code. First you'll need to grab the latest FASTBuild tools from here. We use v0.93 Windows x64 version in this tutorial. Download it and extract all the files. Here you have several choices:

• Place the files under any folder which could be found with your system's PATH environment variable. To see where these folders are, run the PATH command in a command prompt window;
• Place the files under the Engine\Binaries\ThirdParty\FASTBuild folder of your engine. This is the recommended place;
• Place the files anywhere you like. This is not recommended because you'll have to hard-code the path later.

trentpolack

// Generally, developers in UE4 tend towards the following convention for enumerations:
UENUM( BlueprintType )
enum class ENoiseGeneratorCellularType : uint8
{
	NGCT_Natural			UMETA( DisplayName = "Natural" ),
	NGCT_Euclidean			UMETA( DisplayName = "Euclidean" ),
	NGCT_Manhattan			UMETA( DisplayName = "Manhattan" ),

	NGCT_Max			UMETA( Hidden )
};

sbarratt

def get_jacobian(net, x, noutputs):
    x = x.squeeze()
    n = x.size()[0]
    x = x.repeat(noutputs, 1)
    x.requires_grad_(True)
    y = net(x)
    y.backward(torch.eye(noutputs))
    return x.grad.data

mwufi

# First let's update all the packages to the latest ones with the following command
sudo apt update -qq

# Now we want to install some prerequisite packages which will let us use HTTPS over apt
sudo apt install apt-transport-https ca-certificates curl software-properties-common -qq

# After that we will add the GPG key for the official Docker repository to the system
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -

# We will add the Docker repository to our APT sources

boocs

Announcement

Please stop using this extension and Microsoft's C++ extension for Unreal code completion.

clangd

The VSCode extension clangd has blazing fast code completion in comparison. I've made a VSCode extension for it:

https://github.com/boocs/unreal-clangd

You will use clangd for code completion(Intellisense) and use Microsoft's C++ extension for Building/Debugging

emilianavt

Best VTuber software

This is a list of the most commonly used and relevant vtubing software. The "best" will always be subjective and depend on your specific requirements. Overall, the information in this list is as accurate as I could figure it out, but there might be errors or some details might become out of date. If you find anything that needs to be corrected, please let me know. You can also note it in a comment.

Additional explanations:

• iPhone means that an iPhone is basically required
• iFacialMocap support means that tracking data can be received from the iFacialMocap iPhone app
• VMC protocol means that the application can send and/or receive tracking data from other VMC protocol capable applications, allowing the combination of multiple tracking methods (e.g. VSeeFace receiving VR tracking from Virtual Motion Capture and iPhone/ARKit face tracking from Waidayo)
• Tobii means that the Tobii eye tracker is supported

jachiam

# Script for converting a HF Diffusers saved pipeline to a Stable Diffusion checkpoint.
# *Only* converts the UNet, VAE, and Text Encoder.
# Does not convert optimizer state or any other thing.
# Written by jachiam

import argparse
import os.path as osp

import torch

harubaru

Waifu Diffusion 1.4 Overview

_{An image generated at resolution 512x512 then upscaled to 1024x1024 with Waifu Diffusion 1.3 Epoch 7.}

Goals

• Improving image generation at different aspect ratios using conditional masking during training. This will allow for the entire image to be seen during training instead of center cropped images, which will allow for better results when generating full body images, portraits, and improving the composition.
• Expanded the input context from 77 tokens to 231 tokens or perhaps to an unlimited amount of tokens. Out of 77 tokens for input, only 75 are useable. This does not give nearly enough room for complex prompting that requires a lot of detail.