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@raysan5
raysan5 / custom_game_engines_small_study.md
Last active April 26, 2024 11:50
A small state-of-the-art study on custom engines

CUSTOM GAME ENGINES: A Small Study

a_plague_tale

A couple of weeks ago I played (and finished) A Plague Tale, a game by Asobo Studio. I was really captivated by the game, not only by the beautiful graphics but also by the story and the locations in the game. I decided to investigate a bit about the game tech and I was surprised to see it was developed with a custom engine by a relatively small studio. I know there are some companies using custom engines but it's very difficult to find a detailed market study with that kind of information curated and updated. So this article.

Nowadays lots of companies choose engines like Unreal or Unity for their games (or that's what lot of people think) because d

@liorshk
liorshk / mlflow_gridsearch.py
Created April 22, 2020 15:24
Create MLFlow runs with Sklearn Gridsearch object
def log_run(gridsearch: sklearn.GridSearchCV, experiment_name: str, model_name: str, run_index: int, conda_env, tags={}):
"""Logging of cross validation results to mlflow tracking server
Args:
experiment_name (str): experiment name
model_name (str): Name of the model
run_index (int): Index of the run (in Gridsearch)
conda_env (str): A dictionary that describes the conda environment (MLFlow Format)
tags (dict): Dictionary of extra data and tags (usually features)
@jzakiya
jzakiya / twinprimes_ssoz.cr
Last active January 10, 2024 15:44
Twinprimes generator, multi-threaded, using SSoZ (Segmented Sieve of Zakiya), written in Crystal
# This Crystal source file is a multiple threaded implementation to perform an
# extremely fast Segmented Sieve of Zakiya (SSoZ) to find Twin Primes <= N.
# Inputs are single values N, or ranges N1 and N2, of 64-bits, 0 -- 2^64 - 1.
# Output is the number of twin primes <= N, or in range N1 to N2; the last
# twin prime value for the range; and the total time of execution.
# Code originally developed on a System76 laptop with an Intel I7 6700HQ cpu,
# 2.6-3.5 GHz clock, with 8 threads, and 16GB of memory. Parameter tuning
# probably needed to optimize for other hardware systems (ARM, PowerPC, etc).
@cashiwamochi
cashiwamochi / simple_triangulation.cc
Last active September 16, 2023 14:19
This code is used for simple triangulation. It uses findEssentialMat, recoverPose, triangulatePoints in OpenCV. For viewer, PCL is used. You can watch 3D points and 2 camera poses. I checked alcatraz2.jpg and alcatraz1.jpg in pcv_data.zip (https://www.oreilly.co.jp/pub/9784873116075/). Perhaps there is something wrong ( actually it looks working…
#include <opencv2/opencv.hpp>
#include <pcl/common/common_headers.h>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/point_cloud.h>
#include <pcl/visualization/pcl_visualizer.h>
#include <Eigen/Core>
#include <Eigen/LU>
@bishboria
bishboria / springer-free-maths-books.md
Last active April 25, 2024 06:27
Springer made a bunch of books available for free, these were the direct links
@RichardBronosky
RichardBronosky / pep8_cheatsheet.py
Created December 27, 2015 06:25
PEP-8 cheatsheet
#! /usr/bin/env python
# -*- coding: utf-8 -*-
"""This module's docstring summary line.
This is a multi-line docstring. Paragraphs are separated with blank lines.
Lines conform to 79-column limit.
Module and packages names should be short, lower_case_with_underscores.
Notice that this in not PEP8-cheatsheet.py
@GilLevi
GilLevi / README.md
Last active June 17, 2023 20:58
Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns

Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns

Convolutional neural networks for emotion classification from facial images as described in the following work:

Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns, Proc. ACM International Conference on Multimodal Interaction (ICMI), Seattle, Nov. 2015

Project page: http://www.openu.ac.il/home/hassner/projects/cnn_emotions/

If you find our models useful, please add suitable reference to our paper in your work.

@bpierre
bpierre / README.md
Last active February 15, 2024 18:40
Switch To Vim For Good

Switch To Vim For Good

NOTE: This guide has moved to https://github.com/bpierre/switch-to-vim-for-good

This guide is coming from an email I used to send to newcomers to Vim. It is not intended to be a complete guide, it is about how I switched myself.

My decision to switch to Vim has been made a long time ago. Coming from TextMate 1, I wanted to learn an editor that is Open Source (so I don’t lose my time learning a tool that can be killed), cross platform (so I can use it everywhere), and powerful enough (so I won’t regret TextMate). For these reasons, Vim has always been the editor I wanted to learn, but it took me several years before I did it in a way that works for me. I tried to switch progressively, using the Janus Vim distribution for a few months, then got back to using TextMate 2 for a time, waiting for the next attempt… here is what finally worked for me.

Original gist with comments: https://gist.github.com/bpierre/0a0025d348b6001394e0

@romainl
romainl / .ctags
Last active June 14, 2023 09:19
My ctags config
--langdef=less
--langmap=less:.less
--regex-less=/^[ \t&]*#([A-Za-z0-9_-]+)/\1/i,id,ids/
--regex-less=/^[ \t&]*\.([A-Za-z0-9_-]+)/\1/c,class,classes/
--regex-less=/^[ \t]*(([A-Za-z0-9_-]+[ \t\n,]+)+)\{/\1/t,tag,tags/
--regex-less=/^[ \t]*@media\s+([A-Za-z0-9_-]+)/\1/m,media,medias/
--regex-less=/^[ \t]*(@[A-Za-z0-9_-]+):/\1/v,variable,variables/
--regex-less=/\/\/[ \t]*(FIXME|TODO)[ \t]*\:*(.*)/\1/T,Tag,Tags/
--langdef=scss
@kastnerkyle
kastnerkyle / optimizers.py
Last active January 12, 2021 13:46
Theano optimizers
# Authors: Kyle Kastner
# License: BSD 3-clause
import theano.tensor as T
import numpy as np
import theano
class rmsprop(object):
"""
RMSProp with nesterov momentum and gradient rescaling