Home Database Mysql Tutorial 新版本cocos2d-x工程项目的创建(本版本为cocos2d-x

新版本cocos2d-x工程项目的创建(本版本为cocos2d-x

Jun 07, 2016 pm 03:49 PM
c create project new version Version Purpose

据说cocos2d-x从2.1.2以后就可以使用python创建项目工程,我是从2.1.3开始学习的,之前没有注意到这一点,一直都是用那些比较复杂的办法创建工程,感觉也有点蛋疼,最近下载了2.1.5来使用,发现里面没有了vs模版,没有create-project.bat等创建win32和androi

据说cocos2d-x从2.1.2以后就可以使用python创建项目工程,我是从2.1.3开始学习的,之前没有注意到这一点,一直都是用那些比较复杂的办法创建工程,感觉也有点蛋疼,最近下载了2.1.5来使用,发现里面没有了vs模版,没有create-project.bat等创建win32和android的项目文件,于是上网查询,才知道2.1.5以后彻底采用pyhton来创建项目工程了,我按照网上办法使用了一下觉得很是方便和简单,早知道这事的话就不用浪费这么多时间在工程配置上了!下面开始创建工程:

1、需要下载python2.7.3安装(http://pan.baidu.com/share/link?shareid=1463897023&uk=4061830256),安装目录如下

新版本cocos2d-x工程项目的创建(本版本为cocos2d-x

2、配置python环境变量在path中加入python安装路径我的是D:\python2.7.3

新版本cocos2d-x工程项目的创建(本版本为cocos2d-x

3、自己写一个create-project.bat放于cocos根目录

@echo off
cd tools\project-creator
set /p projectName=projectName:
if "%projectName%"=="" goto lblExit
set /p packageName=packageName:
if "%packageName%"=="" goto lblExit2
create_project.py -project %projectName% -package %packageName% -language cpp
pause
exit
:lblExit
@echo 项目名称不能为空!
:lblExit2
@echo 包名称不能为空!
pause
Copy after login

 

注意如果出现错误请在这儿下载http://pan.baidu.com/s/1mTsf5一个已经做好的,不需要任何修改。

新版本cocos2d-x工程项目的创建(本版本为cocos2d-x

4、这样就可以直接使用create-project.bat创建工程

如下图,依次输入工程名、包名(注意一定要是org.test.hello这种类型),回车就能创建项目

新版本cocos2d-x工程项目的创建(本版本为cocos2d-x

5、打开D:\Cocos2dx\cocos2d-x_v2.1.5b\projects可以看到我们刚才创建的工程

新版本cocos2d-x工程项目的创建(本版本为cocos2d-x

打开Test可以看到里面已经自动创建了包括androidioswin32mac等主流平台的工程

新版本cocos2d-x工程项目的创建(本版本为cocos2d-x

6、运行win32下的工程Test.sln前提得装好vs)文件即可打开win32工程

新版本cocos2d-x工程项目的创建(本版本为cocos2d-x

等文件与库自动加载完毕之后可以在解决方案中看到已经自动加载了所需要的常用库(如下图),这样直接运行程序就ok了,过程与以前相比真是十分的简单

 

新版本cocos2d-x工程项目的创建(本版本为cocos2d-x

 

新版本cocos2d-x工程项目的创建(本版本为cocos2d-x

7、在android下使用也是特别的简单,只需要将安装好adteclipse打开(前提是电脑得安装好cygwinndk),导入Test文件下的pro.android运行即可

新版本cocos2d-x工程项目的创建(本版本为cocos2d-x

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
4 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Best Graphic Settings
4 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. How to Fix Audio if You Can't Hear Anyone
4 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Chat Commands and How to Use Them
4 weeks ago By 尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

The author of ControlNet has another hit! The whole process of generating a painting from a picture, earning 1.4k stars in two days The author of ControlNet has another hit! The whole process of generating a painting from a picture, earning 1.4k stars in two days Jul 17, 2024 am 01:56 AM

It is also a Tusheng video, but PaintsUndo has taken a different route. ControlNet author LvminZhang started to live again! This time I aim at the field of painting. The new project PaintsUndo has received 1.4kstar (still rising crazily) not long after it was launched. Project address: https://github.com/lllyasviel/Paints-UNDO Through this project, the user inputs a static image, and PaintsUndo can automatically help you generate a video of the entire painting process, from line draft to finished product. follow. During the drawing process, the line changes are amazing. The final video result is very similar to the original image: Let’s take a look at a complete drawing.

Topping the list of open source AI software engineers, UIUC's agent-less solution easily solves SWE-bench real programming problems Topping the list of open source AI software engineers, UIUC's agent-less solution easily solves SWE-bench real programming problems Jul 17, 2024 pm 10:02 PM

The AIxiv column is a column where this site publishes academic and technical content. In the past few years, the AIxiv column of this site has received more than 2,000 reports, covering top laboratories from major universities and companies around the world, effectively promoting academic exchanges and dissemination. If you have excellent work that you want to share, please feel free to contribute or contact us for reporting. Submission email: liyazhou@jiqizhixin.com; zhaoyunfeng@jiqizhixin.com The authors of this paper are all from the team of teacher Zhang Lingming at the University of Illinois at Urbana-Champaign (UIUC), including: Steven Code repair; Deng Yinlin, fourth-year doctoral student, researcher

Posthumous work of the OpenAI Super Alignment Team: Two large models play a game, and the output becomes more understandable Posthumous work of the OpenAI Super Alignment Team: Two large models play a game, and the output becomes more understandable Jul 19, 2024 am 01:29 AM

If the answer given by the AI ​​model is incomprehensible at all, would you dare to use it? As machine learning systems are used in more important areas, it becomes increasingly important to demonstrate why we can trust their output, and when not to trust them. One possible way to gain trust in the output of a complex system is to require the system to produce an interpretation of its output that is readable to a human or another trusted system, that is, fully understandable to the point that any possible errors can be found. For example, to build trust in the judicial system, we require courts to provide clear and readable written opinions that explain and support their decisions. For large language models, we can also adopt a similar approach. However, when taking this approach, ensure that the language model generates

arXiv papers can be posted as 'barrage', Stanford alphaXiv discussion platform is online, LeCun likes it arXiv papers can be posted as 'barrage', Stanford alphaXiv discussion platform is online, LeCun likes it Aug 01, 2024 pm 05:18 PM

cheers! What is it like when a paper discussion is down to words? Recently, students at Stanford University created alphaXiv, an open discussion forum for arXiv papers that allows questions and comments to be posted directly on any arXiv paper. Website link: https://alphaxiv.org/ In fact, there is no need to visit this website specifically. Just change arXiv in any URL to alphaXiv to directly open the corresponding paper on the alphaXiv forum: you can accurately locate the paragraphs in the paper, Sentence: In the discussion area on the right, users can post questions to ask the author about the ideas and details of the paper. For example, they can also comment on the content of the paper, such as: "Given to

Axiomatic training allows LLM to learn causal reasoning: the 67 million parameter model is comparable to the trillion parameter level GPT-4 Axiomatic training allows LLM to learn causal reasoning: the 67 million parameter model is comparable to the trillion parameter level GPT-4 Jul 17, 2024 am 10:14 AM

Show the causal chain to LLM and it learns the axioms. AI is already helping mathematicians and scientists conduct research. For example, the famous mathematician Terence Tao has repeatedly shared his research and exploration experience with the help of AI tools such as GPT. For AI to compete in these fields, strong and reliable causal reasoning capabilities are essential. The research to be introduced in this article found that a Transformer model trained on the demonstration of the causal transitivity axiom on small graphs can generalize to the transitive axiom on large graphs. In other words, if the Transformer learns to perform simple causal reasoning, it may be used for more complex causal reasoning. The axiomatic training framework proposed by the team is a new paradigm for learning causal reasoning based on passive data, with only demonstrations

A significant breakthrough in the Riemann Hypothesis! Tao Zhexuan strongly recommends new papers from MIT and Oxford, and the 37-year-old Fields Medal winner participated A significant breakthrough in the Riemann Hypothesis! Tao Zhexuan strongly recommends new papers from MIT and Oxford, and the 37-year-old Fields Medal winner participated Aug 05, 2024 pm 03:32 PM

Recently, the Riemann Hypothesis, known as one of the seven major problems of the millennium, has achieved a new breakthrough. The Riemann Hypothesis is a very important unsolved problem in mathematics, related to the precise properties of the distribution of prime numbers (primes are those numbers that are only divisible by 1 and themselves, and they play a fundamental role in number theory). In today's mathematical literature, there are more than a thousand mathematical propositions based on the establishment of the Riemann Hypothesis (or its generalized form). In other words, once the Riemann Hypothesis and its generalized form are proven, these more than a thousand propositions will be established as theorems, which will have a profound impact on the field of mathematics; and if the Riemann Hypothesis is proven wrong, then among these propositions part of it will also lose its effectiveness. New breakthrough comes from MIT mathematics professor Larry Guth and Oxford University

The first Mamba-based MLLM is here! Model weights, training code, etc. have all been open source The first Mamba-based MLLM is here! Model weights, training code, etc. have all been open source Jul 17, 2024 am 02:46 AM

The AIxiv column is a column where this site publishes academic and technical content. In the past few years, the AIxiv column of this site has received more than 2,000 reports, covering top laboratories from major universities and companies around the world, effectively promoting academic exchanges and dissemination. If you have excellent work that you want to share, please feel free to contribute or contact us for reporting. Submission email: liyazhou@jiqizhixin.com; zhaoyunfeng@jiqizhixin.com. Introduction In recent years, the application of multimodal large language models (MLLM) in various fields has achieved remarkable success. However, as the basic model for many downstream tasks, current MLLM consists of the well-known Transformer network, which

LLM is really not good for time series prediction. It doesn't even use its reasoning ability. LLM is really not good for time series prediction. It doesn't even use its reasoning ability. Jul 15, 2024 pm 03:59 PM

Can language models really be used for time series prediction? According to Betteridge's Law of Headlines (any news headline ending with a question mark can be answered with "no"), the answer should be no. The fact seems to be true: such a powerful LLM cannot handle time series data well. Time series, that is, time series, as the name suggests, refers to a set of data point sequences arranged in the order of time. Time series analysis is critical in many areas, including disease spread prediction, retail analytics, healthcare, and finance. In the field of time series analysis, many researchers have recently been studying how to use large language models (LLM) to classify, predict, and detect anomalies in time series. These papers assume that language models that are good at handling sequential dependencies in text can also generalize to time series.

See all articles