Course material for the Multi-agents and computer graphics course

Overview

TC2008B

Course material for the Multi-agents and computer graphics course.

Setup instructions

  • Strongly recommend using a custom conda environment.
  • Install python 3.8 in the environment: conda install python=3.8 Using 3.8 for compatibility reasons. Maybe 3.9 or 3.10 are compatible with all the packages, but will have to check.
  • Installing mesa: pip install mesa
  • Installing flask to mount the service: pip install flask
  • By this moment, the environment will have all the packages needed for the project to run.

Instructions to run the local server and the Unity application

  • Run either the python web server: Server/tc2008B_server.py, or the flask server: Server/tc2008B_flask.py. Flask is considerably easier to setup and use, and I strongly recommend its use over python's http.server module. Additionally, IBM cloud example used flask.
  • To run the python web server:
python tc2008B_server.py
  • To run a flask app:
export FLASK_APP=tc_2008B_flash.py
flask run
  • You can change the name of the app you want to run by changing the environment variable FLASK_APP.

  • Alternatively, if you used the following code in your flask server:

if __name__=='__main__':
    app.run(host="localhost", port=8585, debug=True)

you can run it using:

python tc2008B_flask.py
  • To run a flask app on a different host or port:
flask run --host=0.0.0.0 --port=8585
  • Either of these servers is what will run on the cloud.
  • Once the server is running, launch the Unity scene TC2008B that is in the folder: IntegrationTest.
  • The scene has two game objects: AgentController and AgentControllerUpdate. I left both so that different functionality can be tested: AgentController works with the response of the python web server, while AgentControllerUpdate works with the reponse from the flask server.
  • I updated the AgentController.cs code, and introduced AgentControllerUpdate.cs. Each script parses data differently, depending on the response from either the python web server, or from the flask server. The AgentController.cs script parses text data, while AgentControllerUpdate.cs parses JSON data. I strongly recommend that we use JSON data.
  • The scripts are listening to port 8585 (http://localhost:8585). Double check that your server is launching on that port; specially if you are using a flask server.
  • If the Unity application is not running, or has import issues, I included the Unity package that has the scene Sergio Ruiz provided.

Instruction to run the cloud server and Unity application

Installing dependencies, and locally running the sample

# ...first add the Cloud Foundry Foundation public key and package repository to your system
wget -q -O - https://packages.cloudfoundry.org/debian/cli.cloudfoundry.org.key | sudo apt-key add -
echo "deb https://packages.cloudfoundry.org/debian stable main" | sudo tee /etc/apt/sources.list.d/cloudfoundry-cli.list
# ...then, update your local package index, then finally install the cf CLI
sudo apt update
sudo apt install cf8-cli
  • To get the sample app running:
git clone https://github.com/IBM-Cloud/get-started-python
cd get-started-python
  • To run locally:
pip install -r requirements.txt
python hello.py

To deply the sample to the cloud

  • All the requiered files for the sample app to run are inside the IBMCloud folder.
  • We first need a manifest.yml file. The one provided in the example repository contains the following:
applications:
 - name: GetStartedPython
   random-route: true
   memory: 128M
  • You can use the Cloud Foundry CLI to deploy apps. Choose your API endpoint:
cf api 
   

   

Replace the API-endpoint in the command with an API endpoint from the following list:

URL Region
https://api.ng.bluemix.net US South
https://api.eu-de.bluemix.net Germany
https://api.eu-gb.bluemix.net United Kingdom
https://api.au-syd.bluemix.net Sydney
  • Login to your IBM Cloud account:
cf login
  • From within the get-started-python directory push your app to IBM Cloud:
cf push
  • This process can take a while. All the dependencies are downloaded and installed, and the app in started.
  • After you push the application, in the cloud dashboard you can see a new cloud foundry app.
  • This can take a minute. If there is an error in the deployment process you can use the command cf logs --recent to troubleshoot.
  • When deployment completes you should see a message indicating that your app is running. View your app at the URL listed in the output of the push command. You can also issue the cf apps.
  • With the cf apps command you can see the route for the app.

To deploy a custom app to the cloud

  • I created an app within the cloud foundry in the ibm cloud by following the document Manual IBM Cloud - Python.pdf.
  • Created an additional folder inside the IBMCloud folder, named boids, that contains the required files.
  • In the manifest.yml I renamed the name to the one I used for the app in cloud foundry. From GetStartedPython to Boids.
  • Then, modified the ProcFile file as follows:
web: python tc2008B_flask.py
  • Modified the setup.py file, but I do not think it matters.
  • Then changed to the boids folder, and used:
cf push
  • Then, update the url for the service in Unity with the url for the service that cloud foundry assigns.

Notes

  • Using VSCode to develop everything.
  • Although not stated in the requirements, Git needs to be installed on the system.
  • I am running windows, and using the WSL. I ran the server code in WSL, and the Unity client in windows. My WSL machine runs Ubuntu 20.
  • Using Thunder Client extension as a replacement for postman to test the apis.
  • Pip does not allow us to search anymore.
  • As of 2021-10-17, the WWWForm method to post from Unity to the web service still works with Unity 20.20.3.4. However, the support apparently is going away soon.
  • Using flask because it is ideal for building smaller applications. Django could be used, but since it is much more robust, the additional utilities were not needed for this project.
  • The demo app push process went rather smoothly, but for the boids app it did not. It took too long, and ended up failing with a timeout error. I issued the command again.
  • Timeout again. Modified the manifest, and tried again.
  • After that, the app failed when it tried to start. Apparently, numpy was missing from the requirements.

TO DO

  • [ x ] Add the mesa code instead of the Boids code.
  • [ x ] Check synchronization, clients, maybe in the cloud, most likely in flask
  • Check cloud documentation or ask for a course? Instances, connections, etc.

Dependencies

question‘s area recognition using image processing and regular expression

======================================== Paper-Question-recognition ======================================== question‘s area recognition using image p

Yuta Mizuki 7 Dec 27, 2021
governance proposal to make fei redeemable for eth

Feil Proposal 🌲 Abstract Migrate all ETH from Fei protocol-controlled value into Yearn ETH Vault. Allow redemptions of outstanding FEI for yvETH. At

13 Mar 31, 2022
Convert scans of handwritten notes to beautiful, compact PDFs

Convert scans of handwritten notes to beautiful, compact PDFs

Matt Zucker 4.8k Jan 01, 2023
kaldi-asr/kaldi is the official location of the Kaldi project.

Kaldi Speech Recognition Toolkit To build the toolkit: see ./INSTALL. These instructions are valid for UNIX systems including various flavors of Linux

Kaldi 12.3k Jan 05, 2023
Simple app for visual editing of Page XML files

Name nw-page-editor - Simple app for visual editing of Page XML files. Version: 2021.02.22 Description nw-page-editor is an application for viewing/ed

Mauricio Villegas 27 Jun 20, 2022
Pure Javascript OCR for more than 100 Languages 📖🎉🖥

Version 2 is now available and under development in the master branch, read a story about v2: Why I refactor tesseract.js v2? Check the support/1.x br

Project Naptha 29.2k Jan 05, 2023
Super Mario Game With Python

Super_Mario Hello all this is a simple python program which tries to use our body as a controller for the super mario game Here I have used media pipe

Adarsh Badagala 219 Nov 25, 2022
OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched

OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched or copy-pasted. ocrmypdf # it's a scriptable c

jbarlow83 7.9k Jan 03, 2023
DouZero is a reinforcement learning framework for DouDizhu - 斗地主AI

[ICML 2021] DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning | 斗地主AI

Kwai 3.1k Jan 05, 2023
Image processing in Python

scikit-image: Image processing in Python Website (including documentation): https://scikit-image.org/ Mailing list: https://mail.python.org/mailman3/l

Image Processing Toolbox for SciPy 5.2k Dec 30, 2022
A version of nrsc5-gui that merges the interface developed by cmnybo with the architecture developed by zefie in order to start a new baseline that is not heavily dependent upon Python processing.

NRSC5-DUI is a graphical interface for nrsc5. It makes it easy to play your favorite FM HD radio stations using an RTL-SDR dongle. It will also displa

61 Dec 22, 2022
Using python libraries to track hands

Python-HandTracking Using python libraries to track hands on a camera Uses cv2 and mediapipe libraries custom hand tracking module PyCharm IDE Final E

Martin Matsudaira 1 Dec 17, 2021
TextField: Learning A Deep Direction Field for Irregular Scene Text Detection (TIP 2019)

TextField: Learning A Deep Direction Field for Irregular Scene Text Detection Introduction The code and trained models of: TextField: Learning A Deep

Yukang Wang 101 Dec 12, 2022
The open source extract transaction infomation by using OCR.

Transaction OCR Mã nguồn trích xuất thông tin transaction từ file scaned pdf, ở đây tôi lựa chọn tài liệu sao kê công khai của Thuy Tien. Mã nguồn có

Nguyen Xuan Hung 18 Jun 02, 2022
Random maze generator and solver

Maze Generator and Solver I wrote a maze generator that works with two commonly known algorithms: Depth First Search and Randomized Prims. Both of the

Daniel Pérez 10 Sep 23, 2022
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

EasyOCR Ready-to-use OCR with 80+ languages supported including Chinese, Japanese, Korean and Thai. What's new 1 February 2021 - Version 1.2.3 Add set

Jaided AI 16.7k Jan 03, 2023
With the virtual keyboard, you can write on the real time images by combining the thumb and index fingers on the letter you want.

Virtual Keyboard With the virtual keyboard, you can write on the real time images by combining the thumb and index fingers on the letter you want. At

Güldeniz Bektaş 5 Jan 23, 2022
Fatigue Driving Detection Based on Dlib

Fatigue Driving Detection Based on Dlib

5 Dec 14, 2022
A simple Security Camera created using Opencv in Python where images gets saved in realtime in your Dropbox account at every 5 seconds

Security Camera using Opencv & Dropbox This is a simple Security Camera created using Opencv in Python where images gets saved in realtime in your Dro

Arpit Rath 1 Jan 31, 2022
EAST for ICPR MTWI 2018 Challenge II (Text detection of network images)

EAST_ICPR2018: EAST for ICPR MTWI 2018 Challenge II (Text detection of network images) Introduction This is a repository forked from argman/EAST for t

QichaoWu 49 Dec 24, 2022