AI-Critters : STEP Summer 2024

Learn about AI computer vision through building cameras and detecting animals on the Bronx Community College Campus!

Resources

• ai-4-all.org
• AI Image Training - Teachable Machine

Week 1 : Introduction to Computer Terminals, AI and Image Classification

• Learning Goals and Industry Context: Students will be able to code a visual program using P5 javascript. They will incorporate machine learning into their P5 javascript projects, using Teachable Machine.
• Implementation: 1.0.1 - 1.3.2
• Final Outcome or Product: Create an AI model with Teachable Machine of students face and run it on AI Object Detection model in P5Javascript, where it will display a coded self portrait.

1.0.1 : Monday Morning

Introduction to CMD (the windows terminal) Learn how to talk and navigate computer systems like a pro (hacker!).

1.0.2: Monday Afternoon

Terminal / BASH, open source projects

• LECTURE: What is Bash?

• LECTURE: What is Github?

• Workshop : Terminal Basics : Cheat Sheet 1 ,

• Workshop : Understanding SSH : Video : Log into the mainframe!

• Over the Wire Workshop (Abdon):

1.1.1 : Tuesday Morning | Afternoon

Students will be presented with potential classes available in the summer. Students will provide a ranked vote of the classes they would like to participate in.

1.2.1 : Wednesday Morning

Introduction to P5js. Students will learn the basics of P5js, including how to make shapes. Their task will be to complete a self portrait using basics shapes.

1.2.2 : Wednesday Afternoon

Students will complete their Self portraits. Hour of Code Lesson: Self Portrait: https://www.code-art.com/hour-of-code-self-portrait/

1.3.1 : Thursday Morning

Students will use Teachable machine and make a AI Computer vision model of their faces. They will spend time perfecting the model. Teachable Machine: https://teachablemachine.withgoogle.com/train/image

1.3.2: Thursday Afternoon

Students combined Self Portraits with AI computer vision models.
The project is based on: https://thecodingtrain.com/tracks/teachable-machine P5js template:

WEEK 2: Introduction to AI, Computer Vision and building DIY Cameras

Learning Goals and Industry Context:

• Students will be able explore AI computer vision concepts.
• Students will learn how to create and program IOT Camera and firmware using WyzeCam or ESP32.
• Students will leave knowing methods for creating outdoor housing for cameras.

Implementation: 2.0.1 - 2.3.2

Final Outcome or Product:

• Create an AI model with Teachable Machine of students face and run it on AI Object Detection model in P5 Javascript, where it will display a coded self portrait.
• see: Teachable Faces P5 project
• Create P5 project with Teachable machine using their bodies to create "letters" and then showing the letter on screen.

2.0.1 : Monday

• Build an AI computer from computer parts.
• Prototype an outdoor housing box for WyzeCam.
• Complete self portrait - combined sketch.
• Complete Teachable Machine Model

2.1.1 : Tuesday Morning

• AI can be used in diverse fields including art and creativity Students learn these things by exploring drawing in Google Quick, Draw! Resources: https://drive.google.com/drive/u/2/folders/1RNtEVZSK2u1xcrB7ruHvrfqjCrvIPpXI

• Explore RunwayML - Sign up for Runway ML

• Make images on RunwayML using prompts.

• Finish Facial Recognition Project.

2.2.1 : Wednesday Morning

Hands on: build a DIY camera using a WYZECAM.

2.3.1 : Thursday Morning

Hands on: build a DIY camera housing made of wood.

WEEK 3

Learning Goals and Industry Context:

• Students will install all packages to run professional AI based models. installation includes pyorch, and CUDA, on Intel PCs with NVidia 3070 Graphics Card.
• Students will learn how to install and create pytorch AI models.

Implementation: 3.0.1 - 3.3

Final Outcome or Product:

• Working prototype of Camera in wooden housing, automatically sending images to a Pytorch AI serer.
• Begin training a BCC Animal Model.

3.0.1 : Monday

• Install AI software: Forest Buddy Server.
• Complete P5 Teachable Machine Project: https://editor.p5js.org/Kimoni/sketches/RLXL3Ymkh on big screen.

3.1.0 : Tuesday

• Understand PyTorch, And Yolo V8 AI Model.

• Create a large critter box

• Create 4 wood boxes, 1 solar powered.

• Letters to

WEEK 4

WEEK 5

WEEK 6

Introduction to Artificial Intelligence (AI)

• Definition and basics of AI
• Real-world applications of AI (e.g., self-driving cars, virtual assistants, recommendation systems)
• Overview of the AI Critters project and its objectives
• Introduction to the concept of image classification and its use in wildlife monitoring

Introduction to GitHub.

• Prerequisites: Install WSL resource: https://learn.microsoft.com/en-us/windows/wsl/install

  • Windows 11: wsl --install
  • Github Account

• Install AI software: Pytorch + YoloV8:

• Install AI software: Stable Diffusion:

  • Official documentation: AUTOMATIC1111
  • Step by step documentation: https://stable-diffusion-art.com/install-windows/ |

• Install AI Model Creation (yourFACE) on Stable Diffusion: https://www.run.ai/guides/generative-ai/stable-diffusion-training