Course Curriculum

Introduction to Ultimate AI-CV

     
    Introduction to Ultimate AI-CV Pro
     
    Course Requirements
     
    How to Join the Private FB Group

Module 1 – YOLO v3 – Robust Deep Learning Object Detection in 1 hour

     
    1.1 – Yolo V3 Intuition (12:10)
     
    1.2 – Execute Yolo V3 (8:50)
     
    1.3 – 4 Steps to Setting up a Supervisely Deep Learning Cluster (9:32)
     
    1.4 – How to Web Scrape Images for your Dataset like a PRO! (6:21)
     
    1.5 – The Best Way to Annotate your Dataset (4:22)
     
    1.6 – How to let the AI Annotate your Dataset for you – Human in the Loop Annotation (2:49)
     
    1.7 – Got Little Data? No Problem! Data Augmentation to the Rescue 😉 (4:28)
     
    1.8 – How to Train a Yolo V3 Network (5:04)
     
    1.9 – A Quick and Easy Method Deploying your Custom Object Detector after Training (6:37)
     
    1.10 – How to Record video, change bounding box color and add confidence percentage (5:32)
     
    1.11 – Cleaning up you Supervisely Cluster and Cluster Maintenance (1:37)

Module 2 – Mask R-CNN – Robust Deep Learning Segmentation in 1 hour

     
    2.1 – Mask R-CNN Intuition (10:07)
     
    2.2 – Anaconda Install and Setup for Mask RCNN (1:57)
     
    2.3 – Installing the requirements, dependencies (10:56)
     
    2.4 – Real-time Mask RCNN – How to execute like a boss. (5:32)
     
    2.5 – Set up Supervisely Cluster (9:32)
     
    2.6 – Annotating Images (8:10)
     
    2.7 – Data Augmentation (4:38)
     
    2.8 – How to Train a Mask RCNN model (5:50)
     
    2.9- How to Deploy a Custom Mask RCNN after Training (3:55)
     
    2.10 – Segmentation Area Analysis – How to Count Potholes and its Area Size (2:55)

Module 3 – Pose Estimation Master Class using OpenPose Framework

     
    3.1 – OpenPose Intuition & How it Works (11:07)
     
    3.2 – OpenPose Github Repository
     
    3.3 – Setup & Execution of Pose Estimation (5:30)
     
    3.4 – App 1 : People Counter using Open Pose (4:26)
     
    3.5 -App 2 : Fall Detection (6:52)
     
    3.6 – App 3 : Yoga Pose Angle Corrector (6:44)
     
    3.7 – App 4: Plank Pose Recongition (7:41)
     
    3. 8 – App 5 : Body Ratio Calculator (6:52)
     
    3.9 – App 6 : OpenPose in Unity [UPDATED!!] (6:04)

Module 4 – AI Android Development

     
    4. Introduction to AI Development on Android – TensorFlow Lite (6:01)
     
    4.1 – Data Collection, Cleaning & Annotation (non-supervisely solution)
     
    4.2 – Data Training [Coming Soon]     
    4.3 – Data Validation [Coming Soon]     
    4.4 – Data Testing [Coming Soon]     
    4.5 – Frozen graph & model generation in Tensorflow [Coming Soon]     
    4.5.1 – Convert to TFLite Model (TOCO API) [Coming Soon]     
    4.5.2 – Tensorflow Lite Basics [Coming Soon]     
    4.5.3 – Import Tensorflow in Gradle [Coming Soon]     
    4.6 – Project Setup and Run Inference on Android [Coming Soon]     
    4.6.1 – Object Detection – Selecting between image, video or live camera [Coming Soon]     
    4.6.2 – Adding logic to AI on Android [Coming Soon]     
    4.6.3 – App 1 [Coming Soon]     
    4.6.4 – App 2 [Coming Soon]

Project E.D.I.T.H. – Spiderman (Far from Home) AI Glasses [BONUS]

     
    Phase 1 – AI Face Detection in Unity (9:36)
     
    Phase 2 – Facial Recognition (17:09)
     
    Phase 3 – Object Detection (19:49)
     
    Phase 4 – AI Assistant Text to Speech (TTS) & Speech to Text (STT) (18:18)
     
    Phase 5 – IoT using AI Assistant (11:53)
     
    Phase 6 – Android Integration of Project E.D.I.T.H. (10:00)
     
    Phase 7 – AR Glasses Integration of AI Capabilities [Coming Soon]

Bonus Section

     
    B1 – Artificial Neural Networks (18:30)
     
    B2 – Convolutional Neural Network (11:17)
     
    B3 – Recurrent Neural Networks (12:22)
     
    B4 – FREE Accelerated Deep Learning on Raspberry Pi Course