Complete Computer Vision Bootcamp: YOLO to Multimodal AI

About this course

This course takes you from the basics of YOLO11 to advanced computer vision applications. You’ll explore object detection, segmentation, pose estimation, and image classification, while also learning to create analytical graphs and track object movements. Beyond YOLO11, you’ll build real-world projects with Streamlit, enhance detection with SAHI, estimate distances with Depth Pro, and explore cutting-edge multimodal AI models like Qwen2.5-VL, Florence 2, and Google Gemini 2.5. By the end, you’ll have hands-on experience with modern tools to solve practical computer vision challenges.

What You Will Learn:

Getting Started with YOLO11:

YOLO11 Updates and New Features

Implementing YOLO11 in Google Colab:

• YOLO11 for Object Detection, Segmentation, Pose Estimation & Classification

Creating Analytical Graphs and Visualizing Data with YOLO11:

How to Generate Analytical Graphs with YOLO11Counting Object Entries and Exits using YOLO11 and DeepSORT:Tracking Objects with YOLO11 and DeepSORT for Entry–Exit CountsStreamlit Application: Object Detection, Segmentation & Pose Estimation:

• Building a Streamlit App for Object Detection, Segmentation, and Pose Estimation

Using Ultralytics YOLO11 with SAHI for Object Detection in Drone Footage:

YOLO11 + SAHI = Better Detection for Small Objects! (Step-by-Step Guide)Estimate Real Distance to Objects with ML Depth Pro and YOLO11:

• Learn how to estimate real distances to objects using Depth Pro and YOLO11.

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