Computer Vision Roadmap with Tutorials

1️⃣ Prerequisites

🔹 Mathematics for Computer Vision

1. Linear Algebra: Essence of Linear Algebra (3Blue1Brown)
2. Probability & Statistics: MIT Probability Course
3. Calculus: MIT Calculus Course

🔹 Python Basics

• Python for Data Science - FreeCodeCamp

2️⃣ OpenCV & Image Processing

🔹 Learn OpenCV (Computer Vision Basics)

• Complete OpenCV Course: OpenCV Full Course (FreeCodeCamp)
• Hands-on OpenCV: OpenCV Python Tutorials
• Image Processing:

📌 Project: Implement Face Detection using OpenCV Haar Cascades. 🔗 Haar Cascade Face Detection

3️⃣ Deep Learning for Computer Vision

🔹 Neural Networks & Convolutional Neural Networks (CNNs)

• Stanford CS231n Course: CS231n - Convolutional Neural Networks for Visual Recognition
• CNN Intuition: CNN Explanation
• TensorFlow Deep Learning: TensorFlow Full Course

📌 Project: Train a CNN for handwritten digit recognition using MNIST. 🔗 MNIST CNN with TensorFlow

4️⃣ Object Detection & Image Segmentation

🔹 Object Detection (YOLO, Faster R-CNN, SSD)

• YOLOv8 Tutorial: Train a YOLOv8 Model
• Faster R-CNN PyTorch Implementation: Faster R-CNN Guide

📌 Project: Build a real-time object detection app using YOLOv8.

🔹 Image Segmentation (U-Net, Mask R-CNN)

• U-Net Image Segmentation: U-Net Explanation
• Mask R-CNN Implementation: Mask R-CNN Guide

📌 Project: Segment lung regions in chest X-rays using U-Net.

5️⃣ Face Recognition & Pose Estimation

🔹 Face Recognition (DeepFace, OpenCV, FaceNet)

• DeepFace Library: DeepFace GitHub
• Face Recognition with OpenCV: Face Recognition Tutorial

📌 Project: Build a face recognition attendance system.

🔹 Pose Estimation

• Google MediaPipe Pose Tracking: Mediapipe Pose

📌 Project: Implement a real-time body pose estimation app.

6️⃣ Advanced Topics in Computer Vision

🔹 Generative Models (GANs, VAEs, StyleGAN)

• GANs Introduction: What are GANs?
• GANs with PyTorch: Hands-on GANs

📌 Project: Train a GAN to generate realistic human faces.

🔹 Vision Transformers (ViTs, Swin Transformers)

• Vision Transformer Explained: ViT YouTube Video

📌 Project: Fine-tune a ViT model for image classification.

🔹 3D Computer Vision (NeRF, Point Clouds, SfM)

• NeRF (Neural Radiance Fields): NeRF Research

📌 Project: Reconstruct 3D scenes from 2D images using NeRF.

7️⃣ Deployment & Optimization

🔹 Edge Deployment (TensorFlow Lite, OpenVINO, NVIDIA Jetson)

• TensorFlow Lite Optimization: TF Lite Guide
• NVIDIA Jetson AI Projects: Jetson Developer

📌 Project: Deploy a deep learning model on a Raspberry Pi.

🔹 Cloud Deployment (AWS, Google Cloud, Azure)

• AWS Sagemaker: AWS Sagemaker for AI

📌 Project: Host an object detection API on AWS.

🔹 Model Optimization (ONNX, Pruning, Quantization)

• TensorFlow Model Optimization: TF Model Optimization

📌 Project: Convert a large deep learning model to an optimized ONNX format.

📌 Final Projects & Challenges

🚀 Kaggle Competitions:

• Kaggle Computer Vision Challenges

📌 Final Projects:

✅ Traffic Sign Detection System

✅ AI-Powered Image Captioning

✅ AI-Powered Medical Image Analysis