Great — Computer Vision , here’s a 12-week interactive learning journey combining theory, coding, real-world case studies, and mini-projects.

🔍 Phase 1: Core Foundations (Weeks 1–3) Goal: Build intuition and skills in image processing, filtering, and foundational CV operations.

Week 1: Introduction & Image Processing Topics:

What is computer vision?

Image representation (pixels, channels)

Color spaces (RGB, HSV, Grayscale)

Basic transformations (resize, crop, rotate)

Tools: OpenCV, NumPy

Practice: Load and manipulate images using OpenCV

Mini Project: Build a real-time webcam-based filter (grayscale, sepia, invert)

Week 2: Image Filtering & Thresholding Topics:

Blurring (Gaussian, Median)

Edge detection (Sobel, Canny)

Thresholding & masking

Practice: Apply filters to noisy images

Case Study: Noise reduction in scanned documents

Week 3: Contours & Shapes Topics:

Contour detection

Shape approximation

Drawing and bounding boxes

Mini Project: Object counter (e.g., count coins from an image)

Case Study: Automatic shape detection in agricultural imaging

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🧠 Phase 2: Learning with Machines (Weeks 4–6) Goal: Learn how machine learning integrates with vision tasks.

Week 4: Feature Extraction Topics:

HOG, SIFT, ORB (overview)

Feature matching

Practice: Image similarity checker

Case Study: Matching logo in different images

Week 5: Object Classification Topics:

Train/test split

Basic ML models: SVM, KNN for image classification

Tools: scikit-learn, OpenCV

Project: Classify traffic signs using custom dataset

Case Study: Disease classification from leaf images

Week 6: Deep Learning Intro (CNNs) Topics:

CNN architecture basics

Convolution, pooling, activation functions

Tools: TensorFlow/Keras or PyTorch

Project: Train a CNN to classify handwritten digits (MNIST)

Case Study: Emotion recognition using FER2013

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🤖 Phase 3: Real-World Applications (Weeks 7–10) Goal: Apply CV in major domains with case-driven tasks.

Week 7: Face & Emotion Recognition Topics:

Face detection (Haar, DNN)

Emotion classification with CNNs

Project: Real-time emotion detector from webcam

Case Study: Monitor classroom engagement

Week 8: OCR & Text Detection Topics:

Tesseract OCR

Scene text detection

Project: Scan and digitize handwritten notes

Case Study: Bill scanner for expense tracking

Week 9: Satellite & Agricultural CV Topics:

NDVI computation

Image segmentation basics

Project: Crop health monitoring from drone images

Case Study: Land use classification using satellite data

Week 10: Autonomous Vehicle Basics Topics:

Lane detection

Object detection (YOLO intro)

Project: Build a basic lane follower using video feed

Case Study: Real-time pedestrian detection from dashcam footage

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🔐 Phase 4: Advanced Topics & Deployment (Weeks 11–12)

Week 11: Steganography, Cryptography & Security Topics:

LSB technique for hiding data

Image hashing and tamper detection

Project: Hide & retrieve message from image

Case Study: Image authentication for forensics

Week 12: Model Deployment & Final Capstone Topics:

Streamlit/Flask for CV app deployment

On-device inference (TFLite/ONNX)

Capstone Project: Choose one domain from the above and build a full pipeline:

Input → Processing → Detection → Result → UI

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🛠 Tools Used Python, OpenCV

TensorFlow/Keras or PyTorch

Tesseract OCR

Streamlit/Flask for deployment

Git for version control

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📦 Deliverables (by the end) 8+ mini projects

1 capstone app

Case-study-based documentation

Resume-ready GitHub repo